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SUMMARY:Crop Yield Modelling Using Remote Sensing-based LUE Model
DTSTART:20250731T133000
DTEND:20250731T143000
DTSTAMP:20260408T161137Z
UID:c9f6c2fb297b4ec886499e72589bd35c@www.uni-bonn.de
CREATED:20250722T082658Z
DESCRIPTION:Presenter: Dr. rer. nat. Bikash Ranjan Parida\, Associate Prof
 essor and Head\, Department of Geoinformatics\, Central University of Jhar
 khand\, Ranchi\, India.\nAgriculture is key to India’s food and economic
  security. The fertile Indo-Gangetic Plain (IGP) plays a major role. Due t
 o population growth and climate change\, technologies for cropland monitor
 ing are increasingly important. Remote sensing\, especially SAR data and L
 UE-based models\, improve crop yield estimates. A case study in Chandauli 
 shows that ML algorithms like RF and XGBoost provide reliable food insecur
 ity maps—a method scalable across the IGP.
LAST-MODIFIED:20250722T093826Z
URL:https://www.uni-bonn.de/en/events/crop-yield-modelling-using-remote-se
 nsing-based-lue-model
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