Deutsch Intern
Earth Observation Research Cluster

Maninder Singh Dhillon, Dr.

 

Department of Remote Sensing

  +49 (0)931 31-81890
 maninder.dhillon@uni-wuerzburg.de

Institute for Geography und Geology
Department for Remote Sensing
John Skilton Str. 4a
97074 Würzburg

upon request

  • Agricultural remote sensing
  • Crop yield modeling
  • Land-use diversity
  • Biodiversity
  • Sustainable agriculture
  • Precision agriculture

Since 03/2024
Postdoc at the Department of Remote Sensing of the University of Wuerzburg / Lead of the working package “Biodiversity” at the JMU in the EO4CAM project

04/2023 – 02/2024
Scientific employee at the Department of Remote Sensing, University of Wuerzburg

03/2019 – 03/2023
PhD student at the Department of Remote Sensing, University of Wuerzburg
Topic: "Potential of Remote Sensing in Modeling Long-Term Crop Yields"

07/2018- 02/2019
Research assistant at the Department of Remote Sensing, University of Wuerzburg

02/2018 - 04/2018
Intern, German Aerospace Center (DLR), Neustrelitz, Germany

09/2016 – 02/2019
Studies of Earth Observation and Geoanalysis "EAGLE" (M.Sc.), University of Wuerzburg
Master thesis: "Comparing the perfomance of crop growth models using synthetic remote sensing data at DEMMIN, Germany"

12/2015- 09/2016
Research Assistant at the Punjab Remote Sensing Center (PRSC), Ludhiana, India

2024[ to top ]
  • Liepa, A.; Thiel, M.; Taubenböck, H.; Steffan-Dewenter, I.; Abu, I.-O.; Singh Dhillon, M.; Otte, I.; Otim, M. H.; Lutaakome, M.; Meinhof, D.; Martin, E. A.; Ullmann, T. (2024): Harmonized NDVI time-series from Landsat and Sentinel-2 reveal phenological patterns of diverse, small-scale cropping systems in East Africa. In: Remote Sensing Applications: Society and Environment, 35, 101230.
2023[ to top ]
  • Dhillon, M. S.; Dahms, T.; Kübert-Flock, C.; Liepa, A.; Rummler, T.; Arnault, J.; Steffan-Dewenter, I.; Ullmann, T. (2023): Impact of {STARFM} on Crop Yield Predictions: Fusing {MODIS} with Landsat 5, 7, and 8 {NDVIs} in Bavaria Germany. In: Remote Sensing, 15 (6), 1651.
  • Dhillon, M. S.; Dahms, T.; Kuebert-Flock, C.; Rummler, T.; Arnault, J.; Stefan-Dewenter, I.; Ullmann, T. (2023): Integrating random forest and crop modeling improves the crop yield prediction of winter wheat and oil seed rape. In: Frontiers in Remote Sensing, 3
  • Dhillon, M. S.; Kübert-Flock, C.; Dahms, T.; Rummler, T.; Arnault, J.; Steffan-Dewenter, I.; Ullmann, T. (2023): Evaluation of MODIS, Landsat 8 and Sentinel-2 data for accurate crop yield predictions: A case study using STARFM NDVI in Bavaria, Germany. In: Remote Sensing7, 15, 1830.
2022[ to top ]
  • Benjamin, C. S.; Uphus, L.; Lüpke, M.; Rojas-Botero, S.; Dhillon, M. S.; Englmeier, J.; Fricke, U.; Ganuza, C.; Haensel, M.; Redlich, S.; Riebl, R.; Tobisch, C.; Uhler, J.; Zhang, J.; Menzel, A.; Peters, W. (2022): Modelling the Relative Abundance of Roe Deer (Capreolus capreolus L.) along a Climate and Land-Use Gradient. In: Animals, 12 (3)
  • Dhillon, M. S.; Dahms, T.; Kübert-Flock, C.; Steffan-Dewenter, I.; Zhang, J.; Ullmann, T. (2022): Spatiotemporal fusion modelling using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria. In: Remote Sensing3, 14, 677.
  • Redlich, S.; Zhang, J.; Benjamin, C.; Dhillon, M. S.; Englmeier, J.; Ewald, J.; Fricke, U.; Ganuza, C.; Haensel, M.; Hovestadt, T. (2022): Disentangling effects of climate and land use on biodiversity and ecosystem services—A multi‐scale experimental design. In: Methods in Ecology and Evolution2, 13, 514-27.
2021[ to top ]
  • Dhillon, M. S.; Kaur, S.; Sidana, B. K.; Aggarwal, R. (2021): Groundwater irrigation and energy nexus in central Punjab-trends and analysis. In: Journal of Agricultural Development and Policy2, 31, 222-27.
2020[ to top ]
  • Dhillon, M. S.; Dahms, T.; Kuebert-Flock, C.; Borg, E.; Conrad, C.; Ullmann, T. (2020): Modelling Crop Biomass from Synthetic Remote Sensing Time Series: Example for the DEMMIN Test Site, Germany. In: Remote Sensing, 12 (11), 1819.
2019[ to top ]
  • Singh Dhillon, M.; Kaur, S.; Aggarwal, R. (2019): Delineation of critical regions for mitigation of carbon emissions due to groundwater pumping in central Punjab. In: Groundwater for Sustainable Development
2018[ to top ]
  • Singh, M. D.; Kaur, S.; Sood, A.; Aggarwal, R. (2018): Estimation of carbon emissions from groundwater pumping in central Punjabed. by Carbon Management. In: Carbon Management, 9 (4), 425-35.