GI-Forum

The GI-Forum takes place every Tuesday from 12 to 2 pm during semester in room 242 at the Institute for Geoinformatics (Heisenbergstraße 2, 48151 Münster). The Forum is open to the public and all interested are welcome to attend.

These open sessions present an opportunity to discuss a variety topics across GI Science, generally in the form of presentations of around 45 minutes followed by 15-30 minutes for questions and general discussion, before closing with light refreshments.

Speakers are drawn from a range of academic disciplines, as well as from industry and policy areas, and present results of ongoing research and/or practical outcomes.

GI-Forum Summer 23

Date	Topic	Presenter	Affiliation
04.04.2023	Institute Meeting (ifgi staff only)
Sorry, no abstract available yet.
11.04.2023	An integrated Geoinformation based approach for spatiotemporal modelling of the environmental impacts of climate change in global dying lakes	Bakhtiar Feizizadeh	ifgi
In many parts of the world, lake drying is caused by water management failures, while the phenomenon is exacerbated by climate change. Lake Urmia in Northern Iran is drying up at such an alarming rate that it is considered to be a dying lake, which has dire consequences for the whole region. While salinization caused by a dying lake is well understood and known to influence the local and regional food production, other potential impacts by dying lakes are as yet unknown. The food production in the Urmia region is predominantly regional and relies on local water sources. To explore the current and projected impacts of the dying lake on food production, we investigated changes in the climatic conditions, land use, and land degradation for the period 1990–2020. We examined the environmental impacts of lake drought on food production using an integrated scenario-based Geoinformation framework. The results show that the lake drought has significantly affected and reduced food production over the past three decades. Based on a combination of cellular automaton and Markov modeling, we project the food production for the next 30 years and predict it will reduce further. The results of this study emphasize the critical environmental impacts of the Urmia Lake drought on food production in the region. We hope that the results will encourage authorities and environmental planners to counteract these issues and take steps to support food production. As our proposed integrated Geoinformation approach considers both the extensive impacts of global climate change and the factors associated with dying lakes, we consider it to be suitable to investigate the relationships between environmental degradation and scenario-based food production in other regions with dying lakes around the world.
18.04.2023	Deep learning and Earth Observation to support the Sustainable Development Goals	Claudio Persello	University of Twente
The combination of deep learning (DL) models and Earth observation (EO) promises significant advances to support the United Nations’ Sustainable Development Goals (SDGs). New developments and applications are already changing how humanity will face our planet’s challenges. This talk provides an overview of research activities on DL methods for EO data, along with their applications toward monitoring the progress and achieving the SDGs most impacted by the rapid development of DL in EO. Case studies will be presented to achieve zero hunger (SDG 2), create sustainable cities (SDG 11), deliver tenure security (multiple SDGs), and mitigate and adapt to climate change (SDG 13). Important societal, economic, and environmental implications are covered.
02.05.2023	Switching between space and time: Spatio-temporal analysis with cubble	Sherry Zhang	Monash University
Weather data have a spatial component given by the station coordinates and a temporal component that provides measurements of precipitation, maximum and minimum temperature. Spatial and temporal software have been separately developed for each component, using different data formats. This creates friction when attempting to analyze spatio-temporal data, as analysts must constantly rearrange the data format to match the requirements of each software. In this talk, I will introduce a new data structure, `cubble`, designed to organize spatio-temporal data so that spatial and temporal information can be easily accessed for exploratory data analysis. I will provide an example of how to create a glyph map to explore the spatio-temporal pattern of weather station data.
09.05.2023	Predicting and managing pollinator health in a changing world	Christina Grozinger	Pennsylvania State University
Bees and other pollinators are essential for supporting terrestrial food webs and agricultural production. However, populations of many species have been showing alarming declines across the world. Our studies have demonstrated that land use and climate are the primary drivers of these declines, but different species are sensitive to different biotic and abiotic factors. I will discuss our efforts to develop automated monitoring systems to provide information at the spatial and temporal scales necessary to build predictive models, as well as the decision support tools that we have developed to help individuals and policymakers adopt strategies to better manage both landscapes and pollinator populations.
16.05.2023	On the Semantics of Big Earth Observation Data	Gilberto Câmara	National Institute for Space Research (INPE)
This presentation will explore the profound impact that the availability of petabytes of Earth observation (EO) data has on our ability to monitor changes in the planet. We will argue that the sheer volume of data available creates a paradigm shift, necessitating a rethinking of traditional concepts used in remote sensing data analysis. Specifically, continuous monitoring with EO requires new approaches that focus on event recognition and detection, rather than content analysis. We need to reconsider how training data is collected and labeled, and the types of algorithms needed for analysis. To illustrate the benefits of an event-driven approach to training and classification of big EO data, we will provide concrete examples that demonstrate how this perspective can yield new insights and more effective ways to monitor our planet. By focusing on detecting changes, rather than simply analyzing content, we can leverage the power of big data to improve our understanding of the Earth's environment.
23.05.2023	Institute Meeting (ifgi staff only)
Sorry, no abstract available yet.
30.05.2023	Generic Object Detection for Autonomous Driving with Deep Learning	Fabian Gigengack, Simon Boeder und Holger Janssen	Bosch Research
The Robert Bosch GmbH develops innovative solutions across a wide range of fields, including automotive, robotics, artificial intelligence, and internet of things. In the first part of this talk, we will introduce the Bosch Corporate Research (CR) including the Computer Vision Lab in Hildesheim. In the second part, one of our PhD students presents his current work on the following topic: In the autonomous driving task, conventional camera-based object detection models rely on large datasets of annotated images to detect objects belonging to specific object classes, such as pedestrians or cars. However, ensuring the safety of autonomous vehicles requires detecting any object that has the potential to collide with the vehicle, regardless of whether it has been labeled or seen during training, opening the field of generic object detection. In this talk, we will present some recent advancements in machine learning and computer vision, such as Neural Radiance Fields (NeRF), that have made it possible to generate realistic 3D reconstructions of environments and train powerful AI models that can detect arbitrary objects in 3D, without requiring costly annotations.
06.06.2023	Using dynamic time warping to reconstruct Australia’s hydroclimate throughout the last 23 million years	David de Vleeschouwer	Institute for Geology and Paleontology, WWU Münster
Australia experiences different climate regimes, being under the tropical climate belt in the north, the subtropical climate belt (including deserts and grasslands) in the centre, and the temperate Mediterranean-style climate belt in the south. Therewith, Australian climate is underpinned by the Hadley and Ferrel atmospheric cells. Satellite observations and climate models suggest that the Intertropical Convergence Zone (ITCZ) is currently narrowing and strengthening, with no reversal of this trend projected in the near future. More extensive changes in latitudinal extent and intensity of these atmospheric cells may have existed on geologic timescales, much beyond the instrumental record. However, the lack of high-resolution paleoclimate reconstructions (in space and time) hampers the assessment of Australian climate sensitivity to a variety of natural climate forcings. During this GI Forum, I will present a new DFG-funded project that aims at expanding the range of the observational record with geological sedimentary sequences obtained through scientific and industrial ocean drilling. The starting point of the project is based on the fact that rainfall patterns in Australia experienced major regime shifts on million-year timescales, throughout the Neogene. However, a spatiotemporal overview is still lacking. This project aims at providing the spatial continent-scale paleoclimate picture, generating paleoclimate time-slice maps based on ocean-drilling proxy data of the last 23 Myr. Sequencing those maps results in a paleoclimate time-lapse, visualizing hydroclimate and sea surface temperature (SST) change through space and time. This Big Data approach exploits the potential to valorise existing data in ways we have not before.
13.06.2023	The Energy and Environmental Impacts of Digital Devices and Services	Mike Hazas	Uppsala University
Information technology is often touted as part of the solution to addressing humanity's growing energy demand and carbon emissions. But, IT itself has significant energy and environmental impacts. This talk has two parts. In the first part, I will summarise those growing impacts, and pitch a few different ways of characterising and tackling the problem. In the second part, I will discuss a previous study we undertook to observe and describe online service usage in a small number of homes - focusing in particular on video streaming, and the meaning and importance this held for our participants.
27.06.2023	t.b.a.	Antonio Krüger	German Research Center for AI (DFKI)
Sorry, no abstract available yet.
04.07.2023	t.b.a.	Dimitar Valkov	German Research Center for AI (DFKI)
Sorry, no abstract available yet.
11.07.2023	Institute Meeting (ifgi staff only)
Sorry, no abstract available yet.

GI-Forum Winter 22/23

Date	Topic	Presenter	Affiliation
11.10.2022	Institute Meeting (ifgi staff only)
Sorry, no abstract available yet.
18.10.2022	Spatiotemporal functional models for irregular and large environmental data sets	Prof. Dr. Philipp Otto	Leibniz University Hannover
In this talk, I will show the results of two different articles -- one about the morphological evolution of coastal profiles and one about the usage patterns of a bike-sharing system. Whereas the first data set is highly irregular and often has incomplete measurements, the second data set has a very detailed but regular temporal resolution. For both cases, we applied a functional model, which accounts for latent spatial and temporal effects, in combination with a spatial subsampling/bootstrap approach. I will show how this model can be used in two completely different situations and how we made the procedure scalable while accounting for the full spatial and temporal dependence. In general, beach profile data sets provide valuable insight into the morphological evolution of sandy shorelines, but to be precise, our aim was (1) to determine the temporal and spatial variability of beach profiles while accounting for autoregressive dependencies, (2) to identify effects of external influences, (3) to predict complete beach profiles at unknown locations, and (4) to forecast complete beach profiles accounting for external influences, such as storm events or nourishments. Regarding the second analysis, the station hire data is analysed in a spatiotemporal functional setting, where the number of bikes at a station is defined as a continuous function of the time of day. Understanding the usage patterns for bike-sharing systems is essential in terms of supporting and enhancing operational planning for such schemes. Studies have demonstrated how factors such as weather conditions influence the number of bikes that should be available at bike-sharing stations at certain times during the day. However, the influences of these factors usually vary over the course of a day, and if there is good temporal resolution, there could also be significant effects only for some hours/minutes (e.g., rush hours).
25.10.2022	Geospatial technologies meet health: prediction of air pollution exposures at high spatiotemporal resolution	Carles Milà	Pompeu Fabra University
Outdoor air pollution is the largest environmental risk factor for human health in Europe, with more than 300,000 premature deaths attributed to it every year. In order to estimate the association of the different air pollutants with health outcomes, epidemiologists require exposure estimates at high spatiotemporal resolution that can be linked to study participants. Nonetheless, air pollution monitoring is complex, expensive, and limited to a generally small number of locations. Therefore, predictive modelling approaches are frequently used to estimate spatially-continuous concentrations of the pollutants using atmospheric remote sensing, climate and atmospheric forecasts, as well as other geographical data. In this talk, I will review the challenges found in air pollution exposure assessment including ground measurements, spatial sampling, atmospheric remote sensing, and exposure modelling and validation. As an example, I will present an exposure assessment study where we modelled daily concentrations of PM2.5, PM10, NO2 and O3 for the period 2018-2020 to assess the association between air pollution and COVID-19 severity in Catalonia, Spain (COVAIR-CAT project). Briefly, a 2-step modelling framework was used where 1) missing pixels in the atmospheric remote sensing products were reconstructed via imputation models using atmospheric forecasts, and 2) a quantile random forest algorithm with residual kriging was used to model the concentrations measured at the ground stations while quantifying the model uncertainty in the predictions. Strengths and limitations of the approach and future lines of work will be highlighted.
08.11.2022	Sustainable Development Research for Insect Monitoring & Protection - Using Computer Vision & Machine Learning Systems	Prof. Dr. Benjamin Risse	ifgi
Over the past 50 years insects have declined by 75%. This decline has catastrophic implications for our ecosystems and all terrestrial and freshwater food chains and food webs. Quantifying these developments is however notoriously difficult for current computer vision and machine learning systems: Tiny, low contrast and fast moving objects have to be localised in cluttered and dynamic scenes resulting in visual ambiguities, frequent occlusions and the need to process huge video files with inappropriate foreground-background ratios and sparse visitation events. In my presentation I will summarise some of the most prominent challenges of visual insect monitoring and introduce solutions and tools to extract high-throughput and high-accuracy characteristics for a wide range of ecological and biological applications. In particular, I will discuss our progress in building tools and algorithms to quantify the impact of pesticides on insect behaviour, present insights into our attempts of building a versatile insect camera trap and in developing an appearance-agnostic in-field animal detection and tracking algorithm to extract accurate measurements from camera footage. I will close by presenting complementary environmental mapping approaches that yield rich contextual information, and moreover can be combined with behavioural data to achieve the urgently needed lab-level quantifications in wildlife conditions.
15.11.2022	A Glimpse into Statistical Relational AI: Indistinguishability for the Win!	Jun.-Prof. Dr. Tanya Braun	WWU Münster - Computer Science Department
Statistical relational artificial intelligence, StaRAI for short, focuses on combining reasoning in uncertain environments with reasoning about individuals and relations in those environments. An important concept in StaRAI is indistinguishability, where groups of individuals behave indistinguishably in relation to each other in an environment. This indistinguishability manifests itself in symmetries in a propositional model and can be encoded compactly using logical constructs in relational models. Lifted inference then exploits indistinguishability for efficiency gains. This talk showcases how to encode indistinguishability in models using logical constructs and highlights various ways of using indistinguishability during probabilistic inference.
22.11.2022	Building bridges with pen and paper: Sketch maps make local knowledge visible	Dr. Carolin Klonner	Heidelberg University
Worldwide, more and more people are affected by floods. The disaster in the Ahr valley shows us very clearly that new methods are urgently needed to obtain up-to-date and locally relevant information. This is where the inhabitants of the affected regions come into play, because their local knowledge can serve as a valuable supplement to data collected with technical devices. The question arises as to how this knowledge can be made visible and usable. As an answer to this question, Dr. Carolin Klonner from the Department of Geography at the University of Heidelberg will present the sketch map method, which can be used for river floods and flash floods. Her research areas are in Chile, Germany and Brazil.
29.11.2022	Enhancing navigation services for pedestrians - Selected research results of the research group cartography of TU Wien	Prof. Dr. Georg Gartner	TU Wien
Navigation services are prominent examples of Location-based Services and have become quite popular for pedestrians in indoor- and outdoor environments. In this presentation I will focus on selected aspects of enhancing pedestrian navigation services by applying a user-centred focus. Case studies demonstrate various attempts, including the use of signs as landmarks, integrating subjective relations to places and introducing a semantic framework.
06.12.2022	Fostering walking in the city with geospatial methods – three related works	Dr. Tessio Novack	ifgi
Walking has several physical and mental health benefits and should be incentivized by cities valuing sustainability and social integration. In this talk, I present three of my recent works related to fostering walking with geospatial methods. The first work introduces an application for generating customized pleasant pedestrian routes with data from OpenStreetMap. The second work is on detecting building facades with graffiti artwork based on user-generated photos and Google Street View imagery. The third work is an ongoing one. Based on a user-survey, Google Street View imagery, and image feature extraction, I address the questions of (1) which streetscape attributes correlate with positive and negative perceptions of street walkability and (2) how this correlation is dependent on socio-demographic characteristics. Lastly, I quickly discuss how this ongoing work links to my initial research plans at ifgi.
13.12.2022	Lowering the barrier for modern cloud-based geospatial (big) data analysis: the Geospatial Computing Platform	Dr. Ing. Serkan Girgin	ITC, University of Twente
Geospatial data is getting bigger and such large and complex datasets are becoming more and more difficult to process by using traditional systems and methods, such as individual workstations and single-threaded applications. Numerous spatial computing solutions have been developed to tackle this challenge by enabling distributed data stores, parallel and distributed computing capabilities, and special computing units (e.g., GPU/TPU) to enable discovery, delivery, analysis, and visualisation of geospatial data. However, these solutions require specialized know-how and expertise, as well as access to adequate computing infrastructure that is mostly located remotely in the Cloud. Therefore, a transition in modus operandi is necessary. The Geospatial Computing Platform lowers the barrier by providing a state-of-the-art computing infrastructure designed for (big) geospatial analysis tasks that combines low-energy, high-performance Edge AI units with powerful GPU-enabled big data computing units in a seamless and innovative manner. Through the platform the users can access thousands of scientific software packages (e.g. Python / R) that are kept up to date regularly. Public datasets available platform-wide improve data access and reduce data duplication, whereas shared workspaces allow research groups to work in a collaborative manner. Beside a modern interactive notebook interface, the platform also allows remote desktop access for desktop applications (e.g., QGIS, SNAP) and features integrated geospatial database, map serving, and data collection services to benefit from existing well-established tools and technologies. This talk will provide information about the design and architecture of the platform, current use cases, and lessons learned during the operation period of two years, involving 200,000+ hours of multi-core/GPU computation and a user community of more than 800 users.
10.01.2023	[cancelled] Dimitar Valkov
Sorry, no abstract available yet.
17.01.2023	(12:15) The nexus of spatial analysis and digital geographies	Jun.-Prof. Dr. René Westerholt	Department of Spatial Planning, TU Dortmund University
Spatial statistical analysis is an offspring of the so-called quantitative turn that affected large parts of the social sciences from the 1950s onwards. The core of spatial analysis developed at the intersection of statistics, regional science, economics, and geography, complemented by contributions from application domains such as ecology and epidemiology. In terms of analysing human-geographic phenomena, the field is conceptually underpinned by ideas that respond to a largely analogue world. In that world, human spatial experiences were hardly influenced by real-time information and there was no profound interweaving between everyday geographical experience and digital technologies. These circumstances have changed fundamentally in recent years. Digital technologies, whether visible or invisible, are now routinely embedded in everyday practices. Geographers have begun to theorise the new kinds of geographies that emerge from these socio-technical contexts, but spatial analysis has so far hardly responded to these new kinds of spaces. This talk begins with an overview of digital geographies and corresponding space concepts. Building on this, challenges for spatial analysis will be discussed, including some contributions the speaker has made in recent years.
17.01.2023	(14:15) Liberation from the physical constraints of the service space	Assist. Prof. Keiichi Zempo	University of Tsukuba
Physical laws do not bind interaction through VR space. Therefore, remote persons can wear avatars of their choice, easily connect with remote persons, and individually customize the shared space, for example, by adjusting the volume individually. In the first half of this presentation, we will show examples of service applications that break physical constraints in VR space, and in the second half, I will show how to create contact points in VR space without using HMDs. First, I introduce the audiovisual experience in a virtual reality (VR) service context that enables a more effective interaction between a user immersed in a virtual environment (VE) and an avatar as a store staff. By utilizing the characteristics of VE experiences, we find the effects of this unrealistic relationship between the visual and auditory positions of the avatar presented to the user variable rather than uniformly presented in the same position. In this study, we experimented with investigating how the positional deviation between the sound and visual images can be tolerated in VE, the effect of positional deviation on the interpersonal distance to the avatar, and the possibility of manipulating the impression of the avatar by deviating the sound image from the visual image. Next, I present research on hardware that enables interaction with virtual objects without the need to wear an HMD. This study seeks to demonstrate that a navigation system using stereophonic sound technology effectively supports visually impaired people in public spaces. In the proposed method, the stereophonic sound is produced by a pair of parametric speakers for a person who comes to a specific position, detected by an RGB-D sensor. The sound is a stereophonic earcon representing the target facility. The recipient can intuitively understand the direction of the target facility. K. Zempo, A. Yamazaki, N. Wakatsuki, K. Mizutani and Y. Okada, Mouth-in-the-Door: The Effect of a Sound Image of an Avatar Intruding on Personal Space That Deviates in Position From the Visual Image, in IEEE Access, vol. 10, pp. 125772-125791, 2022, doi: 10.1109/ACCESS.2022.3222804. Y. Mashiba, R. Iwaoka, H.E. Bilal Salih, M. Kawamoto, N. Wakatsuki, K. Mizutani and K. Zempo, Spot-Presentation of Stereophonic Earcons to Assist Navigation for the Visually Impaired, in Multimodal Technol. Interact. vol. 4, 42, 2020, doi: 10.3390/mti4030042. N. Kuratomo, H. Miyakawa, S. Masuko, T. Yamanaka and K. Zempo, Effects of acoustic comfort and advertisement recallability on digital signage with on-demand pinpoint audio system, In Applied Acoustics, vol. 184, 108359, 2021, doi: 10.1016/j.apacoust.2021.108359.
24.01.2023	[ERCIS Lunchtime Seminar] New innovation paradigms for networked urban ecosystems	Rui José	Universidade de Minho
Becoming a smart city is now a common aspiration for cities across the world. Many have established innovation ecosystems to promote the digital transformation of their territories, embracing a broad range of dimensions, such as mobility, energy, digital governance, sustainability or the entrepreneurial context. A few years into this transformation process, we now have a considerable body of research literature reporting on the successes and limitations of various types of innovation strategies and how they have been applied across numerous smart city initiatives. The promotion of local innovation ecosystems composed of multiple types of stakeholders, including citizens, is often mentioned as a key success factor. However, this idea of many independent ecosystems, each focused only on a specific territory, can also lead to considerable fragmentation and may fail to offer the type of combinatorial innovation and shared learning that is essential for the consolidation of successful practices and for the acceleration of the transformation process. This talk analyses how the promotion of extra-ecosystems connections may unlock new sources of innovation and discusses some of the areas where this approach could be more valuable. Short Bio: Rui José got his PhD in Computer Science in 2001 from Lancaster University, UK, and he is now a full member of Centro Algoritmi, where he leads the Urban Computing Lab. His research interests include Ubiquitous Systems, Sustainable Mobility, Smart Cities and Digital Innovation. He has over 140 publications in books, book chapters, journals and conference proceedings. Rui José has been PI or co-PI in 9 competitive funding projects, including projects funded by international programs, such as FP7, FET-OPEN and Portugal/CMU. Rui José is also an entrepreneur, having created 3 companies, two of which were officially awarded the label of University of Minho spin-offs.
31.01.2023	Institute Meeting (ifgi staff only)
Sorry, no abstract available yet.

