Zeitschriftenbeiträge

Aljoumani, B., Sanchez-Espigares, J., Kluge, B., Wessolek, G. and Kleinschmit, B. (2022). Analyzing Temporal Trends of Urban Evaporation Using Generalized Additive Models [9]. Land

Vallentin, C., Harfenmeister, K., Itzerott, S., Kleinschmit, B., Conrad, C. and Spengler, D. (2022). Suitability of satellite remote sensing data for yield estimation in northeast Germany [10]. Precision Agriculture, 52–82.

Duarte Rocha, A., Vulova, S., van der Tol, C., Förster, M. and Kleinschmit, B. (2022). Modelling hourly evapotranspiration in urban environments with SCOPE using open remote sensing and meteorological data [11]. Hydrology and Earth System Sciences

Rocchini, D., Salvatori, N., Beierkuhnlein, C., Chiarucci, A., de Boissieu, F., Förster, M., Garzon-Lopez, C., Gillespie, T. W., Hauffe, H., He, K., Kleinschmit, B., Lenoir, J., Malavasi, M., Moudrý, V., Nagendra, H., Payne, D., Šímová, P., Torresani, M., Wegmann, M. and Féret, J.-B. (2021). From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing. [12]. Ecological Informatics. Elsevier, 1-10.

Hölzl, S. E., Veskov, M., Scheibner, T., Le, T. T. and Kleinschmit, B. (2021). Vulnerable socioeconomic groups are disproportionately exposed to multiple environmental burden in Berlin - implications– for planning [13]. International journal of urban sustainable development, 1-18.

Gränzig, T., Fassnacht, F. E., Kleinschmit, B. and Förster, M. (2021). Mapping the fractional coverage of the invasive shrub Ulex europaeus with multi-temporal Sentinel-2 imagery utilizing UAV orthoimages and a new spatial optimization approach. [14]. International Journal of Applied Earth Observation and Geoinformation

Bauhus, J., Seeling, U., Dieter, M., Farwig, N., Hafner, A., Kätzel, R., Kleinschmit, B., Lang, F., Lindner, M., Möhring, B., Müller, J., M., N., Richter, K. and Schraml, U. (2021). Die Anpassung von Wäldern und Waldwirtschaft an den Klimawandel [15]. Berichte über Landwirtschaft-Zeitschrift für Agrarpolitik und Landwirtschaft, 1-158.

Schulz, C., Holtrave, A. and Kleinschmit, B. (2021). Large-scale winter catch crop monitoring with Sentinel-2 time series and machine learning–An alternative to on-site controls? [16]. Computers and Electronics in Agriculture

Vulova, S., Meier, F., Rocha, A. D., Quanz, J., Nouri, H. and and Kleinschmit, B. (2021). Modeling urban evapotranspiration using remote sensing, flux footprints, and artificial intelligence [17]. Science of The Total Environment, 1-13.

Döpper, V. U., Rocha, A. D., Gränzig, T., Kleinschmit, B. and Förster, M. (2021). Using radiative transfer models for mapping soil moisture content under grassland with UAS-borne hyperspectral data [18]. Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII

Vulova, S., Meier, F., Fenner, D., Nouri, H. and Kleinschmit, B. (2020). Summer Nights in Berlin, Germany: Modeling Air Temperature Spatially With Remote Sensing, Crowdsourced Weather Data, and Machine Learning [19]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-15.

Holtgrave, A., Röder, N., Ackermann, A., Erasmi, S. and Kleinschmit, B. (2020). Comparing Sentinel-1 and -2 Data and Indices for Agricultural Land Use Monitoring [20]. remote sensing, 1-27.

Fersch, B., Francke, T., Heistermann, M., Schrön, M., Döpper, V., Jakobi, J., Baroni, G., Blume, T., Bogena, H., Budach, C., Gränzig, T., Förster, M., Güntner, A., Hendricks Franssen, H., Kasner, M., Köhli, M., Kleinschmit, B., Kunstmann, H., Patil, A., Rasche, D., Scheiffele, L., Schmidt, U., Szulc-Seyfried, S., Weimar, J., Zacharias, S., Zreda, M., Heber, B., Kiese, R., Mares, V., Mollenhauer, H., Völksch, I. and Oswald, S. (2020). A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany [21]. Earth System Science Data, 2289-2309.

Fenske, K., Feilhauer, H., Förster, M., Stellmes, M. and Waske, B. (2020). Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series [22]. International Journal of Applied Earth Observation and Geoinformation, 1-13.

Döpper, V., Gränzig, T., Kleinschmit, B. and Förster, M. (2020). Challenges in UAS-Based TIR Imagery Processing: Image Alignment and Uncertainty Quantification. [23]. remote sensing, 1-22.