Prof. Dr. Hanna Meyer

• 2025
• 2024
• 2023
• 2022
• 2021
• 2020
• 2019
• 2018
• 2017
• 2016
• 2015
• 2014
• 2013

2025

• Baumberger, M, Haas, B, Tewes, W, Risse, B, Meyer, N, and Meyer, H. 2025. “Gated recurrent units for modelling time series of soil temperature and moisture: An assessment of performance and process reflectivity.” Environmental Modelling and Software, № 183: 106245–106245. doi: 10.1016/j.envsoft.2024.106245.
• Giese, L, Baumberger, M, Ludwig, M, Schneidereit, H, Sánchez, E, Robroek, BJ, Lamentowicz, M, Lehmann, J, Hölzel, N, Knorr, K, and Meyer, H. 2025. “Recent trends in moisture conditions across European peatlands.” Remote Sensing Applications: Society and Environment, № 37: 101385–101385. doi: 10.1016/j.rsase.2024.101385.
• Krämer, A, Meyer, H, and Buchholz, S. 2025. “Habitat Suitability of the Sand Lizard (Lacerta agilis) at Its Distribution Limit—An Analysis Based on Citizen Science Data and Machine Learning.” Journal of Biogeography, № n/a (n/a) doi: 10.1111/jbi.15099.

2024

• Meyer, H, Ludwig, M, Milà, C, Linnenbrink, J, and Schumacher, F. 2024. “The CAST package for training and assessment of spatial prediction models in R.” arXiv doi: 10.48550/arXiv.2404.06978.
• Milà, C, Ludwig, M, Pebesma, E, Tonne, C, and Meyer, H. 2024. “Random forests with spatial proxies for environmental modelling: opportunities and pitfalls.” Geoscientific Model Development, № 2024 (17): 6007–603. doi: 10.5194/gmd-17-6007-2024.
• Linnenbrink, J, Milà, C, Ludwig, M, and Meyer, H. 2024. “kNNDM CV: k-fold nearest-neighbour distance matching cross-validation for map accuracy estimation.” Geoscientific Model Development, № 17 (15): 5897–5912. doi: 10.5194/gmd-17-5897-2024.
• Baumberger, M, Haas, B, Sivakumar, S, Ludwig, M, Meyer, N, and Meyer, H. 2024. “High-resolution soil temperature and soil moisture patterns in space, depth and time: An interpretable machine learning modelling approach.” Geoderma, № 451: 117049–117049. doi: 10.1016/j.geoderma.2024.117049.
• Schumacher, F, Knoth, C, Ludwig, M, and Meyer, H. 2024. “Estimation of local training data point densities to support the assessment of spatial prediction uncertainty.” EGUsphere doi: 10.5194/egusphere-2024-2730.
• Bald, L, Ziegler, A, Gottwald, J, Koch, TL, Ludwig, M, Meyer, H, Wöllauer, S, Zeuss, D, and Frieß, N. 2024. “Leveraging heterogeneous LiDAR data to model successional stages at tree species level in temperate forests.” Environmental Data Science, № 3: e24–e24. doi: 10.1017/eds.2024.31.
• Datta, R, Katurji, M, Nielsen, E, Meyer, H, Zawar-Reza, P, and Valdes, ML. 2024. “The Winter Foehn Footprint Across McMurdo Dry Valleys of Antarctica Using a Satellite-Derived Data Set-AntAir v1.0.” Journal of Geophysical Research: Atmospheres, № 129 (23): e2023JD039300. doi: 10.1029/2023JD039300.

2023

• Ludwig, M, Moreno-Martinez, A, Hölzel, N, Pebesma, E, and Meyer, H. 2023. “Assessing and improving the transferability of current global spatial prediction models.” Global Ecology and Biogeography, № 00: 1–13. doi: 10.1111/geb.13635.
• Ziegler, A, Heisig, J, Ludwig, M, Reudenbach, C, Meyer, H, and Nauss, T. 2023. “Using GEDI as training data for an ongoing mapping of landscape-scale dynamics of the plant area index.” Environmental Research Letters, № 18 (7) doi: 10.1088/1748-9326/acde8f.
• Nielsen, EB, Katurji, M, Zawar-Reza, P, and Meyer, H. 2023. “Antarctic daily mesoscale air temperature dataset derived from MODIS land and ice surface temperature.” Scientific data, № 10 (1): 833–833. doi: 10.1038/s41597-023-02720-z.

