Rapid population growth, economic development and industrialization have created many problems related to municipal solid waste management (MSWM) in developing countries like Turkey. Solid waste disposal has become mandatory because of increasingly common factors such as global warming and contamination of water resources. In recent years, this situation has revealed the need for effective management of solid waste. Suitable site selection requires evaluation and analysis of multiplefactor. Therefore, it is very important that the design of landfill site selection take into account environmental, economical and sociologicalfactors. In order to do this, the Geographical Information System (GIS) used with Multi Criteria Decision Making (MCDM) techniques is a useful tool for creating a model. One such MCDM is the Spatial-integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In this study, TOPSIS was applied to integrate environmental, economical and sociological sensitivity into determine alternative solid waste landfill sites for Bursa Province, Turkey. Using the data obtained by comparing the geo-statistics, six of the most suitable landfill areas were determined. In the final stage, as a result of this study, the Kayapa district was identified as the most suitable landfill area.

Tourism is one of the largest contributors and fastest-growing economic sectors in many sub-Saharan Africa countries. However, most countries face management and promotional challenges because they use static methods such as brochures, books, posters and television broadcasts as well as websites with non-interactive maps to manage and promote tourism resources. These approaches are not only expensive due to information update and expirations, but also do not provide sufficient abstractions to guide tourists when planning for travel. This study designed a Web-based Geographic Information System (GIS) model with dynamic and interactive maps for managing and promoting tourism resources using data collected in Tanzania. The results of spatially based tourism data flow and database models were used to design and create web maps contained in a web-based GIS with more abstractions. The designed model provides an opportunity to manage and promote tourism resources for successful and sustainable tourism industry.

In accordance with current demands, the natural gas transmission pipeline (NGTP) is one of the most appropriate methods used in the distribution of existing reserves. Construction of long-distance pipelines requires large expenditures. Decreasing the time and cost of such construction and minimising environmental damage depend upon identifying the optimum routes from the onset of the project. Route determination is one of the most important steps in NGTP projects. The route determination process requires obtaining the existing graphic and non-graphic data from different institutions and organisations, as well as gathering, storing, querying and analysing non-existing data in an appropriate and efficient manner. Accessing the correct results rapidly by analysing such large data-sets can be achieved with spatial multicriteria decision-making technologies based on the geographic information system as an effective decision support tool. In this study, three methods were implemented for two NGTP projects of 103.60 and 60.89 km in length. At the end of this study, it was concluded that Spatial technique for order preference by similarity to ideal solution was the most effective of the three pipeline routing methods and that it could reduce project costs by approximately 21%.

Cancer is an important health issue in Turkey because it ranks as the second cause of death in the country. Examination of the relationships between the distribution of cancer cases and geo-environmental factors is significant in determining the causes of cancer. In this study, GIS were used to provide data about the distribution of cancer types in Trabzon province, Turkey. To determine the cancer occurrence density, the cancer incidence rates were calculated according to local census data, then a cancer density map was produced, and correlations between cancer types and geographical factors were examined.