Remote Sensing | |
Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics | |
Jan Dempewolf1  Bernard Adusei2  Inbal Becker-Reshef1  Matthew Hansen1  Peter Potapov1  Ahmad Khan1  | |
[1] Department of Geographical Sciences, University of Maryland, 2181 Samuel J. LeFrak Hall, College Park, MD 20742, |
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关键词: agriculture; wheat; yield; production; forecast; MODIS; WDRVI; | |
DOI : 10.3390/rs6109653 | |
来源: mdpi | |
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【 摘 要 】
Policy makers, government planners and agricultural market participants in Pakistan require accurate and timely information about wheat yield and production. Punjab Province is by far the most important wheat producing region in the country. The manual collection of field data and data processing for crop forecasting by the provincial government requires significant amounts of time before official reports can be released. Several studies have shown that wheat yield can be effectively forecast using satellite remote sensing data. In this study, we developed a methodology for estimating wheat yield and area for Punjab Province from freely available Landsat and MODIS satellite imagery approximately six weeks before harvest. Wheat yield was derived by regressing reported yield values against time series of four different peak-season MODIS-derived vegetation indices. We also tested deriving wheat area from the same MODIS time series using a regression-tree approach. Among the four evaluated indices, WDRVI provided more consistent and accurate yield forecasts compared to NDVI, EVI2 and saturation-adjusted normalized difference vegetation index (SANDVI). The lowest RMSE values at the district level for forecast
【 授权许可】
CC BY
© 2014 by the authors; licensee MDPI, Basel, Switzerland
【 预 览 】
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RO202003190021028ZK.pdf | 2896KB | ![]() |