Extending the vegetation-impervious-soil model using simulated EnMAP data and machine learning

Remote Sensing of Environment

Volumn 158, Issue , 2015, Pages 69-80

  Okujeni, Akpona ^a   van der Linden, Sebastian ^a   Hostert, Patrick ^a  

^a HUMBOLDT UNIVERSITY   (Germany)

Author keywords

EnMAP; Hyperspectral; Imaging spectrometry; Sub pixel mapping; Support vector regression (SVR); Urban rural gradient; VIS model

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE RESOLUTION; LEARNING SYSTEMS; PHOTOMAPPING; REMOTE SENSING; RURAL AREAS; SPECTROMETERS; VEGETATION;

ENMAP; HYPERSPECTRAL; IMAGING SPECTROMETRY; SUB-PIXEL MAPPING; SUPPORT VECTOR REGRESSION (SVR); URBAN-RURAL GRADIENTS;

TREES (MATHEMATICS);

DATA SET; LANDSAT; MAPPING; NUMERICAL MODEL; PIXEL; RURAL AREA; SATELLITE MISSION; SPATIAL RESOLUTION; SPECTROMETRY; URBAN AREA; VEGETATION;

BERLIN; GERMANY;

EID: 84913528798     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2014.11.009     Document Type: Article

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