Combining spectral and texture features using random forest algorithm: Extracting impervious surface area in Wuhan

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 41, Issue , 2016, Pages 351-358

  Shao, Zhenfeng ^a,b   Zhang, Yuan ^a   Zhang, Lei ^a   Song, Yang ^c   Peng, Minjun ^d  

^a WUHAN UNIVERSITY   (China)

^b Shenzhen Research and Development Centre   (China)

^c Guangzhou Urban Planning and Design Survey Research Institute   (China)

^d Wuhan Urban Planning Information Center   (China)

Author keywords

Impervious surface area; Random forest; Texture features

Indexed keywords

ALGORITHMS; ENVIRONMENTAL MANAGEMENT; FORESTRY; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; NEURAL NETWORKS; PIXELS; REMOTE SENSING;

CLASSIFICATION ALGORITHM; HIGH RESOLUTION REMOTE SENSING IMAGES; IMPERVIOUS SURFACE AREA; MULTI-RESOLUTION REMOTE SENSING; RANDOM FORESTS; SPECTRAL MIXTURE ANALYSIS; SUB-PIXEL CLASSIFICATION; TEXTURE FEATURES;

DECISION TREES;

EID: 84979591032     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5194/isprsarchives-XLI-B7-351-2016     Document Type: Conference Paper

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