2022

• Mila, C, Mateu, J, Pebesma, E, and Meyer, H. 2022. “Nearest neighbour distance matching leave-one-out cross-validation for map validation.” Methods in Ecology and Evolution, № 13: 1304–1316. doi: 10.1111/2041-210X.13851.
• Meyer, H, and Pebesma, E. 2022. “Machine learning-based global maps of ecological variables and the challenge of assessing them.” Nature Communications, № 13 doi: 10.1038/s41467-022-29838-9.
• Ziegler, A, Meyer, H, Otte, I, Peters, MK, Appelhans, T, Behler, C, Böhning-Gaese, K, Classen, A, Detsch, F, Deckert, J, Eardley, CD, Ferger, SW, Fischer, M, Gebert, F, Haas, M, Helbig-Bonitz, M, Hemp, A, Hemp, C, Kakengi, V, Mayr, AV, Ngereza, C, Reudenbach, C, Röder, J, Rutten, G, Schellenberger Costa, D, Schleuning, M, Ssymank, A, Steffan-Dewenter, I, Tardanico, J, Tschapka, M, Vollstädt, MGR, Wöllauer, S, Zhang, J, Brandl, R, and Nauss, T. 2022. “Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro.” Remote Sensing, № 14 (3): 786. doi: 10.3390/rs14030786.
• Ludwig, M, Bahlmann, J, Pebesma, E, and Meyer, H. 2022. “Developing Transferable Spatial Prediction Models: a Case Study of Satellite Based Landcover Mapping.” contribution to the ISPRS, Nice doi: 10.5194/isprs-archives-XLIII-B3-2022-135-2022.
• Kleinewillinghöfer, L, Olofsson, P, Pebesma, E, Meyer, H, Buck, O, Haub, C, and Eiselt, B. 2022. “Unbiased Area Estimation Using Copernicus High Resolution Layers and Reference Data.” Remote Sensing, № 14 (19): 4903. doi: 10.3390/rs14194903.

2021

• Lezama Valdes, M, Katurji, M, and Meyer, H. 2021. “A Machine Learning Based Downscaling Approach to Produce High Spatio-Temporal Resolution Land Surface Temperature of the Antarctic Dry Valleys from MODIS Data.” Remote Sensing, № 13 (22) doi: 10.3390/rs13224673.
• Petermann, E, Meyer, H, Nussbaum, M, and Bossew, P. 2021. “Mapping the geogenic radon potential for Germany by machine learning.” Science of the Total Environment, № 754: 142291. doi: 10.1016/j.scitotenv.2020.142291.
• Meyer, H, and Pebesma, E. 2021. “Predicting into unknown space? Estimating the area of applicability of spatial prediction models.” Methods in Ecology and Evolution, № 12: 1620–1633. doi: 10.1111/2041-210X.13650.
• Meyer, H, and Pebesma, E. 2021. “Estimating the Area of Applicability of Remote Sensing-Based Machine Learning Models with Limited Training Data.” in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS doi: 10.1109/IGARSS47720.2021.9553999.

2020

• Hess, B, Dreber, N, Liu, Y, Wiegand, K, Ludwig, M, Meyer, H, and Meyer, KM. 2020. “PioLaG: a piosphere landscape generator for savanna rangeland modelling.” Landscape Ecology, № 35 (9): 2061–2082. doi: 10.1007/s10980-020-01066-w.
• Schumacher, B, Katurji, M, Meyer, H, Appelhans, T, Otte, I, and Nauss, T. 2020. “Atmospheric moisture pathways of East Africa and implications for water recycling at Mount Kilimanjaro.” International Journal of Climatology, № 2020 doi: 10.1002/joc.6468.

