基于CASI高光谱遥感数据的森林叶面积指数反演

Estimating forest leaf area index based on CASI remote sensing data

高光谱遥感技术能够快捷、准确、无损坏地估测森林LAI,从而有效地监测森林长势,估测森林生物量,评价森林病虫害等。以黑龙江凉水自然保护区为例,利用高光谱遥感技术和GPS测量技术,结合地面实测LAI数据,采用从CASI图像提取的NDVI、SR、MSAVI 3种植被指数,与地面实测的LAI建立统计回归模型,然后再从众多的统计模型中根据相关系数,筛选出由CASI反演LAI的最佳植被指数和回归模型。

Hyperspectral remote sensing technology can be fast,accurate,no-damage to estimate forest LAI,effective monitoring of forest growing,estimating forest biomass,evaluating forest pests and diseases ect.In this paper,Liangshui Nature Reserve as the study area,hyperspectral remote sensing technology and GPS measurements were adopted,Combined with ground truth LAI data.NDVI,SR and MSAVI extracted from the CASI image were established statistical regression model with the ground truth LAI,and then screened the best VIs and model form a large number of statistical models based on the correlation coefficient.