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应用生态学报 ›› 2021, Vol. 32 ›› Issue (5): 1581-1592.doi: 10.13287/j.1001-9332.202105.014

• 景观生态学专栏 • 上一篇    下一篇

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

韩磊1,2,3*, 火红4, 刘钊1,3, 赵永华1,3, 朱会利5, 陈芮4, 赵子林4   

  1. 1长安大学土地工程学院, 西安 710054;
    2中国科学院地球环境研究所黄土与第四纪地质国家重点实验室, 西安 710061;
    3陕西省土地整治重点实验室, 西安 710054;
    4长安大学地球科学与资源学院, 西安 710054;
    5长安大学地质工程与测绘学院, 西安 710054
  • 收稿日期:2020-10-12 接受日期:2021-02-02 出版日期:2021-05-15 发布日期:2021-11-15
  • 通讯作者: *E-mail: hanshuanglei@chd.edu.cn
  • 作者简介:韩磊,男,1979年生,副教授,博士。主要从事资源遥感和土壤侵蚀研究。E-mail:hanshuanglei@chd.edu.cn
  • 基金资助:
    国家自然科学基金项目(41871190)、黄土与第四纪地质国家重点实验室开放基金项目(SKLLQG2002)和中央高校基本科研业务项目(300102279208)资助

Spatial and temporal variations of vegetation coverage in the middle section of Yellow River Basin based on terrain gradient:Taking Yan'an City as an example.

HAN Lei1,2,3*, HUO Hong4, LIU Zhao1,3, ZHAO Yong-hua1,3, ZHU Hui-li5, CHEN Rui4, ZHAO Zi-lin4   

  1. 1School of Land Engineering, Chang'an University, Xi'an 710054, China;
    2State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China;
    3Shaanxi Key Laboratory of Land Consolidation, Xi'an 710054, China;
    4School of Earth Sciences and Resources, Chang'an University, Xi'an 710054, China;
    5School of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China
  • Received:2020-10-12 Accepted:2021-02-02 Online:2021-05-15 Published:2021-11-15
  • Contact: *E-mail: hanshuanglei@chd.edu.cn
  • Supported by:
    National Science Foundation of China (41871190), the Open Fund of State Key Laboratory of Loess and Quaternary Geology (SKLLQG2002) and the Fundamental Research Funds for the Central Universities (300102279208).

摘要: 植被恢复是黄河流域生态保护和高质量发展的关键,深入研究植被的时空分异特征具有重要的现实意义。本研究以4期Landsat TM/OLI为遥感数据源,采用像元二分模型估算植被覆盖度,运用转移矩阵、地学信息图谱和重心迁移模型分析1988—2018年黄河流域中段延安市植被覆盖的时空演变特征;并结合地形数据,利用地形分布指数分析高程、坡度上植被覆盖的空间响应规律。结果表明: 研究期间,延安市植被覆盖呈北低南高的空间分布特征,植被覆盖受政策影响而大幅增高;1988—2018年,延安市植被变化模式以持续向好和稳定不变为主导,有50%的区域植被覆盖情况改善,83%的高植被覆盖区域保持稳定。在各高程和坡度等级上,高植被覆盖的分布优势度随时间变化而增大;在各坡度等级上,植被增加百分比和植被稳定性随坡度增加而增大。延安不同等级植被覆盖的迁移方向与植被覆盖整体的迁移趋势基本一致,总体向北偏西转移。延安植被建设已取得显著成效,但北部植被覆盖状况仍待提高,优化植被类型和结构是未来植被建设的重要方向。

关键词: 植被覆盖, 时空变化, 地形梯度, 地学信息图谱

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 cove-rage 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.

Key words: vegetation coverage, spatiotemporal change, terrain gradient, geo-informatic tupu