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.. 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. 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.. 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. Berichte über Landwirtschaft-Zeitschrift für Agrarpolitik und Landwirtschaft, 1-158.

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. 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. 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. 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. 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. 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. 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.. remote sensing, 1-22.

Kattenborn, T., Lopatina, J., Förster, M., Braun, A. C. and Fassnacht, F. E. (2019). UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data. Remote Sensing of Environment, 61-73.

Vallentin, C., Dobers, E. S., Itzerott, S., Kleinschmit, B. and Spengler, D. (2019). Delineation of management zones with spatial data fusion and belief theory. Precision Agriculture. Springer, 1-29.

Schulz, C. and Kleinschmit, B. (2019). Zentralasiatische Tugai-Auwälder – Ein gefährdetes Ökosystem. Auenmagazin, 11-17.

Holtgrave, A.-K., Förster, M., Greifeneder, F., Notarnicola, C. and Kleinschmit, B. (2018). Estimation of Soil Moisture in Vegetation-Covered Floodplains with Sentinel-1 SAR Data Using Support Vector Regression. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85–101.