Search Results (224)

This study introduces an innovative and scalable approach for automated road surface assessment by integrating Mobile Mapping System (MMS)-based LiDAR data analysis with an open-source WebGIS platform. In a U.S.-based case study, over 20 datasets were collected along Interstate I-65 in West Lafayette, Indiana, using the Purdue Wheel-based Mobile Mapping System—Ultra High Accuracy (PWMMS-UHA), following Indiana Department of Transportation (INDOT) guidelines. Preprocessing included noise removal, resolution reduction to 2 cm, and ground/non-ground separation using the Cloth Simulation Filter (CSF), resulting in Bare Earth (BE), Digital Terrain Model (DTM), and Above Ground (AG) point clouds. The optimized BE layer, enriched with intensity and color information, enabled crack detection through Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Random Forest (RF) classification, with and without intensity normalization. DBSCAN parameter tuning was guided by silhouette scores, while model performance was evaluated using precision, recall, F1-score, and the Jaccard Index, benchmarked against reference data. Results demonstrate that RF consistently outperformed DBSCAN, particularly under intensity normalization, achieving Jaccard Index values of 94% for longitudinal and 88% for transverse cracks. A key contribution of this work is the integration of geospatial analytics into an interactive, open-source WebGIS environment—developed using Blender, QGIS, and Lizmap—to support predictive maintenance planning. Moreover, intervention thresholds were defined based on crack surface area, aligned with the Pavement Condition Index (PCI) and FHWA standards, offering a data-driven framework for infrastructure monitoring. This study emphasizes the practical advantages of comparing clustering and machine learning techniques on 3D LiDAR point clouds, both with and without intensity normalization, and proposes a replicable, computationally efficient alternative to deep learning methods, which often require extensive training datasets and high computational resources. Full article

The digitization of cultural and intellectual heritage is expanding the research scope and methodologies of the scientific discipline of Humanities. Culturally diverse epigraphic systems reveal a range of methodological impediments on the way to their integration into digital epigraphic data preservation systems—EAGLE and FAIR ontologies predominantly based on Greco-Roman cultural categorization. We suggest an interdisciplinary approach—drawing from Heritage Studies, Cultural Epistemology, and Social Semiotics—to ensure the comprehensive encoding, preservation, and accessibility of at-risk cultural artifacts. Heritage Studies emphasize inscriptions as material reflections of historical memory. Cultural Epistemology helps us to understand how different knowledge systems influence data categorization, while semiotic analysis reveals how inscriptions function within their social and symbolic contexts. Together, these methods guide the integration of culturally specific information into broader digital infrastructures. The case of Ukrainian epigraphy illustrates how this approach can be applied to ensure that local traditions are accurately represented and not flattened by standardized international systems. We argue that the same methodology can also support the digitization of other non-Greco-Roman heritage. FAIR Ontology and EAGLE vocabularies prioritize standardization and interoperability, introducing text mining, GIS mapping, and digital visualization to trace patterns across the vast body of texts from different historical periods. Standardizing valuable elements of cultural categorization and reconstructing and integrating lost or underrepresented cultural narratives will expand the capacity of the above systems and will foster greater inclusivity in Humanities research. Ukrainian epigraphic classification systems offer a unique, granular approach to inscription studies as a worthwhile contribution to the broader cognitive and epistemological horizons of the Humanities. Through a balanced use of specificity and interoperability principles, this study attempts to contribute to epigraphic metalanguage by challenging the monocentric ontologies, questioning cultural biases in digital categorization, and promoting open access to diverse sources of knowledge production. Full article

