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Öğe LAND USE/COVER CHANGE MODELLING IN A MEDITERRANEAN RURAL LANDSCAPE USING MULTI-LAYER PERCEPTRON AND MARKOV CHAIN (MLP-MC)(Corvinus Univ Budapest, 2018) Ersoy Mirici, Merve; Berberoglu, S.; Akın Tanrıöver, Anıl; Satir, O.Mediterranean land use and land cover (LULC) have a very dynamic structure as a result of continuous transformation process due to anthropogenic effects and environmental gradients. LULC dynamics are important indicator of environmental condition in temporal and spatial scales. The aim of this paper was to simulate the future LULC of a Mediterranean type watershed located at the Eastern Mediterranean Region of Turkey by incorporating multi-layer perceptron (MLP), artificial neural network (ANN) and Markov chain (MC) approaches. Landsat TM/OLI images in 1990, 2003 and 2014 over the study area were classified using hybrid classification approach. The Kappa statistics of the hybrid classification that combines K-means, decision tree and object based classification method for these three images were 0.81, 0.85 and 0.87 respectively. The LULC map of 2014 was simulated using LULC maps of 1990 and 2003 for calibration and validation. The simulation results were compared with the actual 2014 LULC map to assess the accuracy of the simulation, and the rate of overlap was found as 89%. LULC map of 2025 was estimated using LULC maps of 2003 and 2014. These results indicated that, the area of bareground will reduce 13.31% whereas the rate of forest and agricultural area will increase 8.70% and 6.51% respectively.Öğe THE SPATIOTEMPORAL LAND USE/COVER CHANGE of ADANA CITY(Copernicus Gesellschaft Mbh, 2013) Akın Tanrıöver, Anıl; Erdogan, M. A.; Berberoglu, S.The major driving factors for land use planning are largely limited to socio-economic inputs that do not completely represent the spatio-temporal patterns and ecological inputs have often been neglected. Integration of remote sensing and GIS techniques enabled successful applications in characterizing the spatiotemporal trends of land use/land cover (LULC) change. This study demonstrated an approach that combines remote sensing, landscape metrics, and LULC change analysis as a promising tool for understanding spatiotemporal patterns of Adana city. Calculation of spatial metrics was based on a categorical, patch-based representation of the landscape. Landscape metrics are conceptual framework for sustainable landscape and ecological planning. LULC change analysis was performed by considering the metric calculation. Post-classification technique was used for the metric based change detection and two different remotely sensed data set recorded in 1967 (CORONA) and 2007 (ALOS AVNIR) were used for the analysis. Additionally, a LULC projection for the year 2023 was also generated and integrated to the change analysis. SLEUTH model was utilised as a urban growth model for the future developments of study area in the scope of Cellular Automata (CA). SLEUTH model contains the main elements that characterize the core characteristics of CA: it works in a grid space of homogeneous cells, with a neighburhood of eight cells, two cell states and five transition rules that act in sequential time steps. Most useful and relevant metrics for landscape including: percentage of landscape, patch density, edge density, largest patch index, Euclidian mean nearest neighbor distance, area weighted mean patch fractal dimension and contagion were calculated for the 1967, 2007 and 2023 LULC maps and temporal changes were determined for the study area. Most considerable change was observed on the agricultural areas. Urban sprawl is the major driving factor of the LULC change.