摘要
叶面积指数(leaf area index,LAI)是森林生态系统中最重要的参数之一。以多角度数据MISR和MODIS土地覆盖类型数据为数据源,采用5-Scale几何光学模型与统计模型相结合的方法反演小兴安岭地区植被叶面积指数。研究结果表明:比值植被指数(simple ratio,SR)与研究区LAI的相关性最好,最适合该区LAI的遥感提取。反演精度为95.7%,均方差为0.34,误差均在合理范围之内。反演精度较高,反演结果较好。研究区域植被LAI随着纬度的增加呈现递减趋势,LAI均值为1.21,最大值为9.28,最小值为0.83,以多角度数据为信息源采用5-Scale模型与统计模型相结合的方法为大区域LAI的遥感反演提供一个有效途径。
Leaf area index（LAI）is one of the most important parameters of forest ecosystem.The multi-angle data MISR along with MODIS data of land cover types were used as data source and the vegetation LAI in Xiaoxing＇an Mountain was estimated by 5-scale geometric optical model combined with statistical model.The results showed that at the study site the simple ratio vegetation index（SR）are highly correlated with measured LAI,which could be used as the best predictor of LAI.The errors are within the acceptable range with inversion accuracy of 95.7% and mean-square deviation of 0.34.The higher the inversion accuracy,the better the inversion results are.The LAI at the study site decreased with the increase of elevation with a mean value of 1.21,the maximum value of 9.28,and the minimum value of 0.83.The study has provided an effective means of estimating LAI by remote sensing for large areas.
出处
《森林工程》
2013年第4期8-13,17,共7页
Forest Engineering
基金
"十二五"国家科技支撑项目(2011BAD37B01)
国防科工局专项(E0305/1112/01/01)
关键词
叶面积指数
多角度数据
几何光学模型
比值植被指数SR
模型反演
leaf area index
multi-angle data
5-scale geometric optical model
simple ratio vegetation index
model inversion
