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    DETERMINING THE LOCATIONS OF POTENTIAL FIREFIGHTING TEAMS BY USING GIS TECHNIQUES
    (Copernicus Gesellschaft Mbh, 2018) Akay, Abdullah Emin; Karas, I. R.; Kahraman, I.
    Wild forest fires are one of the most important disasters that affect the forest ecosystem especially in the regions with arid climate conditions. Besides, forest fires threats human life and results in seriously property loss. In order to fight forest fires effectively, it is crucial that firefighting team should reach fire location and start fire extinguishing activities within the critical response time. Since firefighting teams are transported to fire locations by fire-trucks, the optimum route with minimum travel time should be determined by considering available road network. "New Service Area" tool under "Network Analyst" extension of ArcGIS can be used to determine a region that can be reached from a point within a specified time period. In this study, it was aimed to evaluate the locations of current firefighting teams and investigate locations of potential firefighting teams using "New Service Area" tool. The study area is located in Mustafakemalpasa in Bursa where forest lands are sensitive to forest fires at the second degree and there is currently one firefighting team in the area. The results indicated that 31.28% of forest land can be reached by current firefighting team within the critical response time. When including new firefighting teams, it was found that accessible forest lands increased to 71.55%. It can be concluded that locating new firefighting teams should be established in the study area to increase the accessible forested areas on time and GIS-based decision support systems can be effectively used to fight forest fires regarding with disaster management.
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    ROAD EXTRACTION TECHNIQUES FROM REMOTE SENSING IMAGES: A REVIEW
    (Copernicus Gesellschaft Mbh, 2018) Kahraman, I.; Karas, I. R.; Akay, Abdullah Emin
    The importance of analysis high resolution satellite imagery plays an important research topic for geographical information analysis of cities. Geospatial data plays an important role in important issues such as governmental, industrial, research topics on traffic management, road monitoring, GNSS navigation, and map updating. In this study, road detection from satellite imagery methods are classified as classification-based, knowledge-based, mathematical morphology and dynamic programming. In the beginning, the road structures including feature and model are analyzed. Then, the advantages and disadvantages of road detection methods are evaluated and summarizez their accuracy and performance based on road detection principles. Therefore, in order to obtain remarkable results for road detection, it is better to use more than one method. In after days, performing a complex road extraction from a satellite image is still a necessary and important research topic.