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    Evaluating the efficiency of future crop pattern modelling using the CLUE-S approach in an agricultural plain
    (Elsevier, 2022) Akin, Anil; Erdogan, Nurdan; Berberoglu, Sueha; cilek, Ahmet; Erdogan, Akif; Donmez, Cenk; Satir, Onur
    Land Use Land Cover (LULC) change detection is an essential source of information for understanding the magnitude of environmental change to implement future development strategies. Sophisticated techniques (i.e. modelling) have been applied in the last decades worldwide for accurate LULC classification and future pro-jections. However, using these techniques in heterogeneous agricultural regions to extract crop-related infor-mation is still challenging. This study aimed to evaluate the efficiency and applicability of crop pattern prediction for the year 2050 with the CLUE-S model in an agricultural plain. The model was calibrated and validated based on the LULC changes to model future changes of the crop pattern by 2050. Twelve driving factors were utilised to quantify the relationship of LULC classes. The statistical relationship among the factors was examined with a Binomial Logistic Regression approach. Additionally, the magnitude of change in agricultural crop patterns between 2015 and 2050 was calculated according to local/regional policies and incorporated to the model as scenario layer. Future model results indicated that the cotton would increase by % 45 whereas maize would decrease by % 10 compared to 2015. The model performance was evaluated using the ground truth from the field observations considering the agricultural policies through the ROC (Receiver Operating Characteristic) indicators. The mean ROC value for the agricultural crop patterns was calculated as 0.71, while ROC values for other LULC classes were over 0.90. Overall a 0.79 ROC value was achieved as the model accuracy.
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    Monitoring the Mediterranean type forests and land-use/cover changes using appropriate landscape metrics and hybrid classification approach in Eastern Mediterranean of Turkey
    (Springer, 2020) Ersoy Mirici, Merve; Satir, Onur; Berberoglu, Suha
    Monitoring the Land-Use/Cover Change (LUCC) is an important tool to evaluate the reasons for environmental changes in ecologically sensitive landscapes like natural forestlands. Rural landscapes are of vital importance for ecosystem productivity, ecosystem services, and biological diversity to continue sustainably. The purpose of this paper was to detect LUCC and its effects on landscape ecology through landscape metrics in the Eastern Mediterranean of Turkey. In this study, a hybrid classification approach was used to classify the Land-Use/Cover (LUC) and detailed forest tree diversity considering topography, plant density, and satellite waveband reflectance values. To this extent, detailed LUC classification, LUCC analyses from 2003 to 2014, habitat quality differences by generating landscape metrics in two levels are called landscape and class-level metrics were carried out in the study area. Habitat quality evaluation on forest formation scale using a hybrid classification approach provided a great advantage and made it possible to examine the landscape metrics of the plant types within the scope of temporal change. The study method was implemented in seven stages including: (1) classification of forest-no forestlands with the K-Means algorithm, (2) creating a data set of reflected signals over stand types, (3) determining the rules and thresholds of decision tree algorithm, (4) object-based classification of agricultural, rocky, and settlement areas, (5) obtaining the land-cover maps for 2003 and 2014, (6) post-classification change detection analyses, and (7) assessing the habitat quality via landscape metrics. The results indicated that forest areas increased by 10.73%, while bare soil decreased by 17.70% in 12 years. The habitat quality increased in the same period in the study area according to the results of class area, mean shape index, mean patch size index, edge density, patch number, and Shannon's diversity index values.
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    Simulating the impact of natural disasters on urban development in a sample of earthquake
    (Springer, 2023) Satir, Onur; Kemec, Serkan; Yeler, Okan; Akin, Anil; Bostan, Pinar; Mirici, Merve Ersoy
    Natural disasters have been increased in areas, where people live densely, day by day. Istanbul 1999, Van 2011, and Izmir 2020 earthquakes were just some of the tragic events in the near past in Turkiye. The aim of this study was to define Van 2011 earthquakes effects as a sample on urban development by using land use/land cover projecting techniques. In this case, Van urban development (in urban macroform scale) was simulated without Van 2011 earthquakes based on existing urban development using the Cellular Automata Markov Chain (CA-MARKOV) approach for the year 2018. Effects of the earthquake were determined on urban development by comparing modeling results with observed 2018 built up areas. So that significant physical and social driving factors were evaluated including road distance, slope, hillshade, ground stability, and land use ability, and weighting values on urban development were calculated under the influence of the natural disaster. Van urban built up areas were mapped using high-spatial resolution remote sensing instruments such as SPOT, ASTER, RapidEye, and Gokturk 2 satellite dataset for 1988-2002-2011, and 2018 images applying an object-based classification approach (OBC). First of all, the model was validated using 1988, 2002, and 2011 urban development maps. The Kappa accuracy was found to be 0.85, respectively, for the model. Defined urbanization drivers were applied to the 2002-2011 time period to simulate 2018 urban areas without any earthquake. The results indicated that urban areas were affected by earthquakes. If there was no earthquake, urban development to the periphery would be 30% less. Additionally, 10% more built up areas would be constructed on ground sensitive areas, and only 2% of the new constructions would be established on suitable lands. Today this ratio is around 8%. As a result, urban development has been a trend to move from flat land to slight slopes and has been moved away from roads and settlements. It was determined that the spread into the city was accelerated as well as spread toward the periphery due to the earthquake.