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Volumn 99, Issue , 2018, Pages 1-10

A Machine Learning approach for automatic land cover mapping from DSLR images over the Maltese Islands

Author keywords

Decision trees; Land cover mapping; Machine learning; Pattern recognition

Indexed keywords

AERIAL PHOTOGRAPHY; ANTENNAS; ARTIFICIAL INTELLIGENCE; LANDFORMS; LEARNING SYSTEMS; PATTERN RECOGNITION; SATELLITE IMAGERY; VEGETATION MAPPING;

EID: 85035037271     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2017.09.014     Document Type: Article
Times cited : (13)

References (15)
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  • 2
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  • 3
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    • (2016)
    • Joinson, S.1
  • 5
    • 0004255908 scopus 로고    scopus 로고
    • Machine Learning
    • McGraw-Hill, Inc. New York, NY, USA
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    • Mitchell, T.1
  • 6
    • 79151481003 scopus 로고    scopus 로고
    • Decision tree classification of land use land cover for Delhi, India using IRS-P6 AWiFS data
    • Punia, M., Joshi, P.K., Porwal, M.C., Decision tree classification of land use land cover for Delhi, India using IRS-P6 AWiFS data. Expert Syst. Appl. 38:5 (2011), 5577–5583.
    • (2011) Expert Syst. Appl. , vol.38 , Issue.5 , pp. 5577-5583
    • Punia, M.1    Joshi, P.K.2    Porwal, M.C.3
  • 9
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    • Schneider, A., Friedl, M.A., Potere, D., Mapping global urban areas using MODIS 500-m data: new methods and datasets based on ‘urban ecoregions’. Remote Sens. Environ. 114:8 (2010), 1733–1746.
    • (2010) Remote Sens. Environ. , vol.114 , Issue.8 , pp. 1733-1746
    • Schneider, A.1    Friedl, M.A.2    Potere, D.3
  • 10
    • 79953801638 scopus 로고    scopus 로고
    • Combining Random Forests and object-oriented analysis for landslide mapping from very high resolution imagery
    • Stumpf, A., Kerle, N., Combining Random Forests and object-oriented analysis for landslide mapping from very high resolution imagery. Procedia Environ. Sci. 3 (2011), 123–129.
    • (2011) Procedia Environ. Sci. , vol.3 , pp. 123-129
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    • Classifier ensembles for land cover mapping using multitemporal SAR imagery
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    • Waske, B.1    Braun, M.2
  • 14


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.