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https://hdl.handle.net/20.500.12451/283

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Investigation of landslide areas in Tokat-Almus road between Baklmll-Almus by the PS-InSAR method (Türkiye)
(Walter de Gruyter GmbH, 2025) Oktar, Osman
Landslides and ground deformations pose significant risks to infrastructure safety, leading to road damage, economic losses, and potential hazards for transportation networks. There are visible deformations in the section of the Tokat-Almus road between the village of Baklmll and the town of Almus. In this part of the road, the road has narrowed due to landslides, and subsidence has occurred in some sections. To analyze and quantify these deformations, the persistent scatterer interferometric synthetic aperture radar (PS-InSAR) method was applied. Both ascending and descending synthetic aperture radar (SAR) images covering the same period (30 images between February 2022 and February 2023) were analyzed. Thus, the annual movements in the line of sight (LOS) were obtained. Considering the annual velocities in the LOS direction and given the PS-InSAR analysis results, the highest annual subsidence value was found to be 22.9 mm and the highest annual uplift value to be 17.2 mm. Standard deviation values for these velocities were determined to range between 0.7 and 10.5 mm. Decomposition was carried out to examine LOS results in detail. Examining the annual velocities in the vertical direction, the highest annual subsidence value was found to be 37 mm and the highest annual uplift value to be 23 mm. Considering the annual velocities in the horizontal direction, the annual velocity rate was found to range between -19 and 24 mm. The surface movements determined in this study provide significant contributions to the planning of engineering measures, especially in landslide risk areas such as the Tokat-Almus road. The results of the study provide valuable inferences in terms of road safety and disaster management by demonstrating the effectiveness of the PS-InSAR method in long-term deformation monitoring processes. The obtained data can be guiding not only for the improvement of highway routes and taking structural measures in landslide risk areas, but also for the development of disaster management strategies.
Determination of Anatolian Plate’s tectonic block boundaries with clustering analysis using GNSS sites velocities
(Taylor and Francis Ltd., 2025) Şafak Yaşar, Şeyma; Tiryakioğlu, İbrahim; Aktuğ, Bahadır; Erdoğan, Hediye; Özkaymak, Çağlar
The Anatolian Plate is an important tectonic structure containing different types of faults. In this study, block boundary studies were performed by clustering analysis using horizontal velocity data for 841 GNSS sites located on the Anatolian Plate. Four algorithms were used to determine the most appropriate cluster number. Cluster analysis was performed with K-means analysis. Different to other studies, the analysis included the location parameter for the GNSS sites in the cluster analysis. Generally block boundaries followed active fault zones and surface ruptures forming as a result of earthquakes. In this block study, 3 previously undocumented block boundaries were defined based on GNSS data. When all parameters are assessed in cluster analysis, the most appropriate cluster number was determined to be 9.
Creation of Wind Speed Maps and Determination of Wind Energy Potential with Geographic Information Systems: The Case of Kırklareli Province, Türkiye
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Karataş, Kamil; Karataş, Kamil
The intensive use of fossil fuels for energy production harms the environment. The adoption of sustainable energy systems can reduce the damage. Wind energy is one of the most widely used renewable sources. The most important problem in establishing new wind power plants (WPPs) is estimating the wind energy potential (WEP) in potential installation locations where there are no measured data. Many geographic information system (GIS)-based studies have been conducted on this subject. In this study, based on the technical specifications of a wind turbine selected for the Kırklareli Province of Türkiye, wind speed maps at 125 m height were created using many station points with known locations and wind speeds and the WEP of Kırklareli was calculated. In addition, the WEP map of Kırklareli was created by first determining the areas where WPPs cannot be installed and creating the wind speed map. After removing exclusion areas where wind turbines cannot be installed, the wind speeds at 125 m ranged between 3.12 m/s and 8.51 m/s. The wind speed was found to be higher in the south of the province, and the total WEP in areas with wind speeds higher than 6 m/sec was 6628.21 MW.
