A LandTrendr Algorithm-Based Study of Forest Disturbance from 2000 to 2020 in Jilin Province, China
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National Disaster Reduction Center of China, MEM, Beijing, China
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, China
Land Spatial Data and Remote Sensing Technology Institute of Shandong Province, Jinan, Shandong, China
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, China
Submission date: 2022-08-15
Final revision date: 2022-09-05
Acceptance date: 2022-09-09
Online publication date: 2022-11-23
Publication date: 2022-12-21
Corresponding author
Xiurong Xue   

Land Spatial Data and Remote Sensing Technology Institute of Shandong Province, China
Pol. J. Environ. Stud. 2023;32(1):309-319
Forest resources are of great importance for achieving human sustainable development and carbon neutrality goals. Therefore, this study evaluated forest disturbance in Jilin Province, China, from 2000 to 2020 using the LandTrendr algorithm. The results of the study showed that the overall area of forest disturbance was 448.76 km2 in Jilin Province during the period 2000-2020. Forest disturbance in Jilin Province mainly occurred in Yanbian Korean Autonomous Prefecture and Baishan City. Although forest disturbance changes occurred to varying degrees in all prefecture-level cities, few forest disturbances occurred in the cities of Baicheng City, Liaoyuan City, Siping City and Songyuan City. The main causes of forest disturbance in Jilin Province were annual average temperature, total resources of arable land area at the end of the year, total arable land resources at the beginning of the year, total sown area, rural labor force in agriculture, forestry, fishing and animal husbandry, gross output value of agriculture, forestry, fishery and animal husbandry, annual precipitation, the expansion of construction land and the over-detection of image stitching and thick and dense clouds. This study provides data support for the government to formulate appropriate forest protection policies, and also has implications for monitoring forest dynamics in other regions.
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