2019

• Meyer, H, Schmidt, J, Detsch, F, and Nauss, T. 2019. “Hourly gridded air temperatures of South Africa derived from MSG SEVIRI.” International Journal of Applied Earth Observation and Geoinformation, № 78: 261–267. doi: 10.1016/j.jag.2019.02.006.
• Lehnert, LW, Meyer, H, Obermeier, WA, Silva, B, Regeling, B, and Bendix, J. 2019. “Hyperspectral Data Analysis in R: The hsdar Package.” Journal of Statistical Software, № 89 (12) doi: 10.18637/jss.v089.i12.
• Meyer, H, Reudenbach, C, Wöllauer, S, and Nauss, T. 2019. “Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction.” Ecological Modelling, № 411: 108815. doi: 10.1016/j.ecolmodel.2019.108815.
• Ludwig, M, Morgenthal, T, Detsch, F, Higginbottom, TP, Lezama Valdes, M, Nauß, T, and Meyer, H. 2019. “Machine learning and multi-sensor based modelling of woody vegetation in the Molopo Area, South Africa.” Remote Sensing of Environment, № 222: 195–203. doi: 10.1016/j.rse.2018.12.019.

2018

• Reudenbach, C, and Meyer, H. 2018. uavRst: Unmanned Aerial Vehicle Remote Sensing Tools. R package version 0.5-2.,
• Meyer, H, Reudenbach, C, and Nauss, T. 2018. CAST: 'caret' Applications for Spatial-Temporal Models. R package version 0.1.0.,
• Meyer, N, Meyer, H, Welp, G, and Amelung, W. 2018. “Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy.” Geoderma, № 323: 31–40. doi: 10.1016/j.geoderma.2018.02.031.
• Higginbottom, TP, Symeonakis, E, Meyer, H, and Linden, S. 2018. “Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data.” ISPRS Journal of Photogrammetry and Remote Sensing, № 139: 88–102. doi: 10.1016/j.isprsjprs.2018.02.010.
• Wang, Y, Lehnert, LW, Holzapfel, M, Schultz, R, Heberling, G, Görzen, E, Meyer, H, Seeber, E, Pinkert, S, Ritz, M, Fu, Y, Ansorge, H, Bendix, J, Seifert, B, Miehe, G, Long, R, Yang, Y, and Wesche, K. 2018. “Multiple indicators yield diverging results on grazing degradation and climate controls across Tibetan pastures.” Ecological Indicators, № 93: 1199–1208. doi: 10.1016/j.ecolind.2018.06.021.
• Meyer, H, Reudenbach, C, Hengl, T, Katurji, M, and Nauss, T. 2018. “Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation.” Environmental Modelling and Software, № 101: 1–9. doi: 10.1016/j.envsoft.2017.12.001.

2017

• Meyer, H, Lehnert, LW, Wang, Y, Reudenbach, C, Nauss, T, and Bendix, J. 2017. “From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?” International Journal of Applied Earth Observation and Geoinformation, № 55: 21–31. doi: 10.1016/j.jag.2016.10.001.
• Meyer, H, Kühnlein, M, Reudenbach, C, and Nauss, T. 2017. “Revealing the potential of spectral and textural predictor variables in a neural network-based rainfall retrieval technique.” Remote Sensing Letters, № 8 (7): 647–656. doi: 10.1080/2150704X.2017.1312026.
• Messenzehl, K, Meyer, H, Otto, J, Hoffmann, T, and Dikau, R. 2017. “Regional-scale controls on the spatial activity of rockfalls (Turtmann Valley, Swiss Alps) — A multivariate modeling approach.” Geomorphology, № 287: 29–45. doi: 10.1016/j.geomorph.2016.01.008.
• Meyer, H, Drönner, J, and Nauss, T. 2017. “Satellite-based high-resolution mapping of rainfall over southern Africa.” Atmospheric Measurement Techniques, № 10 (6): 2009–2019. doi: 10.5194/amt-10-2009-2017.