Land-Use Land-Cover Dynamics and Future Projections Using GEE, ML, and QGIS-MOLUSCE: A Case Study in Manisa
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Gündüz, Halil İbrahim
Urban expansion reshapes spatial patterns over time, leading to complex challenges such as environmental degradation, resource scarcity, and socio-economic inequality. It is critical to anticipate these transformations in order to devise proactive urban policies and implement sustainable planning practices that minimize negative impacts on ecosystems and human livelihoods. This study investigates LULC changes in the rapidly urbanizing Manisa metropolitan area of Turkey using Sentinel-2 satellite imagery and advanced machine learning algorithms. High-accuracy LULC maps were generated for 2018, 2021, and 2024 using Random Forest, Support Vector Machine, k-Nearest Neighbors, and Classification and Regression Trees algorithms. Among these, the Random Forest algorithm demonstrated superior accuracy and consistency in distinguishing complex land-cover classes. Future LULC scenarios for 2027 and 2030 were simulated using the Cellular Automata–Artificial Neural Network model and the QGIS MOLUSCE plugin. The results indicate significant urban growth, with built-up areas projected to increase by 23.67% between 2024 and 2030, accompanied by declines in natural resources such as bare land and water bodies. This study highlights the implications of urban expansion regarding ecological balance and demonstrates the importance of integrating machine learning and simulation models to forecast land use changes, enabling sustainable urban planning and resource management. Overall, effective policies must be developed to manage the negative environmental impacts of urbanization and conduct land use planning in a balanced manner.
Seismic Hazard Evaluation and Strain Dynamics in the Simav Fault Zone: A Comprehensive Analysis of Earthquake Recurrence and Energy Release Patterns
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Solak, Halil İbrahim; Gezgin, Cemil
This study aims to determine the earthquake hazard of the Simav Fault Zone (SFZ), one of the key tectonic features of Western Anatolia—a region that serves as a natural laboratory for geoscientists due to its complex tectonic structure and swarm-type seismic activity generated by multiple active graben systems. For this purpose, the a (6.33) and b (0.92) seismic parameters based on the Gutenberg–Richter magnitude–frequency relationship were first calculated using M ≥ 3 earthquakes that occurred between 1900 and 2024 along the SFZ. Moreover, the recurrence periods of events with magnitudes between M = 5 and M = 7.1 were determined (ranging 32 and 982 years), and the seismic hazard levels in the region were identified. The spatial density of the earthquakes and the regional distribution of the energy they released were analyzed, and the variations in seismic activity along the fault and energy flow in the region were investigated. For the evaluation of past earthquakes with the current strain field of the region, using geodetic velocity data, the strain rates of each segment of SFZ were calculated (reaching 90 ns/year) and findings related to stress accumulation processes were obtained. The findings, along with previous events, indicate that the region is susceptible to seismic hazards and that even moderate earthquakes pose a significant threat to both infrastructure and the population. This study, which seeks to enhance the understanding of seismic hazards and regional strain accumulation in the SFZ, is expected to serve as a valuable tool in seismic hazard assessments and local disaster management strategies, and to provide a critical reference for decision-makers in effective earthquake risk management.
Explainable Sinkhole Susceptibility Mapping Using Machine-Learning-Based SHAP: Quantifying and Comparing the Effects of Contributing Factors in Konya, Türkiye
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Bilgilioğlu, Süleyman Sefa; Gezgin, Cemil; İban, Muzaffer Can; Bilgilioğlu, Hacer; Gündüz, Halil İbrahim; Arslan, Şükrü
inkholes, naturally occurring formations in karst regions, represent a significant environmental hazard, threatening infrastructure, agricultural lands, and human safety. In recent years, machine learning (ML) techniques have been extensively employed for sinkhole susceptibility mapping (SSM). However, the lack of explainability inherent in these methods remains a critical issue for decision-makers. In this study, sinkhole susceptibility in the Konya Closed Basin was mapped using an interpretable machine learning model based on SHapley Additive exPlanations (SHAP). The Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) algorithms were employed, and the interpretability of the model results was enhanced through SHAP analysis. Among the compared models, the RF model demonstrated the highest performance, achieving an accuracy of 95.5% and an AUC score of 98.8%, and was consequently selected for the development of the final susceptibility map. SHAP analyses revealed that factors such as proximity to fault lines, mean annual precipitation, and bicarbonate concentration difference are the most significant variables influencing sinkhole formation. Additionally, specific threshold values were quantified, and the critical effects of these contributing factors were analyzed in detail. This study underscores the importance of employing eXplainable Artificial Intelligence (XAI) techniques in natural hazard modeling, using SSM as an example, thereby providing decision-makers with a more reliable and comparable risk assessment.
