树种在遥感信息上的差异分析

Difference analysis among tree species in remote sensing image spectra.

通过典型抽样建立了甘肃省小陇山党川林场的40块典型样地,利用GPS测量、后差分平差处理获取了每块样地的坐标,调查了每块样地的树种.对这一区域的TM影像进行几何校正,读取了每块样地对应的影像灰度值并计算了其派生数据.该研究通过实验区13个树种的TM影像灰度值及其派生数据分析,发现油松、华山松、落叶松、云冷杉、栎类、桦类、杂木的波段灰度及植被指数的差异;探讨了遥感影像基于光谱分类对树种的可分性、树种分类应选择的波段和指数.

This study is to identify the different tree species in remote sensing image spectra and discuss the possibility of tree species classification using middle resolution image.Forty typical standard and plots were built and a typical sampling method was used in Dangchuan Forest Station of Xiaolongshan Forest Management Bureau in Gansu Province.The plots were positioned by GPS by measuring four corners and the central point of each one,and the none-real-time difference adjustment method was adopted in the calculation.The tree species of the plots were investigated and the TM images of research area captured during the growing season of trees were rectified to make accuracy less than one pixel.By intersecting plot central point shape file to images using ERDAS software,the grey data of each plot in all bands were obtained,and the vegetation index,BRIGHT,GREEN,and WET were calculated.Then the data were subjected to a comparison.Difference between Pinus tabulaeformis and other species,and that between Quercus spp.and other species were found.The results indicate that most species have obvious differences in vegetation index and GREEN,and a few species have difference less than 10%.From the research,the TM image classification for tree species could be achieved by composing the bands TM2,TM3,TM4,TM5,TM7,NDVI,RVI,GREEN,BRIGHT and WET.