Search Results (113)

This paper presents a conceptual and methodological framework for using Geographical Information Systems (GIS) to “deep map” cultural heritage sites along Ireland’s Wild Atlantic Way, with a focus on the 1588 Spanish Armada wrecks in County Kerry and archaeological landscapes in County Sligo’s “Yeats Country.” Drawing on interdisciplinary dialogues from the humanities, social sciences, and geospatial sciences, it illustrates how digital spatial technologies can excavate, preserve, and sustain intangible cultural knowledge embedded within such palimpsestic landscapes. Using MAXQDA 24 software to mine and code historical, literary, folkloric, and environmental texts, the study constructed bespoke GIS attribute tables and visualizations integrated with elevation models and open-source archaeological data. The result is a richly layered cartographic method that reveals the spectral and affective dimensions of heritage landscapes through climate, memory, literature, and spatial storytelling. By engaging with “deep mapping” and theories such as “Spectral Geography,” the research offers new avenues for sustainable heritage conservation, cultural tourism, and public education that are sensitive to both ecological and cultural resilience in the West of Ireland. Full article

As vital material carriers of human civilization, earthen sites are experiencing continuous surface deterioration under the combined effects of weathering and anthropogenic damage. Traditional surface conservation techniques, due to their poor compatibility and limited reversibility, struggle to address the compound challenges of micro-scale degradation and macro-scale deformation. With the deep integration of digital twin technology, spatial information technologies, intelligent systems, and sustainable concepts, earthen site surface conservation technologies are transitioning from single-point applications to multidimensional integration. However, challenges remain in terms of the insufficient systematization of technology integration and the absence of a comprehensive interdisciplinary theoretical framework. Based on the dual-core databases of Web of Science and Scopus, this study systematically reviews the technological evolution of surface conservation for earthen sites between 2000 and 2025. CiteSpace 6.2 R4 and VOSviewer 1.6 were used for bibliometric visualization analysis, which was innovatively combined with manual close reading of the key literature and GPT-assisted semantic mining (error rate < 5%) to efficiently identify core research themes and infer deeper trends. The results reveal the following: (1) technological evolution follows a three-stage trajectory—from early point-based monitoring technologies, such as remote sensing (RS) and the Global Positioning System (GPS), to spatial modeling technologies, such as light detection and ranging (LiDAR) and geographic information systems (GIS), and, finally, to today’s integrated intelligent monitoring systems based on multi-source fusion; (2) the key surface technology system comprises GIS-based spatial data management, high-precision modeling via LiDAR, 3D reconstruction using oblique photogrammetry, and building information modeling (BIM) for structural protection, while cutting-edge areas focus on digital twin (DT) and the Internet of Things (IoT) for intelligent monitoring, augmented reality (AR) for immersive visualization, and blockchain technologies for digital authentication; (3) future research is expected to integrate big data and cloud computing to enable multidimensional prediction of surface deterioration, while virtual reality (VR) will overcome spatial–temporal limitations and push conservation paradigms toward automation, intelligence, and sustainability. This study, grounded in the technological evolution of surface protection for earthen sites, constructs a triadic framework of “intelligent monitoring–technological integration–collaborative application,” revealing the integration needs between DT and VR for surface technologies. It provides methodological support for addressing current technical bottlenecks and lays the foundation for dynamic surface protection, solution optimization, and interdisciplinary collaboration. Full article

With the rapid development of science and technology, the global demand for renewable energy is increasing. In the urban context, solar energy has become one of the key ways to increase urban energy self-sufficiency and reduce carbon emissions due to its flexibility in installation and ease of expansion of applications. Therefore, based on Geographic Information System (GIS) and deep learning modeling, this paper proposes a method to efficiently assess the potential of urban rooftop solar photovoltaic (PV), which is analyzed in a typical area of Lanzhou New District, which is divided into 8774 units with an area of 87.74 km². The results show that the method has a high accuracy for the identification of the roof area, with a maximum maxF_β of 0.889. The annual solar PV potential of industrial and residential buildings reached 293.602 GWh and 223.198 GWh, respectively, by using the PV panel simulation filling method for the calculation of the area of roofs where the PV panels can be installed. Furthermore, the rooftop PV potential of the industrial buildings in the research area provided can cover 75.17% of the industrial electricity consumption. This approach can provide scientific guidance and data support for regional solar PV planning, which should prioritize the development of solar potential of industrial buildings in the actual consideration of rooftop PV deployment planning. Full article

