Publications of the Remote Sensing and Spatial Modelling Research Group

Peer-Reviewed Papers

2020
  • Durán J, Rodríguez A, del Mora A, de los Ríos A, Lehmann JRK, Heiðmarsson S (in press): Cryptogamic cover determines soil attributes and functioning in polar terrestrial ecosystems. Science of The Total Environment.[https://doi.org/10.1016/j.scitotenv.2020.143169]
  • Petermann E, Meyer H, Nussbaum M, Bossew P (in press): Mapping the geogenic radon potential for Germany by machine learning. Science of The Total Environment. [https://doi.org/10.1016/j.scitotenv.2020.142291]
  • Heringer G, Thiele J, Amaral C, Meira-Neto J, Matos F, Lehmann JRK, Buttschardt T, Neri A (2020): Acacia invasion is facilitated by landscape permeability: the role of habitat degradation and road networks. Applied Vegetation Science. [https://doi.org/10.1111/avsc.12520]
  • Hess B, Dreber N, Liu Y, Wiegand K, Ludwig M, Meyer H, Meyer K (2020): PioLaG: a piosphere landscape generator for savanna rangeland modelling. Landscape Ecology. [https://doi.org/10.1007/s10980-020-01066-w]
  • Schumacher B, Katurji M, Meyer H, Appelhans T, Otte I, Nauss T. (2020). Atmospheric moisture pathways of East Africa and implications for water recycling at Mount Kilimanjaro. International Journal of Climatology 2020. [doi: https://doi.org/10.1002/joc.6468]
2019
  • Lehnert LW, Meyer H, Obermeier WA, Silva B, Regeling B, Bendix J (2019) Hyperspectral Data Analysis in R: the hsdar-Package. Journal of Statistical Software 89(12): 1–23 [doi:10.18637/jss.v089.i12] Open Access
  • Meyer H, Reudenbach C, Wöllauer S,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]
  • Meyer H, Schmidt J, Detsch F, 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]
  • Ludwig M, Morgenthal T, Detsch F, Higginbottom TP, Lezama Valdes M, Nauß T, 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]
  • Carl C, Lehmann JRK, Landgraf D, Pretzsch H (2019). Robinia pseudoacacia L. in Short Rotation Coppice: Seed and Stump Shoot Reproduction as well as UAS-based Spreading Analysis. Forests 10, Nr. 3 [doi.org/10.3390/f10030235]
  • Teickner H, Lehmann JRK, Guth P, Meinking F, Ott D (2019) Recognize the Little Ones: UAS-Based In-Situ Fluorescent Tracer Detection Drones 3, Nr. 1 [doi: 10.3390/drones3010020]
2018
  • Higginbottom TP, Symeonakis E, Meyer H, van den 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]
  • Meyer H, Reudenbach C, Hengl T, Katurij M, Nauss T (2018) Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation. Environmental Modelling & Software 101: 1–9 [doi:10.1016/j.envsoft.2017.12.001]
  • Meyer N, Meyer H, Welp G, Amelung W (2018) Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy. Geoderma 323(1): 31–40 [doi:10.1016/j.geoderma.2018.02.031]
  • 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 RJ, Yang YP, 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]
2017
  • Messenzahl K, Meyer H, Otto JC, Hoffmann T, 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, 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]
  • Meyer H, Kühnlein M, Reudenbach C, 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]
  • Meyer H, Lehnert LW, Wang Y, Reudenbach C, Nauss T, 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]
  • Lehmann JRK, Prinz T, Ziller SR, Thiele J, Heringer G, Meira-Neto JAA, Buttschardt TK. (2017) Open-Source Processing and Analysis of Aerial Imagery Acquired with a Low-Cost Unmanned Aerial System to Support Invasive Plant Management. Frontiers in Environmental Science 5: 44 [doi: 10.3389/fenvs.2017.00044]
2016
  • Ludwig A, Meyer H, Nauss T (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]
  • Meyer H, Katurji M, Appelhans T, Müller MU, Nauss T, Roudier P, Zawar-Reza P (2016) Mapping Daily Air Temperature for Antarctica Based on MODIS LST. Remote Sensing 8(9): 732 [doi:10.3390/rs8090732] Open Access
  • Meyer H, Kühnlein M, Appelhans T, Naus T (2016) Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals. Atmospheric Research 169(B): 424–433 [doi:10.1016/j.atmosres.2015.09.021]
  • Lehmann JRK, Münchberger W, Knoth C, Blodau C, Nieberding F u. a. (2016) High-Resolution Classification of South Patagonian Peat Bog Microforms Reveals Potential Gaps in Up-Scaled CH4 Fluxes by use of Unmanned Aerial System (UAS) and CIR Imagery. Remote Sensing 8, Nr. 3: 173 [doi: 10.3390/rs8030173]
2015
  • Gasch C, Hengl T, Gräler B, Meyer H, Magney T, Brown DJ (2015) Spatio-temporal interpolation of soil moisture, temperature, and electrical conductivity in 3D+T: the Cook Farm data set. Spatial Statistics 14 (A): 70–90 [doi:10.1016/j.spasta.2015.04.001]
  • Lehnert LW, Meyer H, Wang Y, Miehe G, Thies B, Reudenbach C, 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]
  • Lehmann, J. R. K, Große-Stoltenberg, A., Römer, M., Oldeland u. a. (2015): Field Spectroscopy in the VNIR-SWIR Region to Discriminate between Mediterranean Native Plants and Exotic-Invasive Shrubs Based on Leaf Tannin Content. Remote Sensing Journal 2015, Nr. 7: 1225-1241. [doi: 10.3390/rs70201225]
  • Lehmann JRK, Nieberding F, Prinz T, Knoth C. (2015) Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels.’ Forests 6, Nr. 3: 594--612 [doi: 10.3390/f6030594].
  • Lehmann JRK, Smithson KZ, Prinz T. (2015) Making the invisible visible: using UAS-based high-resolution color-infrared imagery to identify buried medieval monastery walls. Journal of Unmanned Vehicle Systems 3, Nr. 2: 58-67 [doi: 10.1139/juvs-2014-0017]
2014
  • Lehnert LW, Meyer H, Meyer N, Reudenbach C, 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, 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 [doi:10.1080/1747423X.2012.718378]

