Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ4Sustainable land management under uncertainty: A hybrid Bayesian BWM and RPM framework for spatial prioritization
Konurhan, Zekeriya
Sustainable land management is a complex problem due to environmental constraints and decision-maker uncertainty. This study presents an integrated solution combining Geographic Information Systems (GIS), the Bayesian Best-Worst Method (Bayesian BWM), and the Ratio Product Model (RPM) to improve the accuracy of spatial prioritization in land-use decisions. The integration of the Bayesian BWM and RPM statistically minimizes the cognitive uncertainty in expert opinions whilst enabling the most suitable areas to be ranked with precision within their own categories, without any normalization constraints. The proposed model was developed for three main categories —residential, industrial, and agricultural— in the province of Balıkesir. The analysis results revealed that the ‘ease of access to services’ (0.5660) criterion was the most decisive factor for residential suitability, whilst ‘distance to power transmission lines’ (0.1322) and ‘average rainfall’ (0.1315) were the most decisive factors for industry and agriculture, respectively. The suitability maps show that the Bandırma-Susurluk corridor is strategically prioritized for industry, whilst the Manyas-Gönen basin is prioritized for agricultural production. RPM scores (0.2750 for settlement, 0.6036 for industry, and 0.3868 for agriculture) quantify implementation priorities, providing a reliable decision-support tool for managing uncertainty in spatial planning.
- MakaleYalnız künye2026Scopus SJRQ1Hydrogeochemical controls on chromium speciation and potential human health risks in surface waters of an ultramafic mining watershed
Kutlu, Banu; Baydar, Tarık; Yıldırım, Vesile; Konurhan, Zekeriya
Accurate assessment of chromium contamination in mining-influenced watersheds requires distinguishing between the environmentally contrasting Cr(III) and Cr(VI) species, yet environmental monitoring and risk assessments still rely predominantly on total chromium concentrations. This study evaluated whether chromium speciation provides additional information beyond operational total chromium for assessing chromium occurrence and potential human health risks in an ultramafic, mining-influenced watershed. Surface-water samples were collected from 28 sampling stations across the Pülümür and Ovacık regions of the Eastern Anatolia Basin (Türkiye) between March 2025 and February 2026. Chromium speciation was determined using species-specific UV–Visible spectrophotometric methods and integrated with hydrochemical characterization, multivariate statistical analyses, mineralogical investigations (XRD, SEM–EDS, and FTIR), and deterministic and empirical-bootstrap human health risk assessments. Operational total chromium, defined as the sum of separately measured Cr(III) and Cr(VI), ranged from below the detection limit to 578.13 µg L−1. For contextual screening, this calculated value exceeded World Health Organization (WHO) drinking-water guideline for total chromium at 14 stations; however, it was not an independently measured total-Cr concentration. The highest Cr(VI) concentration occurred at a localized hotspot, whereas Cr(III) predominated throughout most of the watershed. Nevertheless, Cr(VI)-based screening thresholds were exceeded at multiple stations under the assumed untreated drinking-water ingestion scenario, indicating that operational total chromium alone did not consistently identify the spatial distribution of Cr(VI)-related potential risk. Screening-level hazard quotient (HQ) estimates were higher for children than for adults; however, direct untreated consumption of the sampled surface waters was not verified. Mining-influenced stations generally exhibited higher chromium concentrations, although the relative contributions of geogenic weathering and mining-related mobilization could not be quantitatively apportioned. Overall, chromium speciation provided additional environmentally and toxicologically relevant information beyond operational total chromium for evaluating chromium mobility and screening-level potential human health risks in this ultramafic watershed.
