[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 degrees 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 degrees. 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.
Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin 541004, China. yangqiyong0739@163.com
Qi-Yong
QY
Yang
Zhong-Cheng
ZC
Jiang
Zu-Lu
ZL
Ma
Jian-Hua
JH
Cao
Wei-Qun
WQ
Luo
Wen-Jun
WJ
Li
Xiao-Fang
XF
Duan
D002681:China; D003247:Conservation of Natural Resources / Q000379:methods*; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D005544:Forecasting; D063245:Plant Development; D058998:Remote Sensing Technology; D062206:Spatial Analysis; D014197:Trees / Q000254:growth & development / Q000502:physiology