Downscaling Global Gridded Crop Yield Data Products and Crop Water Productivity Mapping Using Remote Sensing Derived Variables in the South Asia.

ABSTRACT: Local scale crop yield and crop water productivity information is critical for informed decision making, crop yield forecasting and crop model calibration applications. In this study, we have attempted to downscale coarse resolution primary season rice yield datasets to a local scale of 500 m using a minimum-median downscaling approach. Sixteen mainland countries in south and southeast Asia region were considered as study region to downscale global rice yield datasets for 2000-2015. Four medium resolution remote sensing derived vegetation indices such as Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Gross Primary Product (GPP) were used to downscale coarse resolution global rice yield datasets. A kharif season district level rice

SUBMITTER: Mohanasundaram S 

PROVIDER: S-EPMC9648444 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature