TY  - JA
AU  - Yulin Jiang
AU  - Zhou Lu
AU  - Shuo Li
AU  - Yongdeng Lei
AU  - Qingquan Chu
AU  - Xiaogang Yin
AU  - Fu Chen
TI  - Large-scale and high-resolution crop mapping in China using Sentinel-2 satellite imagery
SN  - 2077-0472
PY  - 2020///
CY  - Basel (Switzerland)
PB  - MDPI, 
KW  - Crops
KW  - AGROVOC
KW  - Indicators
KW  - Classification
KW  - Cropping systems
KW  - Satellite imagery
KW  - China
N1  - Peer review; Open Access
N2  - 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
UR  - https://doi.org/10.3390/agriculture10100433
DO  - https://doi.org/10.3390/agriculture10100433
T2  - Agriculture
ER  -