Turkey has a high potential for wildfires along its Mediterranean coast because of its dense forest cover and mild climate. An average of 250 wildfires occurs every year with more than 10,000 hectares destroyed due to natural and human-related causes. The study area is sensitive to fires caused by lightning, stubble burning, discarded cigarette butts, electric arcing from power lines, deliberate fire setting, and traffic accidents. However, 52% of causes could not be identified due to intense wildfires occurring at the same time and insufficient equipment and personnel. Since wildfires destroy forest cover, ecosystems, biodiversity, and habitats, they should be spatially evaluated by separating them according to their causes, considering environmental, climatic, topographic and forest structure variables that trigger wildfires. In this study, wildfires caused by lightning, the burning of agriculture stubble, discarded cigarette butts and power lines were investigated in the provinces of Aydın, Muğla and Antalya, where 22% of Turkey’s wildfires occurred. The MaxEnt method was used to determine the spatial distribution of wildfires to identify risk zones for each cause. Wildfires were used as the species distribution and the probability of their occurrence estimated. Additionally, since the causes of many wildfires are unknown, determining the causes is important for fire prediction and prevention. The highest wildfire occurrence risks were 9.7% for stubble burning, 30.2% for lightning, 4.5% for power lines and 16.9% by discarded cigarette butts. In total, 1,266 of the 1,714 unknown wildfire causes were identified by the analysis of the cause-based risk zones and these were updated by including cause-assigned unknown wildfire locations for verification. As a result, the Area under the ROC Curve (AUC) values were increased for susceptibility maps.

Crop selection for sustainable and effective agricultural land management has to take into accounts several issues such as chemical, physical, environmental, economic and social conditions. Especially after land consolidation projects, sustainable agricultural crop management should be investigated for each crop which are suitable for the project area to benefit from the land consolidation contributions such as irrigation, roads, modified parcel boundaries and surfaces. Thus, Geographical Information Systems (GIS) aided suitability analysis techniques are required to determine the suitable crops for the consolidated areas. In this study, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria decision techniques are integrated with GIS to determine most suitable crops for parcels. The suitability maps of wheat, clover, sugar beet and corn crops are generated for the projected area using 63 Land Mapping Units (LMU) with considering pH, lime, texture, salinity, organic matter, electrical conductivity, permeability, slope, aspect and the distance to settlements and roads within chemical, physical, topological and socio-economic criteria.

Beekeeping activities have a rapidly increasing importance due to their derived products and their contributions to human health, biodiversity, agriculture, and pollination. Moreover, beekeeping can play a major role in supporting rural development and bringing the benefits of sustainable developments and productivity. Thus, the decision on correct apiary locations via suitability analysis techniques seems essential to sustain and increase the yield and efficiency. However, this decision-making process requires a large number of parameters including the topography of the field surrounding environment and climate conditions. At this point, Multi Criteria Decision Analysis techniques can provide efficient solutions for decision making on suitable apiary locations. In this study, suitable apiary site selection analysis for beekeeping activities via Analytical Hierarchy Process (AHP) and The Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) methods was proposed for Konya city located in Central Anatolia as a pilot application. Aspect, elevation, slope, flora, water resources, roads, railroads, settlements, electricity lines, buildings, precipitation, and natural disaster area criteria were assessed to generate beekeeping suitability for apiaries. The restrictions and requirements of beekeeping activities were specified considering expert beekeeper decisions and recent studies for the study area. The AHP and PROMETHEE suitability maps were validated with existing 461 apiary locations to be able to determine the reliability and applicability.