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Estimation of forest fuel load from radar remote sensing

IEEE Transactions on Geoscience and Remote Sensing

By:
, , , and
DOI: 10.1109/TGRS.2006.887002

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Abstract

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar (SAR) imagery acquired over a large area of the Yellowstone National Park by the Airborne SAR sensor to estimate the distribution of forest biomass and canopy fuel loads. Semiempirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, namely: 1) canopy fuel weight; 2) canopy bulk density; and 3) foliage moisture content. These estimates, when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy and, when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar-generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R2 = 85 for the canopy fuel weight, R 2 = 0.84 for canopy bulk density, and R2 =0.78 for the foliage biomass. ?? 2007 IEEE.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Estimation of forest fuel load from radar remote sensing
Series title:
IEEE Transactions on Geoscience and Remote Sensing
DOI:
10.1109/TGRS.2006.887002
Volume
45
Issue:
6
Year Published:
2007
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
IEEE Transactions on Geoscience and Remote Sensing
First page:
1726
Last page:
1740