Comparison and accuracy assessment of unmanned aerial vehicle and terrestrial measurement in base map production
(Elsevier B.V., 2025) Yıldız, Veysel; Yaman, Aydan
In the present era, unmanned aerial vehicles (UAVs) have become a prevalent tool for data and map production in the domain of remote sensing and photogrammetry, driven by advancements in technology. The production of base maps has become more straightforward, precise, economical, and time-efficient in recent years, largely due to the advent of UAVs and the subsequent development of new techniques. The base maps of the area were produced using two methods: Terrestrial measurement and UAV data. The squared mean errors were calculated and found to be my = ±1.49 cm, mx= ±1.58 cm and mz = ±2.52 cm for ground control points, my = ±1.54 cm, mx= ±1.65 cm and mz = ±2.55 cm for check points and my = ±2.41 cm, mx= ±2.66 cm and mz= ±3.47 cm for detail points. The results were found to fall within the specified limit values. It was therefore concluded that UAVs provide the anticipated accuracy for the production of base maps, which are required to be continually updated and form the basis for a range of projects and can be readily employed in this regard. This study demonstrates that base maps produced with UAV data meet the requisite scientific and academic standards, including accuracy and precision. Additionally, it illuminates the advantages of UAV data in base map production, particularly in terms of time, accuracy, and cost.
Hybrid GIS-MCDM Based Modeling Approach for Determination of Land Suitability of Wheat Cultivation in Konya Closed Basin, Türkiye
(Ankara University, 2025) Yaman, Aydan; Mutlu, Mert
In countries with high population growth and migration potential, such as Türkiye, agricultural lands are gradually decreasing due to the increase in food demand and the misusage policies and urbanization applied to the lands. Land suitability activities carried out within the scope of agricultural sustainability in order to increase agricultural production and soil productivity are important. This study focuses on identifying the agricultural lands suitable for wheat cultivation by evaluating the Konya closed basin in the Central Anatolia Region of Türkiye by using a hierarchy developed with the integration of the AHP method, which is one of the GIS and MCDM techniques. Within this framework, 15 criteria were delineated under 4 main headings as meteorological criteria, topographic criteria, soil criteria, infrastructure and economic criteria and their weight values for their sub-criteria were calculated. The most effective criteria were determined as the average temperature of October (0.1379), followed by the average annual temperature (0.1300) and the land use capability (0.1191). Finally, the land suitability map was created for wheat cultivation. According to the suitability map, 0.39% (15 815 km2) of the study area is found to be very highly suitable for wheat cultivation, 61.24% (2 494 461 km2) is found to be highly suitable in terms of suitability. The districts of Kadinhani, Sarayonu, Altinekin, Cihanbeyli, Kulu, Karapinar and Emirgazi, which are located in the north of the study area, have been determined as very suitable regions for wheat cultivation. This study aims to contribute to the existing literature by identifying precise and suitable areas by combining GIS and AHP in the wheat cultivation site selection process. In the study, a new research perspective is presented by taking into account the uncertainty in the site selection process and the concept of sustainability in four different dimensions: meteorological, topographical, soil, and infrastructure and economic, thus aiming to guide decision-makers for future studies. According the current literature, that no comprehensive study has yet been conducted that covers such a large basin for the wheat plant, which is the raw material of humanity's basic nutritional needs. In addition, the average annual pressure criterion that is not examined in the literature was discussed in the study and its importance for wheat plant development was also examined. Consequently, the outcome of this study delineates that the methods and criteria used in this study may be guiding for site selection for wheat cultivation in future studies covering such wide areas.
