WG mem­bers’ pu­bli­ca­ti­ons (ISI lis­ted on­ly)

  • Grüner E., Astor T., Wachendorf M. (2019): Biomass Prediction of Heterogeneous Temperate Grasslands Using an SfM Approach Based on UAV Imaging. Agronomy 2019, 9(2), 54. PDF

  • Schulze-Brüninghoff D., Hensgen F., Wachendorf M., Astor T. (2019): Methods for LiDAR-based estimation of extensive grassland biomass. Computer and Electronics in Agriculture 156, 693-699. PDF
  • Wijesingha J, Moeckel T., Hensgen F., Wachendorf M. (2019): Evaluation of 3D point cloud-based models for the prediction of grassland biomass. International Journal of Applied Earth Observation and Geoinformation 78, 352-359. PDF
  • Möckel T., Dayananda S., Nidamanuri R.R., Nautiyla S., Hanumaiah N., Buerkert A., Wachendorf M. (2018): Estimation of Vegetable Crop Parameters by Multi-temporal UAV-Borne Images. Remote Sensing 2018, 10, 805. PDF
  • Löfgren O., Prentice H. C., Möckel T., Schmid B. C., Hall K. (2018): Landscape history confounds the ability of the NDVI to detect fine-scale variation in grassland communities. Methods in Ecology and Evolution. Methods in Ecology and Evolution 2018, 9, (9), 2009-2018. PDF
  • Wachendorf M., Fricke T., Möckel T. (2018) Remote sensing as a tool to assess botanical composition, structure, quantity and quality of temperate grasslands. Grass and Forage Science. DOI: 10.1111/gfs.12312. PDF