Geographic Information Systems and the use of thematic maps have become well-established tools in archaeology. However, not all the sectors of archaeology still take advantage of these technologies. One such sector is numismatics, where there are still relatively few works on the implementation of coin spatial databases and the related maps. This can be verified both in academic journals indexed in major scientific databases (such as Scopus, ScienceDirect, and Web of Science) and in broader platforms like Google Scholar. In this paper, in an attempt to begin filling the gap, the methodology and results of the creation of the GIS and the Atlas of Antoniniani in Sicily are presented. The second half of the third century ASD is an interesting period because of the socioeconomic crisis that characterized it. The Atlas serves as a useful tool for providing a fresh new insight into the economy and coin circulation during this time. Full article

This study proposes a novel framework integrating Building Information Modeling (BIM) and Geographic Information Systems (GIS) with real-time crowd analytics from Closed-Circuit Television (CCTV) for quantitative walkability assessment. The framework extends open data standards (IFC and CityGML) to model infrastructural and pedestrian flow attributes comprehensively. A walkability scoring mechanism quantifies route quality based on accessibility, efficiency, and physical comfort, differentiating among pedestrian groups, such as individuals sensitive to weather conditions or carrying belongings. Implemented at the Hong Kong University of Science and Technology (HKUST), results indicate that the framework effectively captures variations in walkability scores due to directional differences (uphill vs. downhill), crowd conditions, and operational constraints like facility closures. Statistical tests confirm significant differences in walking costs across these scenarios with variations of up to 30%, demonstrating the framework’s robustness and practical utility for real-time, human-centric urban infrastructure planning. Full article

Quality management during construction is critical to ensuring compliance with technical specifications and quality standards. Traditional practices often rely on manual, paper-based documentation, leading to inefficiencies, data fragmentation, and poor traceability. This study presents QualiSite, a novel digital workflow that integrates Building Information Modeling (BIM) and Geographic Information Systems (GIS), aligned with ISO 9001:2015 requirements, to enhance quality management in building projects. The research is framed under the Design Science Research Method (DSRM), guiding the iterative development and validation of the tool. QualiSite was tested in a real-world case study involving the construction of reinforced concrete walls. The results demonstrated functional improvements in inspection traceability, consistency of quality records, and coordination between field data and BIM elements. Using structured digital forms contributed to more consistent data capture and greater efficiency in recording, organizing, and visualizing quality control statuses within the 3D environment. These outcomes enabled transparent inspection processes and clear visualization of quality status across construction elements. The digital workflow also facilitated the identification of nonconformities and streamlined communication between field inspectors and model managers. This approach advances traditional quality management by embedding inspection records into a Cyber-Physical Systems (CPS) framework, contributing to the digital transformation of the Architecture, Engineering, and Construction (AEC) industry and supporting the vision of Smart Industry. Full article

Higher education institutions have played a central role in building sustainability awareness. However, current models only show an effect on students’ knowledge about sustainable development, with a large gap in transformative solutions that shift from understanding problems towards solutions. This case study explores a new model that integrates sustainability reflections in a Geographic Information Science (GIS) Capstone Project course. Through collaborations with external partners and reflections on sustainability modules, students analyzed complex problems and developed sustainability competencies. The assessment tool adopted in this study combines reflective writing, scenario testing, performance observation, and self-assessment. Based on the set of key competencies in sustainability, half of the students developed systems-thinking and strategies-thinking, while a quarter of the students developed futures-thinking and values-thinking. Their development of sustainability competencies went beyond simply acquiring knowledge, also critically evaluating different perspectives and implementing or integrating the concepts when addressing the problems. Geospatial information tackles three key aspects of sustainability, which are relational, distributional, and directional, making it ideal in analyzing sustainability issues and providing insights for informed decisions. This study fills another important gap of integrating sustainability competency development in GIS education. Full article

In port management, the integration of geographic information systems (GIS) is essential for geospatial analysis in a complex environment shaped by digitalisation and energy transition. Although the adoption of GIS and spatial data infrastructures (SDI) are growing, their use remains with challenges in interoperability and collaborative data management. This study conducts a systematic review to identify the main publications from the past 10 years on the use of GIS and SDI in the maritime sector, using the Scopus and Web of Science databases. The results revealed an annual growth of 8.59% in scientific publications over the past decade, with a focus on environmental monitoring, machine learning, and digitalisation. The findings also suggest the limited use of SDI in the maritime sector, reinforcing the need for future research on interoperability and spatial data integration. Nevertheless, the main trends include the integration of GIS with machine learning, advanced spatial applications, and artificial intelligence, showing an increasing focus on sustainability, environmental monitoring, and innovative management systems. Full article