Post-Fire Burned Area Detection Using Machine Learning and Burn Severity Classification with Spectral Indices in İzmir: A SHAP-Driven XAI Approach
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Gündüz, Halil İbrahim; Torun, Ahmet Tarık; Gezgin, Cemil
This study was conducted to precisely map burned areas in fire-prone forest regions of İzmir and analyze the spatial distribution of wildfires. Using Sentinel-2 satellite imagery, burn severity was first classified using the dNBR and dNDVI indices. Subsequently, machine learning (ML) algorithms—RF, XGBoost, LightGBM, and AdaBoost—were employed to classify burned and unburned areas. To enhance model performance, hyperparameter optimization was applied, and the results were evaluated using multiple accuracy metrics. This study found that the RF model achieved the highest performance, with an overall accuracy of 98.0% and a Kappa coefficient of 0.960. In comparison, classification based solely on spectral indices resulted in overall accuracies of 86.6% (dNBR) and 81.7% (dNDVI). A key contribution of this study is the integration of Explainable Artificial Intelligence (XAI) through SHapley Additive exPlanations (SHAP) analysis, which was used to interpret the influence of key spectral and environmental variables in burned area classification. SHAP analysis made the model decision processes transparent and identified dNBR, dNDVI, and SWIR/NIR bands as the most influential variables. Furthermore, spatial analyses confirmed that variations in spectral reflectance across fire-affected regions are critical for accurate burned area delineation, particularly in heterogeneous landscapes. This study provides a scientific framework for post-fire ecosystem restoration, fire management, and disaster strategies, offering decision-makers data-driven and effective intervention strategies.
Geochemical and physical properties of historical mortars from the Tyana Octagonal Church: implications for restoration
(Springer Science and Business Media Deutschland GmbH, 2025) Bilgilioğlu, Hacer
This study aims to investigate the mineralogical, petrographic, geochemical, and physical properties of mortar samples from the Octagonal Church in the Ancient City of Tyana using multiple analytical methods to provide critical data for both the characterization of ancient building materials and the restoration process. Mortar samples were analyzed by optical microscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM-EDS), X-ray fluorescence (XRF), salt tests, grain size analysis, water absorption capacity, unit volume weight, and porosity analysis. The findings show that the mortars are largely composed of local materials, which are compatible with the geological structure of the region. The findings indicate that the mortars were made of local materials and contained air-hardening calcite and gypsum. High CaO and MgO contents indicate the use of dolomitic lime, while high porosity indicates the risk of water-salt interaction deterioration. This study provides important data for the preservation and durability of the mortars of the Octagon Church.
Hasas Baba Türbesi’nin Fotogrametrik Rölöve Alımı ve Farklı Yazılımlarda Doğruluk Araştırması
(Fırat Üniversitesi, 2024) Yıldırım Demir, Pelinsu; Yaman, Aydan
Fotogrametrik rölöve çalışmaları kültürel mirasımızın dokümantasyon işlemlerinde yıllardır kullanılmaktadır. Son zamanlarda gelişen teknoloji ile birlikte fotogrametrik çalışmalar da sürekli yenilenmektedir ve tarihi ve kültürel miraslarımızın daha hızlı, kolay bir şekilde ve yeterli doğruluklarda belgeleme çalışmalarının yapılmasına olanak sağlamaktadır. İnsansız Hava Aracı (İHA) fotogrametrisi de özellikle son yıllarda oldukça tercih edilen bir fotogrametri tekniği olarak kendisine yer edinmiştir. Bu çalışmada, Aksaray il merkezinde bulunan, hakkında yazılı bir kitabe olmadığından dolayı tam olarak tarihi bilinmeyen ancak mimari özellikleri göz önüne alındığında Anadolu Selçuklu Devleti’nin son zamanlarında ya da Karamanoğulları zamanında inşa edildiği düşünülen Hasas Baba Türbesi, İHA uçuş verileri ve üç farklı fotogrametrik yazılım kullanılarak 3B modellenmiştir. Fotogrametrik tekniklerle 3B modelleme çalışması için Agisoft Metashape Professional yazılımı, Pix4D Mapper yazılımı ve Context Capture yazılımı kullanılmıştır. Daha sonra her üç yazılım için de konum ve yükseklik hatası araştırılmış ve elde edilen sonuçlar incelendiğinde her üç yazılım için sırasıyla konum hatası 3.39cm, 3.66 cm ve 3.42 cm bulunmuştur. Yükseklik hatası ise sırasıyla 3.04 cm, 3.24 cm ve 3.28 cm olarak bulunmuştur. Sonuçların hata sınırı içerisinde kaldığı ve restorasyon projelerinde altlık olarak kullanılabileceği sonucuna varılmıştır.
