Abstract:

Irrigated area is the basic data required for effective agricultural water conservation, yet traditional survey and statistical methods no longer meet current monitoring needs. In this research, GF-1 and Sentinel-2 satellite images were 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 were synergistically extracted. Results show that the main planting pattern in Zaohe irrigation district is rice-wheat rotation. From 2017 to 2022, the actual irrigated area was 85.11 km², 91.91 km², 103.65 km², 95.85 km², 97.72 km² and 88.24 km². respectively. Validation using sample points and a confusion matrix yielded an overall accuracy of 89.71% and a Kappa coefficient of 0.80, indicating higher accuracy and better extraction effects compared to existing products like IrriMap_Syn and IWMI products. This method is suitable for extracting the irrigated area in south China, and can provide technical and data support for the daily supervision of management departments and the optimization of water resource allocation.

Key words: irrigated area, planting structure, spectral matching, remote-sensing, Zaohe irrigation district