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生态学杂志 ›› 2021, Vol. 40 ›› Issue (8): 2541-2552.doi: 10.13292/j.1000-4890.202108.004

• 研究报告 • 上一篇    下一篇

近40年青海省草地植被时空变化及其与人类活动的关系

魏晓旭1*,魏伟2,刘春芳1,3   

  1. 1西北师范大学社会发展与公共管理学院, 兰州 730000;2西北师范大学地理与环境科学学院, 兰州 730000; 3甘肃省土地利用与综合整治工程研究中心, 兰州 730070)
  • 出版日期:2021-08-10 发布日期:2021-08-17

Spatiotemporal variation of grassland vegetation and its relationship with human activities in Qinghai Province in recent 40 years.

WEI Xiao-xu1*, WEI Wei2, LIU Chun-fang1,3   

  1. (1College of Social Development and Public Administration, Northwest Normal University, Lanzhou 730000, China; 2College of Geographical and Environmental Science, Northwest Normal University, Lanzhou 730000, China; 3Gansu Engineering Research Center of Land Utilization and Comprehension Consolidation, Lanzhou 730070, China).
  • Online:2021-08-10 Published:2021-08-17

摘要: 基于Landsat 8 OLI、GIMMS NDVI 3G数据、MODIS数据及相关统计数据,采用趋势分析法、相关分析法以及地理加权回归法,分析了1982—2018年青海省草地植被时空变化及其对人类活动的响应。结果表明:(1)1982—2018年青海省草地NDVImax总体呈减少趋势,年均减少速率为1.2×10-4。(2)从空间分布特征看,西南部和中部草地NDVImax对放牧强度响应程度明显,而东北部草地NDVImax对放牧强度的响应不明显,这可能与农业和牧业互补优势明显及生态工程实施有关。(3)从扰动要素看,人均GDP、交通、居民点以及总人口与草地NDVImax的局部回归系数分别为0.20、0.11、0.04和0.03。其中,人均GDP与草地NDVImax的局部回归系数呈西部高、东部低的分布格局,其他呈现东西部高、中部低的空间格局,主要是由于西部拥有丰富的矿产资源,东部是交通枢纽和人口聚集区。

关键词: NDVImax, 趋势, 人类活动, 空间格局

Abstract: We analyzed the temporal and spatial changes of grassland vegetation cover and its response to human activities in Qinghai Province by trend analysis method, linear correlation analysis, and geographical weighted regression method, based on Landsat 8 OLI, GIMMS NDVI 3G data, MODIS data and statistical data from 1982 to 2018. The results showed that: (1) From 1982 to 2018, NDVImax of grassland in Qinghai Province showed an overall decreasing trend, with an average rate of 1.2×10-4. (2) The NDVImax was sensitive to grazing intensity in the southwest and central parts of Qinghai Province, while it was not sensitive in the northeast. This may be related to the complementary advantages of agriculture and animal husbandry and the implementation of ecological engineering. (3) The regression coefficients between NDVImax and per capita GDP, traffic, residential area, and total human population were 0.20, 0.11, 0.04 and 0.03, respectively. The local regression coefficients of per capita GDP and grassland NDVImax were high in the west and low in the east, while that for other regression relationships were high in the west and east and low in the east region. This is mainly due to the rich mineral resources in the west and a transportation hub and population gathering area in the east.

Key words: NDVImax, trend, human activity, spatial pattern.