Recent advances in computer science and geomatics have enabled the digitalization of complex two-dimensional and three-dimensional spatial environments and the sharing of geospatial data on the web. Simultaneously, the widespread adoption of Internet of Things (IoT) technology has facilitated the rapid deployment of low-cost sensor networks in various scientific applications. The integration of real-time IoT data acquisition in 3D urban environments lays the foundation for the development of Urban Digital Twins. This work proposes a possible low-cost solution as a sample of a structure for 3D digital twinning on the web, presenting a case study related to weather monitoring analysis. Specifically, an indoor-outdoor environmental conditions monitoring system integrated with 3D geospatial data on a 3D WebGIS platform was developed. This solution can be considered as a first step for monitoring human and environmental wellness within a geospatial analysis system that integrates several open-source modules that provide different kinds of information (geospatial data, 3D models, and IoT acquisition). The structure of this system can be valuable for municipalities and private stakeholders seeking to conduct environmental geospatial analysis using cost-effective solutions. Full article

With the development of the economy and improvements in living standards, public demand for sports activities has continued to increase. However, the supply–demand relationship of urban sports venues remains unbalanced in many cities. Existing theoretical research on the spatial allocation of sports venues predominantly focuses on macro-level functional configuration and the equitable distribution of sports resources, lacking more rigorous and quantitative evaluation frameworks for evaluating spatial allocation. This study innovatively integrates multi-source data into the assessment and sustainable optimization of sports venue allocation in urban planning, using Xi’an as a case study. By analyzing geographic information, road network topology, OpenStreetMap (OSM), population distribution, and social media Points of Interest (POI), and using analytical tools such as ArcGIS 10.8 and Stata 17, the appropriateness of resource distribution of public sports venues in Xi’an’s main urban area is evaluated from three dimensions: accessibility, equity, and spatial activity. The results reveal the appropriateness of venue distribution in urban spatial allocation, the equitable distribution of resources, and imbalances in spatial activity and resource distribution. Finally, the study proposes a series of sustainable optimization strategies, including increasing venue coverage in low-supply areas, adaptive reuse of idle industrial buildings into sports venues guided by green sustainability principles, constructing a “15-min fitness circle” spatial system, optimizing low-carbon mobility networks around venues, enhancing the compatibility of sports venues, and improving commercial operation and management capabilities. These strategies aim to optimize the distribution of public sports venues in Xi’an to improve fairness and operational efficiency in service delivery while promoting sustainable urban development. Full article

Real-time collaborative WebGIS represents a significant trend in the evolution of Geographic Information Systems. Current commercial collaborative WebGIS platforms, such as ArcGIS Online and Felt, rely on centralized servers for data storage and spatial analysis. However, this centralized architecture poses notable limitations: the software becomes non-functional in the absence of a network connection or if the service is discontinued. Moreover, data ownership resides with the commercial providers, exposing users to potential data loss in the event of service disruptions. To address these challenges, this paper introduces the concept of local-first software into WebGIS. By leveraging Conflict-free Replicated Data Types (CRDTs) and advanced web technologies, we develop a user-friendly, interactive, and offline-capable local-first WebGIS application that supports real-time collaboration. The application enables multi-user collaborative editing, offline functionality, and efficient browser-based spatial analysis. This paper outlines the design methodology and system prototype for the local-first WebGIS application, utilizing open-source software and libraries throughout the development process. Practical examples are provided to demonstrate the application’s functionality. The proposed solution enhances real-time collaboration and data security in WebGIS, ultimately improving user productivity and collaborative experiences. Full article

Groundwater recharge is critical for sustainable water management in water-scarce regions like North Algeria, where climate change and urbanization exacerbate resource challenges, particularly in the populous Algiers watershed. This study evaluates groundwater recharge potential using the Analytical Hierarchy Process (AHP) and its fuzzy extension (FAHP), integrated with Geographic Information Systems (GIS), to map recharge zones. Employing open-source data, AHP and FAHP assessed factors such as lithology, slope, and rainfall, classifying the watershed into high, moderate, and low recharge potential zones. Results show AHP identifying 44.01% (528.95 km²) as high, 52.82% (634.93 km²) as moderate, and 3.18% (38.14 km²) as low potential, with FAHP yielding similar outcomes (44.35%, 52.47%, and 3.17%, respectively). Validation using borehole drawdown data confirmed a 73.3% accuracy and an AUC of 0.72, indicating moderate to good reliability. High recharge zones were concentrated in the central and northern areas with permeable soils and gentle slopes, moderate zones dominated the region, and low zones were minimal. This study concludes that both AHP and FAHP are effective for preliminary recharge assessments, with AHP favored for its simplicity, though FAHP excels with uncertain data. Limited high-resolution hydrogeological data highlight the need for further refinement, yet the approach offers a replicable framework for managing groundwater in arid, urbanized regions facing similar environmental pressures. Full article

