岩溶区峰丛洼地植被指数的克里格分析

为了全面掌握岩溶区峰丛洼地植被指数(NDVI)的空间分布状况,解决岩溶区峰丛洼地遥感影像山体阴影区域NDVI信息"缺失"的问题,对广西平果县果化生态重建示范区内的典型峰丛洼地非阴影区域NDVI进行了提取.利用地统计学的方法对NDVI的空间结构特征进行了分析,并对山体阴影区的NDVI进行了预测与验证.结果表明,研究区域NDVI主要受到内在因子的作用,具有强烈的空间自相关性,自相关距离为300 m;Kriging插值结果表明,研究区域NDVI的均值为0.196,在空间分布上表现为条带状和斑块状分布,NDVI高值区域主要分布在峰丛坡度>25°的山体区域,低值区域主要分布在峰丛坡度<25°的山脚和洼地等区域;Kriging插值验证结果表明,研究区域NDVI具有非常高的预测精度,能很好地估计山体阴影区NDVI,为岩溶区生态环境监控、石漠化评估提供了新的思路与方法.

Kriging Analysis of Vegetation Index Depression in Peak Cluster Karst Area

In order to master the spatial variability of the normal different vegetation index(NDVI)of the peak cluster karst area, taking into account the problem of the mountain shadow "missing" information of remote sensing images existing in the karst area,NDVI of the non-shaded area were extracted in Guohua Ecological Experimental Area,in Pingguo County,Guangxi applying image processing software,ENVI. The spatial variability of NDVI was analyzed applying geostatistical method,and the NDVI of the mountain shadow areas was predicted and validated. The results indicated that the NDVI of the study area showed strong spatial variability and spatial autocorrelation resulting from the impact of intrinsic factors, and the range was 300 m. The spatial distribution maps of the NDVI interpolated by Kriging interpolation method showed that the mean of NDVI was 0.196, apparently strip and block. The higher NDVI values distributed in the area where the slope was greater than 25° of the peak cluster area, while the lower values distributed in the area such as foot of the peak cluster and depression, where slope was less than 25°. Kriging method validation results show that interpolation has a very high prediction accuracy and could predict the NDVI of the shadow area, which provides a new idea and method for monitoring and evaluation of the karst rocky desertification.