期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B7
页码：471-478
出版社：Copernicus Publications
摘要：The study shows that leaf area index (LAI) and canopy chlorophyll content can be mapped in a heterogeneous Mediterranean grassland from canopy spectral reflectance measurements. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of LAI and chlorophyll content. We tested the utility of univariate techniques, involving narrow band vegetation indices and the red edge inflection point, as well as multivariate calibration techniques, such as partial least squares regression. Among the various investigated models, canopy chlorophyll content was estimated with the highest accuracy (R 2 cv = 0.74, relative RMSE cv = 0.35) and LAI was estimated with intermediate accuracy (R 2 cv = 0.67). Compared with narrow band indices and red edge inflection point, partial least squares regression generally improved the estimation accuracies. The results of the study highlight the significance of using multivariate techniques such as partial least squares regression rather than univariate methods such as vegetation indices for providing enhanced estimates of heterogeneous grass canopy characteristics. To date, partial least squares regression has seldom been applied for studying heterogeneous grassland canopies. However, it can provide a useful exploratory and predictive tool for mapping and monitoring heterogeneous grasslands
关键词：Hyperspectral; Vegetation; Estimation; Leaf Area Index; Chlorophyll