Introduction. The global challenge of physical inactivity necessitates innovative approaches and strategies to optimize built environments in order to promote healthy and sustainable lifestyles, such as active transportation. For this reason, walkability is a crucial area of research in urban health, with several studies focusing on assessment frameworks. However, a gap persists between theoretical development and practical implementation. This study explores the application of the Milan Walkability Measurement Tool (MWM-Tool), a walkability assessment framework previously developed by Politecnico di Milano, to evaluate the urban features in favor of walkability by integrating GIS technology with an extended testing scope. It is based on a scientific approach utilizing 10 sub-indicators divided into three macro-areas (Density, Diversity, Design), identified through a comprehensive literature review. Method. Focusing on the application of the MWM-Tool in Milan, the study employs the 88 Nuclei of Local Identity (NILs), which are the official designations for Milan’s neighborhoods, as the units of urban analysis. Based on previous experience, the digitalization of the assessment framework has been improved: geospatial data corresponding to 10 sub-indicators were filtered to generate vector layers, primarily sourced from two public geographical platforms. The GIS-based method produces thematic maps evaluating all neighborhoods according to the dimensions of Density, Diversity, and Design. Darker and lighter colors represent the range of the scores. Both single indicators and macro-area maps, as well as overall walkability level maps, were generated to illustrate the results. Result. The results of the macro dimension assessment, combining 10 sub-indicators, provide an objective view of the distribution of walkable space quality in Milan. Only 7 out of 88 neighborhoods achieved the highest score, all of which are located in the city center, while suburban areas showed significantly lower scores. By incorporating census GIS data, the study also identified the population distribution across areas with varying walkability levels. Based on the results of the assessment, it may be possible to develop and prioritize the optimization of walkable features, revitalizing underserved areas and fostering a healthier community environment. Conclusion. The georeferenced-data maps represent an effective tool to highlight both neighborhoods with high urban quality, which could be used to promote active mobility and healthy lifestyle adoption, as well as those requiring improvement strategies from policy and decision makers. The research output provides a reference for further urban planning initiatives in Milan and contributes to enhancing pedestrian-oriented built environments. Using GIS open-source data, the method is scalable and can be easily replicated in other cities. It could also be used as a system for monitoring walkability over time. Full article

The rapid urbanization of recent decades has intensified climate change challenges, demanding sophisticated solutions to build resilient and sustainable cities. A key aspect of sustainable urban planning is decentralizing and democratizing its processes, which requires citizen involvement from the early design stages. While current solutions such as digital tools, participatory workshops, gamification, and social media can enhance participation, they often exclude non-experts or those lacking digital skills. To address these limitations, this manuscript proposes a VR/AR gamified solution using open-source software and open GIS data. Specifically, it investigates the euPOLIS game as an innovative participatory tool offering an alternative to traditional approaches. This game decentralizes urban planning by shifting technical tasks to experts while citizens engage interactively, focusing solely on proposing solutions. To explore the potential of the proposed methodology, the euPOLIS game was demonstrated as a workshop activity in TNOC 2024 Festival, where 30 individuals from different academic background (i.e., citizens, architects, planners, etc.) voluntarily engaged and provided their impressions and feedback. The findings suggest that gamified solutions such as serious/simulation AR/VR games can effectively promote co-design, co-participation, and co-creation in urban planning in an inclusive and engaging manner. Full article