Food transition has been widely inspiring regional and local food system transformation strategies to accomplish the Sustainable Development Agenda goals. Considering the urgency required to transform food systems by 2030, actions should be supported by principles of science-based and practical effectiveness. Within the framework of the Food Transition Strategy for the Lisbon Metropolitan Area (FTS-LMA), a methodology to identify the potential to establish Multifunctional Agrofood Parks (MAPs) has been applied to inform decision-makers where this potential is located as an opportunity to transform local food system towards healthier and more affordable food production. The method uses an Analytical Hierarchy Process (AHP) operated in a Geographic Information System (GIS) to integrate a multicriteria environment and socioeconomic variables for determining suitable territories for MAP implementation. The results show the higher suitability for the MAP establishment in the LMA is over 30% of the region, which drives a thorough reflection on how to set up a socio-territorial transformation of the metropolitan food system envisioned by the FTS-LMA by using current results as part of a food system planning exercise to determine where the ecological suitability for sustainable food production overlap with the capacity for intervention by the fabric of producers in each of the 18 municipalities. Full article

This study explores the interplay between digital transformation and environmental sustainability in four emerging European Union economies—Bulgaria, Hungary, Poland, and Romania—through the lens of geographic information science and technology (GIS&T). Leveraging panel data from 2010 to 2022, digitalization is quantified through infrastructure, affordability, and user adoption metrics, consolidated into a comprehensive digitalization index. Environmental sustainability is assessed via greenhouse gas emissions and the share of renewable energy in total energy consumption, capturing critical spatial and ecological dynamics. Applying a generalized linear model, the results reveal that enhanced digital infrastructure and affordability contribute to emissions reduction, whereas increased user adoption correlates with higher energy demand and emissions. Furthermore, digitalization fosters improved integration of renewable energy sources, highlighting the strategic role of GIS&T in monitoring and optimizing sustainability initiatives. These insights emphasize the necessity of embedding geospatial analytics into policy frameworks to align digital transformation with environmental and socioeconomic sustainability goals. Full article

The growing complexity of natural disasters, intensified by climate change, has amplified the challenges of managing emergency shelter demand. Accurate shelter demand forecasting is crucial to optimize resource allocation, prevent overcrowding, and ensure evacuee safety, particularly during concurrent disasters like hurricanes and pandemics. Real-time decision-making during evacuations remains a significant challenge due to dynamic evacuation behaviors and evolving disaster conditions. This study introduces a spatiotemporal modeling framework that leverages connected vehicle data to predict shelter demand using data collected during Hurricane Sally (September 2020) across Santa Rosa, Escambia, and Okaloosa counties in Florida, USA. Using Generalized Additive Models (GAMs) with spatial and temporal smoothing, integrated with GIS tools, the framework captures non-linear evacuation patterns and predicts shelter demand. The GAM outperformed the baseline Generalized Linear Model (GLM), achieving a Root Mean Square Error (RMSE) of 6.7791 and a correlation coefficient (CORR) of 0.8593 for shelters on training data, compared to the GLM’s RMSE of 12.9735 and CORR of 0.1760. For lodging facilities, the GAM achieved an RMSE of 4.0368 and CORR of 0.5485, improving upon the GLM’s RMSE of 4.6103 and CORR of 0.2897. While test data showed moderate declines in performance, the GAM consistently offered more accurate and interpretable results across both facility types. This integration of connected vehicle data with spatiotemporal modeling enables real-time insights into evacuation dynamics. Visualization outputs, like spatial heat maps, provide actionable data for emergency planners to allocate resources efficiently, enhancing disaster resilience and public safety during complex emergencies. Full article

The service-learning (SL) approach has shown effectiveness in fulfilling both academic and community-oriented objectives. This paper focuses on a specific case study for a Cartography, Remote Sensing, and Geographical Information Systems (GIS) course for Environmental Sciences undergraduate students. The main goals for implementing SL practice were (1) to enhance students’ GIS knowledge and to develop cross-cutting skills by working with real-world problems; (2) to share with society the knowledge acquired by students and ensure that it is valued; and (3) to prompt reflection on urban waste issues among students. The activity consisted of analyzing the waste containers along the 1 km riverbanks in León (Spain) and elaborating a proposal for the location of new rubbish bins to deliver to a City Council’s environmental technician. The results showed an improvement in students’ GIS management skills to solve environmental problems compared to those from the previous 3 years and a satisfactory response from environmental professionals with delivering the results. Together, an increase in students discussing urban waste was observed during the sessions. Projects like this not only teach technical skills but also provide a deeper understanding of data collection and implementation processes in environmental issues, which are closely aligned with professional experiences, and awareness of the practical application of the knowledge acquired. Full article

