Multiple cropping is a widespread approach for intensifying crop production through rotations of diverse crops. Maps of cropping intensity with crop descriptions are important for supporting sustainable agricultural management. As the most populated country, China ranked first in global cereal production and the percentages of multiple-cropped land are twice of the global average. However, there are no reliable updated national-scale maps of cropping patterns in China. Here we present the first recent annual 500-m MODIS-based national maps of multiple cropping systems in China using phenology-based mapping algorithms with pixel purity-based thresholds, which provide information on cropping intensity with descriptions of three staple crops (maize, paddy rice, and wheat). The produced cropping patterns maps achieved an overall accuracy of 89% based on ground truth data, and a good agreement with the statistical data (R2 ≥ 0.89). The China Cropping Pattern maps (ChinaCP) are available for public download online. Cropping patterns maps in China and other countries with finer resolutions can be produced based on Sentinel-2 Multispectral Instrument (MSI) images using the shared code. Measurement(s) area of different cropping patterns Technology Type(s) phenology-based approach Factor Type(s) type of cropping pattern Sample Characteristic - Organism Organism Sample Characteristic - Environment cultivated environment Sample Characteristic - Location China Measurement(s) area of different cropping patterns Technology Type(s) phenology-based approach Factor Type(s) type of cropping pattern Sample Characteristic - Organism Organism Sample Characteristic - Environment cultivated environment Sample Characteristic - Location China
Maps of cropping patterns in China during 2015–2021
Bingwen Qiu,Xiang Hu,Chongcheng Chen,Zhenghong Tang,Peng Yang,Xiaolin Zhu,Chao Yan,Zeyu Jian
Published 2022 in Scientific Data
ABSTRACT
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- Publication year
2022
- Venue
Scientific Data
- Publication date
2022-08-05
- Fields of study
Agricultural and Food Sciences, Geography, Medicine, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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