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Öğe Bridging expert knowledge and machine intelligence: a hybrid spatial indicator framework for ecotourism suitability(Elsevier, 2026) Karadeniz, Enes; Er, Selman; Aydogdu, Mujde; Sunbul, FatihEcotourism suitability assessments increasingly rely on ecological indicators that capture spatial heterogeneity, ecosystem sensitivity, and biodiversity value. This study develops a hybrid indicator-based framework that combines fuzzy expert knowledge with ensemble machine learning to quantify ecotourism suitability in Malatya Province, T & uuml;rkiye. Fifteen ecological and socio-environmental predictors, including elevation, slope, climate variables, river proximity, biodiversity richness, endemic species distributions, and land-cover patterns, were incorporated into a GIS-based analytical environment. Expert-derived fuzzy weights were computed using the Fuzzy Logarithmic Methodology of Additive Weights (F-LMAW) to generate an Ecological Suitability Indicator (ESI). Complementarily, K-Means clustering was used to derive data-driven suitability classes, which were modeled using Random Forest and XGBoost with spatial-block cross-validation. XGBoost demonstrated superior classification performance (accuracy = 66.8%; kappa = 0.585). Across all models, biodiversity richness, endemic species presence, slope gradients, and river corridors consistently emerged as key ecological determinants. While the ESI produced conservative suitability zones, ensemble learning identified broader high-quality ecological landscapes, including the Levent Valley corridor, Nemrut foothills, and river-based habitats. The convergence between expert- and data-driven indicators demonstrates the reliability of hybrid ecological assessment. The proposed framework offers a transparent and transferable approach for constructing ecological suitability indicators in data-scarce, biodiversity-rich regions.Öğe Determination of drilling rate index based on mineralogical and textural properties of natural stones(Springer Heidelberg, 2023) Tumac, Deniz; Shaterpour-Mamaghani, Aydin; Hojjati, Shahabedin; Polat, Can; Er, Selman; Copur, Hanifi; Balci, CemalOver the last few decades, researchers have focused on developing models that aim to predict the drillability of natural stones based on their physicomechanical properties using regression analyses. This study aims to investigate the relationships between the drilling rate index (DRI) of natural stones and their mineralogical and textural properties. A database composed of 37 natural stone samples was used to develop new DRI estimation models using regression analysis and the application of an evolutionary algorithm. The results revealed that the DRI could be predicted based on the texture coefficient, Shore scleroscope hardness, and the product of the uniaxial compressive strength and Brazilian tensile strength based on an analysis of the combined dataset consisting of natural stones of metamorphic, sedimentary, and magmatic origins. The non-linear models developed by the evolutionary computation algorithm revealed that the texture coefficient, mean grain size, uniaxial compressive strength, and Brazilian tensile strength could be used to predict the DRI of metamorphic natural stones. This study differs from previous studies through its use of a novel evolutionary algorithm based on a combination of gene expression programming and particle swarm optimization, which was used to perform a non-linear regression analysis to identify models that could accurately predict DRI. To improve the generalizability of the proposed models, more types of natural stones, especially those with magmatic origins, should be included in the database analyzed in this study.Öğe Enhancing Geosıte Accessibility Assessment: A New Mcdm Model(Springer Heidelberg, 2024) Bilgic, Sevgi; Karadeniz, Enes; Er, SelmanGeosites are significant geological heritage areas that serve as field laboratories for researchers. They offer insights into geological processes that have occurred from the past to the present and hold high potential for geotourism. To preserve and make geosites sustainable, their accessibility is a prerequisite. For this purpose, a model consisting of various parameters was developed in accordance with the Multi-Criteria Decision Making (MCDM) method, identifying 183 geosite areas that have been determined by experts and are subjects of literature. As a result, four evaluation criteria were established, including accessibility, access to service/attractiveness areas, scientific importance, and geomorphological features. Taking these parameters into account, a collective evaluation map was obtained using GIS-based AHP, drawing upon literature and expert opinions. The study concluded that the most critical parameter for accessibility to geosites is accessibility itself, accounting for 50% of the importance. Other parameters have influenced the accessibility of geosites in the following order of importance: 25% land, 15% scientific importance, and 10% service/attractiveness. Consequently, the areas where accessibility to geosites in T & uuml;rkiye is most convenient are those with the highest road density. Road density, in turn, exhibits a pattern based on the characteristics of topography, population, and trade factors. Additionally, a parallel outcome emerged between areas that are more suitable in terms of these factors and the density of geosites. As a validation of the newly created model, the accessibility of T & uuml;rkiye's areas recognized by UNESCO was found to be very high, indicating that the model is a suitable and convenient method that can be applied to different areas.