Redai dili (Nov 2024)
Remote Sensing Method of Forest Logging in the Beijiang River Basin Based on Recent Intensive Satellite Data
Abstract
Forests are important natural and strategic resources, and deforestation is a significant cause of soil erosion. Given the high uncertainty and limited temporal-spatial resolution of land features classified by remote sensing, especially the lack of regional studies on the dynamic distribution of forest deforestation, it is urgent to extract the multi-temporal dynamic distribution of forest deforestation using remote sensing techniques. Based on the spectral features of ground objects before and after deforestation, 930 optical remote sensing images from Sentinel-2 in the Beijiang River Basin from 2017 to 2022 were selected as experimental data. The Google Earth Engine cloud platform was utilized for data collection and preprocessing to calculate the NDVI vegetation index from 2017 to 2022. Following the extraction of forest distribution using the threshold segmentation method, the dynamic change in deforestation distribution between 2017 and 2022 in the study area was analyzed. The results showed that: (1)229 sampling points were randomly selected in the deforestation area, and the accuracy of remote sensing mapping of deforestation in 2020-2021 was evaluated using historical high-resolution images, achieving a verification accuracy of 72.05%. (2)From 2017 to 2022, deforestation in the Beijiang River Basin exhibited an increasing trend year by year, except in 2020 and 2021, with an average annual increase of about 9%. In terms of distribution, the largest proportion of deforestation occurred in the Wujiang River Basin during 2017-2022, with an average annual deforestation rate of 3.27% of the total area of the basin. The lowest proportion of deforestation was observed in the Nanshui River Basin, with an average annual deforestation rate of 1.47% of the total area of that basin. (3)In the Beijiang River Basin, the distribution of deforestation across different slopes is more uniform. The deforestation area is primarily concentrated on slopes between 8° and 25°, which account for 53.3% of the total basin area and generate 48% to 57% of the deforestation area. Deforestation is more likely to occur on slopes below 15°, with a felling ratio of 3.76%, which is 1.14% higher than that of slopes above 15°. (4)The standardized NDVI average of 56 feature points decreased from 0.84 in 2017 to 0.43 in 2018 and then increased by an average of 0.08 per year thereafter. The NDVI characteristics of forest land generally recovered in the third year after deforestation. Using the Google Earth Engine cloud platform and the threshold segmentation method of NDVI, the dynamic characteristics of multi-temporal deforestation distribution were extracted. This approach addresses the limitations of remote sensing extraction and monitoring of the dynamic distribution of forest deforestation in the Beijiang River Basin, which is of great significance for the rational development and utilization of regional water resources and forest resource management.
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