气候变化领域集成服务门户(CCPortal): Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources

CCPortal

DOI	10.1088/1748-9326/ab80f0
	Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources
	Luo Y.; Zhang Z.; Li Z.; Chen Y.; Chen Y.; Zhang L.; Cao J.; Tao F.; Tao F.
发表日期	2020
ISSN	17489318
卷号	15 期号:7
英文摘要	Reliable and continuous information on major crop harvesting areas is fundamental to investigate land surface dynamics and make policies affecting agricultural production, land use, and sustainable development. However, there is currently no spatially explicit and time-continuous crop harvesting area information with a high resolution for China. The spatiotemporal patterns of major crop harvesting areas at a national scale have rarely been investigated. In this study, we proposed a new crop phenology-based crop mapping approach to generate a 1 km harvesting area dataset for three staple crops (i.e. rice, wheat, and maize) in China from 2000 to 2015 based on GLASS leaf area index (LAI) products. First, we retrieved key phenological dates of the three staple crops by combining the inflexion- and threshold-based methods. Then, we determined the grids cultivated for a certain crop if its three key phenological dates could be simultaneously identified. Finally, we developed crop classification maps and a dataset of annual harvesting areas (ChinaCropArea1 km), comprehensively considering the characteristics of crop phenology and the references of drylands and paddy fields. Compared with the county-level agricultural statistical data, the crop classification had a high accuracy, with R2 values consistently greater than 0.8. The spatiotemporal patterns of major crop harvesting areas during the period were further analyzed. The results showed that paddy rice harvesting areas had expanded aggressively in northeastern China but decreased in southern China. Maize harvesting areas expanded substantially in major maize cultivation areas across China. Wheat harvesting areas declined overall, although they increased notably in their major production areas. The spatiotemporal patterns could be ascribed to various anthropogenic, biophysical, and social-economic drivers, including urbanization, reduced cropping intensity in southern China, frequent disasters from climate change, and large areas of abandoned farmland in northern and southwestern China. The resultant dataset can be applied for many purposes, including land surface modeling, agro-ecosystem modeling, agricultural production and land use policy-making. © 2020 The Author(s). Published by IOP Publishing Ltd.
英文关键词	agricultural system; cropland; land use/cover change; maize; rice; wheat
语种	英语
scopus关键词	Agricultural robots; Biology; Classification (of information); Climate change; Cultivation; Ecosystems; Glass industry; Harvesting; Land use; Surface measurement; Abandoned farmland; Agricultural productions; Agro-ecosystem modeling; Crop classification; Land surface modeling; Spatially explicit; Spatio-temporal changes; Spatiotemporal patterns; Crops; agricultural land; crop plant; crop production; dryland farming; harvesting; identification method; integrated approach; leaf area index; paddy field; phenology; policy making; spatiotemporal analysis; Triticum aestivum; Zea mays
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/153968
作者单位	State Key Laboratory of Earth Surface Processes and Resource Ecology, Moe Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
推荐引用方式 GB/T 7714	Luo Y.,Zhang Z.,Li Z.,et al. Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources[J],2020,15(7).
APA	Luo Y..,Zhang Z..,Li Z..,Chen Y..,Chen Y..,...&Tao F..(2020).Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources.Environmental Research Letters,15(7).
MLA	Luo Y.,et al."Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources".Environmental Research Letters 15.7(2020).