Preliminary Results on Deformations of the Central North Anatolian Fault Zone
(Hitit Üniversitesi, 2024) Aladoğan, Kayhan; Alkan, Mehmet Nurullah; Tiryakioğlu, İbrahim; Yavaşoğlu, Hasan Hakan; Gezgin, Cemil; Özkan, Ali; Eyübagil, Eda Esma; Şahiner, Furkan; Çakanşimşek, Ece Bengünaz; Köse, Zafer
to date globally (SEGERS 2007). Here we report new records of bdelloid rotifers from a
Evaluation of alteration in the geothermal province west of Cappadocia, Türkiye: Mineralogical, petrographical, geochemical, and remote sensing data
(Walter de Gruyter GmbH, 2024) Bilgilioğlu, Hacer
This study determines the mineralogical, petrographical, and geochemical properties of the rocks outcropping in geothermal areas west of the Cappadocia geothermal region. These areas include Ziga, Narllgöl, Belislrma, Illsu, and Sivrihisar. The study reveals their hydrothermal alteration characteristics. Also, the study aims to determine the zones of hydrothermal alterations using remote sensing. Rock samples from geothermal areas were performed using optical microscopy, X-ray diffraction (XRD), scanning electron microscopy, X-ray fluorescence spectroscopy, and inductively coupled plasma-mass spectrometry techniques for the determination of mineralogical assemblages and major, trace and REE's analyses. Rock samples, determined as ignimbrites and tuff, exhibit intensive alterations. XRD analysis determined the association of alteration minerals. The dominant clay minerals were kaolinite, montmorillonite, and illite. The analyses and mineral associations are compatible with argillic, mid-argillic alteration, and silicification zones. Alteration zones were identified by classifying the ASTER satellite images of kaolinite, illite, and montmorillonite using the CROSTA technique. The alteration zones observed in this study are close to existing geothermal areas. In addition, different regions with these alterations have been identified within the study area and are expected to be a valuable reference for future geothermal exploration.
Investigation of the usability of Göktürk-2 data and UAV data for pond construction project
(Elsevier B.V., 2024) Karataş, Hüseyin; Yaman, Aydan
Today, many professions need maps that can be produced quickly, precisely, and in detail, as well as the data from these maps. Land data is very important, especially in mapping engineering, both in the public and private sectors. Providing these data and maps is seen as an important expense for individuals or institutions in terms of time, cost and labor force. This study aims to investigate the usability of the data obtained by satellite images and Unmanned Aerial Vehicles (UAV), which can be easily obtained for the design of the pond/dam body within the scope of the pond construction project for irrigation purposes. Within the scope of the study, the data obtained by adding digital terrain models to Göktürk-2 satellite images were compared with the data obtained from the flight study conducted with the UAV; two separate ponds were designed using the created orthophoto and elevation data. As a result, benefit/cost ratios were calculated. The benefit/cost ratio calculated from remote sensing satellite data was 1.32, while the benefit/cost ratio calculated according to the project created with the UAV was 1.48, and the difference between the two data was calculated as 10.73%. According to this result, it was concluded that satellite images could be used in works such as ponds, closed system irrigation works, and land slope analysis, especially in preliminary project design studies. In contrast, data produced by UAV photogrammetry should be used in processes requiring higher precision. With this study, it is aimed that 25 households in the study area will benefit from the irrigation system. Furthermore, the findings of this study will enable institutions to select and utilise data that is appropriate to the purpose of the study and the desired accuracy, taking into account the benefit/cost ratios, without the need for prior fieldwork. By selecting and using the most economical data in accordance with the purpose of the work in engineering projects, optimum benefit will be obtained by saving time and labor.
