近10 a来祁连山植被覆盖变化研究

NDVI作为植被生长状况及植被覆盖度的最佳指示因子,被认为是监测地区或全球植被和环境变化的最有效指标。基于2000-2011年250 m分辨率的MODIS NDVI数据并结合气候资料,采用最大值合成法、均值法、斜率分析法、相关分析法,研究祁连山生长季植被覆盖的时空变化及其与气候因子的相关性。结果表明：祁连山植被覆盖总体上自西向东递增,呈现东多西少的分布格局;植被覆盖变化存在明显的空间差异,表现为中西部植被覆盖增加,增加面积为79 149 km2,占祁连山总面积的52.93%;东部植被覆盖减少,减少面积为22 865 km2,占祁连山总面积的11.09%。近10 a来植被覆盖整体上呈增加趋势,生长季各月植被覆盖整体上呈增加趋势,全球气候变暖导致的降水增加是祁连山植被覆盖增加的主要原因。NDVI与气温、降水的相关性较高并存在一定的滞后性,6、7月NDVI分别与前期1月和前期2月的降水显著相关,相关系数分别为0.788和0.684;8、9月NDVI分别与当月、前期1月的气温极显著相关,相关系数分别为0.825和0.829。

Change of Vegetation Coverage in the Qilian Mountains in Recent 10 Years

As the best instruction factor of vegetation coverage, NDVI is regarded as the most effective indicator to monitor regional or global change of vegetation and ecological environment. Based on MODIS NDVI data with spatial resolution of 250 m and climate data during the period from 2000 to 2011, in this paper the spatiotemporal change of vegetation coverage and its correlations with climatic factors in the Qilian Mountains were researched using the methods of maximum value composite, trend line analysis and correlation analysis as well as averaging method. The results showed that the vegetation coverage in the Qilian Mountains increased gradually from the west to the east, and it in the eastern part of the Qilian Mountains was higher than that in the western part. There were some significant spatial differences of vegetation coverage change, for example, it increased in the central and western parts of the Qilian Mountains, but decreased in the eastern part. The area with an increase of vegetation coverage was 79 149 km2 and accounted for 52.93% of the total area investigated in the Qilian Mountains, and the area with a decrease of that was 22 865 km2 and accounted for 11.09％ of the total. The vegetation coverage was in a significant increase trend in recent 10 years, and the monthly vegetation coverage in growth season was also in an increase trend. The increase of vegetation coverage in the Qilian Mountains was caused by the increase of precipitation under global warming. There were the significant correlations between NDVI and temperature and precipitation, and there was also a time lag in their changes. There was a significant correlation between the NDVI in June and July and the precipitation in previous one month and two months, and their correlation coefficients were 0.788 and 0.684, respectively; there was an extremely significant correlation between the NDVI in August and September and the temperature in the same month and previous one month, and their correlation coefficients were 0.825 and 0.829, respectively.