Book chapters

  • Peters T, Drobnik T, Meyer H, Rankl M, Richter M, Rollenbeck R, Thies B, Bendix J (2013) Environmental changes affecting the Andes of Ecuador. In: Beck E, Bräuning A, Makeschin F, Mosandl E, Scheu S, Wilcke W (eds.) Ecosystem services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador. Ecological Studies (Analysis and Synthesis) 221: 19–29 [doi:10.1007/978-3-643-38137-9_2]
  • 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, Beck E (2013) Current provisioning services: Pasture development and use, weeds (bracken) and management. In: Beck E, Bräuning A, Makeschin F, Mosandl E, Scheu S, Wilcke W (eds.) Ecosystem services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador. Ecological Studies (Analysis and Synthesis) 221: 205–217 [doi:10.1007/978-3-642-38137-9_15]
  • Windhorst D, Silva B, Peters T, Meyer H, Thies B, Bendix J, Frede HG, Breuer L (2013) Impacts of local land use change on local climate and hydrology. In: Beck E, Bräuning A, Makeschin F, Mosandl E, Scheu S, Wilcke W (eds.) Ecosystem services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador. Ecological Studies (Analysis and Synthesis) 221: 275–286 [doi:10.1007/978-3-642-38137-9_20]

R packages

  • Meyer H, Reudenbach C, Nauss T (2018) CAST: 'caret' Applications for Spatial-Temporal Models. R package version 0.3.1 [Link]
  • Reudenbach C, Meyer H (2018) uavRst: Unmanned Aerial Vehicle Remote Sensing Tools. R package version 0.5-2 [Link]
  • Lehnert LW, Meyer H, Bendix J (2016) hsdar: Manage, analyse and simulate hyperspectral data in R. R package version 1.0.0 [Link]
  • Nauss T, Meyer H, Detsch F, Appelhans T (2015) Manipulating satellite data with satellite. R package version 1.0.1 [Link]