Retrieval of canopy biophysical variables from remote sensing data using contextual information

被引：0

作者：

肖志强 ^{[1
,2
]}

王锦地 ^{[1
,2
]}

梁顺林 ^{[3
]}

屈永华 ^{[1
,2
]}

万华伟 ^{[1
,2
]}

机构：

[1] State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications,Chinese Academy of Sciences

[2] School of Geography,Beijing Normal University

[3] Department of Geography,University of Maryland,College Park

来源：

Journal of Central South University | 2008年 / 15卷 / 06期

基金：

中国国家自然科学基金;

关键词：

inverse problem; canopy biophysical variables; contextual information; leaf area index;

D O I：

暂无

中图分类号：

TP751 [图像处理方法];

学科分类号：

081002 ;

摘要：

In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data, a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensing images. The developed algorithm was used for inversion of leaf area index (LAI) from Enhanced Thematic Mapper Plus (ETM+) data by combining with optimization method to minimize cost functions. The results show that the distribution of LAI is spatially consistent with the false composition imagery from ETM+ and the accuracy of LAI is significantly improved over the results retrieved by the conventional pixelwise retrieval methods, demonstrating that this method can be reliably used to integrate spatial contextual information for inverting LAI from high-resolution remote sensing images.

引用

页码：877 / 881

页数：5

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