GI-Forum Summer 22

Date	Topic	Presenter	Affiliation
05.04.2022	Institute Meeting
(for ifgi staff only)
12.04.2022	Artificial neural networks with partial convolutions for spatiotemporal gap filling	Marius Appel	ifgi
Deep learning models have been demonstrated to be able to learn dynamics like advection and diffusion of spatiotemporal processes. Applying such models on satellite observations is, however, often difficult due to large gaps in the data. This talk presents some ongoing work how partial convolutions can be used to fill gaps in spatiotemporal image time series. As such, a U-Net-like three-dimensional (partial) convolutional neural network is applied on Sentinel-5P data to create quasi-global gap-free images of atmospheric carbon monoxide. Some challenges and future ideas are discussed.
19.04.2022	A framework for processing big Earth Observation data for the Brazil Data Cube platform	Vitor Gomez	ifgi / INPE
In recent years, Earth observation satellites have generated large amounts of geospatial data freely available for society and researchers. This scenario challenges traditional spatial data infrastructures to properly store, process, disseminate and analyze these big data sets. To meet these demands, novel technologies have been proposed and developed, including the Brazil Data Cube (BDC) platform. In this talk, I will give an overview of the BDC project and the work in progress for the development of a framework for processing large volumes of EO data for the BDC platform. The purpose of this framework is to facilitate the build and distributed execution of chains of processes applied to EO data. This framework will support the OpenEO interface to provide users with a standardized way to customize and run pre-defined chains of processes.
26.04.2022	Long-term NO2 exposure assessment: statistical mapping and space-time activity simulation	Meng Lu	University of Bayreuth
Poor ambient air quality represents one of the largest environmental risks to public health. Quantification of long-term personal exposures over a large population is required in epidemiological studies and risk assessment and abatement. Exposure can be quantified by aggregating spatiotemporal pollutant concentrations along the space-time trajectories of each individual. This implies the challenges of 1) detailed spatialtemporal air pollution mapping and 2) human space-time activity modelling. Problems in air pollution mapping are induced by data deficiency and the heterogeneous pollutant emitting sources and dispersing processes at different areas. Human space-time activity modelling subjects to increased uncertainty associated with an increment in spatial scales due to less human mobility tracks and surveys. Exposure assessment calls for an activity model that quantifies the uncertainty, is flexible in integrating diverse mobility-related data such as national microcensus, geocoded social media data, mobile cellular data, and satellite imagery, as well as can use existing human movement theories and account for human-environment interactions. In this talk, I will introduce the current development of statistical modelling for spatiotemporal mapping and agent-based space-time activity modelling.
03.05.2022	GNSS in displacement monitoring and meteorology applications	Michal Kačmařík	TU Ostrava
Global Navigation Satellite Systems (GNSS) play an important role in our civil as well as professional lifes. After a short introduction of current status of this technology the talk will mainly concentrate on two areas of GNSS applications: displacement monitoring and meteorology. In the case of the former, examples for several natural and artificial phenomena will be given. Although a connection of GNSS and meteorology may sound strange, GNSS meteorology represents a well established technique for estimation of tropospheric water vapour from GNSS signals and its usage in operational meteorological applications. We will take a look on its main principles and usability.
10.05.2022	Earth visualizations: Can eXtended realities provide solutions for societal challenges?	Alexander Klippel	Wageningen University
No doubt, Earth is in a dire situation, and the Anthropocene creates challenges for the planet's health of a magnitude previously unimaginable. The overconsumption of various resources leads to irreparable damages with dire consequences for planetary and human health. At the same time, we have seen substantial advances in science and technology in recent years. Yet, we have never been able to monitor and understand the causes and effects of human action in more detail than today. The challenge is to translate scientific insights into actions and use technology creatively and effectively. Visualization has always played a role in making data more accessible and communicating scientific findings to the public. However, a pessimistic assessment could argue that it has failed so far to make a sufficient difference. With the emergence of immersive technologies, or eXtended realities, as a consumer-oriented technology, we can ask whether recent development in creating more visceral experiences rather than abstract visualizations might hold the key to addressing at least some of the challenges more efficiently. In this presentation, I'll discuss two avenues for research on how eXtended realities can offer potential solutions for societal challenges. First, we can efficiently visualize data and states of the Earth in the present, past, and future and for almost every part of the world. Not just as traditional maps but as actual experiences. Second, we can provide people with powerful tools to explore scenarios and experience the consequences of their decision-making, locally but also globally. The key, as always, is to provide empirical evidence of whether or not eXtended realities are an effective approach.
17.05.2022	Animals in a changing world - challenges and opportunities	Sascha Buchholtz	Institute for Landscape Ecology, WWU
Animals around the world are confronted with novel stressors, such as urbanisation, biological invasions or pollution. But what do these actually mean? How do animals respond to ecological novelty and what is ecological novelty anyway? In this context, we often talk about novel ecosystems, especially in cities. While many scientists assume that cities are rather detrimental to biodiversity, others assume that - despite ecological novelty - new opportunities for biodiversity arise here. This is what I will be talking about. How should current biodiversity dynamics in cities be assessed? Are there winners and losers among animals - and why might that be? How can these questions be addressed experimentally? What potential do cities and other novel ecosystems have for biodiversity conservation?
24.05.2022	Question-Based Spatial Computing, an Update	Werner Kuhn	UC Santa Barbara
GIS have evolved as systems for making maps with computers - and largely remained that way for over half a century. Meanwhile, search engines and other web-based information systems can answer complex questions about a vast range of topics, including geography. How can GIS be thought of and evolve into similarly intuitive and powerful question-answering systems? In this talk, I will present the latest results from my research on Core Concepts of Spatial Information. They constitute a theory of questions about geographic environments, and of the quality of answers to such questions. They also show that clarifying and simplifying the conceptual foundations of GIS enables information systems that are more powerful, more useful, and easier to learn than those we have today.
31.05.2022	Cross validation with spatially clustered samples	Sytze de Bruin	Wageningen University
Mapping of environmental variables often relies on map accuracy assessment through cross-validation with the data used for calibrating the underlying mapping model. When the data points are spatially clustered, conventional cross-validation leads to optimistically biased estimates of map accuracy. The current work acknowledges that the biased map accuracy estimates obtained by conventional cross-validation are due to the domination of small residuals in the regions that are most densely sampled. Alternative cross-validation approaches for assessing map accuracy from such clustered sample data will be presented. The first method uses inverse sampling-intensity weighting to correct for selection bias. Sampling-intensity is estimated by a two-dimensional kernel approach. The two other approaches are model-based methods rooted in geostatistics, where the first assumes homogeneity of residual variance over the study area whilst the second accounts for heteroscedasticity as a function of the sampling intensity. The methods were tested and compared against conventional k-fold cross-validation and blocked spatial cross-validation using above-ground biomass and soil organic carbon stock maps covering western Europe. Results acquired over 100 realizations of five sampling designs ranging from non-clustered to strongly clustered confirmed that inverse sampling-intensity weighting and the heteroscedastic model-based method had smaller bias than conventional and blocked spatial cross-validation for all but the most strongly clustered design. For the strongly clustered design, where large portions of the maps were predicted by extrapolation, blocked spatial cross-validation was closest to the reference error metrics. However, blocked spatial cross-validation is not guaranteed to assess the extrapolation error. Rather, extrapolation is to be avoided by additional sampling or limitation of the study area.
07.06.2022	Pentacoast - No GI Forum
Sorry, no abstract available yet.
14.06.2022	Institute Meeting
(for ifgi staff only)
21.06.2022	Spatial data analytics for sustainable e-mobility	Martin Raubal	ETH Zurich
The transportation sector is one of the largest contributors to greenhouse gas emissions. In order to ensure livable environments for future generations, it will be necessary to reduce our CO2 footprint. Electric mobility promises such reduction by being more environmentally friendly and sustainable. In this presentation I will argue why spatial data analytics is essential for a transition towards sustainable e-mobility by demonstrating case studies including the potential of rooftop photovoltaic generation to cover individual electric vehicle demand and mobility-aware Vehicle-to-Grid (V2G) optimization for carsharing.
28.06.2022	Promoting environmental health equity in noise abatement policies through citizen science: entry points für geo-referencing digital tools	Natalie Riedel	StadtLabor
Environmental health inequities can result from both unequal exposures to environmental stressors such as noise (distributional injustice) as well as from unequal participation opportunities and intervention benefits from noise abatement policies (procedural injustice). A lack of perceived environmental control could link distributional and procedural injustice. Instead of becoming active for acoustic environmental quality, citizens might resign to the seemingly intractable exposure to transportation noise. Citizen science using geo-referencing tools could advance as a remedy by conferring environmental control perceptions – provided that it is embedded in meaningful policy change and succeeds in establishing digital inclusion. In this line, this contribution aims to give an idea of potential entry points for geo-referencing digital tools to promote environmental health equity in noise abatement policies.
05.07.2022	What is "truth" in thematic mapping from Space?	Prof. Dr. Steffen Kuntz	Airbus Defense and Space GmbH
In remote sensing automated classification methods are frequently applied. Especially when satellite imagery is used large areas of the Earth´s surface are acquired and mapped. However, a critical issue which always appears is the quality of the thematic mapping approach. Quality Control of products and services in remote sensing is frequently carried out by an “Accuracy Assessment” comprising an essential (and possibly costly) part of every Land Cover /Land Use (LC/LU) product. Accuracy assessment is necessary for the producer as well as the customer to have quantifiable measures about the product’s quality building up trust in the product and in order to be able to mitigate deviations and justify efforts. However, what is "the [ground] truth" in thematic mapping from Space or how can you be sure that what you see from space is what you need for your planning purposes and how to convince other people that this is really something they might trust? Some thematic classes are always classifiable with high accuracy, such as “water bodies” or “dense forest”. But other classes may show much worse accuracy or could be confused among each other (e.g. winter wheat vs. winter barley, or orchards vs. open forests) as their reflectance properties are very close to each other while their main difference comes from their use (i.e. based on technical or legal definitions). The presentation will discuss the term “ground truth” and will show approaches for an exhaustive accuracy assessment which cares for the production methods, their strict implementation and appliance as well as the geometric and thematic accuracy of the final product (i.e. thematic geo-information with a certain level of validated accuracy).
12.07.2022	Institute Meeting
(for ifgi staff only)

