Combining hyperspectral remote sensing and physical modeling for applications in land ecosystems

被引：11

作者：

Goodenough, David G. ^{[1
]}

Li, Jing Y. ^{[1
]}

Asner, Gregory P.

Schaepman, Michael E.

Ustin, Susan L.

Dyk, Andrew ^{[1
]}

机构：

[1] Natl Res Council Canada, Pacific Forestry Ctr, Victoria, BC, Canada

来源：

2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年

基金：

加拿大自然科学与工程研究理事会;

关键词：

hyperspectral; ecosystem; radiative transfer model; vegetation indices; AVIRIS; EO-1; CHRIS; forestry; bioindicator;

D O I：

10.1109/IGARSS.2006.518

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Land ecosystems, in particular forest ecosystems, are under increasing pressure from environmental changes such as population growth, global warming, wildfires, forest insects, and diseases. Data from hyperspectral sensors can be used to map forest species and determine biophysical and biochemical properties. Modeling plays an important role in accurate determination of ecosystem properties. Radiative transfer models are used to understand how radiation interacts with the atmosphere and the Earth's terrestrial surface and to correct observed radiances to surface reflectance. Canopy models are used to infer through inversion quantitative information from hyperspectral data on canopy structure and foliage biochemistry. This article presents an overview on combining hyperspectral sensing with canopy radiative transfer models to derive ecosystem information products.

引用

页码：2000 / +

页数：3

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