Peer-reviewed articles 17,970 +



Title: ANALYSIS OF LAND USE/LAND COVER CLASSIFICATION RESULTS DERIVED FROM SENTINEL-2 IMAGE

ANALYSIS OF LAND USE/LAND COVER CLASSIFICATION RESULTS DERIVED FROM SENTINEL-2 IMAGE
A.M. MARANGOZ;A. SEKERTEKIN; H.AKCIN
1314-2704
English
17
23
In this study, object-based Land Use Land Cover (LULC) classification performance of Sentinel-2 image has been tested by comparing other medium resolution satellite dataset of Zonguldak test field. The test field covering a small area around Zonguldak is located in the Western Black Sea region of Turkey. It is noted for being one of the main coal mining areas in the world. For the purpose of the study, pan-sharpened Landsat 8 image was used because of its nearly similar ground sampling distance (GSD). The RGB and NIR bands of Sentinel-2 were used for classification and comparison. As a first step, Landsat-8 pan-sharpened image was created using High Pass Filtering (HPF) pan sharp algorithm in ERDAS software package. Following this, resulted images were handled by the eCognition v4.0.6 software with the main steps of segmentation and classification. After determining the optimal segmentation parameters correctly, classification of main Land use/Land cover classes were compared with by Landsat-8 derived LULC classes. Furthermore, the results were verified visually using high resolution satellite image Worldview-2. The accuracy assessment as Kappa statistics for Sentinel-2 and Landsat-8 are 0.74 and 0.66, respectively. The obtained results revealed that Sentinel-2 LULC images give better results than Landsat-8.
conference
17th International Multidisciplinary Scientific GeoConference SGEM 2017
17th International Multidisciplinary Scientific GeoConference SGEM 2017, 29 June - 5 July, 2017
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference-SGEM
Bulgarian Acad Sci; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Slovak Acad Sci; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; World Acad Sci; European Acad Sci, Arts & Letters; Ac
25-32
29 June - 5 July, 2017
website
cdrom
3174
Sentinel-2; Landsat-8; Land Use; Land Cover Image Contents; eCognition; Segmentation; Object-Based Image Analysis (OBIA)