Agricultural Decision Support Service Based on Multi-Source Remote Sensing Data: the Case of the Precision Implementation of Grain Subsidy Policy

Abstract

In order to promote grain production, the government had implemented the agricultural subsidy policy. However, the existing methods were difficult to provide accurate decision-making support information, which made the effectiveness of this policy gradually reduced. In this paper, we proposed a method to calculate the agricultural decision information accurately by using multi-source remote sensing images. Firstly, we accurately extracted the boundary of cultivated land (geo-parcel) from high spatial resolution remote sensing image. Secondly, we constructed a NDVI time series from multi-source medium-resolution remote sensing images, established the growth curve of crop on each geo-parcel, and identify the crop type planted on each geo-parcel. Thirdly, we established the exact calculation model to realize the decision information calculation based on the geo-parcel. On the basis of the method proposed in this paper, we selected Li County, Hunan Province as the study area to carry out the application of grain planting subsidies. We find that the method proposed in this paper had obvious advantages by comparing the results with traditional methods. This method improves the accuracy and the objectivity of the results.