GI-Forum Winter 21/22

Date	Topic	Presenter	Affiliation
12.10.2021	Institute Meeting
For ifgi staff only.
19.10.2021	Observing and predicting patterns of biodiversity using remote sensing data: A study case from the Brazilian Atlantic rainforest	Andrea Paz Velez	ETH Zurich
Understanding how species are distributed is essential for accurate protection of biodiversity. This includes an understanding of the multiple dimensions of biodiversity and their environmental correlates. However, there is little consensus on which environmental variables are best at predicting multiple dimensions of diversity. Here, I show there are common environmental correlates of diversity, despite ecological differences, across nine clades of plants and animals distributed along a single rainforest domain. These environmental correlates can be obtained both from weather station based sources or from satellite observations and the latter are equally good or better at predicting biodiversity patterns. Based on these results I show how environments can be used to predict biodiversity changes in near-real time based on environmental data gathered periodically through remote sensing.
26.10.2021	From Spatial Data to Information	Ben Gräler	52°North Initiative for Geospatial Open Source Software GmbH
Data is omnipresent, ranging from small to large spatial and temporal scales. Data is faced with open questions and challenges that need to be answered and addressed. There are a variety of tools and approaches to turn data into information that provides answers and helpful insights. 52°North is involved in several research and development projects where tools and technologies are tailored to provide answers to open questions. The KI:STE project aims at providing an analysis ready machine learning infrastructure to model earth system data. In MariData, routes of cargo ships shall be optimized based on heterogeneous environmental data and forecasts to reduce their energy demand. RIESGOS is concerned with interoperable chaining of multi-risk models. In my presentation, I will discuss recent activities and developments of these spatial information solutions: ML-based water classification from Landsat and Sentinel SAR images, modeling of marine cargo ships, uncertainty enabled multi-risk models, and custom research data infrastructures.
02.11.2021	[Zoom only] Remembering routes – how do the visual characteristics of a virtual environment affects short and long term recall?	Arzu Çöltekin	University of Applied Sciences and Arts Northwestern Switzerland
Memorability of a route during navigation is affected by multiple factors such as if the learning is incidental or accidental, if the memory capacity of the learner is high or low, or if their attention is focused or wandering. In this talk we present a study that tackles how the manipulating visual characteristics, specifically levels of visual realism, color and height-variability, affect the memorability of a route in a virtual reality experiment. We examine differences based on age, visuospatial memory capacity and declining spatial cognitive abilities on route recall in the context of navigation [1,2,3,4]. References: [1] Lokka, I-E., Çöltekin, A., Wiener, J., Fabrikant, S.I., Roecke, C. (2018). Virtual environments as memory training devices in navigational tasks for older adults. Scientific Reports. https://doi.org/10.1038/s41598-018-29029-x, https://www.nature.com/articles/s41598-018-29029-x (open access) [2] Lokka, I-E., Çöltekin, A. (2020). Perspective switch and spatial knowledge acquisition: Effects of age, mental rotation ability and visuospatial memory capacity on route learning in virtual environments with different levels of realism. Cartography and Geographic Information Science. https://doi.org/10.1080/15230406.2019.1595151 [3] Lokka, I-E., Çöltekin, A. (2019). Towards optimizing the design of virtual environments for route learning: An empirical study of memorability with changing levels of realism. International Journal of Digital Earth. http://dx.doi.org/10.1080/17538947.2017.1349842 [4] Lokka, I. E., & Çöltekin, A. (2018). Evaluating route learning performance of older and younger adults in differently-designed virtual environments: A task-differential analysis. In: ISPRS -International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4, 383-387. Delft. Netherlands. October 1st-5th, 2018. https://doi.org/10.5194/isprs-archives-XLII-4-383-2018 (open access, CC) This session will be presented online via Zoom only.
09.11.2021	Five initiatives to create an open research environment	Dr. Markus Konkol	University of Twente
Open Science (OS) is an umbrella term comprising principles to increase the transparency of research. Besides Open Access to scientific articles, these principles contain public availability of reusable methods (e.g., code and tools), data, and educational materials. OS can help to advance the scientific field and increase the impact on society, which is particularly important in times of climate change and pandemics. Despite these benefits, OS is rarely done in practice and often perceived as a burden. In this talk, I will outline five initiatives to realise the transition towards OS at the Faculty of Geo-information Science and Earth Observation (ITC). These initiatives address cultural and technical obstacles around OS, considering the needs of different actors involved in a scholarly environment, including authors, readers, reviewers, lecturers, and students.
16.11.2021	[Zoom only] Smart Sustainable Cities: Geospatial Challenges and Applications	Dirk Ahlers	Norwegian University of Science and Technology
t.b.a.
23.11.2021	[Zoom only] Your route to adventure - A look behind the scenes at komoot	Jan Torben Heuer	Komoot
Today, komoot is the most successful outdoor app in Europe. But how started everything and what have been obstacles on the way? How do you build a great product for the consumer mass-market? What is powering the komoot backend behind the scenes and what kind of GI technology is used at komoot? This virtual tour through komoot & history should answer all your questions.
30.11.2021	[Zoom only] Reproducible Cartography	Timothée Giraud	Centre national de la recherche scientifique
As any scientific production, maps must be disputed and debated. The implementation of reproducible processes based on free software and open data is essential. This objective can be achieved in the R software thanks to its rich, dynamic and mature spatial ecosystem. Several R packages allow to leverage the power of major FOSS libraries (like GDAL, GEOS or PROJ) for spatial data management. mapsf is an R package that takes advantage of this ecosystem to create and integrate thematic maps in R workflows. It helps designing various cartographic representations and offers several functions to display layout elements improving the graphic presentation of maps. Moreover, R, via its package system, offers a framework allowing to easily disseminate innovative or complex spatial representations that can be challenging or cumbersome to create with more classical GIS solutions. In this talk, we will present the thematic cartography package mapsf and a set of smaller packages dedicated to more specific map types. Spatial representations created with R are fully reproducible and we argue that they can reach the same visual quality level as those built with a classical mapping or GIS software.
07.12.2021	[Zoom only] Semantic based spatial predictions using deep learning	Marvin McCutchan	TU Vienna / IARAI
Spatial predictions often rely on raster data (e.g remotely sensed imagery) as information source. While such regular data might be ideal for deep neural networks (DNNs) as input, it also simplifies the representation of the world. In contrast, geospatial vector data such as from openstreetmap or linkedgeodata provide a geographically and semantically detailed description of the world. However, the irregular structure of their semantic (e.g. the feature type, such as restaurant or school) and geometric features (points, polygons, linestings) make it a challenging task to pass it to DNNs as input to spatially predict. In this presentation, one of the most prominent spatial prediction tasks is used as a use-case, namely land use and land cover (LULC) classification, to illustrate, how geospatial vector data with semantic annotations (from linkedgeodata) can be used to spatially predict. In this realm, the advantages of semantic and vector-based data sources over raster data are shown, how they synergize, as well as current and future research on how DNNs can encode, embed, or explicitly model this irregular information sources.
14.12.2021	[Zoom only] Linking Earth observation to global supply chains to support sustainable development	Victor Wegner Maus	Vienna University of Economics and Business
Complex international supply chains drive land-use changes worldwide, creating local environmental and social impacts that are spatially heterogeneous. Linking these impacts to the production of specific commodities is thus key to analysing the sustainability of consumption patterns. However, spatial information on the sourcing sites for raw materials (e.g. crops and minerals) are usually not reported. This talk will present recent advances using Earth observation data to map environmental impacts driven by global demand. I will show applications of Earth observation to assess the global mining sector's land use and deforestation and two case studies in Brazil. In the first example, I show an assessment of regional development associated with mining and, in the second example, the spatial links from soy production sites to consumption.
21.12.2021	[Zoom only] Geospatial Data Science for Public Health Surveillance	Paula Moraga	King Abdullah University of Science and Technology
Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. In this talk, I will give an overview of statistical methods and computational tools for geospatial data analysis and health surveillance. I will illustrate some of my projects in the following areas: 1. Geostatistical models for the integration of spatially misaligned data with applications in air pollution. 2. Modeling architectures to understand the spatio-temporal patterns and identify targets for intervention of tropical diseases. 3. Open-source statistical software such as the R packages epiflows for risk assessment of travel-related spread of disease, and SpatialEpiApp for disease mapping and the detection of clusters. Finally, I will describe my future research and how it can inform policymaking and improve population health globally.
11.01.2022	[Zoom only] Eye Tracking and Visualization	Kuno Kurzhals	ETH Zurich
This talk is about the different applications of eye tracking technology and how visualization supports the analysis of recorded gaze data. We will cover basic techniques that are applied, as well as latest research from our side. While many good techniques exist to investigate data from remote eye tracking on monitors, the analysis of mobile eye tracking data (e.g., recorded with glasses or in AR/VR) still poses many challenges. We will discuss how image-based approaches might leverage the combination of machine learning and interactive visualization techniques to support the analysis of mobile eye tracking data in the future. Furthermore, we will also address how gaze-based interaction can be applied to support visual interfaces.
18.01.2022	Institute Meeting
For ifgi staff only.
25.01.2022	[Zoom only] Smart City Münster	André Wolf	Smart City Münster
Münster has set out to become a Smart City. The city wants to remain attractive by using data and digital applications for future generations, for business, science and Münster's citizens and neighbors: Münster wants to use the possibilities of digitalasation in such a way that life in Münster gets better - more comfortable, more livable, more climate-friendly, healthier, more mobile, more social, safer and more resilient. At its core, it is about urban development in the digital age. To this end, the Smart City Unit was established at the city of Münster in September 2019. The talk gives an overview of: What is the understanding and what is the status of the Smart City Strategy? Which projects already exist and what is being worked on? Who are key stakeholders and partners in the development of a Smart City? It is also pointed out that a smart city not only requires data and technology, but also good communication and participation.
01.02.2022	[Zoom only] Development of the ability to imagine spatial transformations	Andrea Frick	University of Fribourg
One of the most impressive skills of the human species is the ability to generate mental images of 3D objects or scenes, and to transform the spatial properties of these mental representations in various ways (e.g., rotating, bending, or folding them). Over a century of psychological research has established that such spatial thinking is foundational to many cognitive tasks. It also helps reasoning in domains that are not obviously spatial, and thus has important applications in various science disciplines and professions. Using mental spatial transformation, a neurosurgeon can visualize particular brain areas and plan a surgical procedure, an engineer can anticipate how various forces affect the design of a structure, and a geoscientist can conceive of the processes that affected the formation of the earth. In this presentation, we will take a closer look at the development and usefulness of the ability to imagine things and to mentally transform them in a prospective fashion.

