The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1417–1421, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1417-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1417–1421, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1417-2020

  22 Aug 2020

22 Aug 2020

ADVANCED CLASSIFICATION OF OPTICAL AND SAR IMAGES FOR URBAN LAND COVER MAPPING

D. Amarsaikhan D. Amarsaikhan
  • Institute of Geography and Geoecology, Mongolian Academy of Sciences, Mongolia

Keywords: Urban land cover, Optical, Synthetic aperture radar (SAR), Feature, Classification method

Abstract. The aim of this research is to classify urban land cover types using an advanced classification method. As the input bands to the classification, the features derived from Landsat 8 and Sentinel 1A SAR data sets are used. To extract the reliable urban land cover information from the optical and SAR features, a rule-based classification algorithm that uses spatial thresholds defined from the contextual knowledge is constructed. The result of the constructed method is compared with the results of a standard classification technique and it indicates a higher accuracy. Overall, the study demonstrates that the multisource data sets can considerably improve the classification of urban land cover types and the rule-based method is a powerful tool to produce a reliable land cover map.