Dr. Michael Förster

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 [8]. Hydrology and Earth System Sciences, 26(4). doi: doi.org/10.5194/hess-26-1111-2022 [9]

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. [10]. Ecological Informatics, 61, pp. 1-10. doi: https://doi.org/10.1016/j.ecoinf.2020.101195 [11]

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. [12]. International Journal of Applied Earth Observation and Geoinformation, 96(102281).

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 [13]. Earth System Science Data, 12, pp. 2289-2309. doi: https://doi.org/10.5194/essd-12-2289-2020 [14]

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 [15]. International Journal of Applied Earth Observation and Geoinformation, 87, pp. 1-13. doi: https://doi.org/10.1016/j.jag.2019.102036 [16]

Döpper, V., Gränzig, T., Kleinschmit, B. and Förster, M. (2020): Challenges in UAS-Based TIR Imagery Processing: Image Alignment and Uncertainty Quantification. [17]. remote sensing, 12(1552), pp. 1-22. doi: https://doi.org/10.3390/rs12101552 [18]

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 [19]. Remote Sensing of Environment, 227(2019), pp. 61-73.

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 [20]. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2018, pp. 85–101.

Klinke, R., Kuechly, H., Frick, A., Förster, M., Schmidt, T., Holtgrave, A.-K. a. K. B., Spengler, D. and Neumann, C. (2018): Indicator-Based Soil Moisture Monitoring ofWetlands by Utilizing Sentinel and Landsat Remote Sensing Data [21]. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2018, pp. 71–84.

Möller, M., Gerstmann, H., Gao, F., Dahms, T. C. and Förster, M. (2017): Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk [22]. Catena, 170, pp. 192-205. doi: 10.1016/j.catena.2016.11.016 [23]