Multisource Earth Observation Data for Land-Cover Classification Using Random Forest

IEEE Geoscience and Remote Sensing Letters

Volumn 15, Issue 5, 2018, Pages 789-793

  Xu, Zhigang ^a,b   Chen, Jike ^a   Xia, Junshi ^c   Du, Peijun ^a   Zheng, Hongrui ^a   Gan, Le ^a  

^a NANJING UNIVERSITY   (China)

^b LONGYAN UNIVERSITY   (China)

^c UNIVERSITY OF TOKYO   (Japan)

Author keywords

Digital surface model (DSM); land cover; local climate zones (LCZs); random forest (RF); thermal infrared sensor (TIRS)

Indexed keywords

CLIMATE MODELS; DECISION TREES; DIGITAL RADIO; INFRARED DETECTORS; INFRARED DEVICES; INFRARED RADIATION; OBSERVATORIES; RADIOMETRY; REMOTE SENSING; SOILS; SUPPORT VECTOR MACHINES; VEGETATION;

DIGITAL SURFACE MODEL (DSM); LAND COVER; LAND SURFACE; LOCAL CLIMATE; RADIO FREQUENCIES; RANDOM FORESTS; THERMAL INFRARED SENSORS; VEGETATION MAPPING;

CLASSIFICATION (OF INFORMATION);

DIGITAL TERRAIN MODEL; EOS; HETEROGENEITY; LAND COVER; REGIONAL CLIMATE; SUPPORT VECTOR MACHINE; THERMAL INFRARED MULTISPECTRAL SCANNER;

EID: 85043390098     PISSN: 1545598X     EISSN: 15580571     Source Type: Journal    
DOI: 10.1109/LGRS.2018.2806223     Document Type: Article

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