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This dissertation by Sadia Alam Shammi presents a remote sensing-driven geospatial approach to modeling regional crop growth and yield, focusing on soybean crops. It aims to monitor crop growth, assess climate impacts on yield, and forecast production using remote sensing technology and various vegetative growth metrics. The study provides valuable insights for farmers and agricultural strategists in the U.S. Department of Agriculture to enhance food security and agricultural planning.

Author

tipid79632

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EN