- MakaleAçık Erişim2025Suçun Coğrafi Dağılımını Afet-Suç İlişkisi Bağlamında İncelemek: 6 Şubat 2023 Depremlerinin Mala Karşı İşlenen Suçlara Etkisi
Avaner, Tekin; Konurhan, Zekeriya; Abdulvahitoğlu, Adnan; Başaran, Erkin; Yayla, Mustafa
Doğal afetlerden hemen sonraki süreçte yaşanan kargaşa ve kamu otoritesinin azalmasına bağlı olarak suç oranlarının artış gösterdiği bilinmektedir. Depremler gerek etki alanlarının büyüklüğü gerek de çok sayıda insanı etkilemeleriyle bu afetler arasında özel bir yere sahip olup, kriminal yansımaları özellikle uluslararası literatürden anlaşılabildiği üzere cana ve mala karşı suçlar temelinde çok farklı suç şekilleri olarak karşımıza çıkabilmektedir. Bu çalışmada 6 Şubat 2023’te 7.7 ve 7.6’lık iki büyük dalga halinde gerçeklemiş ve asrın felaketi olarak nitelenen depremlerden hemen sonraki 1 ay içerisinde meydana gelen mala karşı suç olayları bir önceki yılın aynı dönemine göre karşılaştırmalı olarak mekansal ve zamansal bazda incelenmiştir. İçişleri Bakanlığın’dan temin edilen suç verileri Çok Kriterli Karar Verme (ÇKKV) ve Hotspot yöntemleri kullanılarak analiz edilmiş, daha sonra bu analizlerden yola çıkılarak veriler kriminoloji çalışmalarında en yaygın kullanılan teorilerden olan Rutin Faaliyetler Teorisi ve Kırık Pencereler Teorisi temelinde yorumlanmıştır. Suç coğrafyası çalışmalarında yaygın olarak kullanılan CBS’den Hotspot yöntemiyle bu çalışmada da istifade edilmiştir. Ancak ÇKKV ve teorik yorumlamayla birlikte üç farklı yöntemin kullanıldığı böyle bir sentez suç coğrafyası araştırmalarında mevcut değildir ki, araştırmanın özgün değeri burada ortaya çıkmaktadır.
- MakaleAçık Erişim2025Shaping the Future of Datça Peninsula: Exploring Suitable Settlement Areas and Land-Use Scenarios
Konurhan, Zekeriya; Ceylan, Mehmet Akif
This study examines land use/land cover (LULC) scenarios and identifies areas suitable for settlement on the Datça Peninsula. Datça is one of the four peninsulas in the Aegean Sea and is administratively part of the Muğla province of Türkiye. Forests prevail across the landscape, especially around the stretch shaped by the Datça–Marmaris highway, while agriculture is concentrated on the Datça Plain, Cumali, and Yaka. This study aims to determine land use scenarios and identify suitable areas for future development and settlement. The GeoSOS-FLUS software package, developed based on Markov Chains and Artificial Neural Networks for land use simulations, was used. Aware of the limitations of simulations that do not consider land suitability, a suitability analysis was performed using the Best-Worst Method (BWM), one of the Multi-Criteria Decision Making approaches. Sixteen criteria within four groups—topography, socioeconomics, location, and environment—were evaluated. The suitability analysis results were compared with simulated land use scenarios, and the most suitable areas for future settlements in the Datça Peninsula were identified. This integrated approach provides important information for the sustainable development of the region and the shaping of land use planning.
AtıfOpenAlex1TR Dizin1
İncele - Kitap BölümüYalnız künye2025Bayesian Best–Worst Method Application for Assessing the Potential Effecting Areas of Climate Change: A Case Study in Turkey
Konurhan, Zekeriya; Yücesan, Melih; Gul, Muhammet
‘Climate Change’ is a term used to refer to global changes in the Earth's average temperature and the consequences of changes in temperature. More clearly, it demonstrates changes in temperature and weather patterns over time. The emergence of this situation directly or indirectly affects irreparable damages and major/minor disasters in many areas. Determining the answer to the question of which of these areas has an impact at what level of importance will provide guidance on which one should be prioritized in carrying out an effective treatment. Therefore, in this study, this problem is ad-dressed as a multi-criteria decision problem using Bayesian Best–Worst Method. The potential impacts have been categorized under 8 main areas and weighted via participating of 8 competent experts (geography, emergency disaster management, geomorphologist, climate scientist etc.) in the field of climate change. The study results determined that B (Ecosystems and Water Resources) has the most critical impact area, with 0.200. The least essential domain is G4 (Adaptation and Resilience Strategies in the Tourism Industry), which weighs 0.012. The results showed that they provide important clues regarding which impacts should be addressed first.
