The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W6, 91–93, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W6-91-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W6, 91–93, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W6-91-2017

  13 Nov 2017

13 Nov 2017

PIXEL-BASED CLASSIFICATION ANALYSIS OF LAND USE LAND COVER USING SENTINEL-2 AND LANDSAT-8 DATA

A. Sekertekin, A. M. Marangoz, and H. Akcin A. Sekertekin et al.
  • BEU, Engineering Faculty, Geomatics Engineering Department 67100 Zonguldak, Turkey

Keywords: Land Use Land Cover, Pixel Based Image Classification, Supervised Classification, Landsat-8 OLI, Sentinel-2 MSI

Abstract. The aim of this study is to conduct accuracy analyses of Land Use Land Cover (LULC) classifications derived from Sentinel-2 and Landsat-8 data, and to reveal which dataset present better accuracy results. Zonguldak city and its near surrounding was selected as study area for this case study. Sentinel-2 Multispectral Instrument (MSI) and Landsat-8 the Operational Land Imager (OLI) data, acquired on 6 April 2016 and 3 April 2016 respectively, were utilized as satellite imagery in the study. The RGB and NIR bands of Sentinel-2 and Landsat-8 were used for classification and comparison. Pan-sharpening process was carried out for Landsat-8 data before classification because the spatial resolution of Landsat-8 (30m) is far from Sentinel-2 RGB and NIR bands (10m). LULC images were generated using pixel-based Maximum Likelihood (MLC) supervised classification method. As a result of the accuracy assessment, kappa statistics for Sentinel-2 and Landsat-8 data were 0.78 and 0.85 respectively. The obtained results showed that Sentinel-2 MSI presents more satisfying LULC images than Landsat-8 OLI data. However, in some areas of Sea class Landsat-8 presented better results than Sentinel-2.