Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2021Temporal monitoring of land use/land cover change in Kahramanmaraş city center
Aliyazicioglu, Kubra; Beker, Fatmanur; Topaloglu, Raziye Hale; Bilgilioglu, Burhan Baha; Comert, Resul
Irregular urbanization causes problems such as decrease in fertile agricultural areas, irregular industrialization and urbanization. To provide a healthier life opportunity for future generations without disturbing nature, it is essential to determine the temporal changes in land use and to make land management plans accordingly. In this study, land use/land cover (LULC) change occurred in Kahramanmaras province within 30 years was investigated by remote sensing and integration of Geographic Information Systems. Landsat satellite images of 1988-1998-2008-2018 were obtained for the production of LULC maps. Each image was classified according to supervised classification approach using the support vector machines (SVMs) algorithms. The confusion matrix was created for each year to examine the accuracy of the LULC maps. The overall accuracy of the thematic maps was obtained as 91.76%, 93.56%, 86.89% and 88.29%, respectively. Also, Kappa values of thematic maps for each year were obtained as 0.88, 0.91, 0.81 and 0.84, respectively. When the results were examined, the development of industry in the city area and the construction of the airport contributed to the development of the social and economic structure of the city. The increase in the number of housing in the related regions has led to an increase in the amount of urban areas and a decrease in agricultural areas.
- BildiriYalnız künye2015Virtual Mouse Control with Hand Gesture Information Extraction and Tracking
Dogan, Ramazan Ozgur; Dogan, Hulya; Köse, Cemal
Virtual mouse implemented with hand gesture tracking based on image is one of studies in human-computer interaction. In this study that human-computer interaction is implemented with virtual mouse is purposed. This study consists of three main steps that are hand gesture tracking, features of hand region extraction and classification of these features. In this study hand gesture tracking is generated with Camshift (Continuously Adaptive Mean Shift) algorithm, features of hand gestures are extracted with bag of visual words and these features are classified with support vector machines. Detailed tests are performed to compare success of tracking, features extraction and classisfication methods and that this system works successfully is shown.