- MakaleAçık Erişim2025Scopus SJRQ1Investigating forest fire causes through an integrated Bayesian network and geographic information system approach
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet
Forests are among the most critical natural resources worldwide and are essential for a sustainable ecosystem. In recent years, climate change and human activities have increased their impact on forests, and forest fires-especially in summer- have caused significant forest losses globally. This paper integrates Bayesian Network (BN) and Geographic Information Systems (GIS) to pinpoint the possible causes of forest fires and analyze their complex interactions. The study used data from 1465 fires between 2017 and 2022 in Muğla province in southwestern Türkiye. Within the scope of the study, 11 variables were chosen, such as elevation, slope, aspect, wind speed, population density, and road network, to build a BN model that combines physical and human geographical features. These variables overlapped using the pairwise intersect tool from ArcGIS Pro during the BN model setup, and probability values were calculated. The overall probability of fire in the BN model was determined to be 0.81, with probabilities ranging from 0.81 to 0.56 in low-altitude, moderately sloped, and south-facing areas. Scenario analyses examined fire risk under different conditions, highlighting the most influential variables for fire prevention efforts. The study identified fire-prone areas as spatial data, revealing that densely forested coastal and certain inland regions are at higher risk, whereas bare high-altitude areas with steep slopes pose lower risk. The BN model can be further enhanced by incorporating additional variables, making it a valuable tool for future fire risk assessment and mitigation strategies research.
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İncele - BildiriYalnız künye2024Scopus SJRQ4Constructing the Criteria in Determining the Product Groups for Agriculture 4.0 Applications
Erdoğan, Melike; Konurhan, Zekeriya; Yücesan, Melih; Gül, Muhammet; Mirzazadeh, A.; Molamohamadi, Z.; Erdebilli, B.; Babaee Tirkolaee, E.; Weber, G.-W.
With Agriculture 4.0, the use of techniques such as sensors, robots, artificial intelligence, and machine learning in agriculture has started. It is aimed to increase productivity in agriculture by reducing food loss and waste through Agriculture 4.0. It is a critical decision to determine which products should be handled first for Turkey to benefit from the advantages of Agriculture 4.0 as soon as possible compared to developed countries in the field of agriculture. At this point, the problem of which factors should be addressed in the determination of product & product groups arises. To handle this, in this study, a multi-criteria analysis has been applied to prioritize the factors that should be considered in the determination of the critical fruit and vegetable group for export, which should be considered as a priority within the scope of Agriculture 4.0. In this context, a multi-criteria analysis has been carried out by adopting the Bayesian Best Worst Method BWM (B-BWM), which is an improved version of a pairwise comparison-based BWM method and applied to group decisions. As a result of the analysis, the most important and least important criteria to be used in determining which products or product groups are more suitable for Agriculture 4.0 applications in Turkey and which should be invested in priority have been determined.
- MakaleAçık Erişim2023Rüzgâr Enerji Santrali (RES) Yer Seçimi için BWM-CBS Tabanlı Bir Yaklaşım: Tunceli Örneği
Konurhan, Zekeriya; Başaran, Erkin
Günümüz dünyasında fosil yakıtların yerine alternatif bir enerji kaynak arayışı oldukça popüler bir yaklaşımdır. Güneş panelleri ve rüzgâr enerjisi santralleri gibi yenilenebilir enerji kaynakları fosil yakıtların alternatifleri arasındadır. Rüzgâr enerjisi santralleri hem denizde hem de karada olmak üzere dünyanın birçok bölgesinde aktif olarak kullanılmaktadır. Türkiye’de de RES’ler özellikle 2000’lerin başından itibaren kullanılmaya başlamıştır. Türkiye’deki RES’ler daha çok Ege ve Marmara Bölgesinde yer almaktadır. Çalışma alanı olan Tunceli’de ise herhangi bir RES bulunmamaktadır. Bu çalışmanın temel amacı Tunceli için uygun RES alanlarını önermektir. Bu kapsamda Best-Worst yöntemi (BWM) CBS’ye entegre edilerek kullanılmıştır. BWM yöntemi ikili karşılaştırmaya dayanan Çok Kriterli Karar Verme (ÇKKV) yöntemidir. Çalışmada BWM modeli kullanılarak “topografya”, “sosyo-ekonomik”, “teknik” ve “lokasyon” olmak üzere dört ana kriter altında 16 kriter belirlenmiştir. Her bir kriter farklı disiplinlerden uzmanlar tarafından anket olarak değerlendirilmiş ve uygun yer seçimi için kullanılmıştır. 16 kriter için ayrı ayrı haritalar oluşturulmuş, kriterlerin açıklamaları yapılmış ve bu haritalar sonuç haritasında kullanılmıştır. BWM modeli kullanılarak tespit edilen kriter ağırlıkları CBS’ye entegre edilerek Tunceli için uygun RES kurulum alanları belirlenmiştir. Buna göre, Tunceli’nin güneydoğusunda yer alan Pertek ve Mazgirt çevresi ile Pülümür’ün kuzeyi ve Çemişgezek’in çevresinde fiziki coğrafya açısından uygun şartları sağlayan bazı alanlar RES kurulumuna elverişlidir.
