The design of a natural gas pipeline route is a very important stage in Natural Gas Transmission Pipeline projects. It is a very complicated process requiring many different criteria for various areas to be evaluated simultaneously. These criteria include geographical, social, economic, and environmental aspects with their obstacles. In the classical approach, the optimum route design is usually determined manually with gathering the spatial references for suitable places and obstructions from the ground. This traditional method is not effective because it does not consider all the factors that affect the route of the pipeline. Today, the powerful tools incorporated in Geographical Information Systems (GIS) can be used to automatically determine the optimum route. An automatic pipeline route finder algorithm can calculate the best convenient route avoiding geographic and topological obstructs and selecting suitable places depending on their weights. In this study, an automatic natural gas pipeline design study was carried out in the east western region of Turkey. At the end of the study, an automatic natural gas pipeline route was determined using GIS and a least cost path algorithm, and an alternative study was conducted using a traditional method. In addition, a cartographic line simplification process with a point removal algorithm was used to eliminate the high vertex points and a simplified route was determined. The results were compared with the results of a finished Muş natural gas project constructed by The Turkish Petroleum Pipeline Corporation (BOTAŞ) and the negative and positive effects were evaluated. It was concluded that the use of GIS capabilities and the lowest cost path distance algorithm resulted in a 20% reduction of the cost through the simplification.

This study evaluates green space suitability in İzmir’s Konak district using the analytic hierarchy process, machine learning, weighted linear combination, and the technique for order preference by similarity to ideal solution methods, integrated with geographic information systems. The approach enhances reliability in green space identification by ensuring consistent integration of weights determined by different methods. Machine learning enables dynamic adjustments to criterion weights, yielding the best results with the random forest algorithm. The analysis revealed that 75% of green spaces were sub-optimally located, with optimal zones in the western and northern regions. The technique for order preference by similarity to ideal solution methodology prioritized area ZGS_6 as the most suitable area, while ZGS_4 ranked lowest. This method supports efficient resource allocation and improves budgeting processes. Hence, the integration of multi-criteria decision-making and machine learning with geographic information systems enhances the planning of sustainable cities and offers critical insights to decision-makers who prioritize sustainability and livability.

Modern cities have been trying to meet their needs for space by using not only surface structures but also by considering subsurface space use. It is also anticipated that without planning of underground spaces for supporting surface city life in the years and generations to come, there will be serious and unavoidable problems with growing populations. The current Turkish cadastral system, including land right registrations, has been trying to meet users’ needs in all aspects since 1924. Today Turkey’s national cadastre services are carried out by the General Directorate of Land Titles and Cadastre (TKGM). The Cadastre Law, Number 3402, was approved in 1985 to eliminate problems by gathering all existing cadastral regulations under one law and also to produce 3D cadastral bases to include underground spaces and determine their legal status in Turkey. Although the mandate for 3D cadastre works is described and explained by the laws, until now the bases have been created in 2D and the reality is that legal gaps and deficiencies presently exist in them. In this study, the usage of underground spaces for the current cadastral system in Turkey was briefly evaluated, the concept of 3D cadastral data is examined and the need for using subsurface and 3D cadastre in addition to the traditional 2D register system, related problems and registration are mentioned with specific examples, but without focusing on a specific model.

Geographical Information Systems (GIS) have been gaining a growing interest in Turkey. Many local governments and public agencies have been struggling to set up such systems to serve the needs and meet public requirements. Urban life shelters the advertisement reality which is presented at various places, on vehicles, shops etc. in daily life. It can be said that advertisement is a part of daily life in urban area, especially in city centers. In addition, one of the main sources of revenue for municipalities comes from advertising and notices. The advertising sector provides a great level of income today. Therefore advertising is individually very important for local governments and urban management. Although it is valuable for local governments, it is also very important for urban management to place these advertisement signs and billboards in an orderly fashion which is pleasing to the eye. Another point related to this subject is the systematic control mechanism which is necessary for collecting taxes regularly and updating. In this paper, first practical meaning of notice and advertisement subject, problem definition and objectives are described and then legal support and daily practice are revised. Current practice and problems are mentioned. Possibilities of measuring and obtaining necessary information by using digital images and transferring them to spatial databases are studied. By this study, a modern approach was developed for urban management and municipalities by using information technology which is an alternative to current application. Criteria which provide environmental harmony such as urban beauty, colour, compatibility and safety were also evaluated. It was finally concluded that measuring commercial signs and keeping environmental harmony under control for urban beauty can be provided by Digital Photogrammetry (DP) technique and GIS capabilities which were studied with pilot applications in the city center of Ankara.

Predicting earthquake risk areas and risk levels is vital in minimizing the loss of life. In this study, earthquake risk assessment has been conducted by producing predictions for both five-class and two-class risk levels. The methods were tested on Izmir province. For this purpose, the city was divided into 28 zones. Twenty-two different evaluation criteria were assessed using geographic information systems. Risky areas were predicted using Support Vector Machines, k-Nearest Neighbors, Naive Bayes, Decision Trees, and Ensemble classifiers. It has been concluded that the F1 score results, the highest prediction success in training is ensemble classifier with 96%, and tests is decision tree methods with 45% for five classes. In addition, the training results is the ensemble classifier with 98%, and the test results is the decision tree methods with 76% for two classes. When all machine learning results were examined together, test prediction success on data labeled with two-classes was found to be significantly more successful than on data labeled with five classes. As a result of this study, it has been observed that Multi-Criteria Decision Making and machine learning give significant results in the area-based earthquake vulnerability analysis performed together. In addition, this study provides a practical contribution to urban planning and the improvement of development strategies in İzmir by identifying high-risk areas to mitigate seismic risks. Furthermore, the findings offer a data-driven framework for enhancing disaster management policies, enabling authorities to effectively plan emergency responses in vulnerable regions, implement appropriate construction techniques in high-risk areas, and optimize resource allocation.

Şehirler, artan nüfus yoğunluklarıyla sürekli gelişim halindedir. Bu durum kentlerin planlamasını ve sürdürülebilirliklerini sağlamak için plancılara çeşitli sorunlar oluşturmaktadır. Günümüz insanının şehirlerde en çok eksikliğini hissettiği alanlar yeşil alanlardır. İnsanların yaşam kalitesinin arttırılmasında ve ortaya çıkan sorunların giderilmesinde en önemli faktörlerden biri olan yeşil alanların planlanması oldukça önemlidir. Bu çalışmada, Ankara ili Çankaya ilçesine bağlı Emek, Bahçelievler ve Yukarı Bahçelievler mahalleleri çalışma alanı seçilmiş ve yeşil alan analizinin yapılabilmesi için on iki kriter belirlenmiştir. Bu kriterlerin birbirlerine göre ağırlıklarını tespit edilmesi için analitik hiyerarşi süreci (AHP) metodu kullanılmış ve kriterlerin konum analizleri için coğrafi bilgi sistemlerinden (CBS) yararlanılmıştır. En uygun yeşil alanların önem sıralarını belirlemek için ise TOPSIS metodu uygulanmıştır. TOPSIS yönteminde hem eşit ağırlıklı hem de AHP ağırlıklı hesaplar yapılmış ve analizler sonucunda, belirlenen dokuz bölgenin %44,4’ünün sıralamasının benzerlik gösterdiği tespit edilmiştir. Çalışma sonucunda, çalışma alanının yeşil alanlar bakımından yetersiz olduğu belirlenerek, uygulanan yöntemin sürdürebilir kent modelleri için kullanımı değerlendirilmiştir.