GI-Forum Summer 21

Date	Topic	Presenter	Affiliation
20.04.2021	Individual differences in cognitive mapping and the possibility of training: How do people differ and can they be trained and assisted?	Toru Ishikawa	Tokyo University
Spatial ability plays important roles in academic learning in STEM (science, technology, engineering, and mathematics) disciplines and everyday activities. Because of its importance, thinking about space has now been extensively discussed in a broader context of spatial thinking. A type of spatial thinking that is of particular significance to people's daily lives is cognitive mapping, that is, the process of acquiring, representing, and using knowledge about spatial environments. The skill of cognitive mapping shows large individual differences, however, and the task of spatial orientation and navigation poses great difficulty for some people. Given such large individual differences, it is not very meaningful to ask whether people's cognitive maps are maplike; rather, it is important to explore how and why people differ so much in the fundamental ability of cognitive mapping. In this talk, I will look at the motivation and findings in the research on spatial knowledge acquisition from an individual differences perspective, and particularly discuss the possibility of improving cognitive mapping by training and adjusting the society to the wide variations in spatial aptitudes and preferences among people. I also discuss possible cognitive consequences of the use of satellite navigation on people's sense of place and orientation. Biographical Sketch: Toru Ishikawa is a Professor in the Department of Information Networking for Innovation and Design (INIAD) at Toyo University, Tokyo, Japan. He has a PhD in geography from the University of California, Santa Barbara, and is an associate member of the Science Council of Japan. He specializes in cognitive-behavioral geography, geographic information science, and urban residential environments and planning. His research interests include cognitive maps and mapping, wayfinding and navigation, spatial thinking in geoscience, and geospatial awareness and technology. He is an editorial board member of the Journal of Environmental Psychology, Spatial Cognition and Computation, Cognitive Research: Principles and Implications, and the Journal of Architectural and Planning Research, and an author of the book Human Spatial Cognition and Experience: Mind in the World, World in the Mind (London: Routledge, 2020).
27.04.2021	Postponed to June 29
Sorry, no abstract available yet.
04.05.2021	Using mathematical modelling studies for political decision-making during the pandemic - chances and challenges	André Karch	Institute of Epidemiology and Social Medicine, WWU
Results of dynamic mathematical models simulating the spread of infections in populations have been featured intensively in the media during the first, second and third wave of the SARS-CoV-2 pandemic. In this talk I will discuss the chances and limitations of using dynamic mathematical models in the field of public health decision-making during the early and advanced phase of a pandemic. I will present the methodology behind these models, and specifically focus on how assumptions about heterogeneity in effective spreading and contact behaviour affect modelling results and public health conclusions. For this, I will present results from the COVIMOD study, an ongoing contact behaviour survey performed by our group in Germany. I will also discuss how geographical heterogeneity is and needs to be taken into account in different modelling approaches, and which challenges arise.
11.05.2021	Applications of navigation research in complex urban environments	Panos Mavros	Future Cities Laboratory (FCL) of the Singapore-​ETH Centre
Spatial cognition and wayfinding research have focused extensively to the study of our interactions with the environment, how we perceive, think and navigate in space. Besides fundamental research, wayfinding studies can also contribute to our understanding of how different types of environments and interfaces are understood and used by people. In turn, such studies can inform how spaces and interfaces are designed, in the rapidly developing evidence-based design paradigm. In this talk I will present different studies conducted at the Cognition Perception and Behaviour in Urban Environments group, at the interface between spatial cognition research and urban design. In particular, how wayfinding studies were devised to understand human behaviour in building typologies popular in Singapore, to evaluate the interface between space and new technologies such as autonomous vehicles and wayfinding systems.
18.05.2021	Micro Metropolis - Towards a new Indoor Urbanism	Ulrich Blum	Münster School of Architecture / Zaha Hadid Architects
Prof. Blum will introduce ideas and concepts of a new Interior Urbanism currently explored by Zaha Hadid Architects and elaborate on methods how those buildings and spaces can be designed, analysed and optimized.
25.05.2021	Pentecost - No GI Forum
Sorry, no abstract available yet.
01.06.2021	Institute Meeting (ifgi employees only, no GI Forum)
Sorry, no abstract available yet.
08.06.2021	Intelligent Software, Healing Environments	Carl Peter Leslie Schultz	Aarhus Universitet
Health and safety in the built environment is an urgent, ubiquitous, and costly issue: in 1999 the National Academy of Sciences reported that annual fatal accidents in US hospitals outnumbered deaths in motor vehicle accidents. There is significant potential for information technology (IT) solutions to assist architects and hospital directors in enhancing health and safety. In my talk I will present our research on "human-centred" automatic building floorplan analysis, specifically: (1) new ways of formally modelling human behaviour and perception in software that natively integrates with industry-standard Building Information Models, and (2) new software tools for rapidly checking qualitative, ambiguous (but official!) building regulations and codes such as: "There shall be no direct line of sight between an access route or accessible route and bathroom facilities".
15.06.2021	Messy Maps: exploring flood risk and resilience in the urban Global South using qualitative GIS	Faith Taylor	Department of Geography, King’s College London
This seminar will present results from an interdisciplinary project looking at how we put a more inclusive definition of resilience on the map. Towns and cities across Sub Saharan Africa are rapidly urbanising, and now 1 in 10 of the world's population live in slums or informal settlements. These slums are increasingly exposed and vulnerable to hazards such as flooding and fire, yet are often 'missing from the map'. In this project, we use a range of qualitative GIS techniques such as immersive 360 degree Storyspheres and spatial social network maps to visualise what resilience means to low-income neighbourhoods in Nairobi (Kenya) and Cape Town (South Africa). I will also reflect on my experience as a quantitative physical geographer coming to grips with qualitative methods and the challenges/opportunities this has brought, especially in the era of Covid-19 disruptions to data collection!
22.06.2021	Starts 18:00! // From the media to storytelling maps: The ways in which maps connect the public to climate change	Carolyn Fish	Department of Cartography, University of Oregon
Maps are one of the myriad ways in which climate change is communicated to the public. They are powerful visuals which illustrate the often spatial and temporal aspects of our changing climate. However, research in climate change communication has shown that simply providing more data or information does little to change the minds of the public. Less is known about visuals, but it is increasingly becoming clear that connecting with people’s emotions and lived experiences are vital ways in which to change people’s attitudes towards climate change and change their attitudes towards taking action. Across three studies, I illustrate the many ways in which maps communicate climate change, are vivid to their readers, and tell stories which connect with readers' emotions. In the first study, I illustrate how data journalists at major news organizations in the United States create vividness in their map designs. In the second study, through content analysis, I show how maps across a plethora of media sources can be vivid in different ways to their readers. And finally, in a recent study we show the potential for storytelling maps to connect with emotions and how these maps are more likely to make these readers take action on climate change.
29.06.2021	EU Open Data Portal	Thore Fechner	con terra GmbH
Open Data in the EU (previously known as Public Sector Information) is heavily influenced by geoinformation / spatial data. Although it is not broadly visible, spatial data is often requested as open data. Due to roughly 20 years of development in the context of INSPIRE, spatial data can easily be made available as open data. However, spatial (open) data providers need to pay close attention to mainstream IT and Open Data trends as they are at risk of missing out on innovations that are currently taking place, e.g., linked data or real-time data. The talk will provide insights in how open data is published / collected in the EU using the EU Open Data Portal as example, while pointing out research potentials from the speaker’s point of view.
06.07.2021	The Influence of Human Mobility on Infectious Disease Spreading	Ben F. Maier	Robert-Koch-Institut
The ongoing COVID-19 pandemic has been dictating our lives for more than a year now, exceeding 175 million confirmed infections and 3.7 million deaths worldwide. While health care workers and medical staff are combating the pandemic on an individual level by pharmaceutical means, public health researchers are working to mitigate the disease’s spread by constantly estimating risks and trying to inform policy makers on efficient ways to mitigate this global crisis. Often, such efforts are supported by means of mathematical modeling of infectious diseases, a discipline with an almost century-long tradition that has been successfully used in numerous past local and global health crises. The simplest of such models usually break down the mechanics of infection to a few key principles, ignoring spatial and behavioral heterogeneities in populations. In this talk we will discuss how those can be incorporated in spreading models, focusing on human mobility and contact behavior that influence the spreading process of an infectious disease on different scales. We show (i) how we forecast the global spread of COVID-19 using the world air traffic network in January 2020, (ii) how the human mobility in Germany changed during the first "lockdown" in 2020 and how that change influenced the disease dynamics, and (iii) how Bluetooth-aided contact tracing apps can or cannot help to contain COVID-19 outbreaks. Finally, we reflect on the usefulness of models of increasing complexity and the boundaries of our field.
13.07.2021	Starts 18:00! // Geospatial Analytics for Urban Planning and Public Policy	Avipsa Roy	University of California, Irvine
Cities are urban systems of ever-evolving complexity. To make cities safer and plan its development in an equitable manner requires geographic data that is robust, nuanced and constantly updated. The growing availability of smartphones, wearable devices, and fitness trackers have resulted in a data boom making such data more available to researchers. However, there is a growing need to make sense of such data to understand how people move around in cities, how we can build our cities to be safer, fairer and more active. Such a challenge has led planners and decision-makers to focus on data-driven applications for policymaking. Geospatial analytics is an up and coming area which enables urban planners gain deeper insights from high resolution spatial and temporal data and extract actionable insights to make informed decisions. This talk will elaborate on how geospatial analytics can be used for urban planning decisions using several case studies such as 1) improved active transportation planning for all ages and abilities, 2) mapping changes in mobility patterns over time, 3) built environment monitoring and 4) exploring the role of social vulnerability on infectious disease spread like COVID-19.
20.07.2021	Institute Meeting (ifgi employees only, no GI Forum)
Sorry, no abstract available yet.

GI-Forum Winter 20/21

Date	Topic	Presenter	Affiliation
03.11.2020	Institute Meeting (ifgi employees only, no GI Forum)
Sorry, no abstract available yet.
10.11.2020	Spherical Geometry	Edzer Pebesma	ifgi
We see increasingly that spatial data come with coordinates expressed in degrees longitude/latitude, referenced e.g. to a WGS84 datum. The legacy GIS way of handling this is to map longitude to x, and latitude to y, which is essentially a Plate Carree projection, and hope that things work out. Many global datasets (e.g. of country boundaries) and even standards like GeoJSON have been adapted to accommodate this approach. However, recent open source libraries such as Google's s2geometry and Uber's H3 make it possible to work effectively under a spherical Earth model. This talk will show where legacy GIS gets things wrong, and discuss challenges with working with spherical geometry, illustrated by recent work in the R packages sf and s2.
17.11.2020	Towards Machine learning-driven Environmental Science	Ribana Roscher	Rheinische Friedrich-Wilhelms-Universität Bonn
Remote sensing observations play an important role in various communities, since they enable an accurate and comprehensive monitoring of the Earth and its changes - close-range as well as from space. The success of machine learning methods, especially neural networks, has led to a considerable spread of machine learning in scientific fields and now offers numerous possibilities for the analysis of remote sensing data. This talk presents selected approaches and looks at their potential for applications in the environmental sciences and agriculture. In this context, explainable machine learning and the possibilities to analyze scientific data are discussed.
24.11.2020	Statistical Machine Learning for Spatio-Temporal Forecasting	Andrew Zammit Mangion (from AU: at 9:00 am (CEST) time!)	University of Wollongong
Conventional spatio-temporal statistical models are well-suited for modelling and forecasting using data collected over short time horizons. However, they are generally time-consuming to fit, and often do not realistically encapsulate temporally-varying dynamics. Here, we tackle these two issues by using a deep convolution neural network (CNN) in a hierarchical statistical framework, where the CNN is designed to extract process dynamics from the process' most recent behaviour. Once the CNN is fitted, probabilistic forecasting can be done extremely quickly online using an ensemble Kalman filter with no requirement for repeated parameter estimation. We conduct an experiment where we train the model using 13 years of daily sea-surface temperature data in the North Atlantic Ocean. Forecasts are seen to be accurate and calibrated. We show the versatility of the approach by successfully producing 10-minute nowcasts of weather radar reflectivities in Sydney using the same model that was trained on daily sea-surface temperature data in the North Atlantic Ocean. This is joint work with Christopher Wikle, University of Missouri.
01.12.2020	Contained Chaos: Ensemble Consistency Testing for the Community Earth System Model	Dorit Hammerling (from US: at 16:00 am CEST)	Colorado School of Mines
State-of-the-science climate models are valuable tools for understanding past and present climates, and are particularly vital for addressing otherwise intractable questions about future climate. Given the societal relevance, maintaining model confidence is critical. The many complex processes characterizing the Earth System lead to inherently chaotic behavior within these models, meaning that output can be highly sensitive to seemingly minor changes to the hardware or software stack. This sensitivity makes defining “correctness” of model output separately from bit-reproducibility a practical necessity. To this end, we have developed a statistical testing framework that utilizes an ensemble of established simulations paired with principal component analysis to perform hypothesis testing for model correctness. This test is already implemented and provides valuable feedback to model developers and users. We are now exploring the impact of ensemble size on this test, specifically as it relates to systematic errors in estimating the unknown correlation matrix of the ensemble simulationsand we will provide an overview of our findings.
08.12.2020	If GIS provides the answer, what was the question again? Geo-analytical question answering as knowledge generation	Simon Scheider	Universiteit Utrecht
Geographic question answering (GeoQA) has gained attention recently as a special and particularly relevant case of question answering. In this talk, I will argue why question-answering with a Geographic Information System (GIS), which we call geo-analytical QA, needs to go beyond information retrieval and should be conceived as a form of knowledge generation instead. Based on examples from Human Geography, I will motivate this idea and discuss some principal thoughts about knowledge generation with a GIS. Work on this problem is currently done within the QuAnGIS project at Utrecht University. I will share some first results about the syntax and semantics of geo-analytical questions, and about the relevance of core concepts and semantic data types for this task. Furthermore, I will report on ongoing developments in the QuAnGIS project, concerning a geo-analytical grammar, the quality of answer workflow synthesis, and a data transformation algebra.
15.12.2020	Sustainability goals using Geoinformation Science: insights from local case studies on rural and urban areas	Tobia Lakes	HU Berlin
In 2015, sustainability goals and targets were agreed to be achieved by 2030. Geoinformation Science can plays an important role by providing indicators and analyses that help to assess the current situation and predict possible future development pathways. This talk will address the benefits and challenges using Geoinformation for addressing the sustainability goals. It will draw from different local case studies to discuss data usage, indicator development, trade-off analyses and scenario development. A critical discussion will conclude the talk.
17.12.2020	Resilience and Pedestrian Navigation Support	Chris Kray	ifgi
Part of the Resilience Colloquium Series. Thursday, December 17, 14:15 https://wwu.zoom.us/j/91080736949?pwd=dUZUcFozNjU3aXl2dGJWSVhFN2hxdz09 In this talk, Chris will present an initial analysis of resilience in the context of pedestrian navigation support systems (PNSS). He will first take a look at fundamental concepts and define key terms before proposing a systematic approach to describe, realise and evaluate resilience in the context of PNSS. Based on this initial framework, he will present a number of examples and strategies for dealing with stressors in PNSS, and he will highlight some gaps requiring further research. Rather than reporting on a fully validated theory, this talk is intended to spark further discussion and ideas in this area.
22.12.2020	Institute Meeting (ifgi employees only, no GI Forum)
Sorry, no abstract available yet.
12.01.2021	STAC and STAC Index	Matthias Mohr	Institute for Geoinformatics, University of Muenster
The SpatioTemporal Asset Catalog (STAC) is an emerging specification enabling better discoverability of spatial and temporal data. It’s driven by state-of-the art technologies and wants to get rid of the overly big numbers of proprietary portals and APIs for geo-data. This talk will give an introduction into the ideas behind the specification and guide you into how to publish your own data. Additionally, we’ll look into the growing ecosystem and will also have an outlook into how STAC Index crawls billions of records to make them available to a broad audience via Google and other search engines.
19.01.2021	Spatial analysis in the domains of ecosystem service assessments, public health and humanitarian mapping	Sven Lautenbach	HeiGIT
Space is of essential importance for an improved understanding of environmental problems as well as public health aspects. The talk is going to highlight the following aspects: 1. Analysis of ecosystem services (ES) with a focus on trade-offs of land use decisions 2. Use of volunteered geographic information (VGI) to assess the demand for ES 3. Use of OpenStreetMap (OSM) to quantify accessibility of health sites The quantification of trade-offs of land use decisions employs a spatial optimization approach based on a genetic algorithm at the examples of global land use allocation and urban development in Switzerland. Use of VGI for the demand of ES is shown at the example of an analysis of Flickr data for land use aesthetics and the use of environmental ambulatory assessments to quantify the effects of urban green space on city dwellers. The last part of the talk touches on the availability of OSM at the global scale and its use in accessibility analysis for health sites in sub-Saharan Africa and Germany.
26.01.2021	FORCE - Analysis Ready Data and Beyond	David Frantz	Humboldt University Berlin, https://www.geographie.hu-berlin.de/en/professorships/eol
We are currently experiencing an exciting new era of Earth Observation, wherein multiple, freely available remote sensing systems provide us with plenty data that might enable us to achieve sustainable development goals by closely monitoring environmental status and change at relevant scales. However, this flood of data can easily be overwhelming, both in terms of volume and usage complexity. While the first point is merely a technical burden, EO data still need to be processed to a considerable degree before being adequate for most analyses. FORCE is being developed to be an ‘all-in-one’ solution for the mass-processing of medium-resolution satellite image archives to enable large area and time series applications. FORCE is capable of processing Landsat 4–8 and Sentinel-2 Level 1 data to Level 2–4 products, which are essentially different degrees of Analysis Ready Data (ARD) and empower much broader user groups in using mass EO data. The term ARD is mostly used to describe data that are radiometrically and geometrically consistent, and that include cloud and other poor quality observation flags that allow filtering data prior to analysis. This definition is well aligned with FORCE Level 2 ARD, i.e. radiometrically corrected Bottom-of-Atmosphere reflectance products. FORCE Level 2 data are accompanied by pixel-based quality information and are stored in a gridded data cube using a single projection across large areas. Whilst these data can indeed be directly analyzed, usage is complex nonetheless. Therefore, FORCE provides Level 3 functionality to provide seamless, gap free, and highly Analysis Ready Data (hARD) over very large areas via Best Available Pixel (BAP) compositing and Spectral Temporal Metrics (STM). Unlike ARD, hARD are much better suited as input for many machine learning applications, e.g. for large area land cover /change classification purposes. FORCE additionally provides Level 4 modules, e.g. for performing time series analyses like change and trend analyses, as well as machine learning functionality to convert hARD into application-ready (hARD+) maps of qualitative or quantitative target variables. The talk will close with a selection of practical use cases highlighting the usage of “ARD and beyond” for national to regional scale mapping of a wide variety of qualitative and quantitative target variables.
02.02.2021	(no GI Forum this week)
Sorry, no abstract available yet.
09.02.2021	Institute Meeting (ifgi employees only, no GI Forum)
Sorry, no abstract available yet.

