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- Title
基于地形梯度的黄河流域中段植被覆盖 时空分异特征———以延安市为例.
- Authors
韩磊; 火红; 刘钊; 赵永华; 朱会利; 陈芮; 赵子林
- Abstract
Vegetation restoration is an important requirement for ecological protection and high-quality development in the Yellow River Basin. In-depth understanding the temporal and spatial differentiation of vegetation has important practical significance. With the four Landsat TM/ OLI remote sensing images as the data source, the pixel binary model was used to estimate vegetation coverage. The transfer matrix, geological information map, and the center of gravity migration model were used to analyze the temporal and spatial variations of vegetation coverage in Yan’an City in the middle of the Yellow River Basin from 1988 to 2018. The spatial variation of vegetation cover to elevation and slope was explored using terrain distribution index combined with terrain data. The results showed that vegetation coverage in Yan’an was low in the north region and high in the south region. The vegetation coverage increased significantly due to policy changes. From 1988 to 2018, the vegetation change pattern in Yan’an was dominated by continuous improvement and stability. Vegetation coverage increased in about 50% of the area. 83% of the study area with high vegetation coverage remained stable. At each elevation and slope level, the advantage of high vegetation coverage increased with time. At each slope level, vegetation cover increased with slope. The transition direction of vegetation cover of different levels in Yan’an was basically consistent with the overall spatial change trend of vegetation cover, with the overall shift being from north to west. The vegetation construction in Yan’an has achieved remarkable results, though the vegetation coverage in the north still needs to be improved. Optimizing vegetation types and structures is an important direction for future vegetation construction.
- Subjects
VEGETATION dynamics; SENSE data; TRANSFER matrix; GROUND vegetation cover; WATERSHEDS; GEOLOGICAL modeling
- Publication
Yingyong Shengtai Xuebao, 2021, Vol 32, Issue 5, p1581
- ISSN
1001-9332
- Publication type
Article
- DOI
10.13287/j.1001-9332.202105.014