2016

• Meyer, H, Kühnlein, M, Appelhans, T, and Nauss, T. 2016. “Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals.” Atmospheric Research, № 169, Part B: 424–433. doi: 10.1016/j.atmosres.2015.09.021.
• Ludwig, A, Meyer, H, and T, Nauss. 2016. “Automatic classification of Google Earth images for a larger scale monitoring of bush encroachment in South Africa.” International Journal of Applied Earth Observation and Geoinformation, № 50: 89–94. doi: 10.1016/j.jag.2016.03.003.
• Lehnert, LW, Meyer, H, and Bendix, J. 2016. hsdar: Manage, analyse and simulate hyperspectral data in R. R package version 0.5.1.,
• Meyer, H, Katurji, M, Appelhans, T, Müller, MU, Nauss, T, Roudier, P, and Zawar-Reza, P. 2016. “Mapping Daily Air Temperature for Antarctica Based on MODIS LST.” Remote Sensing, № 8 (9) doi: 10.3390/rs8090732.

2015

• Lehnert, LW, Meyer, H, Wang, Y, Miehe, G, Thies, B, Reudenbach, C, and Bendix, J. 2015. “Retrieval of grassland plant coverage on the Tibetan Plateau based on a multi-scale, multi-sensor and multi-method approach.” Remote Sensing of Environment, № 164: 197–207. doi: 10.1016/j.rse.2015.04.020.
• Gasch, CK, Hengl, T, Gräler, B, Meyer, H, Magney, TS, and Brown, DJ. 2015. “Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D + T: The Cook Agronomy Farm data set.” Spatial Statistics, № 14, Part A: 70–90.
• Nauss, T, Meyer, H, Detsch, F, and Appelhans, T. 2015. Manipulating satellite data with satellite. R package version 1.0.0.,

2014

• Lehnert, L, Meyer, H, Meyer, N, Reudenbach, C, and Bendix, J. 2014. “A hyperspectral indicator system for rangeland degradation on the Tibetan Plateau: A case study towards spaceborne monitoring.” Ecological Indicators, № 39: 54–64. doi: 10.1016/j.ecolind.2013.12.005.
• Thies, B, Meyer, H, Nauss, T, and Bendix, J. 2014. “Projecting land-use and land-cover changes in a tropical mountain forest of Southern Ecuador.” Journal of Land Use Science, № 9 (1): 1–33.

2013

• Windhorst, D, Silva, B, Peters, T, Meyer, H, Thies, B, Bendix, J, Frede, H, and Breuer, L. 2013. “Impacts of local land-use change on climate and hydrology.” in Ecosystem services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador, Vol. 221 of Ecological Studies, edited by J Bendix, E Beck, A Bräuning, F Makeschin, R Mosandl, S Scheu and W Wilcke. Heidelberg: Springer. doi: 10.1007/978-3-642-38137-9_20.
• Roos, K, Bendix, J, Curatola, G, Gawlik, J, Gerique, A, Hamer, U, Hildebrandt, P, Knoke, T, Meyer, H, Pohle, P, Potthast, K, Thies, B, Tischer, A, and Beck, E. 2013. “Current provisioning services: pasture development and use, weeds (bracken) and management.” in Ecosystem services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador, Vol. 221 of Ecological Studies, edited by J Bendix, E Beck, A Bräuning, F Makeschin, R Mosandl, S Scheu and W Wilcke. Düsseldorf: Springer VDI Verlag. doi: 10.1007/978-3-642-38137-9_15.
• Peters, T, Drobnik, T, Meyer, H, Rankl, M, Richter, M, Rollenbeck, R, Thies, B, and Bendix, J. 2013. “Environmental changes affecting the Andes of Ecuador.” in Ecosystem services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador, Vol. 221 of Ecological Studies, edited by J Bendix, E Beck, A Bräuning, F Makeschin, R Mosandl, S Scheu and W Wilcke. Düsseldorf: Springer VDI Verlag. doi: 10.1007/978-3-642-38137-9_2.