AtıfOpenAlex5TR Dizin3İncele - MakaleAçık Erişim2023Tunceli ilinde iç göç hareketleri
Konurhan, Zekeriya; Ceylan, Mehmet Akif
İç göç, bireyler, topluluklar ve bir bütün olarak ülkeler için geniş kapsamlı etkileri olan, ekonomik, sosyal ve çevresel faktörlerin bir kombinasyonundan etkilenen karmaşık ve çok yönlü bir süreçtir. İç göç hareketleri, bir ülke sınırları içerisinde çeşitli nedenlerden dolayı farklı yönlere doğru gerçekleşir. Türkiye’de de özellikle kırsal alanlardan daha gelişmiş şehirlere doğru bir iç göç hareketi söz konusu olmuştur. Ülkede gerçekleşen göç hareketleri özellikle 1950’li yıllardan itibaren hızlanmış ve 1980-1990’larda üst düzeye çıkmıştır. Bu süreçte özellikle 1980’lerden sonra Doğu ve Güneydoğu Anadolu hem isteğe bağlı hem de zorunlu nedenlerle göç edenlerin en fazla olduğu bölgeler durumuna gelmiştir. Tunceli’de en önemli göç hareketlerinden biri Cumhuriyetin ilk yıllarında Dersim isyanı sonrasında gerçekleşen zorunlu göçlerdir. Yine Tunceli’de 1985-2000 ile 2015-2017 yıllarında yaşanan terör olayları sonrasında göçler meydana gelmiştir. Bunların dışında Tunceli’de daha çok ekonomik sebeplerle isteğe bağlı göçler de yaşanmıştır. Bunun en büyük göstergesi İstanbul şehrinde ikamet eden (yaklaşık 85bin-kişi) ve Tunceli ili nüfusundan fazla olan Tuncelilerin varlığıdır. Çalışmanın temel istatistik verileri, Türkiye İstatistik Kurumu’ndan temin edilmiş olup bazı arşiv belgeleri, literatür ve bazı gözlemlerden de yararlanılmıştır. Çalışma sonuçlarına göre Tunceli ili sürekli göç veren bir ildir. Nitekim Tunceli ili belirli dönemlerde artış ve azalış yaşansa da 2021 yılına kadar genellikle dışarıya göç vermiştir.
AtıfOpenAlex1İncele - MakaleAçık Erişim2023An integrated Bayesian Best-Worst Method and GIS-based approach for offshore wind power plant site selection: A case study in North Aegean and Marmara Sea (Türkiye)
Gul, Muhammet; Yucesan, Melih; Konurhan, Zekeriya
In today’s world, renewable energy sources are in great demand due to the negative ef- fects of fossil fuels on the environment. Wind power plants are an important renewable energy source alternative to fossil fuel consumption. Offshore wind farms established in coastal areas and seas are used effectively in many parts of the world. The wind power plants, especially in the Northwest region of Turkey and the Aegean coasts, constitute an important potential. This study selects suitable sites for offshore wind farms in the Marmara Sea and North Aegean Coasts of Turkey by integrating the Bayesian Best-Worst method (BWM) and GIS. Bayesian BWM improves the traditional BWM integrating the preferences of multiple experts. In the study, 17 sub-criteria were determined under four main criteria of “technical”, “socio-economic”, “environment,” and “location”. Ex- perts’ judgments through the filled enabled the criterion weights to be obtained. The criteria weights found using the Bayesian-BWM model were integrated into the GIS, and suitable locations for the offshore wind farm were determined. Accordingly, the study area off the coasts of Aliağa, Bozcaada, and Gökçeada on the North Aegean coast, and the part south of the Marmara Sea and the area around Kapıdağ Peninsula are sugges- ted as suitable areas for wind power plants.
