Paper
23 February 2023 Dynamic monitoring of Grain for Green Program in Chaoyang city
Yanmin Shuai, Ran Huo, Ge Qu
Author Affiliations +
Proceedings Volume 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022); 125511L (2023) https://doi.org/10.1117/12.2668083
Event: Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 2022, Changchun, China
Abstract
Grain for Green Program (GGP) is an ecological restoration and compensation project carried out by China to protect and improve the environment, which can not only ensure the economic income of peasant households in areas where farmland is returned to forests, but also effectively reduce natural disasters. Taking Chaoyang City as an example, the land cover information of the area is extracted based on the Landsat images from 1985 to 2020, and the changes of the barren hills, cultivated land, forest and grassland during the 36-year GGP are analyzed. The results show that in the past 36 years, the afforestation area of barren hills in Chaoyang has reached 2745.5 km2, and the afforestation area of cultivated land was about 933 km2, GGP has achieved remarkable results. The abandoned lands and reforestation areas are mainly distributed in areas with slope >25° and altitude area over 500 m, and the changes of the two are mainly manifested in the internal structural conversion of the proportion of cultivated land with an altitude of less than 500 m and slope < 25°, which is basically in line with the requirements of the policy of GGP.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yanmin Shuai, Ran Huo, and Ge Qu "Dynamic monitoring of Grain for Green Program in Chaoyang city", Proc. SPIE 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 125511L (23 February 2023); https://doi.org/10.1117/12.2668083
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KEYWORDS
Crop monitoring

Knowledge management

Environmental monitoring

Data conversion

Education and training

Landsat

Sand

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