Downscaling Regional Crop Yields to Local Scale Using Remote Sensing

Local-scale crop yield datasets are not readily available in most of the developing world. Local-scale crop yield datasets are of great use for risk transfer and risk management in agriculture. In this article, we present a simple method for disaggregation of district-level production statistics ove...

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Bibliographic Details
Published in:Agriculture (Basel) 2020-03, Vol.10 (3), p.58
Main Authors: Shirsath, Paresh B., Sehgal, Vinay Kumar, Aggarwal, Pramod K.
Format: Article
Language:English
Subjects:
Agricultural management
Agricultural production
Agriculture
Cereal crops
Correlation coefficient
Correlation coefficients
Crop insurance
Crop production
Crop yield
Crops
Datasets
Design
Disaggregation
downscaling
Methodology
Pixels
Rain
Remote sensing
Risk management
Simulation
Sorghum
Statistics
Vegetation
Vegetation index
Winter
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Summary:Local-scale crop yield datasets are not readily available in most of the developing world. Local-scale crop yield datasets are of great use for risk transfer and risk management in agriculture. In this article, we present a simple method for disaggregation of district-level production statistics over crop pixels by using a remote sensing approach. We also quantified the error in the disaggregated statistics to ascertain its usefulness for crop insurance purposes. The methodology development was attempted in Parbhani district of Maharashtra state with wheat and sorghum crops in the winter season. The methodology uses the ratio of Enhanced Vegetation Index (EVI) of pixel to total EVI of the crop pixels in that district corresponding to the growth phase of the crop. It resulted in the generation of crop yield maps at the 500 m resolution pixel (grid) level. The methodology was repeated to generate time-series maps of crop yield. In general, there was a good correspondence between disaggregated crop yield and sub-district level crop yields with a correlation coefficient of 0.9.
ISSN:2077-0472
2077-0472
DOI:10.3390/agriculture10030058