Detecting change in urban areas at continental scales with MODIS data

Remote Sensing of Environment

Volumn 158, Issue , 2015, Pages 331-347

  Mertes, C M ^a   Schneider, A ^a   Sulla Menashe, D ^b   Tatem, A J ^c,d   Tan, B ^e  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b BOSTON UNIVERSITY   (United States)

^c UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^d NATIONAL INSTITUTES OF HEALTH   (United States)

^e NASA GODDARD SPACE FLIGHT CENTER   (United States)

Author keywords

Change detection; Cities; Classification; Data fusion; Decision fusion; Decision trees; Land cover; Machine learning; Urban areas; Urbanization

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DATA FUSION; DECISION TREES; ECOLOGY; IMAGE RECONSTRUCTION; LEARNING SYSTEMS; MAPPING; PHOTOMAPPING; RADIOMETERS; REMOTE SENSING; SATELLITE IMAGERY; SIGNAL DETECTION; TREES (MATHEMATICS);

CHANGE DETECTION; CITIES; DECISION FUSION; LAND COVER; URBAN AREAS; URBANIZATION;

URBAN GROWTH;

ACCURACY ASSESSMENT; DATA SET; DETECTION METHOD; ERROR ANALYSIS; LAND COVER; MODIS; SPATIOTEMPORAL ANALYSIS; TOPOGRAPHIC MAPPING; URBAN AREA; URBANIZATION; VEGETATION INDEX;

EID: 84920972671     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2014.09.023     Document Type: Article

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