Study on Summer Maize Yield Responses to Remote Sensing Drought Indices in Henan Province with GWR Model

2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)(2019)

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Abstract
Based on MODIS sensor-based vegetation index (MODI 3A3) and surface temperature(MODllA2) product and Henan summer maize yield data, comparing the fitting results of Ordinary Least Square (OLS) and the Geographically Weighted Regression model (GWR), Studied the spatial heterogeneity of drought monitoring index affect on summer maize yield during summer maize growth in Henan Province. The results showed that in Henan Province, the impact of drought on summer maize yield was significantly spatially heterogeneous, and the drought reflected by VCI had a greater impact on summer maize yield than TCI. On the whole, there is a trend of weakening from north to south, and human activities such as fertilization and irrigation will reduce the impact of drought on summer maize yield.
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Key words
Geographically Weighted Regression model (GWR),Drought monitoring,remote sensing,summer maize
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