Evaluation of clustering algorithms for unsupervised change detection in VHR remote sensing imagery

2017 Joint Urban Remote Sensing Event, JURSE 2017

Volumn , Issue , 2017, Pages

  Leichtle, Tobias ^a,b   Geiß, Christian ^b   Wurm, Michael ^b   Lakes, Tobia ^c   Taubenböck, Hannes ^b  

^a Company for Remote Sensing and Environmental Research ^*  (Germany)

^b GERMAN AEROSPACE CENTER DLR   (Germany)

^c HUMBOLDT UNIVERSITY   (Germany)

Author keywords

Change detection; Clustering; Object based image analysis; Very high resolution (VHR) remote sensing

Indexed keywords

CONFORMAL MAPPING; REMOTE SENSING; SELF ORGANIZING MAPS; SPACE OPTICS;

CHANGE DETECTION; CLUSTERING; DYNAMIC URBAN ENVIRONMENTS; OBJECT BASED IMAGE ANALYSIS; PARTITIONING AROUND MEDOIDS; UNSUPERVISED CHANGE DETECTION; VERY HIGH RESOLUTION; VERY HIGH SPATIAL RESOLUTIONS;

CLUSTERING ALGORITHMS;

EID: 85020167602     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/JURSE.2017.7924625     Document Type: Conference Paper

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