首页  |  本刊简介  |  编委会  |  投稿须知  |  订阅与联系  |  微信  |  出版道德声明  |  Ei收录本刊数据  |  封面
岩溶区峰丛洼地植被指数的克里格分析
摘要点击 1858  全文点击 855  投稿时间:2011-07-26  修订日期:2011-08-27
查看HTML全文 查看全文  查看/发表评论  下载PDF阅读器
中文关键词  岩溶区  NDVI  空间变异  半方差函数  遥感
英文关键词  rocky desertification area  normal different vegetation index(NDVI)  spatial variables  semi-variances  remote sensing
作者单位E-mail
杨奇勇 中国地质科学院岩溶地质研究所,桂林 541004 yangqiyong0739@163.com 
蒋忠诚 中国地质科学院岩溶地质研究所,桂林 541004  
马祖陆 中国地质科学院岩溶地质研究所,桂林 541004  
曹建华 中国地质科学院岩溶地质研究所,桂林 541004  
罗为群 中国地质科学院岩溶地质研究所,桂林 541004  
李文军 湖南文理学院资源环境与旅游学院,常德 415000  
段晓芳 邵阳学院城市建设系,邵阳 422000  
中文摘要
      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.
英文摘要
      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.

您是第52856698位访客
主办单位:中国科学院生态环境研究中心 单位地址:北京市海淀区双清路18号
电话:010-62941102 邮编:100085 E-mail: hjkx@rcees.ac.cn
本系统由北京勤云科技发展有限公司设计  京ICP备05002858号-2