Search Results (26)

In response to the increasing demand for effective bridge management and the shortcomings of current proprietary solutions, this work presents an open-source, web-based platform designed to support bridge inspection and data management, particularly for small and medium-sized public administrations, which often lack personnel or funding for implementing context-specific tools. The system addresses fragmented workflows by integrating multi-format geospatial and 3D data—such as point clouds, CAD/BIM models, and georeferenced imagery—within a unified, modular architecture. The platform enables structured inventory, interactive 2D/3D visualization, defect annotation, and role-based user interaction, aligning with FAIR principles and interoperability standards. Built entirely with free and open-source tools, the P.O.N.T.I. prototype ensures scalability, transparency, and adaptability. A multi-layer navigation interface guides users through asset exploration, inspection history, and immersive 3D viewers. Fully documented and publicly available on GitHub, the system allows for deployment across varying institutional contexts. The platform’s design anticipates future developments, including integration with IoT monitoring systems, AI-driven inspection tools, and chatbot interfaces for natural language querying. By overcoming existing proprietary limitations and providing access to a versatile single space, the proposed solution supports decision-makers in the digital transition towards a more accessible, transparent and integrated infrastructure asset management. Full article

In highly urbanised and industrialised settings, managing environmental pressures and enhancing urban resilience demand integrated, spatially explicit approaches. This study presents a methodological framework that integrates topographic data, land cover information, and open geodata to produce a high-resolution vulnerability map. A multi-criteria analysis was performed using indicators such as land use, population density, proximity to emission sources, vegetation cover, and sensitive services (e.g., schools and hospitals). The result is a high-resolution vulnerability map that classifies the urban, peri-urban, and coastal zones into five levels of environmental risk. These evaluation levels are derived from geospatial analyses combining pollutant dispersion modelling with land-use classification, enabling the identification of the most vulnerable urban zones. These findings support evidence-based planning and can guide local governments and environmental agencies in prioritising Nature-based Solutions (NBSs), enhancing ecological connectivity, and reducing exposure for vulnerable populations. Full article

This study aims to identify the added value of smart city technologies in real estate development, one of the most significant factors that would transform traditional real estate into smart ones. In total, 16 technologies utilized at both levels have been investigated. The research followed an integrative review methodology; the review is based on 168 publications. The compiled results based on metadata analysis displayed the state of each technology’s added values and usage in both scales. A total of 131 added values were identified. These added values were categorized based on the real estate life cycle sub-phases and processes. Moreover, the value of the integration between these technologies was revealed. The review and results proved that these technologies are mature enough for practical use; therefore, real estate developers, city management, planners, and experts should focus on implementing them. City management should invest in Big Data and geodata and adopt several technologies based on the aspects required for development. This study can influence stakeholders, enhance their decision-making on which technology would suit their needs, and provide recommendations on who to utilize them. Also, it provides a starting point for stakeholders who aim to establish a road map for incorporating smart technologies in future smart real estate. Full article

Geodata, geographical information science (GISc), and GeoAI (geo-intelligence workflows) play an increasingly important role in predictive disaster risk reduction and management (DRRM), aiding decision-makers in determining where and when to allocate resources. There have been discussions on the ethical pitfalls of these predictive systems in the context of DRRM because of the documented cases of biases in AI systems in other socio-technical systems. However, none of the discussions expound on how to audit geo-intelligence workflows for biases from data collection, processing, and model development. This paper considers a case study that uses AI to characterize housing stock vulnerability to flooding in Karonga district, Malawi. We use Friedman and Nissenbaum’s definition and categorization of biases that emphasize biases as a negative and undesirable outcome. We limit the scope of the audit to biases that affect the visibility of different housing typologies in the workflow. The results show how AI introduces and amplifies these biases against houses of certain materials. Hence, a group within the population in the area living in these houses would potentially miss out on DRRM interventions. Based on this example, we urge the community of researchers and practitioners to normalize the auditing of geo-intelligence workflows to prevent information disasters from biases. Full article