6 Şubat Kahramanmaraş depremleri sonrasında Ecemiş Fayı’nda meydana gelen kabuksal deformasyonların GNSS yöntemiyle belirlenmesi
(Giresun Üniversitesi / Fen Bilimleri Enstitüsü, 2024) Tiryakioğlu, İbrahim; Koçbulut, Fikret; Gezgin, Cemil; Solak, Halil İbrahim; Eyübagil, Eda Esma; Çakanaşimşek, Ece Bengünaz; Aladoğan, Kayhan; Dönmez, Ergin; Poyraz, Fatih
Bu çalışmada, Ecemiş Fayı ve çevresindeki kabuksal deformasyonun belirlenmesi amacıyla kurulan 28 noktalı GNSS ağında 6 Şubat Kahramanmaraş depremleri sonrası meydana gelen kosismik deformasyon incelenmiştir. TÜBİTAK 121Y409 numaralı proje kapsamında kurulan GNSS ağı, bölgede yer alan TUTGA noktaları ve TUSAGA-Aktif istasyonları ile genişletilerek 64 noktalı bir GNSS ağı oluşturulmuştur. Proje ağında kampanya tipi 25 noktada, 2022 Temmuz ayında bir kampanya GNSS ölçümü yapılmıştır. 6 Şubat 2023 tarihinde meydana gelen Kahramanmaraş depremlerinden sonra ise 2023 Temmuz ayında bir kampanya daha ölçüm yapılmıştır. Ayrıca ağda yer alan TUTGA noktalarının ve TUSAGA-Aktif istasyonlarının deprem öncesi (presismik) dönemde en az 3 farklı yıla ait GNSS verileri temin edilmiştir. Tüm GNSS verileri GAMIT/GLOBK yazılımı ile değerlendirilmiştir. Ağda yer alan TUTGA ve TUSAGA noktalarının deprem öncesi verileri ile bu noktalara ait Avrasya sabit (ITRF14) hızları elde edilmiştir. Ayrıca TUSAGA Aktif istasyonlarının deprem sonrası (postsismik) 10 aylık verilerinin değerlendirilmesiyle deprem sonrası hızlar elde edilmiştir. Deprem öncesi ve sonrası hızlar kullanılarak kampanya tipi noktaların hızları enterpolasyon yöntemi ile hesaplanmıştır. Kampanya tipi noktalarda depremin neden olduğu atım miktarları, enterpolasyon ile elde edilen hızlar kullanılarak deprem öncesi ve sonrası koordinatların deprem anı epoğuna kaydırılmasıyla hesaplanmıştır. Kampanya tipi noktalarda atım miktarlarının doğu bileşende 10 mm ile 410 mm ve kuzey bileşende ise 18 mm ile 316 mm arasında değiştiği belirlenmiştir.
A GIS-based multi-criteria decision-making approach (GIS-MCDM) for determination of the most appropriate site selection of onshore wind farm in Adana, Turkey
(Springer Nature, 2024) Yaman, Aydan
Energy stands as an indispensable global need, yet the finite nature of rapidly depleting fossil fuel reserves poses environmental challenges. To address this, numerous nations are shifting toward sustainable energy sources to foster environmental well-being while satisfying their energy requirements. Among these alternatives, wind energy emerges as a particularly efficient option. This study focuses on identifying optimal sites for installing wind power plants in Adana province through the integration of the analytic hierarchy process (AHP) and geographic information system (GIS). Within this framework, a comprehensive set of 15 criteria was delineated along with their respective sub-criteria. It is thought that the criteria used in the study will be useful not only for Adana province but also for other provinces that are suitable for wind turbine placement and planned to be built. The outcome of this investigation delineates potential areas in Adana province deemed suitable for establishing wind power plants. As a result, analysis reveals that 9.94% of the study area is conducive to establishing a wind farm (WF), while 51.66% is deemed moderately suitable. Notably, the districts of Feke, Tufanbeyli, Saimbeyli, and Pozantı emerge as particularly well-suited for this purpose. This study aims to contribute to the existing literature by identifying precise and suitable areas by combining GIS and AHP in the WF site selection process. In the study, a new research perspective is presented by taking into account the uncertainty in the site selection process and the concept of sustainability in three different dimensions: technical, economic, and environmental, thus aiming to guide decision-makers for future WF projects. In addition, it is thought that the methods and criteria used in the study will also be guiding for future WF site selection studies.
