Abstract
Large-scale, high-resolution mapping of crop patterns is useful for the assessment of food security and agricultural sustainability but is still limited. This study attempted to establish remote sensing-based crop classification models for specific cropping systems using the decision trees method and monitored the distribution of the major crop species using Sentinel-2 satellites (10 m) in 2017. The results showed that the cropping areas of maize, rice, and soybean on the Northeast China Plain were approximately 12.1, 6.2, and 7.4 million ha, respectively. The cropping areas of winter wheat and summer maize on the North China Plain were 13.4 and 16.9 million ha, respectively. The cropping areas of wheat, rice, and rape on the middle-lower Yangtze River plain were 2.2, 6.4 and 1.3 million ha, respectively. Estimated images agreed well with field survey data (average overall accuracy = 94%) and the national agricultural census data (R2 = 0.78). This indicated the applicability of the Sentinel-2 satellite data for large-scale, high-resolution crop mapping in China. We intend to update the crop mapping datasets annually and hope to guide the adjustment and optimization of the national agricultural structure.
Highlights
Ensuring global food security is one of the greatest challenges for scientists around the world [1].As the country with the largest population in the world, China’s food security is important to economic development and social stability and to global food patterns [2,3]
We chose the normalized difference vegetation (NDVI), red-edge parameter (REP), and for this area, which can better distinguish widely adapted on the Northeast Plain (NEP)
We found that the value of the NDVI in April between T1 and T2 could identify the rice cropping area
Summary
Ensuring global food security is one of the greatest challenges for scientists around the world [1].As the country with the largest population in the world, China’s food security is important to economic development and social stability and to global food patterns [2,3]. Ensuring global food security is one of the greatest challenges for scientists around the world [1]. China has enacted a series of measures to ensure food security during recent decades, including food self-sufficiency policies and environmentally friendly agricultural development strategies [4,5,6]. These policies limit the scale of water, pesticide, fertilizer, and arable land use, which increases the difficulty of new round adjustment strategies for agricultural structure [7,8,9]. Updated information on crop pattern mapping can provide significant scientific evidence for estimating agricultural production and food security. Additional studies should be performed to enrich crop mapping data to assist in the optimization of agricultural distribution
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