Detection and classification of invasive saltcedar through high spatial resolution airborne hyperspectral imagery

International Journal of Remote Sensing

Volumn 32, Issue 8, 2011, Pages 2131-2150

  Miao, Xin ^a   Patil, Rohit ^b   Heaton, Jill S ^a   Tracy, Richard C ^a  

^a MISSOURI STATE UNIVERSITY   (United States)

^b UNIVERSITY OF NEVADA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE CLASSIFICATION; IMAGE RESOLUTION; MAXIMUM LIKELIHOOD; SPECTROSCOPY; VEGETATION;

CLARK COUNTY , NEVADA; CLASSIFICATION ACCURACY; CLASSIFICATION APPROACH; HIGH SPATIAL RESOLUTION; HYPER-SPECTRAL IMAGERIES; MINIMUM NOISE FRACTION; SPATIAL RESOLUTION IMAGERY; SPECTRAL ANGLE MAPPERS;

PRINCIPAL COMPONENT ANALYSIS;

ACCURACY ASSESSMENT; AIRBORNE SENSING; DETECTION METHOD; IMAGE ANALYSIS; IMAGE CLASSIFICATION; INVASIVE SPECIES; MAXIMUM LIKELIHOOD ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; RIPARIAN VEGETATION; SPATIAL RESOLUTION; SPECTRAL ANALYSIS; VEGETATION COVER;

MUDDY RIVER; NEVADA; UNITED STATES;

PROSOPIS GLANDULOSA;

EID: 79957511390     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161003674618     Document Type: Article

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