Remote Sensing-Enabled Urban Growth Simulation Overlaid with AHP-GIS-Based Urban Land Suitability for Potential Development in Mersin Metropolitan Area, Türkiye
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Şahin, Ezgi; İban, Muzaffer Can; Bilgilioğlu, Süleyman Sefa
This study delves into the integration of analytic hierarchy process (AHP) and geographic information system (GIS) techniques to identify suitable areas for urban development in six districts within the Mersin Metropolitan Area of Turkey. The specific aim is to generate an urban land use suitability map, in order to facilitate informed decision-making for urban development. Drawing on open Landsat satellite imagery and employing the random forest (RF) algorithm, the study spans a fifteen-year period, over which land use/land cover (LULC) changes are measured. Furthermore, a novel approach is introduced by incorporating the urban land use suitability map into an urban growth simulation model developed using a logistic regression (LR) algorithm. This simulation forecasts urban growth up to 2027, enabling planners to evaluate potential development areas against suitability criteria. Findings reveal spatial patterns of land suitability and projected urban growth, aiding decision-makers in selecting optimal areas for development while preserving ecological integrity. Notably, the study emphasizes the importance of considering various factors such as topography, accessibility, soil capability, and geology in urban planning processes. The results showcase significant proportions of the study area as being moderately to highly suitable for urban development, alongside notable shifts in LULC classes over the years. Additionally, the overlay analysis of simulated urban growth and land suitability maps highlights areas with contrasting suitability levels, offering valuable insights for sustainable urban growth strategies. By overlaying the urban land suitability map with a simulated LULC map for 2027, it is revealed that 2247.3 hectares of potential new urbanization areas demonstrate very high suitability for settlement, while 7440.12 hectares exhibit very low suitability. By providing a comprehensive framework for assessing urban land suitability and projecting future growth, this research offers practical implications for policymakers, urban planners, and stakeholders involved in Mersin’s development trajectory, ultimately fostering more sustainable and resilient urban landscapes.
6 Şubat 2023 Sofalaca-Şehitkamil Gaziantep (Mw:7.7) ve Ekinözü Kahramanmaraş (Mw:7.6) Depremlerinin GNSS Gözlemlerine Bağlı Öncül Sonuçları
(Afyon Kocatepe Üniversitesi, 2023) Eyübagil, Eda Esma; Şafak Yaşar, Şeyma; Çakanşimşek, Ece Bengünaz; Duman, Hüseyin; Solak, Halil İbrahim; Özkan, Ali; Gezgin, Cemil; Yavaşoğlu, Hasan Hakan; Tiryakioğlu, İbrahim; Poyraz, Fatih
Bu çalışmada 6 Şubat 2023 tarihinde sırasıyla yerel saat ile 04:17 ve 13:24’te artarda meydana gelen Sofalaca-Şehitkamil Gaziantep (Mw:7.7) ve Ekinözü Kahramanmaraş (Mw:7.6) depremlerinin öncül jeodezik sonuçları verilmiştir. Öncül jeodezik sonuçları elde etmek için deprem odak merkezleri etrafındaki ve etkili olduğu alandaki TUSAGA-Aktif istasyonlarına ait GNSS alıcılarından 30 sn (0,033 Hz) ve 1 sn’lik (1 Hz) GNSS gözlemleri kullanılmıştır. Deprem kaynaklı kosismik yer değiştirmeleri belirlemek için bağıl statik çözümler GAMIT/GLOBK yazılım takımında 30 sn’lik RINEX verileri kullanılarak yapılmıştır. Statik çözümlerde değerlendirmeye alınan istasyonlarda Sofalaca-Şehitkamil Gaziantep depreminde doğu bileşende atımın 1.1-23.4 cm, kuzey bileşende 1.1-30.9 cm aralığında değiştiği görülmüştür. Ekinözü Kahramanmaraş depreminde ise atım miktarı doğu bileşende 1.2-440.4 cm, kuzey bileşende 1.4-69.6 cm aralığında değişmiştir. Kinematik çözümler ise PPP yöntemiyle CSRS-PPP ve PRIDE PPP-AR yazılımları ile 1 sn’lik RINEX verileri kullanılarak elde edilmiştir. Her iki yazılımda seçilen istasyonlardaki deprem anı yer değiştirmeler (deplasman) ve ardışık epok farkları (hız) hesaplanmıştır. Seçilen tüm istasyonlarda hızlar Sofalaca-Şehitkamil Gaziantep depreminde doğu bileşen için 3-12.5 cm/sn, kuzey bileşen için 3.8 - 37.7 cm/sn aralığında; Ekinözü Kahramanmaraş depreminde ise doğu bileşende 3.7-20.5 cm/sn, kuzey bileşende 4.1-20.1 cm/sn tespit edilmiştir. Öncül sonuçların elde edilmesinden sonra bölgenin daha yakından takibi ve yeni noktalarda atımların tespiti için yeni bir GNSS ağı kurulmuştur. Kurulan yeni ağda TÜBİTAK 1002-C Doğal Afetler Odaklı Saha Çalışması Acil Destek Programı çağrısı kapsamında arazi çalışmalarına başlanmıştır.
