Analyzing riparian forest cover changes along the Firniz River in the Mediterranean City of Kahramanmaras in Turkey.

Riparian forests adjacent to surface water are important transitional zones which maintain and enrich biodiversity and ensure the sustainability in a forest ecosystem. Also, riparian forests maintain water quality, reduce sediment delivery, enhance habitat areas for aquatic life and wildlife, and provide ecological corridors between the upland and the downstream. However, the riparian ecosystems have been degraded mainly due to human development, forest operations, and agricultural activities. In order to evaluate the impacts of these factors on riparian forests, it is necessary to estimate trends in forest cover changes. This study aims to analyze riparian forest cover changes along the Firniz River located in Mediterranean city of Kahramanmaras in Turkey. Changes in riparian forest cover from 1989 to 2010 have been determined by implementing supervised classification method on a series of Landsat TM imagery of the study area. The results indicated that the classification process applied on 1989 and 2010 images provided overall accuracy of 80.08 and 75 %, respectively. It was found that the most common land use class within the riparian zone was productive forest, followed by degraded forest, agricultural areas, and other land use classes. The results also indicated that the areas of degraded forest and forest openings increased, while productive forest and agricultural areas decreased between the years of 1989 and 2010. The amount of agricultural areas decreased due to the reduction in the population of rural people. According to these results, it can be concluded that special forest management and operation techniques should be implemented to restore the forest ecosystem in riparian areas.

A GIS-based decision support system for determining the shortest and safest route to forest fires: a case study in Mediterranean Region of Turkey.

The ability of firefighting vehicles and staff to reach a fire area as quickly as possible is critical in fighting against forest fires. In this study, a Geographical Information System-based decision support system was developed to assist fire managers in determining the fastest and the safest or more reliable access routes from firefighting headquarters to fire areas. The decision support system was tested in the Kahramanmaras Forestry Regional Directoratein the Mediterranean region of Turkey. The study area consisted of forested lands which had been classified according to fire sensitivity. The fire response routing simulations considered firefighting teams located in 20 firefighting headquarter locations. The road network, the locations of the firefighting headquarters, and possible fire locations were mapped for simulation analysis. In alternative application simulations, inaccessible roads which might be closed due to fire or other reasons were indicated in the network analysis so that the optimum route was not only the fastest but also the safest and most reliable path. The selection of which firefighting headquarters to use was evaluated by considering critical response time to potential fire areas based on fire sensitivity levels. Results indicated that new firefighting headquarters should be established in the region in order to provide sufficient firefighting response to all forested lands. In addition, building new fire access roads and increasing the design speed on current roads could also increase firefighting response capabilities within the study area.

Using the Remote Sensing and GIS Technology for Erosion Risk Mapping of Kartalkaya Dam Watershed in Kahramanmaras, Turkey.

The soil erosion is the most serious environmental problem in watershed areas in Turkey. The main factors affecting the amount of soil erosion include vegetation cover, topography, soil, and climate. In order to describe the areas with high soil erosion risks and to develop adequate erosion prevention measures in the watersheds of dams, erosion risk maps should be generated considering these factors. Remote Sensing (RS) and Geographic Information System (GIS) technologies were used for erosion risk mapping in Kartalkaya Dam Watershed of Kahramanmaras, Turkey, based on the methodology implemented in COoRdination of INformation on the Environment (CORINE) model. ASTER imagery was used to generate a land use/cover classification in ERDAS Imagine. The digital maps of the other factors (topography, soil types, and climate) were generated in ArcGIS v9.2, and were then integrated as CORINE input files to produce erosion risk maps. The results indicate that 33.82%, 35.44%, and 30.74% of the study area were under low, moderate, and high actual erosion risks, respectively. The CORINE model integrated with RS and GIS technologies has great potential for producing accurate and inexpensive erosion risk maps in Turkey.

Application of GeoWEPP for Determining Sediment Yield and Runoff in the Orcan Creek Watershed in Kahramanmaras, Turkey.

The geo-spatial interface of the WEPP model called GeoWEPP uses digital geo-referenced information integrated with the most common GIS tools to predict sedimentyield and runoff. The model determines where and when the sediment yield and runoffoccurs and locates possible deposition places. In this study, the sediment yield and runofffrom Orcan Creek watershed in Kahramanmaras region was estimated by using GeoWEPPmodel. To investigate the performance of the model, the sediment yield and runoff resultsfrom the GeoWEPP model were compared with the observed monthly data collected fromthe sample watershed. The average Root Mean Square Errors (RMSE) between observedand predicted average annual sediment yield and runoff were 2.96 and 8.43, respectively.The index of agreement was 0.98 and 0.99 for sediment yield and runoff, respectively,which indicated that the model predictions provided good results.

Using ASTER Imagery in Land Use/cover Classification of Eastern Mediterranean Landscapes According to CORINE Land Cover Project.

The satellite imagery has been effectively utilized for classifying land covertypes and detecting land cover conditions. The Advanced Spaceborne Thermal Emissionand Reflection Radiometer (ASTER) sensor imagery has been widely used in classificationprocess of land cover. However, atmospheric corrections have to be made by preprocessingsatellite sensor imagery since the electromagnetic radiation signals received by the satellitesensors can be scattered and absorbed by the atmospheric gases and aerosols. In this study,an ASTER sensor imagery, which was converted into top-of-atmosphere reflectance(TOA), was used to classify the land use/cover types, according to COoRdination ofINformation on the Environment (CORINE) land cover nomenclature, for an arearepresenting the heterogonous characteristics of eastern Mediterranean regions inKahramanmaras, Turkey. The results indicated that using the surface reflectance data ofASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of83.2% and 0.79, respectively) and low-cost cover mapping as a part of inventory forCORINE Land Cover Project.