不同大气校正方法对森林叶面积指数遥感估算影响的比较

利用TM原始图像以及经过6S模型和基于影像自身的Gilabert模型大气校正后的地面绝对反射率图像,分别计算了褒河流域阔叶林和针阔混交林2种林型的5类光谱植被指数(SR、NDVI、MNDVI、ARVI和RSR),并建立各林型森林叶面积指数与同时相的各个植被指数的相关关系。结果表明,2种大气校正模型均显著提高了各植被指数与森林叶面积指数的相关关系,除了对森林叶面积指数与植被指数SR和NDVI的相关关系影响不显著外,对森林叶面积指数与植被指数MNDVI、ARVI和RSR相关关系的影响均非常显著。说明不同大气校正模型对叶面积指数的遥感估算结果有较大影响。因此,在利用遥感数据进行定量分析、信息提取和生态遥感应用时,不仅要进行大气校正,而且还要慎重选择大气校正模型和植被指数。

Comparison of different atmospheric correction models in their effects on Landsat TM estimation of forest leaf area index

To compare the effects of two atmospheric correction models on the relationships between vegetation indices(VIs) and forest leaf area index(LAI),the atmospheric correction reflectance images on the basis of DN image were obtained by using 6S and Gilabert models.The simple ratio(SR),normalizes difference vegetation index(NDVI),modified normalizes difference vegetation index(MNDVI),atmospheric resistant vegetation index(ARVI) and reduced simple ratio(RSR) of the broad-leaved forests and mixed broad-leaved and coniferous forests in Baohe basin were estimated,and the relationships between the VIs and the ground-based measurements of LAI were calculated.The results showed that compared with DN image,the two models significantly increased the correlation coefficients between LAI and VIs except SR and NDVI.Different atmospheric correction models had significant effects on the estimation of forest leaf area.It was suggested that more attention should be paid to choose appropriate atmospheric correction models and VIs when remote sensing data were applied to quantitative analyzing and information collecting in field.