GI-Forum Summer 20

Date	Topic	Presenter	Affiliation
28.04.2020	Wayfinding Through Orientation	Angela Schwering	ifgi
t.b.a.
05.05.2020	Disinformation via Social Media: Social Bots, Campaigns, and Computer Science Approaches to foster Resilience	Christian Grimme	WWU, Department of Information Systems
Social media platforms have become central institutions for social and private content sharing as well as network building. This may foster democratic principles such as open sharing of opinions and freedom of speech. At the same time, however, the tight coupling of global networks, information propagation, and the underlying technical infrastructures allow for strategic manipulation of the public opinion. Automation and coordinated human campaigns can amplify topics worldwide without being recognized as such by users, who lack a global view on the networks. To make it even more complicated, the amount of data and information running through the networks is too large for human analytical capabilities. In this talk, I will give a brief overview on the phenomenon and types of manipulation via social networks as well as on the challenges of detecting automation and orchestrated behavior in this socio-technical ecosystem. This comprises work from the German multi-disciplinary project PropStop as well as perspectives for the current Australia-Germany Joint Research Co-operation Scheme on campaign detection in social media.
12.05.2020	The Cartography of COVID-19	Thomas Bartoschek	Institute for Geoinformatics
Epidemiology and maps belong together. Probably not only starting with John Snows Cholera Map maps helped to understand the spatial distribution of spreading epidemic or pandemic phenomena. Nowadays - in ages where everybody is able to create maps - lacks in cartographical techniques often lead to misunderstanding and misuse of maps and may lead to wrong personal or political decisions. With the COVID-19 pandemic, maps on the spread of the virus and related topics are popping up every minute in online media, social media, news and other channels. This talk gives an overview of map types, mapping techniques and cartographical approaches being used by the “cartographers” and discusses good and bad examples, errors, fails and misunderstandings by surfing through and interacting with online maps.
19.05.2020	Monitoring Changes on Earth and in Space	Fabian Gieseke	WWU, Department of Information Systems
The field of data science has gained considerable attention over the past years. One reason for this phenomenon is the fact that the data volumes in various domains have increased dramatically. This is the case, for instance, in both astronomy and remote sensing, where current projects already produce data volumes in the petabyte range. Upcoming ones will produce such data volumes per day, week, or even per hour. A similar "data flood" can be observed in many other disciplines including medicine, biology, finance, business intelligence, energy systems, or social media. In most cases, the sheer data volumes render a manual analysis impossible. Machine learning techniques aims at extracting knowledge in an automatic manner and have been identified as one of the key drivers for future discoveries and innovation. Processing and analzying the massive amounts of data can, however, still become extremely challenging from a computational perspective and I work on overcoming such computational bottlenecks by developing efficient schemes that are adapted to the specific needs of the tasks at hand. My presentation will cover some of our current research activities that are related to this line of research. In particular, I will sketch the potential of efficient implementations for machine learning models in the context of detecting and monitoring changes in space and on Earth.
02.06.2020	How to combine qualitative interaction analysis and automatic movement tracking to understand people’s movement in public space	Wolfgang Kesselheim	University of Zurich
Tracking people’s movement in public space has long been equated with tracking the movement of individuals. However, our movements in public space often depend on the presence and the movements of other people, e.g. when we go on a shopping spree with our partner, when we cue with other people for the bus, or crowd together with other passers-by in order to watch the performance of a street artist. Furthermore, tracking has so far been limited to determining people’s coordinates in Euclidean space. However, in many cases it is not these coordinates, but the social meaning of areas and objects in public space that are relevant for people’s movements: a shop window, a bus stop, an open square, etc. If we want to fully understand how people make use of public space by automatically tracking their movements, we need to find a way to (a) overcome the individualising, atomising bias of movement tracking and (b) take into account the social meaning of objects and areas in public space. In my presentation, I will illustrate how this could be done by introducing two concepts developed within qualitative research on social interaction into 3-D movement tracking using Microsoft Kinect sensors: the concept of “F-formation”, which describes people’s bodily orientations when they interact with others, and the concept of “usability cues”, which aims at identifying activity potentials of objects and spaces.
09.06.2020	Moisture recycling and Global change	Stefan Dekker	Utrecht University
Tree transpiration may enhance rainfall for downwind forests. Until now it has been unclear how this cascading effect plays out. In this presentation I will show local forest transpiration and the subsequent trajectories of transpired water through the atmosphere by using high spatial and temporal detail. Different scenarios of deforestation and gIobal change are analysed and show which regions are most dependent on their own local recycling. I also will show the role of deep rooted trees and how forests can buffer against droughts.
16.06.2020	Remote sensing data and GIS as tools for archaeological fieldwork	Jana Eger and Tim Karberg	WWU, Institute for Egyptology and Coptic Studies
Since the past two decades, remote sensing data and their analysis by GIS became a common tool in archaeology. While in areas of temperate climate, like Central Europe, the investigation of so-called crop marks (indications of archaeological record within natural or agricultural vegetation) is still one of the most widespread methods in archaeological remote sensing, other approaches are necessary under the conditions of arid areas as well as the specific agricultural patterns of the African Sahel zone. While satellite images in the early 2000’s were mainly used for landscape archaeological investigations, nowadays these data is also in common use for on-site archaeological prospections. In this presentation, we will give a short introduction to the general methods of the archaeological use of remote sensing data and GIS, and further illustrate them by examples of their practical use within the archaeological field projects of the WWU in Sudan.
23.06.2020	Is graphical proximity in a map the same as geographical nearness?	Francis Harvey	University of Leipzig
“Near things are more similar than more distant things” states Tobler’s first law of geography. This seems obvious and has been well studied in cognitive research into the perception of the environment. The statement’s validity for assessments of geographical nearness solely from map symbols however has yet to be ascertained. This presentation considers this issue through a theoretical framework grounded in Gestalt concepts, behavioral ecological psychology and information psychology. It sets out to consider how influential experience or training may be on the association of graphical proximity with geographical nearness. Two pilot studies provide empirical results for the presentation of some initial findings. The findings regarding the influence of experience or training are ambiguous, but point to the rapid acquisition of affordances in the geovisualizations used for the studies as an important factor. A hypothesis is that “map-reading” is learnt and it has become implicit for most people in modern society, following Kant’s proposal that geography education is a propadeutic for scientific learning. The process of assessing distance in maps is generally reliable. How aptitude influences distance assessments and the role of geographical knowledge remain open questions for ongoing research.
30.06.2020	A GIS-based Assistance Tool for A Collective Solution After Participation (CoSolution)	Simge Özdal-Oktay	TU Vienna
Cities are complex, self-organized systems creating responsive social and environmental behaviors. Therefore, urban planning and design need adaptable, flexible, and effective tools for providing optimal, long-term solutions that will meet users’ needs. In this process, it is essential to connect with innovative methodologies for minimizing the possible conflicts between individual, communal, and political priorities. Many studies revealed that existing public participation processes are highly inefficient for understanding time and location-based patterns and providing an overall design outcome that satisfies collective preferences. One of the main reasons for this is the lack of time-efficient methods for the collective analysis of large data obtained through participation. The CoSolution project was developed based on this deficiency and aimed to develop an automated assistance system. The ultimate goal was enabling collective analysis of large spatial participatory data and generating spatial location alternatives for each design element subject to the planning/design activity. To achieve this goal, in the scope of the project, an algorithm was developed in Python which overlaps and time-efficiently analyzes alternative locations for each design element based on the Density-based clustering (DbScan). A participatory process was imitated for data collection purposes over a scenario for the reorganization of the Gusshaus campus courtyard at TU Vienna. During the process, the participants modified the existing layout of the courtyard by interfering with the design elements such as tables, trees, and green areas. Two experiments were conducted in 3D and Virtual environments. Collected modified plans later overlapped automatically on an adjustable grid and collectively analyzed with a series of GIS, and machine learning-based approaches. The results provided a baseline for more comprehensive tools and enabled comparisons between different analysis methods and visualization techniques.
07.07.2020	Google Earth Engine Introduction and Walkthrough	Gennadiy Donchyts	Deltares, The Netherlands
Earth Observation (EO) is a fast-growing field boosted by open-access satellite missions such as Landsat and Sentinel and by Cloud-based processing environment Google Earth Engine (GEE), allowing petabyte-scale processing freely available for research applications. In this presentation, I will talk about how the GEE works, what are the main differences from a classical-style GIS analysis, and how open-source GIS software like QGIS can be combined with the cloud-based GEE processing. We will also see how the GEE is used at Deltares to conduct research and develop EO-aware and Cloud-based software solutions for the monitoring of land-use changes, surface water mapping, and the derivation of bathymetry.

GI-Forum Winter 19/20

Date	Topic	Presenter	Affiliation
08.10.2019	Institute meeting
No GI Forum
15.10.2019	Towards a user-oriented modeling platform for agent-based simulations of infectious diseases	Johannes Ponge	University of Münster, Germany
Even in our modern day and age, infectious diseases and resulting epidemics still impose a great threat to humanity. The latest outbreaks of Ebola, Zika and the ever recurring Flu show, that these problems are a still highly important issue in our highly interconnected world. Agent-based computer simulations can help to understand the dynamics of a disease’s propagation, forecast its impact, and evaluate countermeasures. While many disease propagation models exists, there is an observable trend that many research projects start their simulation efforts from scratch without building upon available models. We argue that this effect slows down progress and makes it ever more challenging for simulations to reach maturity and go beyond current limits. Furthermore, most biomedical or epidemiological researchers do not have extensive background in programming which, in most cases, is necessary to implement sophisticated models. We propose a novel model structure for agent-based epidemics models and an accompanying modeling platform that tackles both problems. An interoperable model design makes it possible to build new models from previous components and add features where needed. A fully code-free modeling platform with visual analytics features enables non-IT experts to design and analyze sophisticated propagation scenarios. I will present the current state of our project and explain our modeling approach on different abstraction levels from a code-free model editor down to the implementation of the agent-based model including some example simulations with our software tool.
22.10.2019	Understanding social-ecological systems in the context of global change	Maria Santos	University of Zürich, Switzerland
The unprecedented rates of biodiversity loss are threatening the functioning and the services that support Earth system processes and livelihoods that depend on them. While global assessments are demonstrating potential collapses in the systems that support carbon cycling, water and nutrient cycling, we lack a detailed assessment on the implications of local social-ecological processes that cumulate to the planetary level. Local processes are far-reaching in space, time and phenomena, and better understanding of the complex relationships and co-evolution between ecosystem and social processes is much needed. In this talk I will present a conceptual framework that aims to depict the complex interaction between social and ecological systems, and show a few examples of its operationalization from different ecosystems (tropical forests, water systems, etc.) that focus on human-resource and human-biodiversity interactions. I will present the work that our group at UZH has been developing, and how we envision that such approach will contribute to broaden our understanding on the interactions and the co-evolution of social ecological systems towards a better prediction of the response space in the context of global change.
29.10.2019	Recent hydro-climatic shifts over Central America	Iris Stewart	Santa Clara University, USA
Smallholder farmers across Central America have relied on rain-fed agricultural practices adapted to local precipitation patterns for food and water security. Droughts in the region have been linked to crop failures, outbreaks of pests and plant disease, economic losses, and health impacts. Under global warming, output from GCMs project overall precipitation decreases for Central America by the end of the century. Although global surface temperature has been increasing, and hydro-climatic shifts consistent with GCM predictions have been observed in other regions, the magnitude, direction, and significance of any recent precipitation changes over Central America is not clear. We use the CHIRPS, ERA5, and MERRA, data sets at the 0.25° spatial resolution to investigate the presence of hydro-climatic shifts in the region for the recent decades (1981 – 2018). The parameters analyzed are (i) trends in the monthly and annual precipitation, (ii) the timing, and magnitude of the rainy season(s), and (iii) the intensity, timing, frequency, duration, and spatial extent of drought. Results indicate shifts in the intensity and timing of the rainy periods and the midsummer drought and more intense and more frequent drought periods along the Meso-American dry corridor. The direction of the shift resembles the much larger shift anticipated with continued climate disruption, and thus may be a starting point for crafting adaptation policy.
05.11.2019	Google Earth Engine - Planetary Scale Analysis for Societal Benefit	Noel Gorelick	Google Earth Engine & University of Zürich, Switzerland
Earth Engine is a data analysis and visualisation platform build on top of Google's massive computing infrastructure. Hosting a 25PB catalog of satellite and remote sensing data, Earth Engine helps many thousands of users from around the world measure, monitor and map the environment at a global scale. This talk will give an overview of the genesis and development of the Earth Engine platform and some examples of how it's being used to address some of society's biggest challenges.
12.11.2019	Diversity of Giftedness and Talent Development - Excellent learning environments across the educational biography	Christian Fischer	University of Münster, Germany
The International Center for the Study of Giftedness (ICBF) is a cooperative research institution of the Universities of Muenster, Osnabrueck and Nijmegen and was founded in 2001. The aim of the ICBF – supported by the ICBF foundation - is to combine and complement the experience and expertise of the involved universities in the areas of talent research, gifted education, as well as teacher training and further education in the area of potential development and talent support. The icbf has grown out to an expert institution in the field on the diversity of giftedness and talent development, offering expertise and a network of international and national researchers and practitioners in the field of excellent learning environments in talent support within pre-school, schools as well as within the field of Higher Education and beyond. The presentation will introduce the three different areas of talent support carried out at the ICBF (Talent Research, Gifted Education, Teacher Training and Further Education), especially focusing on the research of talent promotion programs. Therefore, the nationwide LemaS-project to promote high performing and potentially highly abled students will be further introduced as well as three Erasmus+-projects the ICBF is hugely involved in.
19.11.2019	Opening Innovation in Location AI	Zack Zhu	HERE Research, Switzerland
HERE is in the business of understanding location. Recent progress in AI offers interesting new possibilities, but specialized treatment of spatial-temporal data and tailored development of AI methods is needed to truly capture the dynamics of location. To this end, HERE Research brings strong interlock of AI and GIS researchers to the study of Location AI. We operate in the mode of open innovation and seek close collaboration with academic partners. This talk will first highlight some of HERE's recent steps in this direction, including the establishment of the Institute for Advanced Research in Artificial Intelligence (IARAI) and event organization at premiere AI and GIS venues. Then, an industry point of view into key research questions will be provided to set the stage for an open discussion.
26.11.2019	Institute meeting
No GI Forum
03.12.2019	Location privacy: state of the art and perspectives on research & education	Rania Kounadi	Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
Information about an individual’s location is substantially different from other personal information. The presentation will review on location privacy’s six key topics: 1) Geo-information Disclosure, 2) Protection Methods, 3) Professional Practices, 4) Data Subjects, 5) Information Divergence (Loss/Error), and 6) Thresholds on Anonymity & Divergence. Driven from the current gaps, a research idea will be presented that aims to develop an open-source privacy-by-design system for personal geodata (de-iSpace). Last, a summary of the new course at ITC-UT focusing on location privacy and titled “Space for Ethics” will be discussed, to outline the need to include privacy-preserving curriculum material in GIScience educational programs.
10.12.2019	Supporting Ecological Decision Making Using Feature-Selection and Variable Importance	Patrick Schratz	Friedrich Schiller University Jena, Germany
Hyperspectral imagery is promising for detecting, mapping and predicting ecological processes such as the spatial spread of diseases, (invasive) species or plant strategy types. However, the corresponding data analysis is quite challenging due to the high dimensionality of the data especially when the number of predictor variables exceeds the number of observations of the response. Defoliation can be considered as a proxy for tree health. Predicting defoliation is important for the early detection of a spreading disease. Therefore, we modeled defoliation of pine trees (n=1759) in the Basque country as a function of thousands of features derived from hyperspectral remote-sensing data. The latter included vegetation indices (VI), less widely used normalized ratio indices (NRI) and the hyperspectral reflectances themselves (HR). To deal with the high dimensionality of the data, we applied three feature-selection methods (ensemble filters, simple filters, PCA) and compared them in terms of predictive performance. Ensemble filtering is a relatively new method that showed promising results in recent studies in the field of machine learning. We applied the feature-selection methods to three feature sets (VI (p=90), NRI (p=7380) and HR (p=122)) and determined the models’ performance with the help of spatial block cross-validation. The latter makes sure to derive bias-reduced estimated in the presence of spatial autocorrelation. We used commonly used statistical and machine-learning algorithms (Penalized Regression, Support-Vector-Machines, Random Forests, Extreme Gradient Boosting) to additionally identify algorithm-related differences. This work shows the potential of feature-selection methods in ecological modeling. Ensemble filter methods are a promising new method to enhance predictive accuracy for high-dimensional data. The differing algorithm accuracies underline the potential of algorithm benchmarking to obtain optimal results.
17.12.2019	Geo-information attitudes to young geological mapping of the Lower Rhine valley and delta (Netherlands and North Rhine-Westphalia)	Kim Cohen	Utrecht University, The Netherlands
The landscape and shallow subsurface along the river Rhine is long studied by many different parties and for all kinds of reasons. This has created heaps of diverse raw data that mapping institutes make summaries of. Digital geological maps showing the landscape structure of the Rhine valley (older and younger parts, higher and lower parts, subsurface buried features) are in common use by engineers, by planners, by hydrologist, by archaeologist and so on. They use it because it is easier to use such a summary, than to have to deal with the overloads of underlying raw data. The more raw data exists and the more pluriform that becomes and the faster it accumulates, the more important having the digital maps become, to screen or prune or subselect raw data for example. For the makers of the summary maps, however, the increasing amounts of raw data increase the difficulty of keeping the geo-information in the summary maps up to date and at appropriate accuracy and resolution. In my contribution to the GI-forum, using examples of data sets and interfaces connected to the Lower Rhine area, I will discuss currently deployed geo-information techniques at the meta-level. I will show geological maps and animated time series showing landscape evolution and web-portals unlocking 3D voxel sets of entire Rhine delta that are visual eye candy and powerful communication. But underneath such output is the story of how makers of these data products came to their workflow choices and divisions: of their geo-information attitudes. The talk is based on my work at Utrecht University (1998-present) and collaborations with TNO Geological Survey of The Netherlands, Deltares, The Netherlands’ Cultural Heritage Agency, and NRW counterparts.
07.01.2020	Challenges, limitations and opportunities for assessing and simulating land use change patterns in tropical forest landscapes: Insights from Ecuador, Philippines and Thailand	Melvin Lippe	Thünen Institute, Germany
Tropical forest landscapes are vital for the global carbon cycle, conversation of biodiversity and provisioning of ecosystem service for local populations to name only a few. Despite its global importance, tropical forests are still reducing at an alarming rate caused in particular by agricultural expansion for subsistence and commercial purposes. This study presents three case studies that were conducted in tropical forest landscapes of Ecuador, Philippines and Thailand. The first case study presents outcomes of a study in Northern Philippines to unravel present and emerging future social-ecological systems interlinkages at landscape-level using stakeholder elucidations and participatory mapping techniques. The second case study reveals how the selection of spatial predictors of location suitability influenced simulated land use allocation patterns for a case study in the Ecuadorian Amazonas which arguably appears to be an overlooked issue in landscape modelling. The third case study then presents how stakeholder-driven scenario development was used to simulate land use change patterns for a case study watershed in Northern Thailand. The presentation concludes with the lessons learned, limitations and opportunities when using participatory approaches and qualitative information in assessing and simulating land use change patterns in the Global South.
14.01.2020	From Physical Tracking to Virtual Tracking: Using Tracking Technologies and Virtual Reaility in Urban design	Stefan van der Spek	TU Delft, The Netherlands
In 2005 we introduced tracking technologies in a European Project to validate investments in public space based on actual behavior of visitors of the city centre. Since then we have improved and applied the methodology on both tourism, shopping and residents of specific districts, i.e. Delft from Above comparing students versus families and High-Rise Rotterdam where we collected information on the activity behavior of people living in high-rise residential buildings: do households living in these high-rise buildings contribute to city life? Lessons learned where implemented in the city’s ambitions and guidelines for high-rise development. Since 2015 we are experimenting with Virtual and Augmented Reality (VR+AR) as design and research tools. The objective is to improve urban design by using VR+AR in the beginning of the design process, not only for visualization and communication. Computaitonal Design tools, form a base for the design methodology. VR is now used for design, assessment and participation in both research and education. In collaboration with practice we run three reseach projects: The City at Eye-Level, VRenovate and Conceptual Space. Our VR lab has develop special tools, like the multi-player, interactive demo’s and applied both tracking and eye-tracking technology in VR.
21.01.2020	Digital Counter-Enlightenment and “Surveillance by Design”: On Nudging, Tracking and Data Aggregation in Human-Computer Interaction	Rainer Mühlhoff	Cluster Science of Intelligence, Technische Universität Berlin, Germany
In this talk I will analyze modern human-computer interaction to discuss the question of enlightenment and counter-enlightenment in the digital age. I will focus on the field of “User Experience Design”, a dominant IT discourse that uses insights from behavioral sciences and data-driven evaluation techniques to optimize user interfaces and interaction designs. We will have a closer look at various “design tricks” that nudge users to expose more of their data online, often without explicit knowledge. I will discuss how this data is used to predict user behavior and target users according to their cognitive, behavioral or emotional dispositions. This leads to the diagnosis of “digitale Entmündigung”, or digital counter-enlightenment, which describes a set of systematic aspirations of big industrial players to deprive users of their (cognitive and epistemic) means to make self-determined, knowledgeable and responsible use of technology. With respect to data protection and privacy debates, I will point to the political problem of mass aggregation of data and argue that this problem exists even if the data is anonymous or de-identified.
28.01.2020	Institute meeting
No GI Forum

