Detection of urban sprawl using a genetic algorithm-evolved artificial neural network classification in remote sensing: A case study in Jiading and Putuo districts of Shanghai, China

International Journal of Remote Sensing

Volumn 31, Issue 6, 2010, Pages 1485-1504

  Tong, Xiaohua ^a   Zhang, Xue ^a   Liu, Miaolong ^a  

^a TONGJI UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION ALGORITHMS; GENETIC ALGORITHMS; LAND USE; MAXIMUM LIKELIHOOD; NEURONS; REMOTE SENSING; URBAN GROWTH;

BACK-PROPAGATION NEURAL NETWORKS; CONVENTIONAL CLASSIFICATION METHODS; HIDDEN LAYER NUMBERS; LAND USE AND LAND COVER CHANGE; LANDSAT THEMATIC MAPPER; MAXIMUM LIKELIHOOD CLASSIFIERS; NEURAL NETWORK CLASSIFICATION; REMOTELY SENSED DATA;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; DETECTION METHOD; GENETIC ALGORITHM; IMAGE CLASSIFICATION; LANDSAT THEMATIC MAPPER; REMOTE SENSING; SATELLITE IMAGERY; URBAN AREA;

CHINA; SHANGHAI;

EID: 77951126983     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160903475290     Document Type: Article

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