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应用生态学报 ›› 2012, Vol. 23 ›› Issue (10): 2812-2820.

• 研究报告 • 上一篇    下一篇

区域地表水体、归一化植被指数与热环境多样性格局的关联分析

段金龙1,2,张学雷1,2**   

  1. (1郑州大学自然资源与生态环境研究所, 郑州 450001; 2郑州大学水利与环境学院, 郑州 450001)
  • 出版日期:2012-10-18 发布日期:2012-10-18

Correlative analysis of the diversity patterns of regional surface water, NDVI and thermal environment.

DUAN Jin-long1,2, ZHANG Xue-lei1,2   

  1. (1Institute of Natural Resources and Ecological Environment, Zhengzhou 450001, China; 2College of Water Conservancy & Environmental Engineering, Zhengzhou University, Zhengzhou 450001, China)
  • Online:2012-10-18 Published:2012-10-18

摘要: 以河南省省会郑州市为研究区域,在2 km×2 km网格尺度下将多样性理论与方法应用于区域地表水体、归一化植被指数(NDVI)和地表温度(LST)分布的离散性评价,将NDVI和LST各分为4个等级,计算了其空间分布多样性指数,并探索了它们之间的内在联系.结果表明: 将多样性理论与研究方法应用于区域热环境的空间分布离散性评价具有可操作性和实际研究意义;地表水体分布与最低温区分布具有较高的区位重叠性,高的植被覆盖度往往伴随低的地表温度;1988—2009年,郑州市地表水体分布离散性呈明显降低趋势;地表水体分布离散性与区域内各温度区分布离散性存在紧密联系;NDVI分级分布离散性与各温度区分布离散性之间关系复杂,需引入其他环境影响因素参与评价.

Abstract: Taking Zhengzhou City, the capital of Henan Province in Central China, as the study area, and by using the theories and methodologies of diversity, a discreteness evaluation on the regional surface water, normalized difference vegetation index (NDVI), and land surface temperature (LST) distribution was conducted in a 2 km×2 km grid scale. Both the NDVI and the LST were divided into 4 levels, their spatial distribution diversity indices were calculated, and their connections were explored. The results showed that it was of operability and practical significance to use the theories and methodologies of diversity in the discreteness evaluation of the spatial distribution of regional thermal environment. There was a higher overlap of location between the distributions of surface water and the lowest temperature region, and the high vegetation coverage was often accompanied by low land surface temperature. In 1988-2009, the discreteness of the surface water distribution in the City had an obvious decreasing trend. The discreteness of the surface water distribution had a close correlation with the discreteness of the temperature region distribution, while the discreteness of the NDVI classification distribution had a more complicated correlation with the discreteness of the temperature region distribution. Therefore, more environmental factors were needed to be included for a better evaluation.