Waste is a complex challenge that requires collaboration between multiple stakeholders to achieve a circular economy. In this context, there is a growing demand for digital solutions that integrate physical and digital infrastructure to create digital waste governance systems. Analog management, without accurate data, is becoming increasingly unfeasible in light of the UN Sustainable Development Goals. Tools such as online geographic information systems (WebGIS) allow the collection and integration of large volumes of physical and human data and the establishment of a digital governance structure that brings together different technologies, tools and methods in the same environment. This article aims to present the State of the Art on the topics of zero-waste cities, WebGIS, and disruptive innovation. The article starts from the hypothesis that only a process of disruptive and systemic innovation in the value chain and urban solid waste management (MSWMS), supported by the principle of zero-waste cities, circular economy and webGIS, can effectively help to solve this problem. The research uses an exploratory literature review on the concepts of zero-waste cities, systemic innovation and webGIS applied to waste management, linking them to the theoretical framework of sustainability as a science and to Brazilian public policies, such as the National Solid Waste Policy (Law 12.305/2010), the National Circular Economy Policy (Law 1.874/2022) and the National Digital Government Strategy of Brazil 2024–2027 (ENGD). As a result, scientific publications on zero-waste cities increased from 2018 to 2023 and several countries have adopted zero-waste guidelines in waste management policies. WebGIS, remote sensing, geoprocessing and different technologies are increasingly being incorporated into waste management, generating significant impacts on the diversion of resources from landfills, mitigating climate change, and generating and/or adding value to the useful life of waste and garbage resources, in addition to the optimization and efficiency of collection operators and citizen engagement in public policies. Disruptive innovation has proven to be a concrete process to enable the transition from obsolete sociotechnical systems (such as the linear economy), where sustainable finance and environmental entities play a fundamental role in orchestrating and coordinating the convergence of private, public and civil society actors towards this new sustainable development paradigm. The case study proved to be fruitful in proposing and encouraging the adoption of such methods and principles in municipal waste management, allowing us to outline a first conception of a digital government structure and digitalization of public services for zero-waste cities, as well as pointing out the difficulties of implementing and transforming these systems. This digital governance structure demonstrates the possibility of being replicable and scalable to other cities around the world, which can materialize an important tool for the implementation, articulation and development of a long-term sustainable development paradigm, based on the vision of the circular economy and zero-waste cities. Full article

The United States identifies, monitors, and defends a vast network of controlled airspaces surrounding its own and allied territories. These controlled airspaces include civilian aviation classes (A through G), drone flying regions, and special use (military) air classifications. These controlled spaces are invisible to the naked eye and often go unnoticed. Managing and portraying data that function in two and three dimensions poses significant challenges that have hindered prior analyses or geovisualizations of controlled airspaces, but we demonstrate here how many of these can be surmounted to visually represent the spatial extent and patterns of US-controlled airspace. In this paper, we demonstrate how these complex spaces can be graphically represented and highlight how cartographic and geovisual representations of often-overlooked domains contribute to a richer understanding of the reach and character of US airspace. The methods described for this work can be extended to other types of multidimensional objects and may facilitate more robust considerations of how Geographical Information Science (GIS) can be useful in analyzing and depicting airspace and territorial claims in three dimensions. Full article

Traffic flow prediction is one of the most important and attractive topics in geographical information science (GIS), traffic management, and logistics. Traffic flows exhibit significant complexity and dynamics, requiring a thorough understanding of their spatiotemporal evolution patterns for accurate prediction and analysis. Existing studies utilizing deep learning for traffic flow prediction often suffer from distribution shift issues, leading to poor generalization capabilities when dealing with data that has different spatiotemporal distributions. Based on this, we propose a traffic flow prediction model based on prompt learning, leveraging graph convolutional networks to focus on the spatiotemporal dependencies of traffic flows. The model utilizes spatiotemporal context learning capabilities to capture the periodic states of traffic flows, enhancing the extraction of spatiotemporal features by integrating spatiotemporal information. Experimental results show that the spatiotemporal traffic flow prediction model equipped with a spatiotemporal prompt learning module outperforms several mainstream benchmark models in terms of predictive performance. The model presents efficient learning performance that reaches optimal state in a short period of time, reduces the impact of distribution shifts, and can be adapted to spatiotemporal traffic flow data under varying spatiotemporal contexts. Full article