Deriving land surface biophysical parameters from satellite data for soil carbon sequenstration

被引：0

作者：

Fang, HL ^{[1
]}

Liang, SL ^{[1
]}

van Leeuwen, WJD ^{[1
]}

Drake, S ^{[1
]}

Marsh, SE ^{[1
]}

McClaran, MP ^{[1
]}

Thomson, A ^{[1
]}

Izaurralde, RC ^{[1
]}

Rosenberg, NJ ^{[1
]}

机构：

[1] Univ Maryland, Dept Geog, College Pk, MD 20742 USA

来源：

IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET | 2004年

关键词：

leaf area index (LAI); Vegetation Index (VI); CHRIS; semi-arid rangeland;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

We apply a hybrid inversion algorithm to estimate land surface biophysical variables (e.g., leaf area index) from the CHRIS (Compact High Resolution Imaging Spectrometer), and ETM+. Field campaigns were conducted over Tucson, Arizona to validate the algorithms and the products. The derived products were compared for different human management activities. These products are then available for input to a plant growth model for calculating the potential for carbon sequestration.

引用

页码：4277 / 4280

页数：4

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