Abstract:

Irrigated area is the basic data required for the effective implementation of agricultural water conservation, and the traditional survey and statistical methods can no longer meet the current monitoring needs of irrigated area. In this paper, GF-1 and Sentinel-2 satellite images are fused to construct the sample spectrum of crop growth period. Based on the pixel-scale spectral matching method, the crop planting structure and actual irrigated area of Zaohe irrigation district in Suqian city, Jiangsu province from 2017 to 2022 are synergistically extracted. The results showed that the main planting pattern in the Zaohe irrigation district was rice-wheat rotation. The irrigated areas of the four crops in the irrigation area from 2017 to 2022 were 12.76, 13.78, 15.54, 14.37, 14.65 and 13.23 million mu, respectively. Based on the sample points, the confusion matrix is used to verify the accuracy of the extracted irrigated area results., and the overall accuracy was 89.71%, and the kappa coefficient was 0.80, indicating that the accuracy of the monitoring results is high, and the extraction effect is better than that of IrriMap_Syn products and IWMI products with high accuracy among the currently disclosed products. This method is suitable for extracting the irrigated area in the southern irrigation area, and can provide technical and data support for the daily supervision of the irrigation district management department and the optimization of water resource allocation.

Key words: Zaohe irrigation district, planting structure, irrigated area, spectral matching, NDV