Modeling Percent Tree Canopy Cover: A Pilot Study

被引：172

作者：

Coulston, John W. ^{[1
]}

Moisen, Gretchen G. ^{[2
]}

Wilson, Barry T. ^{[3
]}

Finco, Mark V. ^{[4
]}

Cohen, Warren B. ^{[5
]}

Brewer, C. Kenneth ^{[6
]}

机构：

[1] US Forest Serv, Knoxville, TN 37919 USA

[2] US Forest Serv, Ogden, UT 84401 USA

[3] US Forest Serv, St Paul, MN 55108 USA

[4] Red Castle Resources, Salt Lake City, UT 84119 USA

[5] US Forest Serv, Corvallis, OR 97331 USA

[6] US Forest Serv, Arlington, VA 22209 USA

来源：

PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING | 2012年 / 78卷 / 07期

关键词：

FOREST INVENTORY; BETA REGRESSION; DATABASE; BIOMASS; US; CARBON; AREA;

D O I：

10.14358/PERS.78.7.715

中图分类号：

P9 [自然地理学];

学科分类号：

0705 ; 070501 ;

摘要：

Tree canopy cover is a fundamental component of the landscape, and the amount of cover influences fire behavior, air pollution mitigation, and carbon storage. As such, efforts to empirically model percent tree canopy cover across the United States are a critical area of research. The 2001 national-scale canopy cover modeling and mapping effort was completed in 2006, and here we present results from a pilot study for a 2011 product. We examined the influence of two different modeling techniques (random forests and beta regression), two different Landsat imagery normalization processes, and eight different sampling intensities across five different pilot areas. We found that random forest out-performed beta regression techniques and that there was little difference between models developed based on the two different normalization techniques. Based on these results we present a prototype study design which will test canopy cover modeling approaches across a broader spatial scale.

引用

页码：715 / 727

页数：13

共 40 条

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