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Technical Note

An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data

1
Guangdong Ecological Meteorology Center, Guangzhou 510640, China
2
Center for Monsoon and Environment Research, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
3
Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, CMA, Guangzhou 510641, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(24), 4181; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12244181
Received: 15 November 2020 / Revised: 10 December 2020 / Accepted: 17 December 2020 / Published: 21 December 2020
(This article belongs to the Special Issue Satellite Hydrological Data Products and Their Applications)
Accurate spatial information about irrigation is crucial to a variety of applications, such as water resources management, water exchange between the land surface and atmosphere, climate change, hydrological cycle, food security, and agricultural planning. Our study proposes a new method for extracting cropland irrigation information using statistical data, mean annual precipitation and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover type data and surface reflectance data. The approach is based on comparing the land surface water index (LSWI) of cropland pixels to that of adjacent forest pixels with similar normalized difference vegetation index (NDVI). In our study, we validated the approach over mainland China with 612 reference samples (231 irrigated and 381 non-irrigated) and found the accuracy of 62.09%. Validation with statistical data also showed that our method explained 86.67 and 58.87% of the spatial variation in irrigated area at the provincial and prefecture levels, respectively. We further compared our new map to existing datasets of FAO/UF, IWMI, Zhu and statistical data, and found a good agreement with the irrigated area distribution from Zhu’s dataset. Results show that our method is an effective method apply to mapping irrigated regions and monitoring their yearly changes. Because the method does not depend on training samples, it can be easily repeated to other regions. View Full-Text
Keywords: irrigation; cropland; mean annual precipitation; land surface water index (LSWI) irrigation; cropland; mean annual precipitation; land surface water index (LSWI)
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MDPI and ACS Style

Xiang, K.; Yuan, W.; Wang, L.; Deng, Y. An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data. Remote Sens. 2020, 12, 4181. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12244181

AMA Style

Xiang K, Yuan W, Wang L, Deng Y. An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data. Remote Sensing. 2020; 12(24):4181. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12244181

Chicago/Turabian Style

Xiang, Kunlun, Wenping Yuan, Liwen Wang, and Yujiao Deng. 2020. "An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data" Remote Sensing 12, no. 24: 4181. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12244181

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