The effect of different areas and image band in the road extraction from high-resolution uav images using the Obia method
Yiğit, Abdurahman Yasin
This study semi-automatically detects road lines using object-based classification methods from orthophoto produced from UAV images. Three studies were carried out on images with visible and infrared wavelengths. The study's major aim is to examine the effect of spectral bands and different areas on classification accuracy. First, orthophotos were produced from UAV images of different areas and an object-based classification algorithm was used to detect roads. Then, statistical comparisons were made and, user accuracy in the three study regions ranged from 85 to 91%. Overall accuracies were calculated between 0.819 and 0.889, and the results were within the confidence interval.
Monitoring the change of Turkey’s tourism city Antalya’s Konyaaltı shoreline with multi-source satellite and meteorological data
Yiğit, Abdurahman Yasin
Uncontrolled tourism activities cause the destruction of nature and deterioration of the ecological balance. Since coastal areas are both economically and socially important, monitoring shoreline changes has become one of the important research areas. Monitoring short-term and long-term changes in coastal areas is important to prevent damages that may occur due to natural and human factors and protect the shorelines. In this study, which is an important tourist city of Antalya, Turkey, and the world, coastal changes using historical and recent satellite data have been analyzed. The focus of the study is to analyze long-term coastal change with Landsat data and the data obtained every 5 years between 1985 and 2020 and to analyze short-term change with annual Sentinel-2 data between 2015 and...