GI-Forum Summer 19

Date	Topic	Presenter	Affiliation
02.04.2019	Institute Meeting
Sorry, no abstract available yet.
09.04.2019	Prepare for the Internet of Things: Correct and Reliable Construction of Embedded Systems	Paula Herber	Computer Science Department, WWU
98 % of the processors that are produced world-wide are used in embedded systems, that is, in systems that read sensor data and control actuators, for example to monitor and control our environment, for autonomous driving or other kinds of transportation, or in industrial production systems. At the same time, embedded systems are often used in safety-critical applications, like cars, airplanes or medical systems, where a failure may result in huge financial losses or even endanger human lifes. As a consequence, there is a high demand for automated formal methods to construct safe and secure embedded systems. To achieve this, we require a clear understanding of the models and languages that are used in the development process. However, many industrially relevant languages and models, such as Matlab/Simulink and SystemC, are only informally defined. Together with the restricted scalability of formal design and verification techniques, this makes the correct and reliable construction of embedded systems a major challenge. In this talk, I will summarize some of my contributions and current research activities in this field.
16.04.2019	Tracking Active Mobilities: Lessons from North East England	Seraphim Alvanides	Northumbria University
Adopting Fred Ken's famous quote "If you plan cities for cars and traffic, you get cars and traffic", this session will revisit the past in light of the present transport situation in parts of North East England. Focusing on Newcastle upon Tyne and the surrounding conurbations as a case study, I will present two research projects related to active transport, in light of recent transport policy initiatives. The research design, collection, analysis and reporting will be explained in detail, alongside alternative technologies for tracking and analysing active mobilities. I will conclude by discussing the policy implications of this research, especially for post-industrial cities with "planning baggage" competing with visions of urban futures. I will argue that the casualties of infrastructure conflicts are active and sustainable forms of mobility, such as walking and cycling.
23.04.2019	Postponed to May 7	Christian Beecks	Computer Science Department, WWU
Sorry, no abstract available yet.
30.04.2019	Data and Metadata Management in EOSC-hub and beyond	Claudia Mertens	Deutsches Klimarechenzentrum
Due to the fact that research is becoming increasingly data-intensive, research (data) infrastructures need to deal with challenges concerning data and metadata. The European Open Science Cloud should be the place to develop, establish and maintain a common research data ecosystem; however up to now no one really knows what the EOSC will look like at the end. The project EOSC-hub meanwhile aims at creating a single entry point for researchers to discover, access, use and reuse a broad spectrum of resources for advanced data-driven research. But what does that mean in practice? How does the integration of big data infrastructures take place and what does that mean for potential users? Here I will use the discovery service B2FIND as an example for such an integration work. B2FIND provides a simple and user friendly discovery portal for research data stored within EOSC-hub and beyond as a basic service of the pan-European collaborative research data infrastructure EUDAT-CDI. It is intended to be the central search and indexing tool for EOSC-hub. How this is done will be one part of the talk. The other part will focus on how B2FIND interacts with other EOSC-hub services and what general problems (and/or solutions) arise from the potential integration of different software, workflows or use cases.
07.05.2019	Data Management and Analytics Group @ WWU	Christian Beecks	Computer Science Department, WWU
Data are a central phenomenon in our digital information age. They offer unprecedented opportunities to simplify our daily life and increasingly influence our society, economy and science. The digitization of data and the analysis of their inherent information are among the great challenges of our time. By utilizing Big Data methods, we are able to control unmanageable amounts of data and analyze hidden relationships efficiently. In this talk, I would like to give an insight into this fascinating field of research and introduce the Data Management and Analytics Group of the University of Münster.
14.05.2019	Algorithms for Spatially Informed Visualization	Wouter Meulemans	TU Eindhoven
Data is often visualized in their geographic context, by embedding it in maps. Though "geographically accurate" maps are wide spread, their focus lies on the geospatial dimension, rather than on the data itself. In many scenarios, a schematic map can be more effective, by reducing spatial detail and accuracy to crystalize structures and patterns in the data. That is, we may want to control the degree to which the spatial dimension informs the visual representation. Independent of this trade-off, algorithms are necessary to compute visualizations automatically, by placing symbols, routing connections, simplifying shapes, arranging elements and so forth. Taking this algorithmic perspective, I will discuss various problems and solutions for spatially informed visualization.
21.05.2019	Institute Meeting
Sorry, no abstract available yet.
28.05.2019	Toward Ethical AI (not more AI ethics)	Michael Rovatsos	University of Edinburgh
While the issue of AI ethics is receiving more and more attention as adoption of AI technologies in real-world applications is growing immensely, a lot of the discussion is dominated by conceptual and speculative claims and analyses of how we can make sure future AI benefits humanity. Within the AI community, however, it is widely acknowledge that concrete, technical solutions are needed that actually make AI itself behave ethically. In this talk I will discuss some general issues surrounding ethical problems in AI, and present our own preliminary work on ethical self-regulation of users in online platforms with a focus on algorithmic fairness.
04.06.2019	Panel Discussion: Freedom of Research vs. Societal and Ethical Responsibilities	Edzer Pebesma, Christoph Brox, Christian Kray	ifgi
The freedom of science and research has a long tradition and is deep-seated in the German academic system. Consequently it is the framework for our work at the University of Münster. In the age of Enlightenment, i.e., Humboldt-University Berlin, founded 1809, the ambition was to free science from political, governmental, and religious influences. Instead, science should only be obliged to knowledge and rationality. In Germany, it is a constitutional right of professors to determine the content of their lectures, to do research and to publish the results of their research without prior approval. A different viewpoint is that research has the ethical obligation to serve societal needs. While it might be interesting to analyse the linguistic aspects of the oeuvre of a Russian author of the 19th century, it might be more important to do research on how to increase crop yields in sub-Saharan countries. How should stakeholders decide about allocating resources in academic research such as money, time and people? How should individual scientists and academic institutions act in this context? This GI forum will start with two 10-minutes lightning talks. In a biased roleplay, which is NOT representing the respective personal opinions, Edzer Pebesma will argue for freedom of science and research, whereas Christoph Brox will argue for societal and ethical responsibilities and restrictions. Moderated by Christian Kray, the audience will then discuss the contradictory viewpoints and possible consequences – on a personal level as well as on the institutional level of a research institute such as ifgi.
11.06.2019	Pentecost Holidays
Sorry, no abstract available yet.
18.06.2019	Towards open Spatial Data Infrastructures	Bastiaan van Loenen	TU Delft
In the search for the ideal spatial data infrastructure a common ground has been established for the development of open spatial data infrastructures. Starting from confidential, highly restricted data with use limited to particular public sector users, SDIs across Europe have developed towards a wider focus, civil society oriented infrastructure enabling a multitude of users to access, share, use and re-use datasets and services from a wide variety of domains both nationally and internationally. Especially in recent years, several countries and public administrations started to make a shift towards the establishment of an open spatial data infrastructures (SDIs), in which also businesses, citizens and non-governmental actors were considered as key stake-holders of the infrastructure. The concept of Open SDI is gaining importance since European Commission, European Parliament and European Council have reached an agreement on a revised directive that will facilitate the availability and re-use of public sector data. This new directive on Open Data and Public Sector Information will rule that all public sector content that can be accessed under national access to documents rules is in principle freely available for re-use. In addition, high-value datasets such as geospatial data will have to be made available as open data via Application Programming Interfaces (APIs). In this presentation, the concept of Open SDI is introduced to describe and characterize the development and implementation of more open spatial data infrastructures. The ‘Map of Open SDI in Europe’ will be presented, showing the results of three years of exploration of the openness of NSDI implementation in Europe. Finally the presentation will discuss the ever continuing question of how to involve users in SDI development in a successful manner.
25.06.2019	Language and the Visual World: Communicating Between Cultures	Kenny Coventry	University of East Anglia
In this talk I overview a programme of research examining how speakers of different languages describe object location, remember where objects are located, and how object-location memory is affected by language. The focus will be on spatial demonstratives (words including this and that in English; this cup, that computer) and spatial adpositions (in the cup, on the computer, over the house). Following Coventry and Garrod (2004) and Coventry, Griffiths and Hamilton (2014), I outline a model of the use of spatial language, memory for object-location and the effect of language on memory that combines information in long-term memory with actual spatial information leading to situation-specific uses of words and memories for where objects were. Such a model, consistent with models of predictive coding (e.g. Friston, 2005), conceptualizes meaning as a combination of expectation and current experience. In the second part of the talk I look forward to how such models influence how one communicates science in a ‘post-truth’ world. As an example, I focus on communication of climate science. I outline work in collaboration with the Intergovernmental Panel on Climate Change in the preparation of guidelines for IPCC authors on how to produce visual and verbal representations of data that are easier for non-climate scientists to understand (see for example Harold, Lorenzoni, Shipley, & Coventry, 2016). References Coventry, K. R. & Garrod, S. C. (2004). Seeing, Saying and Acting: The psychological semantics of spatial prepositions. Psychology Press, Taylor and Francis: Hove and New York. Coventry, K. R., Griffiths, D., & Hamilton, C. J. (2014). Spatial demonstratives and perceptual space: Describing and Remembering object location. Cognitive Psychology, 69, 46-70. Friston, K. (2005). A theory of cortical responses. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 360(1456), 815–836. Harold, J., Lorenzoni, I., Shipley, T. F., & Coventry, K. R. (2016). Cognitive and psychological science insights to improve climate change data visualisation. Nature Climate Change, 6, 1-11.
02.07.2019	Reproducibility of research using crowdsourced or volunteered geographic information	Frank Ostermann	University of Twente
Using crowdsourced or volunteered geographic information has become mainstream in geospatial research. Whether georeferenced social media posts or OpenStreetMap data, crowdsourced or volunteered geographic information has been used in diverse studies, ranging from disaster response to urban planning to epidemiology, and many more. At the same time, other scientific disciplines have faced a veritable replication and reproducibility crisis, in which the results from many published studies could not be reproduced or validated by another team of researchers. A recent investigation in the GIScience domain (Nüst et al. 2018) has shown that in our domain as well the state of reproducibility leaves a lot of room for improvement. This talk will examine the crossroads of these two topics: After looking into reproducibility of geospatial research in general, I will examine what the implications of the particularities of crowdsourced and volunteered geographic information are for reproducible geospatial research. News from the latest workshop on reproducible computational geosciences at the 2019 AGILE conference will round off the talk. Reference: Nüst, D., Granell, C., Hofer, B., Konkol, M., Ostermann, F.O., Sileryte, R., Cerutti, V., 2018. Reproducible research and GIScience: an evaluation using AGILE conference papers. PeerJ 6, e5072. https://doi.org/10.7717/peerj.5072
09.07.2019	Institute Meeting
Sorry, no abstract available yet.