The green divide and heat exposure: urban transformation projects in istanbul
(Frontiers Media SA, 2023) Yazar, Mahir; Daloğlu Çetinkaya, İrem; İban, Muzaffer Can; Bilgilioğlu, Süleyman Sefa
Extreme heat events are happening more frequently and with greater severity, causing significant negative consequences, especially for vulnerable urban populations around the globe. Heat stress is even more common in cities with dense and irregular planning and lacking urban blue-green infrastructures. This study investigates the greening and cooling effects of five selected urban transformation projects and their surrounding areas (within a 10-min walking distance) in Istanbul from 2013 to 2021, with a focus on environmental justice and climate adaptation planning perspectives. By employing temporal analysis of Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) values derived from Landsat data sets to detect changes in these five selected urban transformation projects in the megacity of Turkiye, Istanbul, this study finds that the distribution of green infrastructures (e.g., tree canopy) is only limited to project sites of long-running and state-supported urban transformation projects in Istanbul. Consequently, the unequal distribution of green infrastructures creates cooling effects only for the locals residing in the new residential projects. However, the surrounding areas have less urban green infrastructure and are exposed more to the urban heat over time. Urban development policies and planning highly contribute to increasing the climate vulnerabilities among those who do not benefit from the recently developed residential units in Istanbul. Such a trend can affect adaptive capacity of vulnerable communities and redress environmental injustices in urban planning in the megacity of Istanbul.
Automatic building footprint extraction from photogrammetric and LiDAR point clouds using a novel improved-Octree approach
(Elsevier, 2024) Karslı, Buray; Yılmaztürk, Ferruh; Bahadır, Murat; Özdemir, Emirhan; Karslı, Fevzi
Extracting building footprints from optical data is a time-consuming process. Automatic extraction of building footprints from point clouds is a challenging problem in terms of geometric irregularities, noisy points, points density, and accuracy. The aim of this paper is to automatically extract and regularize building footprints using point clouds with a new approach called Improved Octree (I-Octree) by modifying the Octree method. The method consists of the separation of ground and above ground objects from the point cloud by Simple Morphological Filter (SMRF), the removing noisy points from point cloud with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, the automatic extraction of building footprints by I-Octree, and the regularization of the building footprints with Automatic Building Outline Regularization (ABORE) method. The proposed approach was implemented on photogrammetric and Light Detection and Ranging (LiDAR) in four test areas. Ground truth maps were utilized as reference data for accuracy analysis by using pixel-based accuracy method. The accuracy results were above 90 % for the photogrammetric point clouds and above 97 % for the LiDAR point cloud. It was proven that the proposed approach can extract and regularize the selected buildings with high accuracy compared the studies in literature. In conclusion, it was demonstrated that the proposed approach enables the automatic extraction and regularization of building footprints from point clouds. Consequently, the map production process with point cloud data is facilitated to be both more efficient and rapid, and the results confirm the high efficacy of the proposed approach.

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