This study investigates the use of participatory geographic information systems (PGIS) for hazard assessment in small island developing states (SIDS), with a focus on spatial literacy and community-based disaster management. By partnering with the Lavongai community on Papua New Guinea, this research aimed to empower community members through skill development in geodata processing. The program leveraged local knowledge and the global positioning system to create participatory maps, enhancing both community capacity and researcher data quality. Workshops and focus group discussions (FGDs) were conducted to assess the community’s understanding of spatial concepts related to disaster risks. The core objective was a preliminary assessment of the community’s social and economic vulnerability to coastal disasters, using household data and GIS analysis. The results showed varied vulnerability levels within the community, highlighting the need for targeted disaster mitigation training and nature-based solutions. High-resolution satellite imagery and a simple bathtub model simulated sea level rise, identifying land-uses at risk. The program concluded with a community presentation of thematic maps, fostering collaboration and transparency. Future projects will address environmental challenges identified by local leaders and prioritize skill development, social data collection, and water resource mapping. Full article

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. Full article

Integrated geo- and environmental monitoring in mining represents a high-dimensional challenge (location, altitude/depth, time and sensors). This is challenging for experts but poses great problems for a multitude of participants and stakeholders in building up a complete process understanding. The Epe research cooperation aims to elucidate the ground movement at the Epe cavern storage facility with a public participation process. The research cooperation was founded by the city of Gronau, the citizens’ initiative cavern field Epe, the company EFTAS, Münster, and the Research Center of Post-Mining at the Technische Hochschule Georg Agricola, Bochum. This research cooperation is the first in Germany to involve direct collaboration between science and the public. In the cavern field, which has been in operation since the 1970s, brine is extracted, and at the same time natural gas, crude oil and helium, as well as hydrogen in the future, are stored in the subsurface. The technical focus of this work was the development of a high-resolution spatiotemporal analysis of ground movements. The area is monitored annually by the mining company’s mine surveyor. The complexity of the monitoring issue lies in the fact that the western part is a bog area and a former bog area. Furthermore, the soils in the eastern part are very humus-rich and show strong fluctuations in the groundwater and therefore complex hydraulic conditions. At the same time, there are few fixed scatterers or prominent points in the area that allow high-resolution spatiotemporal monitoring using simple radar interferometry methods. Therefore, the SBAS method (Small Baseline Subset), which is based on an aerial method, was used to analyze the radar interferometric datasets. Using an SBAS analysis, it was possible to evaluate a time series of 760 scenes over the period from 2015 to 2023. The results were integrated with the mine survey maps on the ground movement and other open geodata on the surface, the soil layers and the overburden. The results show complex forms of ground movement. The main influence is that of mining. Nevertheless, the influence of organic soils with drying out due to drought years and uplift in wet years is great. Thus, in dry years, ground subsidence accelerates, and in wet years, ground subsidence not only slows down but in some cases also causes uplift. This complexity of ground movements and the necessary understanding of the processes involved has been communicated to the interested public at several public information events as part of the research cooperation. In this way, an understanding of the mining process was built up, and transparency was created in the subsurface use, also as a part of the energy transition. In technical terms, the research cooperation also provides a workflow for developing the annual mine survey maps into an integrated geo- and environmental monitoring system with the development of a transparent participatory geomonitoring process to provide resilience management to a mining location. Full article

In today’s intrinsically connected world, the Water–Food–Energy–Climate Nexus (WFEC Nexus) concept provides a starting point for informed and transparent decision-making based on the trade-offs and synergies between different sectors, including aquatic ecosystems, food security, energy production, and climate neutrality. The WFEC Nexus approach is particularly applicable in regions requiring transboundary water management, such as Central Asia. Unfortunately, this region with unevenly distributed water resources—consisting of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan—is characterized by data scarcity, which limits informed decision-making. However, open-source geodata is becoming increasingly available. This paper aims to fill Central Asia’s WFEC Nexus data gap by providing an overview of key data. We collected geodata through an integrated survey of stakeholders and researchers, stakeholder consultation, and literature screening. Sixty unique datasets were identified, belonging to one of six thematic categories: (1) climate, (2) hydrology, (3) geography and topography, (4) geomorphology, (5) ecology, and (6) anthropogenic uses. For each dataset, a succinct description, including a link to the online source, is provided. We also provide possible applications of using the presented datasets, demonstrating how they can assist in conducting various studies linked to the WFEC Nexus in Central Asia and worldwide. Full article

