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.

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.

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. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 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. Catena, 192-205.

Schmidt, J., Fassnacht, F. E., Neff, C., Lausch, A., Kleinschmit, B., Förster, M. and Schmidtlein, S. (2017). Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status. International Journal of Applied Earth Observation and Geoinformation, 61-71.

Gärtner, P., Förster, M. and Kleinschmit, B. (2016). The benefit of synthetically generated RapidEye and Landsat 8 data fusion time series for riparian forest disturbance monitoring. Remote Sensing of Environment. Elsevier, 237-247.

Neumann, C., Förster, M., Kleinschmit, B. and Itzerott, S. (2016). Utilizing a PLSR-Based Band-Selection Procedure for Spectral Feature Characterization of Floristic Gradients. EEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-15.

Clasen, A., Somers, B., Pipkins, K., Tits, L., Segl, K., Brell, M., Kleinschmit, B., Spengler, D., Lausch, A. and Förster, M. (2015). Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale. remote sensing, 26.

Baur, A. H., Lauf, S., Förster, M. and Kleinschmit, B. (2015). Estimating greenhouse gas emissions of European cities — Modeling emissions with only one spatial and one socioeconomic variable. Science of the Total Environment. Elsevier B.V., 49-58.

Rocchini, D., Andreo, V., Förster, M., Gutierrez, A., Gillespie, W., Hauffe, H., He, K., Kleinschmit, B., Mairota, P., Marcantonio, M., Metz, M., Nagendra, H., Pareeth, S., Ponti, L., Ricotta, C., Rizzoli, A., Schaab, G., Zebisch, M., Zorer, R. and Neteler, M. (2015). Potential of remote sensing to predict species invasions: A modelling perspective. Progress in Physical Geography, 283-309.

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.

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.

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. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 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. Catena, 192-205.

Schmidt, J., Fassnacht, F. E., Neff, C., Lausch, A., Kleinschmit, B., Förster, M. and Schmidtlein, S. (2017). Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status. International Journal of Applied Earth Observation and Geoinformation, 61-71.

Gärtner, P., Förster, M. and Kleinschmit, B. (2016). The benefit of synthetically generated RapidEye and Landsat 8 data fusion time series for riparian forest disturbance monitoring. Remote Sensing of Environment. Elsevier, 237-247.

Baur, A. H., Lauf, S., Förster, M. and Kleinschmit, B. (2015). Estimating greenhouse gas emissions of European cities — Modeling emissions with only one spatial and one socioeconomic variable. Science of the Total Environment. Elsevier B.V., 49-58.

Rocchini, D., Andreo, V., Förster, M., Gutierrez, A., Gillespie, W., Hauffe, H., He, K., Kleinschmit, B., Mairota, P., Marcantonio, M., Metz, M., Nagendra, H., Pareeth, S., Ponti, L., Ricotta, C., Rizzoli, A., Schaab, G., Zebisch, M., Zorer, R. and Neteler, M. (2015). Potential of remote sensing to predict species invasions: A modelling perspective. Progress in Physical Geography, 283-309.

Nieland, S., Moran, N., Kleinschmit, B. and Förster, M. (2015). An ontological system for interoperable spatial generalisation in biodiversity monitoring. Computers & Geosciences, 86-95.

Baur, A. H., Förster, M. and Kleinschmit, B. (2015). The spatial dimension of urban greenhouse gas emissions: analyzing the influence of spatial structures and LULC patterns in European cities. Landscape Ecology. Springer.