Remotely-sensed Monitoring of Irrigated Area in Zaohe Irrigation District of Jiangsu Province Based on Pixel-scale Spectral Matching Method

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.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
DOI
https://doi.org/10.11988/ckyyb.20231288
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Remotely-sensed Monitoring of Irrigated Area in Zaohe Irrigation District of Jiangsu Province Based on Pixel-scale Spectral Matching Method

SHILAP Revista de lepidopterología
Remote Sensing in Agriculture
article

Remotely-sensed Monitoring of Irrigated Area in Zaohe Irrigation District of Jiangsu Province Based on Pixel-scale Spectral Matching Method

article en

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.

SHILAP Revista de lepidopterología
China Institute of Water Resources and Hydropower Research (CN), Ningxia Water Conservancy (CN)
Clean water and sanitation
Openalex Percentile: Top 57%
Remote Sensing in Agriculture
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Remotely-sensed Monitoring of Irrigated Area in Zaohe Irrigation District of Jiangsu Province Based on Pixel-scale Spectral Matching Method · SHILAP Revista de lepidopterología (2025) | TGRS Research Map | TGRS