Abstract
AbstractAs a routine agricultural practice, irrigation is fundamental to protect crops from water scarcity and ensure food security in China. However, consistent and reliable maps about the spatial distribution and extent of irrigated croplands are still unavailable, impeding water resource management and agricultural planning. Here, we produced annual 500-m irrigated cropland maps across China for 2000–2019, using a two-step strategy that integrated statistics, remote sensing, and existing irrigation products into a hybrid irrigation dataset. First, we generated intermediate irrigation maps (MIrAD-GI) by fusing the MODIS-derived greenness index and statistical data. Second, we collected all existing available irrigation maps over China and integrated them with MIrAD-GI into an improved series of annual irrigation maps, using constrained statistics and a synergy mapping method. The resultant maps had moderate overall accuracies (0.732~0.819) based on nationwide reference ground samples and outperformed existing irrigation products by inter-comparison. As the first of this kind in China, the annual maps delineated the spatiotemporal pattern of irrigated croplands and could contribute to sustainable water use and agricultural development.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Reference68 articles.
1. Godfray, H. C. J. et al. Food Security: The Challenge of Feeding 9 Billion People. Science 327, 812–818 (2010).
2. Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci USA 108, 20260–20264 (2011).
3. Salmon, J. M., Friedl, M. A., Frolking, S., Wisser, D. & Douglas, E. M. Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data. Int J Appl Earth Obs Geoinf 38, 321–334 (2015).
4. Siebert, S. & Döll, P. Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation. J Hydrol 384, 198–217 (2010).
5. Thenkabail, P., Hanjra, M., Dheeravath, V. & Gumma, M. A Holistic View of Global Croplands and Their Water Use for Ensuring Global Food Security in the 21st Century through Advanced Remote Sensing and Non-remote Sensing Approaches. Remote Sens 2, 211–261 (2010).
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