Estimation of aboveground carbon stock of Moso bamboo (Phyllostachys heterocycla var. pubescens) forest with a Landsat Thematic Mapper image

International Journal of Remote Sensing

Volumn 32, Issue 5, 2011, Pages 1431-1448

  Xu, Xiaojun ^a   Du, Huaqiang ^a   Zhou, Guomo ^a   Ge, Hongli ^a   Shi, Yongjun ^a   Zhou, Yufeng ^a   Fan, Weiliang ^a   Fan, Wenyi ^b  

^a ZHEJIANG A F UNIVERSITY   (China)

^b NORTHEAST FORESTRY UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BAMBOO; BUDGET CONTROL; FORESTRY; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; MAPPING; NEURAL NETWORKS; REMOTE SENSING;

ABOVE-GROUND CARBONS; ACTIVATION FUNCTIONS; BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; ESTIMATION PERFORMANCE; LANDSAT THEMATIC MAPPER IMAGES; LINEAR REGRESSION MODELS; PARTIAL LEAST-SQUARES REGRESSION; PHYLLOSTACHYS HETEROCYCLA;

CARBON;

ABOVEGROUND PRODUCTION; ARTIFICIAL NEURAL NETWORK; BAMBOO; CARBON BUDGET; ERROR ANALYSIS; LANDSAT THEMATIC MAPPER; LEAST SQUARES METHOD; REGRESSION ANALYSIS; REMOTE SENSING;

BAMBOO; CHINA; ESTIMATION; FORESTRY; MAPPING; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; REMOTE SENSING;

CHINA; SOUTH ASIA; ZHEJIANG;

PHYLLOSTACHYS PUBESCENS;

EID: 79953232362     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160903551389     Document Type: Article

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