Despite advancements, Smart Cities encounter hazards. Smart Cities’ higher reliance on interconnected systems and networks makes them susceptible to risks beyond conventional ones, leading to cascading effects. Hence, the effective use of technological innovations is vital. This effective use involves understanding the existing use of technology innovations for resilience making in Smart Cities and the wise utilisation of them as suitable for different contexts. However, there is a research gap for a fundamental study that synthesises the emerging and disruptive technologies that are being used to improve the disaster resilience in Smart Cities and how they can be classified. Therefore, this research aimed to address that need, so that a Smart City evaluating the technologies/tools for disaster resilience could wisely utilise the available resources and prioritise the most suitable for their context-specific needs. Following a comprehensive literature review, the study identified 24 technologies and/or tools for creating, sustaining, and enhancing the resilience within Smart Cities. In doing so, they should collect and manage citywide geodata and foster public participation. While the wise utilisation of the most suitable and feasible tools and technologies is a measure of smartness in a Smart City, the findings suggested four key factors with which these technologies could be assessed. These four factors included impact on society, the adoption speed by Smart Cities, the maturity of the technology, and the capabilities offered to the community. Full article

Anthropogenic threats are responsible for habitat degradation and biodiversity decline. The mapping of the distribution and intensity of threats to biodiversity can be useful for informing efficient planning in protected areas. In this study, we propose a cumulative spatial and temporal analysis of anthropogenic impacts insisting on an alpine protected area, the Gran Paradiso National Park. The applied methodology starts with the construction of a spatial and temporal dataset of anthropogenic impacts and normalization based on relative intensity. The impacts analyzed include overgrazing, helicopter flights, road networks, built-up areas, worksites, derivations and discharges, sports activities, and dams and hydroelectric power plants. Each impact was assigned a weight based on its temporal persistence. Threats maps obtained from the collected, normalized, and weighted geodata are thus obtained. Finally, the risk map is calculated by combining the impact map with the vulnerability map, estimated through the methodology outlined in the Green Guidelines of the Metropolitan City of Turin. The risk map obtained was cross-referenced with the Park’s cartography to highlight any critical issues to specific habitats. Results show that most of the territory falls in low-risk (63%) or no-risk (35%) areas. However, there are some habitats that are totally or nearly totally affected by some degree of risk, although different to zero, such as the “Lentic waters with aquatic vegetation [incl. cod. 3130]”, the “Lentic waters partially buried”, the “Mountain pine forests (Pinus uncinata) [cod. 9430]”, and the “Mixed hygrophilous woods of broad-leaved trees [incl. cod. 91E0]”. This study highlights both the potential of these analyses, which enable informed management and planning of the fruition of protected areas, and the limitations of such approaches, which require in-depth knowledge of the territory and ecosystems and how they respond to threats in order to refine the model and obtain realistic maps. Full article

Landslides often cause deaths and severe economic losses. In general, forests play an important role in reducing landslide probability because of the stabilizing effect of the tree roots. Although fruit groves consist of trees, which are similar to forests, practical land management, such as the frequent trampling of fields by laborers and compression of the terrain, may cause such land to become prone to landslides compared with forests. Fruit groves are widely distributed in hilly regions, but few studies have examined their role in landslide initiation. This study aims at filling this gap evaluating the predisposing and triggering conditions for rainfall-triggering landslides in part of Uwajima City, Japan. A large number of landslides occurred due to a heavy rainfall event in July 2018, where citrus groves occupied about 50% of the study area. In this study, we combined geodata with a regression model to assess the landslide hazard of fruit groves in hilly regions. We developed maps for five conditioning factors: slope gradient, slope aspect, normalized difference vegetation index (NDVI), land use, and geology. Based on these five maps and a landslide inventory map, we found that the landslide area density in citrus groves was larger than in forests for the categories of slope gradient, slope aspect, NDVI, and geology. Ten logistic regression models along with different rainfall indices (i.e., 1-h, 3-h, 12-h, 24-h maximum rainfall and total rainfall) and different land use (forests or citrus groves) in addition to the other four conditioning factors were produced. The result revealed that “citrus grove” was a significant factor with a positive coefficient for all models, whereas “forest” was a negative coefficient. These results suggest that citrus groves have a higher probability of landslide initiation than forests in this study area. Similar studies targeting different sites with various types of fruit groves and several rainfall events are crucial to generalize the analysis of landslide hazard in fruit groves. Full article

