Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Preventing Urban Floods by Optimized Modeling: a Comparative Evaluation of Alternatives in İzmir (türkiye)(Springer Science and Business Media Deutschland GmbH, 2023) Arslan, Bertan; Salata, Stefano; Salata, Stefano; 02.03. Department of City and Regional Planning; 02. Faculty of Architecture; 01. Izmir Institute of TechnologyIt is widely acknowledged that coastal cities will be heavily threatened by climate change globally. Among these cities, the Mediterranean suffers from a coupled dynamic of sea level rise and pluvial flooding due to their landform and soil characteristics. In this situation, analyzing the morphological and hydrological characteristics to define vulnerable areas is a prerequisite to designing performance-based solutions. But how does the flood vulnerability change with the different configurations of pervious and impervious surfaces? How do soil and landform characteristics affect flood vulnerability? This study assumes the possibility of re-naturing the coastal neighborhood of Karsiyaka, Izmir (Türkiye) while using fifteen alternative scenarios. We modeled the Urban Flood Risk Mitigation using InVEST (Natural Capital Project) and integrated the results with an analysis of the flow accumulation. According to our results, when the de-sealing process occurs in soils with low hydraulic conductibility, the results in terms of run-off containment can be dramatically limited or non-perceptible. The findings demonstrate that modeling with scenarios can guide the decision-makers while understanding exactly where the de-permeabilization can achieve its maximum efficiency. Therefore, performance-based solutions designed to increase water infiltration should carefully consider ex-ante empirical modeling to prevent urban flooding. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Conference Object Matching Aerial Coastline Images With Map Data Using Dynamic Programming(Institute of Electrical and Electronics Engineers Inc., 2006) Kahraman, Metin; Gümüştekin, Şevket; Gümüştekin, Şevket; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyMatching aerial images with map data is an important task in several remote sensing applications such as autonomous navigation, cartography, oceanography. The unique and distinctive shapes of coastlines can be effectively utilized to solve this problem. In this study a completely automatic scheme is proposed to detect coastlines using multiresolution texture analysis and to match the detected coastlines to a map database. A shape matching method using dynamic programming is used and tested on the satellite images of the western coast of Turkey.