GI-Forum Winter 18/19

Date	Topic	Presenter	Affiliation
09.10.2018	Institute Meeting
no GI Forum will take place
16.10.2018	Working with Images in R	Jeroen Ooms	rOpenSci / UC Berkeley
Images in various forms are used for numerous applications across scientific disciplines. Whether you are observing through satellite or microscope, looking at MRI scans or petri dishes, trying to find patterns or abnormalities, the data is in the image. Unfortunately the tools for working with images are traditionally highly fragmented by field, and often narrow in scope. At rOpenSci we are working on a suite of general purpose packages based on powerful c/c++ libraries. These provide an extensible and interoperable foundation for working with images in R, which can be used to implement domain specific-methods. This talk gives a taste of things we can currently do with images in R, and highlights some of the ongoing developments and challenges.
23.10.2018	Use of Unmanned Aircraft Systems for high-resolution remote sensing in landscape ecology applications	Jan Lehmann	Institute for Landscape Ecology
Unmanned Aerial Systems (UAS) presents itself as one of the most recent remote sensing technologies in high-resolution spatial and temporal data acquisition. This talk will address the question of how well, this remote sensing technology can be successfully integrated into landscape ecology, in regards to both basic and applied research. Furthermore, perspectives and frontiers of UAS-based remote sensing within landscape ecology are also brought into light. The proficiencies of low-cost camera sensors for vegetation mapping, monitoring and management are evaluated in particular. Newer, more refined image analysis strategies are therefore presented and appraised in regards to accuracy and ecological reliability. Consequently, different case studies take precedence, each serving as models of innovative remote sensing applications highlighting significant topics in current landscape ecological research.
30.10.2018	An Immersive Science of Place - Paradigm Shifts for Geosciences?	Alexander Klippel	Pennsylvania State University
Immersive technologies are going mainstream. Improved in quality and affordable they provide a unique opportunity for spatial sciences, which have, in parallel, witnessed tremendous advancements in 3D sensing and modeling technologies. These synergistic transitions allow spatial disciplines like geosciences, architecture, landscape architecture, or geography, to revisit possibilities for using immersive technologies for communicating and understanding spatial and environmental issues and challenges. What is missing is a more rigorous, scientific approach that provides evidence-based design guidelines for immersive experiences and allows for connecting theories developed in spatial sciences to the opportunities afforded by immersive experiences. Place, as an omnipresent concept in the sciences named above, has the potential to frame the theoretical basis for scientific grounding of immersive experiences. In this talk, immersive experiences for spatial sciences are discussed: immersive workbenches, experiences of past and future scenarios from Mayan Culture to forest futures, as well as virtual field trips. Empirical evidence will be detailed providing the basis for a deeper evaluation of whether or not immersive experiences are indeed a paradigm shift for Spatial Sciences.
06.11.2018	New insights from monitoring deformations of the earth from space	Ramon Hanssen	TU Delft
Using satellite radar interferometry, we can now observe the dynamics of the earth surface with unprecedented resolution and precision. However, it is a genuine big data problem, where many different physical phenomena are juxtaposed, and the main challenge is to reliably disentangle the different components. In this presentation, we will review the basics of the techniques as well as the new insights we derived from the plethora of data.
13.11.2018	Imputing missing values in satellite data: From parametric to non-parametric approaches	Reinhard Furrer	University of Zurich
Remotely sensed data are typically sparse, which means that data have missing values, for instance due to cloud cover. This is problematic for applications and signal processing algorithms that require complete data sets. Hence, imputing the missing values is common and has been extensively discussed in the past, ranging from mechanistic filtering to classical geostatistical interpolation procedures. In the talk I will give some basic concepts of spatial and spatio-temporal prediction and present the new non-parametric gapfill algorithm. This latter method imputes each missing value separately based on data points in a spatio-temporal neighborhood around the missing data point. The imputation of the missing values and the estimation of the corresponding prediction uncertainties are based on sorting procedures and quantile regression. The procedure is implemented and available in the open-source R package gapfill. We illustrate the gapfill algorithm with MODIS NDVI data from Alaska with realistic cloud cover scenarios featuring up to 50% missing data. Validation against established software showed that the gapfill algorithm has a good performance in terms of the root mean squared prediction error.
20.11.2018	Geomarketing: providing location insights to enhance economic efficiency	Tim Appelhans	GFK
Geomarketing is the fourth P in the marketing mix model (also known as the 4Ps): product, price, promotion and place. In addition to classic market research it uses geographic information on various key factors to disseminate business insights spatially. This is done through a mix of ingredients ranging from map data (seamless global mapset), general market/consumer data (e.g. purchasing power) to customer specific data (e.g. store locations and sales) and consumer location data (dynamic mobile locations). In addition to standard data, map and software products, at GfK Geomarketing we offer a wide range of solutions to aid our customers in various business questions such as regional market share analysis, regional traget group evaluation, branch network and distribution partner optimisation, sales territory planning and real estate consulting. This talk will give a general overview of the product portfolio of GfK Geomarketing, how these data are created/calculated and how they are used by our clients. Specific focus will be given to general purchasing power as it is one of the most important indicators for market research, branch network analysis and micro-geographic data products as they are becoming more and more popular.
27.11.2018	Institute meeting
no GI Forum will take place
04.12.2018	Interactive Map-based Support Systems: Supporting social learning and knowledge-co-production in environmental health issues	Rehana Shrestha	University of Twente
Environmental health issues comprise of several characteristics of the environment (e.g. air and noise pollution, availability of green spaces) that inherently influence the health of people and is gaining increasing attention. Involving various stakeholders from both urban planning and public health disciplines has been widely endorsed as a way to address, tackle and manage. However, involving heterogeneous stakeholders is not without challenge as they may have different interests, perspectives and ways of knowing. In my PhD I developed two approaches that use Interactive Map-Based Support Systems. Interactive Map-based Support System herein is conceptualized as GIS-based tools/methods that use tangible interface such as MapTable for facilitating user engagement. I explored the usefulness of such tools/methods to support collaboration, deliberation and dialogues among diverse stakeholders on environmental health issues. These tools and methods were implemented in face-to-face workshops with stakeholders from Dortmund and Munich to support stakeholders’ engagement during problem exploration and stakeholder based cumulative burden assessment. Results are reported based on the micro analysis of observation protocols, questionnaires survey, screen capture of MapTable, and workshop transcripts. Findings suggest that having map based interactive tool can support in capturing tacit knowledge among stakeholders, ensuring opportunities for social learning and knowledge co-production. In these three months of stay at WWU, Ifgi, I plan to extend my knowledge on environmental health issues, particularly focussing on air and noise pollution and in the context of ‘ordinary smart cities’. I will explore and synthesize findings from a variety of ‘ordinary smart cities’ initiatives dealing with air and noise pollution. A comprehensive literature survey will be conducted to identify as well as to understand the sociotechnical assemblage of actors, their logics and technologies (digital/non-digital) associated with existing interventions and explore the extent to which these interventions have been able to address problems of air and noise pollution.
11.12.2018	Mapping inequality in access to resources	Andy Nelson	University of Twente
More equal access to the resources that sustain human well-being, such as education, employment and health services, underpins the equality agenda of 'leaving no one behind' established by the Sustainable Development Goals of the United Nations. Accessibility can be defined as the ability to interact with locations that offer economic and social opportunities; better access usually means better opportunities and better livelihood outcomes. The accessibility of a particular location can be quantified in several ways: equity (i.e. proximity based on distance or travel time); coverage (i.e. the number of reachable resources per person), or; integration (i.e. the likelihood of interactions or the cost of transactions). Spatial modelling of accessibility uses the geographic location of the population in relation to target locations and the transport means and infrastructure to access those locations. This presentation discusses recent work on mapping equity in access in R using the gdistance package, challenges in scaling this globally and how and the importance of good, up to date and easy to use transport network data for accessibility mapping.
18.12.2018	From daily to decadal movement of snow and ice seen from space	Bas Altena	University of Oslo
The Arctic is changing at a rapid pace, and at the same time Earth observation is revolutionized through lower thresholds for space access. Consequently, it is only recently that constellations and fleets of Earth observation platforms sense the cryosphere with both very high spatial and temporal resolution. Opportunities arise from the broken barrier to space and nowadays big volumes of data are acquired. This talk will highlight the potential of this vast volume of data for displacement extraction. Applications will range from short-term movements, such as river ice floods to long-term glacier speed-ups and slow-downs on a large scale.
08.01.2019	The future of transport planning software: data-driven, modular and open	Robin Lovelace	University of Leeds
Transport modelling software is a vital component of modern transport planning. They generate the evidence base on which strategic investments are made and, furthermore, provide a powerful mechanism for researching alternative futures. It would not be an overstatement to say that software determines the range of futures that are visible to policymakers. The focus of this talk is on the status of transport modelling software and how it may evolve in the future. What will they look like? What will their capabilities be? And who will control? Answers to each of these questions will affect the future of transport systems. With reference to my own experience developing R packages for transport planning (notably stplanr, cyclestreets and stats19) and using other tools, this talk will make the case that transport modelling software used in practice will become increasingly data-driven, modular and open.
15.01.2019	Does Index Insurance Help Households Recover from Disaster? Evidence from IBLI Mongolia (joined with Veronika Bertram-Huemmer)	Kati Krähnert	DIW
This talk investigates the impact of indemnity payments from index insurance on the asset recovery of households following a catastrophic weather disaster. Our focus is on the Index-Based Livestock Insurance (IBLI) in Mongolia. We analyze the effect of IBLI indemnity payments after a once-in-50-year winter disaster struck Mongolia over the 2009/10 winter. The analysis is based on three waves of a household panel survey implemented in western Mongolia 2-5 years after the shock. We employ the bias-corrected matching estimator to account for selection into purchasing IBLI. Results indicate that pastoralist households purchasing IBLI before the shock recover faster from shock-induced asset losses than comparable uninsured households. We find a significant, positive and economically large effect of IBLI indemnity payments on herd size one to three years after the shock. Four years after the shock, the effect vanishes. Results are robust to defining post-shock livestock recovery in different ways, the choice of covariates, and the use of alternative propensity score estimators. An analysis of shock coping strategies suggests that IBLI appears to have relieved households from credit constraints. In addition, indemnity payments helped herders avoid selling and slaughtering animals, thus smoothing their productive asset base. Our article is among the first to provide evidence on the beneficial effects of index insurance after a weather shock in a developing economy.
22.01.2019	Improving the usability of 3D city models	Hugo Ledoux	TU Delft
Many companies and governments around the world have recently invested in reconstructing 3D city models because these are essential in applications such as the estimation of the energy consumption, wind simulation, shadow analysis, etc. However, in practice, these 3D models are seldom used. There are several reasons to this, and I will focus on two during the talk: (1) the standard CityGML has in my opinion drawbacks that hinder the use of 3D city models; and (2) current 3D city models contain several (geometric) errors. I will present an alternative to CityGML called CityJSON and discuss how it can help practitioners exchange, update, and manipulate their 3D city models. I will also discuss the current efforts of my research group on automatic repair methods for 3D models.
29.01.2019	Institute Meeting
no GI Forum will take place

GI-Forum Summer 18

Date	Topic	Presenter	Affiliation
10.04.2018	Institute Meeting
Sorry, no abstract available yet.
17.04.2018	Visual Tracking of Small Animals in Cluttered Natural Environments Using a Freely Moving Camera	Benjamin Risse	WWU Münster
Image-based tracking of animals in their natural habi-tats can provide rich behavioural data, but is very challeng-ing due to complex and dynamic background and target ap-pearances. We present an effective method to recover the positions of terrestrial animals in cluttered environments from video sequences filmed using a freely moving monocu-lar camera. The method uses residual motion cues to detect the targets and is thus robust to different lighting conditions and requires no a-priori appearance model of the animal or environment. The detection is globally optimised based on an inference problem formulation using factor graphs. This handles ambiguities such as occlusions and intersec-tions and provides automatic initialisation. Furthermore, this formulation allows a seamless integration of occasional user input for the most difficult situations, so that the effect of a few manual position estimates are smoothly distributed over long sequences. Testing our system against a bench-mark dataset featuring small targets in natural scenes, we obtain 96% accuracy for fully automated tracking. We also demonstrate reliable tracking in a new data set that includes different targets (insects, vertebrates or artificial objects) in a variety of environments (desert, jungle, meadows, urban) using different imaging devices (day / night vision cameras, smart phones) and modalities (stationary, hand-held, drone operated).
24.04.2018	GIScience for Dynamic Transportation Systems	Anita Graser	Austrian Institute of Technology
Transport research is an interdisciplinary field with a multitude of research topics that overlap with GIScience since movement, by its very nature, happens in space and time across multiple scales and within different context. Applications range from monitoring, understanding, and guiding local movement, to city-wide and global movement analysis and optimization. GIScience provides a strong foundation for understanding spatial aspects as well as the context of movement but the dynamic nature of movement data is a challenge for many established GI approaches. This talk highlights recent GIScience topics, open research questions and challenges relating to pedestrian navigation, as well as analysis of massive movement data at the AIT Dynamic Transportation Systems group. Paper: Graser, A. (2017). Towards landmark-based instructions for pedestrian navigation systems using OpenStreetMap, AGILE2017, Wageningen, Netherlands. https://agile-online.org/images/conference_2017/Proceedings2017/shortpapers/46_ShortPaper_in_PDF.pdf
01.05.2018	May 1
Sorry, no abstract available yet.
08.05.2018	Acquisition and consolidation of hierarchical representations of space	Wiebke Schick	WWU Münster
Navigation – the ability to reach targets which are no visible from the current position depends on the correct recall of the desired target and the environment between one's current position and this target. The content of these representations are subject to influences from different modalities, e.g. vision, and language. A place can be recognized through different cues, e.g. due to a salient object, but also because of the angles of the routes at an intersection, or a name. The location of places as well as the routes connecting them can be integrated and memorized in an allocentric, survey-like representation. Depending on the amount of detail, the granularity level of a representation can be coarser or finer; the different levels are organized hierarchically. Characteristics of a superordinate category, like a region, can affect the perception of its constituting elements, the places; an inheritance of qualities from region to place levels is possible. The formation of superordinate categories depends both on environmental factors as well as individual ones: what is recognized, what is remembered, and which predictions are drawn from this representation? I examine the acquisition of representations of space, in order to identify features that are well suited for being remembered and auxiliary for navigation. I have two research foci: First, I examine the impact of language by using different hierarchically structured naming schemes as place names. Wiener & Mallot (2003) found that characterizing places only with landmarks belonging to different semantic categories influenced route choice as well as the representations of space. I compare these findings to the impact of different naming schemes. I show that there are naming schemes that may influence behavior in a similar way as a landmark does, but that seeing something and reading its name is by far the same thing. The second part focuses on the content of representations established during navigation. With three different navigation experiments, I examine the content of the concepts of space that are acquired during navigation. What is remembered - the location of places, the routes, or the hierarchical structure of the experimental environment? Are there features that are more likely to be consolidated during sleep, e.g., the transfer of concrete knowledge about places and routes into an abstract, survey-like representation? I show that there are improvements in one wayfinding task correlated to sleep. In the other experiments, learning effects were found for both groups. I also address the question of suitable parameters for measuring survey knowledge.
15.05.2018	Visualization of Uncertainty: Empirical Studies	Sarah Fabrikant	University of Zurich
Sorry, no abstract available yet.
22.05.2018	Pentecost Holidays
Sorry, no abstract available yet.
29.05.2018	Institute Meeting
No GI Forum will take place
05.06.2018	Assessing students' individual progress: Concept, trajectories, and effects	Elmar Souvignier	Institut für Psychologie in Bildung und Erziehung, WWU
Assessing students’ individual progress: Concept, trajectories, and effects Elmar Souvignier, University of Münster Does every single student take benefit from my instruction? In contrast to (typical) diagnostic approaches that focus on students’ level of achievement, the idea behind learning progress assessment is to measure change. The concept of ‘progress monitoring’ was designed with the aim to support teachers’ instructional decision making (data-based decision making). In other words: Measuring progress by use of multiple points of measurement (e.g. weekly assessments) should help teachers to differentiate instruction based on objective diagnostic information. This, as a consequence, should lead to positive learning effects. In our research program we designed a web-based system for learning progress assessment with parallel tests for reading and mathematics from grades 1 to 6. First, we analyzed the technical adequacy of these tests (reliability, validity, sensitivity to change, parallelism). As a second research question we were curious about childrens’ learning trajectories over the period of one school year. Analyzing latent classes of learning progress we found that children not only differ with respect to their level of achievement but also according to individual progress of learning. The third focus of our research program was to evaluate effects of providing teachers with diagnostic information about their students’ progress. Throughout three replications we found that learning progress assessment leads to small but reliable positive effects on reading achievement. Future studies deal with the question of optimizing the concept of learning progress assessment by adding feedback-routines and providing teachers with material for differentiated instruction.
12.06.2018	The Earth System Lab: A light-weight data cube approach to study land-atmosphere interactions at the global scale	Miguel Mahecha	Max Planck Institute for Biogeochemistry, Jena
Scientists today are confronted with a plethora of Earth observations (EO) and derived downstream data products. These data streams are extremely valuable for studying processes at the global scale, for instance on how climate extremes influence primary production among others. To jointly exploit these datasets, scientists have to deal with a multitude of data formats, data usage policies, inconsistent resolutions and formatting, as well as getting access to suitable computation and data storage facilities. This time-consuming work slows down scientific progress. The “Earth System Data Lab” is a novel infrastructure for scientists to overcome limitations of this kind. It not only provides a set of harmonized data cubes, but also developed a strong data analytics toolkit in tandem with access to computational facilities to jointly analyze the datasets. The data cube consists on a selection of diverse Earth observation datasets including multiple atmospheric variables, Land-Atmosphere fluxes, biophysical parameters and is currently extended to ocean variables. These datasets are analysis-ready, harmonized on different temporal and spatial resolutions to allow rapid exploitation. The core data analytic toolkit allows users, if proficient in a language of scientific computing like Python or Julia, to apply their own analysis methods on the multivariate data cube. Examples implemented include nonlinear time series analytic tools, dimensionality reduction approaches, or anomaly detectors, among others. To showcase the potential of the approach we will present some scientific case studies demonstrating the full potential of the infrastructure and seek for participants in our early-adopter user engagement call. Our latest paper on using the cube is this one - still in discussion: https://www.biogeosciences-discuss.net/bg-2018-130/bg-2018-130.pdf
19.06.2018	Gaze behavior in natural environments – Why some objects and areas may be more salient than others	Rul von Stülpnagel	Uni Freiburg
When navigating natural environments, some of the elements surrounding us or even entire areas appear more salient than others. They may thus be used, for example, as landmarks that enable us to retrace a route or provide a route description for others. Based on the differentiation of semantic, visual, and structural salience of landmarks, we investigated the gaze behavior of participants during incidental and intentional route learning. We found that visually salient landmarks attracted more gazes in general, independent of learning intention. However, structurally salient landmarks (e.g., landmarks into the turning direction) were particularly relevant during intentional learning. Further evidence for the benefits of structurally salient landmarks on memory for turning directions comes from a controlled lab-study. In a related research vein, we aimed at linking the perception of subjective risk during urban cycling to the gaze distribution in the local environment. Less surprising, people tend to focus on those areas they assume to be dangerous. More interestingly, preliminary findings imply that although cyclists identify most potentially dangerous areas correctly, some spots are literally overlooked, thus contributing to the level of objective risk for an accident.
25.06.2018	Schematic Mapping from an Algorithmic Perspective	Prof. Martin Nöllenburg	TU Wien
Schematic maps deliberately distort topographic reality and use a simplified and rather abstract depiction of spatial objects and relations in order to facilitate selected types of map use. For example, in a schematic public transport map, the most important information is the connectivity of stations and the course of each transit line so as to allow for fast visual route planning in the transport system. In a schematic road map, the important information for a driver who wants to get from A to B is, how to turn at road junctions to get to the destination. Creating schematic network maps automatically is a challenging problem that has also been addressed from a formal, mathematical perspective in the fields of graph drawing and computational geometry. Combining rigorous mathematical modeling and methods from algorithm engineering, the aim is to design and implement efficient algorithms with proven quality guarantees and evaluate them experimentally. This talk gives an overview of different algorithmic approaches for network schematization and their respective properties.
03.07.2018	Interacting with Space and Spatial Data	Ioannis Giannopoulos	TU Wien
Understanding how humans interact with their surroundings during spatial decision-making is crucial for the understanding of several processes, such as navigation. Furthermore, during spatial decision-making humans also with spatial data often presented to them through a display device. Through eye tracking and machine learning we are able to come closer to an understanding, optimize the relevant interaction dialogues, classify relevant interaction spaces and assist humans during the process of spatial decision-making.
10.07.2018	How to test research hypotheses with geographic prisms	Werner Kuhn	University of California, Santa Barbara
The so-called "spatial turn" in the humanities and social sciences can largely be attributed to a fundamental observation that Barney Warf and Santa Arias stated in their 2008 book: “Geography matters, not for the simplistic and overly-used reason that everything happens in space, but because where things happen is critical to knowing how and why they happen.” In my presentation, I ask whether and how this observation can be exploited for scientific hypotheses testing. An analysis of case studies where some form of spatial analysis was beneficially used in hypothesis testing, leads me to conclude that a surprisingly simple recipe can indeed be stated to test hypotheses spatially. The preliminary results can be seen as an operationalization of the "geographic prism” metaphor that has been used informally in the literature.
17.07.2018	Institute Meeting
No GI Forum will take place.