Most of the methods for landslide susceptibility assessment are based on mathematical relationships established between factors responsible for the triggering of the phenomenon, named the conditioning factors. These are usually derived from geographic data commonly handled through Geographical Information System (GIS) technology. According to the adopted methodology, after an initial phase conducted on the GIS platform, data need to be transferred to specific software, e.g., MATLAB, for analysis and elaboration. GIS-based risk management platforms are thus sometimes hybrid, requiring relatively complex adaptive procedures before exchanging data among different environments. This paper describes how MATLAB can be used to derive the most common landslide conditioning factors, by managing the geographic data in their typical formats: raster, vector or point data. Specifically, it is discussed how to build matrices of parameters, needed to assess susceptibility, by using grid cell mapping units, and mapping them bypassing GIS. An application of these preliminary operations to a study area affected by shallow landslides in the past is shown; results show how geodata can be managed as easily as in GIS, as well as being displayed in a fashionable way too. Moreover, it is discussed how raster resolution affects the processing time. The paper sets the future development of MATLAB as a fully implemented platform for landslide susceptibility, based on any available methods. Full article

Disaster risk management (DRM) has always been important, but nowadays, with the increasing number of disasters due to climate changes, it is becoming even more so. Every phase of DRM is heavily reliant on geodata. First of all, each disaster occurs at a specific location, and this location contains geodata, which can be used in DRM, e.g., cadastral data, GNSS data, aerial images, topographic data, elevation data, etc. Geodata are important for making faster and more accurate decisions in disaster situations. It is possible to collect these geodata from many different sources, e.g., the public sector, private sector and citizens. Nevertheless, official geodata coming from competent authorities should be the most accurate and reliable. In this paper, we investigate the importance of official geodata in DRM on several examples from recent disasters in Croatia. Official geodata produced by the Croatian State Geodetic Administration (SGA) were used in managing disasters such as floods, forest fires, earthquakes and war. Our research findings show that DRM is an area in which National Mapping and Cadastral Authorities (NMCAs) should focus more on collecting and sharing geodata and provide more dynamic and innovative products. In these challenging times, more and more geodata are becoming available from different sources, besides official ones. With this plethora of geodata, in order to be relevant and competitive, NMCAs must change their business models and offer more attractive and useful services in order to satisfy the increasing user needs and demands. This paper shows that the SGA in Croatia is on the path towards achieving this goal. Full article

Climate change resulting from global warming has an increasing impact on Earth. The resulting sea level rise is starting to be noticed in some regions today, and based on projections, could have severe consequences in the future. These consequences would primarily be felt by residents of coastal areas, but through the potential for irreparable damage to cultural heritage sites, could be significant for the general public. The primary aim of the research undertaken in this article was to assess the threat to cultural heritage objects on the case study area of Tri-City, Poland. A review of available elevation data sources for their potential use in analyses of sea level changes was required. The selection of the optimal data source for the cultural heritage threat analysis of historic sites was carried out. The analyses were conducted for three scenarios, using ArcGIS Pro 2.7 software. A series of maps were thus prepared to show the threats to specific historic sites for various global sea level rise scenarios. Even with the slightest rise in sea level, monuments could be permanently lost. The authors point out that a lack of action to stop climate change could result not only in economic but also cultural losses. Full article

In order to assess the dynamics of forests and the effectiveness of their management strategies, it is necessary to develop monitoring systems based on qualitative and quantitative tools for their conservation, valorization and restoration. This approach is particularly important for areas that have undergone intense anthropogenic transformations in the last century. In order to do this, it is first necessary to apply a chronological methodology based on historical GIS that allows the integration of different types of geodata. As a result of constantly evolving spatial analysis tools, the monitoring of landscape forest evolution is increasingly more effective and complete. Using as a case study a region representative of common processes of other Mediterranean areas (Southern Italy–Basilicata region), a diachronic analysis of 156 years was applied to evaluate the forest landscape dynamics. Starting from historical cartographies to remotely sensed data available online, a GIS-based approach was implemented to evaluate the spatial and statistical variations of the forest landscape. In this way, it was possible to assess how much, where and how the forest landscape has changed in order to provide a methodology to support more detailed and sectoral studies. Full article