Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data

Remote Sensing of Environment

Volumn 200, Issue , 2017, Pages 170-182

  Liu, Luxia ^a,d   Coops, Nicholas C ^b   Aven, Neal W ^c   Pang, Yong ^d  

^a ANHUI AGRICULTURAL UNIVERSITY   (China)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c Urban Forestry   (Canada)

^d RESEARCH INSTITUTE OF FORESTRY   (China)

Author keywords

Airborne hyperspectral; Airborne LiDAR; British Columbia, Canada; Random forest; Urban tree species classification

Indexed keywords

ANTHOCYANINS; BIODIVERSITY; DECISION TREES; FORESTRY; MAPPING; OPTICAL RADAR; PLANTS (BOTANY); REMOTE SENSING; SPECTROSCOPY; URBAN PLANNING; VEGETATION;

AIRBORNE LIDAR; BRITISH COLUMBIA , CANADA; HYPERSPECTRAL; RANDOM FORESTS; URBAN TREES;

CLASSIFICATION (OF INFORMATION);

BIODIVERSITY; CANOPY ARCHITECTURE; CONIFEROUS TREE; ECOSYSTEM SERVICE; EVERGREEN TREE; FOREST ECOSYSTEM; HEAT ISLAND; LIDAR; MAPPING METHOD; REMOTE SENSING; SATELLITE DATA; SATELLITE IMAGERY; TREE; URBAN AREA; URBAN PLANNING;

BRITISH COLUMBIA; CANADA; SURREY [BRITISH COLUMBIA];

EID: 85028948905     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.08.010     Document Type: Article

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