AtıfOpenAlex7İncele - Kitap BölümüYalnız künye2023A GIS-Based BWM Approach for the Location Selection of Solar Power Plant in Tunceli Province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet; Rezaei, J; Brunelli, M; Mohammadi, M
The world has recently tended to turn to renewable energy sources due to the serious negative impact of fossil fuels on the environment. One of the top priorities for solar energy is the selection of the most suitable location of the solar power plant to be established. In this study, the most suitable solar power plant location selection for Tunceli, a province located in the eastern part of Turkey, is studied with an approach based on Geographic Information System (GIS) and the best-worst method (BWM). A weighting was performed using the BWM model for 16 sub-criteria under four the main criteria of “climatic conditions, geographical conditions, land conditions, and location (distance to crucial points)”. Afterward, maps were created for these criteria, and a 6-point scale in the legends of each map for each sub-criteria was applied. Finally, the most suitable locations were determined with GIS-based calculations.
AtıfScopus6WoS5OpenAlex7İncele - Kitap BölümüYalnız künye2023Avalanche Risk Analysis by a Combined Geographic Information System and Bayesian Best-Worst Method
Konurhan, Zekeriya; Yücesan, Melih; Gul, Muhammet
The formation of avalanches is related to the land structure, climatic conditions, and snow cover. It is usually seen in mountainous and sloping terrains without vegetation. In Turkey, especially in Eastern Anatolia and the Black Sea Region, which have high elevations, avalanche events are observed. This study aims to perform a risk analysis by integrating the Bayesian Best-Worst method (BWM) and Geographic Information System (GIS) for Tunceli province, which is the scene of significant avalanche events. Bayesian BWM is a method that improves the original BWM by effectively integrating the preferences of multiple experts. In the study, 16 sub-criteria, such as elevation, slope, and the number of snowy days, were determined, and experts evaluated these criteria through questionnaires created. The weight of each criterion were calculated using the Bayesian-BWM. By integrating the criteria weights from the Bayesian-BWM model into GIS, the risky places for natural avalanche disasters in Tunceli province were determined, according to which the risk in the northern part of the study area is identified as high.
AtıfScopus5İncele - MakaleAçık Erişim2023Scopus SJRQ1Integrating stratified best–worst method and GIS for landslide susceptibility assessment: a case study in Erzurum province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet
Landslides are among the most destructive geological disasters that seriously damage human life and infrastructures. Landslides mainly occur in mountainous regions around the world. One of the key processes to reduce these damages is to uncover landslide-exposed areas through different data-driven methods such as Geographical Information System (GIS) and multi-criteria decision-making (MCDM). In the literature, there are many studies developed with these fundamental tools. In this study, unlike the literature, a new landslide susceptibility assessment model is proposed by integrating GIS with the stratified best–worst method (S-BWM). This model has four main dimensions and 16 sub-dimensions under topography, environment-land, location, and hydrological factors, weighted with the S-BWM. A network was created considering the different states that may arise in the importance weights of these dimensions in the future. The transition probabilities of these states were predicted and injected into the classical BWM. Then, maps were created for these dimensions and classifications for each sub-dimension according to the map characteristics. Finally, the most susceptive landslide locations were determined with GIS-based calculations. To demonstrate the model’s applicability, a case study was conducted for the Erzurum region, one of Turkey’s landslide-prone regions. In addition, besides the landslide map, an analysis and discussion about the spatial distribution of susceptibility classes was presented, contributing to the study’s robustness. In the results of landslide susceptibility analysis, landslides are higher in the range of about 1600–2500 m. Approximately 42% (35.59 sq. km) of the study area has high landslide susceptibility, while 58% (64.41 sq. km) has medium and low landslide susceptibility.
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