A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
MAPPING and MONITORING WETLANDS USING SENTINEL-2 SATELLITE IMAGERY
4th International GeoAdvances Workshop - GeoAdvances 2017: ISPRS Workshop on Multi-Dimensional and Multi-Scale Spatial Data Modeling -- 14 October 2017 through 15 October 2017 -- -- 131995 ; Mapping and monitoring of wetlands as one of the world's most valuable natural resource has gained importance with the developed of the remote sensing techniques. This paper presents the capabilities of Sentinel-2 successfully launched in June 2015 for mapping and monitoring wetlands. For this purpose, three different approaches were used, pixel-based, object-based and index-based classification. Additional, for more successful extraction of wetlands, a combination of object-based and index-based method was proposed. It was proposed the use of object-based classification for extraction of the wetlands boundaries and the use of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for classifying the contents within the wetlands boundaries. As a study area in this paper Sakarbasi spring in Eskisehir, Turkey was chosen. The results showed successful mapping and monitoring of wetlands with kappa coefficient of 0.95 ; Firat University Scientific Research Projects Management Unit: 1705F121 ; This study was supported by Anadolu University Scientific Research Projects Commission under the grant no: 1705F121.
MAPPING and MONITORING WETLANDS USING SENTINEL-2 SATELLITE IMAGERY
4th International GeoAdvances Workshop - GeoAdvances 2017: ISPRS Workshop on Multi-Dimensional and Multi-Scale Spatial Data Modeling -- 14 October 2017 through 15 October 2017 -- -- 131995 ; Mapping and monitoring of wetlands as one of the world's most valuable natural resource has gained importance with the developed of the remote sensing techniques. This paper presents the capabilities of Sentinel-2 successfully launched in June 2015 for mapping and monitoring wetlands. For this purpose, three different approaches were used, pixel-based, object-based and index-based classification. Additional, for more successful extraction of wetlands, a combination of object-based and index-based method was proposed. It was proposed the use of object-based classification for extraction of the wetlands boundaries and the use of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for classifying the contents within the wetlands boundaries. As a study area in this paper Sakarbasi spring in Eskisehir, Turkey was chosen. The results showed successful mapping and monitoring of wetlands with kappa coefficient of 0.95 ; Firat University Scientific Research Projects Management Unit: 1705F121 ; This study was supported by Anadolu University Scientific Research Projects Commission under the grant no: 1705F121.
MAPPING and MONITORING WETLANDS USING SENTINEL-2 SATELLITE IMAGERY
Kaplan, Gordana (author) / Avdan, Uğur (author) / Anadolu Üniversitesi, Yer ve Uzay Bilimleri Enstitüsü / Avdan, Uğur
2017-01-01
Conference paper
Electronic Resource
English
Classification , Wetlands , Ndwi , Ndvi , Remote Sensing , Sentinel-2
DDC:
710
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