Öğe Evaluation of Potential Geotourism of Levent Valley and Its Surroundings Using GIS Route Analysis(Springer Heidelberg, 2022) Karadeniz, Enes; Er, Selman; Boyraz, Zeki; Coskun, SelahiThe Eastern Anatolia Region which has unique historical, geological and geomorphological features, is home to one of Turkey's culturally important regions. The Levent Valley and its surrounding geosites, as well as the biodiversity and cultural heritage in the Malatya Province have been investigated by systematic research including field survey, archival research, and GIS route analysis. According to geological features of the study area, the oldest unit in and around Levent Valley is the Permian-aged Khorasancal Formation. Furthermore, Mesozoic-aged Hocalikova ophiolite, Medik formation, Tohma formation, and Sarikiz formation are common in the region. Senozoic-aged Gedik formation, Dumanlar formation, Akyar formation, Karaca formation, Yamadag volcanics, and Sultansuyu formation are horizontally located on all these units. There are more than a hundred caves in the Levent valley that were formed in the Gedik, Dumanlar, Akyar, Karaca, Sultansuyu formations and Yamadag volcanics. According to the tourism facilities, the viewing terrace functions as a mini museum for visitors which includes the local cultural items and fossil diversity unearthed in the area. The area also gives an opportunity for adrenaline junkies offering activities such as zipline and bangy jumping. The Monumental Trees with a circumference of 3-6 m found during the field survey and the tulips unique to the region can also be seen in different locations of the valley. Due to the complexity and difficulty of the transport network in the Valley for geotourists, suitable routes were generated using GIS. The proposed GIS route analysis reveals a great geotourism potential in the region regarding geoheritage asset identification in a digital form considering economic benefits and time saving. By this way, almost all of the assets in the field can be discovered and visited by using this route map generated during the analysis. In conclusion, the fundamental investments and rehabilitations that should be conducted in the Valley and its surrounding were also discussed throughout the study.Öğe Malatya ilinde ICONA yöntemi ile CBS ve uzaktan algılama tabanlı erozyon risk analizi(2025) Bilgiç, Sevgi; Er, SelmanErozyon, toprağın su, rüzgâr ve insan faaliyetleriyle aşınması sürecidir ve tarım arazilerinin verimliliğini azaltarak çevresel ve ekonomik sorunlara yol açmaktadır. Bu çalışmada, Malatya ilinin erozyon riskini belirlemek için ICONA yöntemi kullanılmıştır. ICONA, arazinin eğimi, litolojisi, arazi kullanımı ve vejetasyon yoğunluğu gibi parametreleri dikkate alarak risk haritaları oluşturmada etkin bir yöntemdir. Çalışma kapsamında Coğrafi Bilgi Sistemleri (CBS) ve Uzaktan Algılama (UA) teknikleri kullanılarak, Malatya'nın %20.17’sinin düşük, %64.99’unun orta ve %14.19’unun çok yüksek erozyon riski taşıdığı belirlenmiştir. Malatya’nın erozyon riski genellikle eğimin fazla olduğu alanlarda çok yüksek olarak çıkmıştır. Erozyon riskinin çok yüksek olduğu yerler ise Malatya ilinin kuzeyi ve güneyinde eğimli alanlarda yayılış göstermiştir. Ayrıca, eğimin olmadığı ancak litolojik özelliklere bağlı olarak aşınabilirliğin yüksek alanlar ise orta derecede erozyon riskinin olduğu alanlar olarak yayılış göstermiştir. Elde edilen bulgulara göre, erozyon riski, dik eğimler ve yetersiz bitki örtüsü ile karakterize edilen kuzey bölgelerinde yüksek seviyelere ulaşmaktadır. Bulgular, toprak koruma ve sürdürülebilir arazi yönetimi için rehber niteliğindedir. Bu çalışma, bölgesel erozyon riskinin anlaşılmasına katkı sağlamakta ve benzer bölgelerde uygulanabilir bir yöntem sunmaktadır. Doğal kaynakların korunması için alınacak önlemler bilimsel temellere dayandırılmalıdır.Öğe A NEW APPROACH FOR THE PREDICTION OF BRITTLENESS INDEX BASED ON CHEMICAL PROPERTIES OF BASALTIC ROCKS(Acad Sci Czech Republic Inst Rock Structure & Mechanics, 2021) Bilen, Candan; Er, Selman; Tugrul, Atiye; Yilmaz, MuratRock brittleness is one of the most important issues in rock mechanics. There is not yet an available method for defining or measuring directly the rock brittleness. The aim of this study is to suggest a new chemical index parameter for the prediction of basaltic rocks' brittleness. In the order of that abovementioned purpose, a total of 23 basaltic rock samples were collected from different region of Turkey. Samples were initially tested to determine their chemical properties. Then, mechanical tests were carried out to define the brittleness indices (B1, B2, and B3) for each corresponding sample. Finally, relations between parameters obtained from test results and brittleness indices were examined with regression analysis. According to the results obtained, a new chemical parameter (CP) was proposed for predicting brittleness via major oxide element components of basaltic rocks. It was found out that, B1 and B2 are not reliable parameters for predicting the different properties, however; B3 and CP can be employed as good criteria for predicting the different properties of basaltic rocks (especially in terms of chemical and mechanical properties).
