City and Regional Planning / Şehir ve Bölge Planlama
Permanent URI for this collectionhttps://hdl.handle.net/11147/4274
Browse
3 results
Search Results
Article Citation - WoS: 4Citation - Scopus: 4Designing Urban Green İnfrastructures Using Open-source Data-an Example İn Çiğli, Izmir (turkey)(MDPI, 2022) Salata, Stefano; Erdoğan, Bensu; Ayruş, BersuThe city of Izmir (Turkey) has experienced one of the most rapid and fastest urbanization processes in the last thirty years; more than 33 thousand hectares of agricultural and seminatural land have been transformed into urban areas, leading to a drastic reduction of biodiversity and hard deployments of the ecosystem service supply. In this perspective, the potential definition of methodologies to design multifunctional green infrastructures is extremely important to challenge the effects of climate change. The aim of this study is to propose an easy and replicable methodology to design a Green Infrastructure at the neighbourhood level in one of the most important districts of Izmir: Çiğli. To this end, we combined historical land-use change analysis (based on Urban Atlas, Copernicus Land Monitoring Service) with environmental and ecosystem mapping in a Geographic Information System environment (ESRI ArcMap 10.8.1) while creating a composite layer based on unweighted overlays of Imperviousness, Tree Cover Density, and Habitat Quality. Results were used to design the Green Infrastructure of Çiğli and suggest context-based strategies for urban adaptation, including Nature-Based Solutions for core, edge, and urban links.Conference Object Detection of Urban Change Using Remote Sensing and Gis: Izmir Case(Taylor and Francis Ltd., 2008) Tarhan, Çiğdem; Arkon, Cemal; Çelik, M.; Gümüştekin, Şevket; Tecim, V.This study is an example of how land use changes could be detected via high resolution remotely sensed data. In order to perform "change detection" IKONOS satellite images, belonging to 2001 and 2004, have been used. An automated Graphical User Interface (GUI) has been created for detection of environment. Different image enhancement techniques and a fuzzy inference system have been combined in the GUI. The detection results are classified according to some basic levels such as 20-50% and 70%. Additionally, four different change detection algorithms have been applied which are pixel-based, object based, feature based. These algorithms have been examined according to change detection levels with different image enhancement techniques. At the end of the study, the results have been compared.Article Citation - WoS: 5Citation - Scopus: 6Flood Hazard Vulnerability for Settlements of Turkey’s Province of Edirne, Using Aster Dem Data and Landsat-7 Etm+ Image Data(Springer Verlag, 2016) Demirkesen, Ali CanWhile Turkey’s province of Edirne represents one of the country’s most significant cultural heritage areas because it lies in the basins of the Meric and Ergene rivers, this very valuable region is highly susceptible to flooding during heavy rain falls. It becomes particularly vulnerable when neighboring Bulgaria responds to its own threats of heavy rain or snowfall by opening its floodgates of its dams on the River Meric, which flows through the Edirne province. Therefore, for years, the Edirne province has experienced severe floods that are eroding its fertile alluvial agricultural floodplains. An environmental plan based on a determination of the vulnerability levels of the province’s flood hazard risk areas is required if action is taken to alleviate this problem. The objective of this study is to acquire geo-information from the remotely sensed data and to interpret the flood hazard risk levels of the area’s settlements and agricultural floodplains. In this study, the spatial distribution of the flood hazard risk areas in the Edirne province is determined using not only the Advanced Space-Borne Thermal Emission and Reflection Radiometer digital elevation model data of the Edirne province to create maps that illustrate the digital terrain model and the 3D fly-through dynamic model of the study region but also the Landsat-7 Enhanced Thematic Mapper Plus multi-spectral image data set to create land use and land cover types of the study region. The maps exhibit landform characteristics, floodplain topography, and stream drainages. Analysis and interpretation of the maps demonstrate that the areas most susceptible to flooding are Enez, which lies at the northern coastal area of the Aegean Sea and agricultural areas, and the settlements on the Meric River floodplains of Ipsala, Meric, Edirne, and Uzunkopru, listed in decreasing order, respectively.