Optimized sample selection in SVM classification by combining with DMSP-OLS, landsat NDVI and GlobeLand30 products for extracting urban built-up areas

Remote Sensing

Volumn 9, Issue 3, 2017, Pages

  Ma, Xiaolong ^a,b   Tong, Xiaohua ^a   Liu, Sicong ^a   Luo, Xin ^a   Xie, Huan ^a   Li, Chengming ^b  

^a TONGJI UNIVERSITY   (China)

^b CHINESE ACADEMY OF SURVEYING AND MAPPING   (China)

Author keywords

DMSP OLS; GlobeLand30; Initial training samples; Iterative optimization process; NDVI; Probability threshold; Sample optimized approach; SVM classification; Urban built up areas

Indexed keywords

DATA ACQUISITION; EXTRACTION; FORESTRY; IMAGE PROCESSING; ITERATIVE METHODS; SAMPLING; SUPPORT VECTOR MACHINES; VEGETATION;

BUILT-UP AREAS; DMSP-OLS; GLOBELAND30; ITERATIVE OPTIMIZATION; NDVI; PROBABILITY THRESHOLD; SVM CLASSIFICATION; TRAINING SAMPLE;

CLASSIFICATION (OF INFORMATION);

EID: 85019385219     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9030236     Document Type: Article

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