Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 96, Issue , 2014, Pages 76-93

  Ghosh, Aniruddha ^a,b   Joshi, P K ^a  

^a TERI UNIVERSITY   (India)

^b Department of Environmental and Radiological Health Sciences   (United States)

Author keywords

Gradient boosting machine (GBM); Hyperspectral imagery; Land surface temperature (LST); Partial least square (PLS); Sharpening spatial resolution; Support vector machine (SVM)

Indexed keywords

ATMOSPHERIC TEMPERATURE; EXPERIMENTS; FORECASTING; FORESTRY; LAND USE; REGRESSION ANALYSIS; REMOTE SENSING; SOIL MOISTURE; SPECTROSCOPY; SUPPORT VECTOR MACHINES; IMAGE RESOLUTION; SURFACE MEASUREMENT; SURFACE PROPERTIES;

GRADIENT BOOSTING; HYPER-SPECTRAL IMAGERIES; LAND SURFACE TEMPERATURE; PARTIAL LEAST SQUARE (PLS); SPATIAL RESOLUTION;

ALGORITHMS;

ALGORITHM; IMAGERY; LAND SURFACE; LAND USE CHANGE; LANDSAT THEMATIC MAPPER; NUMERICAL MODEL; REGRESSION ANALYSIS; SOIL MOISTURE; SPATIAL RESOLUTION; SURFACE TEMPERATURE; EVAPOTRANSPIRATION; HEAT ISLAND; LAND COVER; LAND USE; LANDSAT; MAPPING; MOISTURE CONTENT; REFLECTANCE; SATELLITE IMAGERY; VECTOR;

HYPERION;

EID: 84905396580     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2014.07.003     Document Type: Article

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