Cloud computing enables performing computations and analysis tasks and sharing services in web-based computer centres instead of local desktop systems. One of the most used areas of cloud computing is geographic information systems (GIS) applications. Although Desktop GIS products are still used in the community frequently, Web GIS and Cloud GIS applications have drawn attention and have become more efficient for users. In this study, a serverless Cloud GIS framework is implemented for the land valuation platform. In order to store, analyse, and share geospatial data, the Aurora Serverless PostgreSQL database is created on Amazon Web Services (AWS). While adopting Aurora Serverless PostgreSQL as a database management system, a simple point in polygon analysis conducted to compare the performances with Amazon Relational Database Service (RDS) instance. Results showed that the serverless database responded to the query faster and scaled up during high workload to decrease latency. Hence, parcel vector data, which conveys ownership information and land values attributes, is shared directly from the PostGIS database as vector tiles. Besides S3 and AWS Lambda services are used for storing and disseminating raster-based land value map tiles. To visualize all shared data and maps through a web browser, open source web mapping library Mapbox GL JS is used.

Bicycle sharing systems (BSSs) in urban areas are considered an effective solution for enabling sustainable transportation. In this sense, the locations of BSS stations (BSSSs) are of vital importance to establish efficient BSSs. In addition, citizens should be able to benefit from suitable cycling infrastructure (CI) for their safety. For this reason, the aim of this article is to propose an integrated framework that includes the best worst method (BWM) and geographic information systems (GIS) techniques to determine optimal locations of BSSSs and CIs simultaneously. Proposed BSSS locations and CIs are ranked to present more elaborate results. Moreover, sensitivity analysis is applied with the aim of revealing the uncertainty in the model. In this connection, the locations close to shorelines are found to be highly suitable, because they have advantages in terms of important criteria such as BSSS and transportation station. Consequently, this study presents the interplay of GIS techniques and multicriteria decision making methods, offering a significant solution for simultaneous location selection of BSSS and CI. The results of the approach proposed in this article can be used as a basis for both transportation planning and urban planning.

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.

The condominium rights, which is a special ownership type that can only exist in the buildings that have an occupancy permit, are needed to be examined and depicted as three-dimensional (3D) in order to prevent misinterpretations and disputes regarding Rights, Restrictions, and Responsibilities (RRRs). This paper, therefore, aims to provide the model that extends the Industry Foundation Classes (IFC) schema by referencing Land Administration Domain Model (LADM) in the sense of reusing the Building Information Modeling (BIM)/IFC model of the building for 3D registration of condominium rights in Turkey. The results of the study show that there is a solid potential to benefit from BIM/IFC model in order for both 3D representation of the ownership rights in the multi-storey buildings and obtaining the semantics of the condominiums in terms of wide ranges of attributes such as area, volume, land share, and RRRs.

In today’s world, effective management and the use of spatial data are of great importance in many sectors. Industries such as land management, asset management, and infrastructure management are areas where spatial data are heavily utilized. Advanced technologies such as Geographic Information Systems (GISs) and Building Information Modeling (BIM) are used in the processes of collecting, analyzing, and managing geographically enabled data (geo-data). These technologies enable the effective processing of large datasets, improve decision-making processes based on geographic information, and facilitate more efficient collaboration across sectors. This study conducts an in-depth examination of the existing literature on asset management, infrastructure management, and BIM-GIS integration using bibliometric analysis and systematic literature review methods. Bibliometric analysis is employed to determine statistical values such as current research trends, frequently cited authors, most used keywords, and country performances in the relevant field. This study’s results highlight future research trends and significant gaps in the areas of asset management, infrastructure management, natural gas pipelines, and BIM-GIS integration. In particular, this study demonstrates the critical importance of asset management and BIM-GIS integration for sustainable infrastructure design, construction, and management. In this context, attention is drawn to the importance of data standardization, digitization, systematic integration, and contemporary land management requirements.