西南地区2001-2014年植被变化时空格局
Spatial-temporal pattern of vegetation changes in Southwest China during 2001-2014
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摘要: 时序植被动态变化研究一直是全球变化研究的热点之一,对地区生态治理有重要意义。基于西南地区2001至 2014年的MODIS植被指数数据集以及DEM数据和土地利用数据,进行季节合成植被指数(SINDVI)的趋势模拟、空间统计和相关分析,探讨西南地区植被变化趋势和空间分异特征,研究结果表明:(1)74.52%的区域SINDVI变化不显著,显著改善的区域占22.07%,而显著退化的区域占3.41%,改善面积远远大于退化面积。(2)从地形因子结果来看,中低海拔地区和缓坡地区植被变化趋势最明显,海拔3 500 m以下植被变化趋势比海拔3 500 m以上明显。随着坡度的增加,改善趋势和退化趋势都在变小。(3)从土地利用分析结果来看,SINDVI变化趋势在人工表面最明显,改善和退化趋势都相对较大。(4)受人类活动的影响,人工表面和裸地的增多、林地的减少是植被呈退化趋势的主要原因。Abstract: The study of temporal vegetation dynamics has been one of focused issues on global change, which has great significance to regional ecological management. Based on time series of MODIS vegetation index data from 2001 to 2014 and the DEM data and land use data in southwest China, the trends of the vegetation changes were calculated and the spatial differentiation characteristics of the changes with the other relative factors were analyzed. The results indicate that 74.52% of change trends of Seasonally Integrated Normalized Difference Vegetation Index (SINDVI) are not significant. The areas with significantly increasing trends account for 22.07% and the areas with significantly decreasing trends account for 3.41% of the total, respectively.So the increasing areas are much more than the decreasing areas. Through analysis results of the terrain factors, the trend of vegetation change in the low or middle altitude areas and gentle slope areas are the most obvious. The trend of vegetation change below the altitude of 3,500 m is more significant than that above 3,500 m. With the increase of slope, increasing and decreasing trends are both smaller. From the analysis results of land use, the SINDVI change trend is the most remarkable on the artificial surface, with relatively faster increasing and decreasing trends. With the influence of human activities, the increases of the artificial surface and the bare land and the decreases of the forest land are the main reasons for the vegetation degradation.
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Key words:
- Southwest China /
- NDVI /
- trend analysis /
- remote sensing
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