GI-Forum Winter 17/18

Date	Topic	Presenter	Affiliation
10.10.2017	Institute Meeting
Sorry, no abstract available yet.
17.10.2017	Remote Sensing in Conflict Analysis and Human Rights Fact-Finding	Christian Knoth	Institute for Geoinformatics, WWU Münster
Timely and detailed information on violent conflicts is essential to assess their impact on civilians and to document human rights issues, such as large-scale destruction and displacement. Remote sensing provides unique capabilities to collect such information and to overcome limitations of ground-based conflict documentation, especially in remote and insecure areas. This presentation will briefly introduce different application fields of remote sensing in a human rights context. I will then give an example by describing my recent work on the use of Geographic Object-Based Image Analysis (GEOBIA) for the detection of conflict damage in bi-temporal remote sensing images of Darfur, Sudan. I will also provide an outlook on how human rights fact-finding based on remote sensing may benefit from an increased availability of open or low-cost data as well as Free and Open-Source Software (FOSS). In addition, some technical and non-technical issues regarding the use of remote sensing and geospatial technologies in this politically precarious field will be discussed.
24.10.2017	Modelling the world with PCRaster	Oliver Schmitz	Utrecht University
Numerical simulation models are essential tools in understanding, analysing and predicting change of environmental systems. Modelling languages aid environmental scientists in the construction of these simulation models. The PCRaster team at Utrecht University (http://pcraster.geo.uu.nl/) develops concepts for spatio-temporal model construction and implements these in their environmental modelling language. The presentation will give a brief introduction to the PCRaster modelling platform and its Python framework work for model construction and execution. We show results from modelling studies, amongst others coming from global hydrology or geo-health. Furthermore, two of our current research themes will be illustrated: First, a better model representation of human-natural systems requires the integration of the field-based and agent-based modelling paradigms. We currently develop and apply a unified data model capable of storing field and agent data, the data model will be basis of a new environmental modelling language. Second, approaches such as hyper-resolution modelling require a better exploitation of available hardware resources. We discuss challenges of a generic modelling platform providing parallel algorithms suitable for execution on shared-memory and distributed-memory systems.
31.10.2017	Reformation day (no GI Forum)
Sorry, no abstract available yet.
07.11.2017	Measuring and Modelling Spatial Cognition in the City	Ed Manley	CASA, University College London
Despite a wealth of advances in behavioural psychology, geography, and neuroscience, conventional measures and models of urban transportation typically ignore the interaction between spatial cognition and travel decision-making. This talk will cover research aiming to bridge this gap, covering the application of new forms of mobility data, novel models of spatial decision-making, and agent-based simulation. Specifically, the talk will describe the analyses of route choices made during over 700,000 vehicular journeys in London, highlighting how travellers deviate from optimal paths between origin and destination towards particular features on the road network. This research supports a hypothesis that route choice decision-making takes a heuristic rather than optimising form within this context, and computational models are subsequently introduced to reflect these behaviours. These models of decision-making are integrated within a large-scale agent-based simulation of traffic in London, United Kingdom, demonstrating an improvement on existing methods.
14.11.2017	Geo-Information for analysing and governing cities	Karin Pfeffer	ITC Twente
Geo-Information, derived from a variety of data sources and by means of different methods and tools, is increasingly used in urban analyses and becoming embedded in urban governance processes. Examples are the spatial mapping and analysis of geocoded register or census data to investigate spatial patterns of socio-economic characteristics, processing remote sensing imagery to map urban dynamics, or GIS-based monitoring applications to follow key indicators such as air pollution levels or housing price developments. Drawing on examples from past research in different geographic contexts, this talk will present: 1) an overview of urban deprivation mapping in Indian cities (Baud et al. 2010; Kuffer et al. 2016), 2) the use of different information sources to produce a typology of transit oriented development applied to Beijing, China (Lyu et al. 2016), 3) a GIS-based monitoring system to monitor spatial concentrations of urban phenomena in the city of Amsterdam (Veldhuizen & Pfeffer, 2016), and 4) GIS practices in local governments in selected cities in the Global South (Baud et al. 2014). The talk concludes with discussing the potential and challenges of using Geo-Information in urban analysis and governance in different geographic contexts (Pfeffer & Verrest, 2016).
21.11.2017	Sensitivity analysis and verification of Agent Based Models	Arend Ligtenberg	Wageningen University
Agent Based Models (ABM) are increasingly used as simulation tool to model social-ecological system (SES) such as cities or agricultural systems. SES are often regarded as complex adaptive systems that show non-linear behaviour and lack clearly identifiable causation due to large numbers of entities in the system (humans, animals). Despite the promising features of ABM to represent such systems there are a number of major issues. First, collecting data to identify behaviour of the represented system is cumbersome. Second it is difficult to assess how an ABM is influenced by its parameters and input variables. Common used sensitivity methods are not directly applicable to ABM. In this talk I will present 1) a project in the Mekong Delta of Vietnam where we combined ABM with Role Playing Games (RPG) to define and verify behaviour rules of small holder shrimp farmers and 2) a research project were sensitivity methods have been developed for ABM that help to identify tipping points and resilience in SES simulations.
28.11.2017	Institute Meeting
Sorry, no abstract available yet.
05.12.2017	A Primer on Structure and Laws in GIScience	Franz-Benjamin Mocnik	Heidelberg University
Structures have turned out to often be invariant under paradigm shifts and are thus an integral part of many theories. However, in GIScience most research focusses on technological and ontological foundations, while laws and structurally stable results are still rare. Tobler's first law of geography is one of the widely known exceptions, though even that law appears to be much less rigorous than comparable counterparts from the natural sciences. In my talk, I present three different examples from the field of GIScience that would benefit from a more structural point of view. First, I discuss how maps are structurally different from texts, which is why they can often not serve for the purpose of telling stories in the same way as text can render complex narratives. Secondly, a structural understanding of the concepts of data quality and fitness for purpose is imparted. Both concepts have been explored for decades, but theoretical foundations of how different quality indicators relate to each other are yet to be discovered. Finally, the example of geographical data is discussed in a more general approach. The guiding question thereby is: how are geographical data shaped by geographic space, and how can the characteristics of geographical data be traced structurally?
12.12.2017	A model-based assessment of the environmental impact of land-use change in Southern Amazonia	Rüdiger Schaldach	Kassel University
During the past decades the expansion of agricultural land has led to a massive conversion of rainforest and Cerrado ecosystems in Southern Amazonia (Brazil), thus degrading biodiversity and altering environmental processes. Although, in the last couple of years the rate of land conversion could be significantly reduced, e.g. by agricultural intensification and environmental protection policies, deforestation rates are on the rise again due to increasing global demands for food, bioenergy and biomaterials, going hand in hand with only weak law enforcement. This presentation introduces a model framework that has been developed with the objective to improve the information basis available to scientists and policy makers, regarding the effects of global change and national environmental policies on future agricultural development and the resulting land-use change. Results from a scenario exercise portray different plausible trajectories of land-use change until 2030 and their impact on climate, water, soil and natural habitats.
19.12.2017	How Interactive Maps Work	Robert Roth	University of Wisonsin - Madison / University of Twente
Advances in personal computing and information technologies have fundamentally transformed how maps are produced and consumed, as many maps now are highly interactive and delivered online or through mobile applications. Increasingly, students need to learn how to encode geographic information based on sound cartographic principles as well as how to code a useful and usable interface for exploring the resulting maps. While much of the empirical research in cartography over the past half century has addressed representation design, evaluating the graphic symbols employed to communicate meaning in geographic information, relatively few empirical studies in cartography approach interaction design, research that is needed to understand how to successfully create digital mapping interfaces that meet user needs and promote geographic understanding. My research grapples with the central question “How do interactive maps work?” In this presentation, I first make the case for cartography in the ever-widening discipline of GIScience by highlighting a series of recent developments in the United States. I then provide an overview of my recent contributions to interactive map design, introducing a composite taxonomy of interaction primitives—the basic building blocks of interaction design that mirror the visual variables in representation design—and walking through several case studies that demonstrate how the interaction primitives can be used to advance both cartographic science and practice. I conclude by discussing how I have refreshed the cartography curriculum at UW-Madison to meet the demand for a new generation of interactive cartographers.
09.01.2018	Open Source business in practice: Earth observation and more	Markus Neteler	Mundialis.de
In my talk I'll present some of our current projects at mundialis, a "free data with free software" startup business. mundialis (https://www.mundialis.de) specializes in the evaluation of remote sensing data and the processing of massive geodata for different purposes. We rely on Free and Open Source GIS in order to create tailor-made solutions for our customers. One of our main focuses lies on the Sentinel satellite data from the European Copernicus program. Time series of these satellites are processed on demand and offered as OGC web services (with added value, i.e., atmospheric correction, estimation of indices, etc.). Satellite images time series provide information on changes in land use, soil moisture, surface temperature or vegetation phenology. In my presentation I will showcase several ongoing and completed projects for WHO, ESA, industry and research fields with focus on geospatial and EO data analysis and high performance computing platforms. The software stack of mundialis includes GRASS GIS, GDAL, QGIS, GeoServer, and SHOGun which enable us to realize applications like "maps mundialis" (Sentinel-2 frontend, https://maps.mundialis.de), "EO-me" (Earth Observation Metadata Enhancer, https://eome.mundialis.de), and a long-term landscape change analysis based on Landsat and openNRW data. The growth of mundialis over the past two years highlights the fact that enterprises can be based on and contribute to Free and Open Source software by applying innovative business models.
16.01.2018	Agent-based modelling of individuals’ activities in space and time: approaches for large-scale simulation	Theo Arentze	Eindhoven University of Technology
Activity-based models constitute the core of large-scale micro-simulation systems that hold many promises for policy evaluation in urban and transportation planning. Using micro-simulation, the new models offer a wealth of information for policy making. However, existing models predict behavior cross-sectionally for a random day of the life of simulated individuals. Although this approach is convenient, it is too restrictive for taking dynamic behavior and bounded-rationality into account. Individuals are reluctant to change existing habits and respond emotionally to losses and gains compared to a reference situation. The field has recognized the need for extending the time-frame of activity-based models and make the transition from static to dynamic modeling of behavior. First steps in this direction have recently been made and are supported by new GPS-based survey technologies which allow collection of activity-travel behavior data for longer periods of time. Although dynamic models offer appealing new perspectives, they also raise new issues when it comes to implementation in large-scale simulation systems and application in practice. In this presentation, I review approaches in the area of dynamic activity-based models for large-scale micro-simulation and discuss theoretical and computational issues as well as first experiences.
23.01.2018	Modelling and Mapping Earth Surface Processes using Statistical and Machine Learning Techniques	Alexander Brenning	Friedrich Schiller University Jena
Novel analysis and prediction methods developed at the intersection between computer science and statistics have been gaining popularity in recent years in Earth surface process modelling and mapping using, for instance, geomorphometric and remotely-sensed predictor variables. These techniques promise to improve predictive performances by overcoming the limitations of statistical models, making better use of highly correlated and interacting predictors such as terrain attributes calculated at different resolutions, or image filter banks. However, these possible improvements come at the cost of potential overfitting and limited interpretability of models. This talk discusses the potential and pitfalls of novel and 'traditional' methods in case studies such as landslide susceptibility modelling and environmental remote sensing.
30.01.2018	Institute Meeting
Sorry, no abstract available yet.

GI-Forum Archive (SS 12 - SS 17)