Enhanced Gap Fraction Extraction From Hemispherical Photography

被引：12

作者：

Diaz, Gaston M. ^{[1
,2
]}

Lencinas, Jose D. ^{[1
,2
,3
]}

机构：

[1] Consejo Nacl Invest Cient & Tecn, Buenos Aires, DF, Argentina

[2] Ctr Invest & Extens Forestal Andino Patagon, RA-9200 Esquel, Argentina

[3] Univ Nacl Patagonia San Juan Bosco, RA-9200 Esquel, Argentina

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2015年 / 12卷 / 08期

关键词：

Fish-eye photography; forestry; fuzzy logic; image classification; image texture analysis; LEAF-AREA INDEX; BOREAL FORESTS; EXPOSURE; PACKAGE; STANDS;

D O I：

10.1109/LGRS.2015.2425931

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Canopy structure can be estimated using gap fraction (GF) data, which can be directly measured with hemispherical photography. However, GF data accuracy is affected by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration. Here, we present an algorithm to classify hemispherical photography, whose aim is to reduce errors in the extraction of GF data. The algorithm, which was implemented in free software, uses color transformations, fuzzy logic, and object-based image analysis. The results suggest that color and texture, rather than only brightness, can be used to extract GF data.

引用

页码：1785 / 1789

页数：5

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