期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 857, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2022.159591
关键词
Arable land; Abandonment; Recultivation; Sliding window; Google Earth Engine
The abandonment of cropland in China poses a threat to food security and has significant impacts on society, economy, and the natural environment. Mapping and monitoring abandoned cropland on a large scale has been a challenge. This study utilized high-resolution satellite data to detect and map abandoned cropland in China from 1990 to 2019, providing valuable insights into its spatial distribution, intensity, trends, frequency, and recultivation.
The abandonment phenomenon is familiar in China. It threatens food security and seriously affects the sustainable development of society, the economy, and the natural environment. However, monitoring and mapping abandoned cropland on a large scale remains a challenge because of its complex land-use change process. According to the World Food and Agriculture Organization, cropland not used for agricultural production for more than 5 years is defined as abandoned cropland. This study uses the Landsat high-precision long-time series product to detect cropland nationwide from 1990 to 2019 by using the sliding window method on Google Earth Engine to profile the spatial distribution, intensity, trend, frequency, and recultivation of abandoned cropland. Between 1992 and 2015, the results illustrate that the total area of abandoned cropland in China was 559,170.26 km(2), 18.59% of the cropland area. Excluding the recultivated cropland area, China's abandoned cropland area amounted to 392,156.24 km(2), 13.03 % of the total cropland. Cropland abandonment is mainly distributed in the second terrain gradient in midwestern and southwestern regions such as Inner Mongolia and Gansu. It rarely happens in western and eastern coastal areas. A high abandonment rate area usually has high elevation and slope. The light index is negatively correlated with the abandonment rate in suburban areas. This study is the first to map the spatiotemporal distribution of abandoned cropland in China with high precision at 30 m resolution. It provides an important basis for policies regarding the recultivation of abandoned cropland.
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