Evaluation of remotely sensed and reanalyzed irrigation maps over China

Xin Tian,Jianzhi Dong,Lingna Wei, Xiaoqi Kang, Huiwen Zhang, Xiaosong Sun, Shuaikun Li, Dexing Zhao, Yuxi Li

crossref(2023)

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摘要
<p>The uncertainty of the irrigated area is a key error source of irrigation modeling. Existing irrigation maps, produced by either remote sensing or reanalyzed dataset, are known to contain substantial inter-product differences. However, relatively little work has been done to comprehensively compare and evaluate these irrigation maps. This study uses censored data collected from the National Bureau of Statistics (NBS) of China to evaluate irrigated areas derived eight commonly used irrigation maps at county levels. The spatial distribution and the temporal variability these products are evaluated using more than 1651 country-level data record during the period of 2000 to 2020. Based on our analysis, we seek to provide insights into the reliability of using current available irrigation maps for large scale modeling analysis and future developments of the large-scale irrigated area mapping.</p>
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