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Proceedings Paper

Forest fuel moisture content estimation from MODIS data
Author(s): Mei Zhou; Guangmeng Guo; Gary Z. Wang; Junhui Zhao
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Paper Abstract

Fuel moisture content (FMC) is an important parameter in determining fire risk and fire behavior. Direct measurement of FMC in the field is very costly and time consuming. Therefore, remote sensing becomes the effective method to retrieve FMC at large scale. Short wave infrared (SWIR) band reflectance has been found negatively related to leaf water content and most of the researches are conducted at leaf level. Here SWIR and NIR (Near Infrared) bands of Moderate Resolution Imaging Spectroradiometer (MODIS) are used to retrieve FMC at canopy level in Northeast China forest. The result shows that the combination of MODIS band 7 and 2 presented the best results for FMC estimates. It is also found that forest fires prone to spread along the dryer area.

Paper Details

Date Published: 1 September 2005
PDF: 7 pages
Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 588406 (1 September 2005); doi: 10.1117/12.618947
Show Author Affiliations
Mei Zhou, Agricultural Univ. of Inner Mongolia (China)
Guangmeng Guo, Institute of Geography Science and Natural Resources Research, CAS (China)
Gary Z. Wang, USDA Forest Service (United States)
Junhui Zhao, Beijing Forestry Univ. (China)

Published in SPIE Proceedings Vol. 5884:
Remote Sensing and Modeling of Ecosystems for Sustainability II
Wei Gao; David R. Shaw, Editor(s)

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