This paper provides a methodology for improving the modelling and design of BIPV façades through in-depth solar irradiation calculations using free and open-source software, mainly GIS, in addition to free data, such as LiDAR, cadastres and meteorological databases. The objective is to help BIPV design with a universal and easy-to-replicate procedure. The methodology is validated with the case study of Building 42 in the CIEMAT campus in Madrid, which was renovated in 2017 to integrate photovoltaic arrays in the east, south and west façades, with monitoring data of the main electrical and meteorological conditions. The main novelty is the development of a methodology where LiDAR data are combined with building vector information to create an enhanced high-definition DSM, which is used to develop precise yearly, monthly and daily façade irradiation estimations. The simulation takes into account terrain elevation and surrounding buildings and can optionally include existing vegetation. Gridded heatmap layouts for each façade area are provided at a spatial resolution of 1 metre, which can translate to PV potential. This methodology can contribute to the decision-making process for the implementation of BIPV in building façades by aiding in the selection of the areas that are more suitable for PV generation. Full article

The transition to renewable energy is crucial for combating climate change but faces challenges like local socio-environmental impacts and territorial conflicts. Scientific research on mapping renewable energy suitability areas and identifying socio-culturally and environmentally sensitive zones is essential to guide project siting appropriately. This study proposes a replicable methodology to analyze scenarios and compare alternatives for agrivoltaics plant siting, using the province of Viterbo, Italy, as a case study. The methodology employs spatial data, thematic maps, and multi-criteria analysis in open-source GIS software to identify suitable solar belts, map environmental sensitivity through 14 criteria, and assess visual sensitivity based on proximity to landscape elements. The resulting workflow and customizable QGIS models provide a comprehensive, transparent decision-support tool to optimize agrivoltaics deployment while minimizing impacts and enhancing acceptance. Mapping multi-factor sensitivity offers crucial insights for sustainable planning and design. The Viterbo case study illustrates the ‘conflict between green alternatives’ where renewable energy development potential clashes with environmental and landscape protection needs. The analysis reveals significant spatial variability in suitability and sensitivity among the province’s municipalities. The study highlights the importance of a nuanced approach to assessing suitability, moving beyond simple binary classification, and provides a tool adaptable to different regulations and contexts. Full article

The study explores the impact of floods, phenomena amplified by climate change and human activities, on the natural and anthropogenic environment, focusing on the analysis of a section of the Cigher River in the Crișul Alb basin in western Romania. The research aims to identify areas vulnerable to flooding under different discharge scenarios, assess the impact on agricultural lands, and propose a reproducible methodology based on the integration of GIS technologies, hydraulic modeling in HEC-RAS, and the use of LiDAR data. The methodology includes hydrological analysis, processing of the Digital Elevation Model (DEM), delineation of geometries, hydraulic simulation for four discharge scenarios (S1–S4), and evaluation of the flood impact on agricultural and non-agricultural lands. Evaluated parameters, such as water velocity and flow section areas, highlighted an increased flood risk under maximum discharge conditions. The results show that scenario S4, with a discharge of 60 m³/s, causes extensive flooding, affecting 871 hectares of land with various uses. The conclusions emphasize the importance of using modern technologies for risk management, protecting vulnerable areas, and reducing economic and ecological losses. The proposed methodology is also applicable to other river basins, representing a useful model for developing sustainable strategies for flood prevention and management. Full article

The closure of coal and lignite mines has the potential to result in long-term environmental risks and socio-economic issues. To solve these, this research aims to improve the hazard assessment and risk management of former mining regions in a European project funded by the Research Fund for Coal and Steel. A multidisciplinary approach integrated historic, geological, topographical, environmental, and socio-economic data to create a methodology to support stakeholders at different decision-making levels in risk assessment and possible mitigation. For this purpose, a spatial decision support system was developed using a multi-hazard, multi-risk methodology. The individual hazards (post-mining, natural, and technical) are weighted using expert knowledge, their interaction analyzed, and then combined into a spatial multi-hazard index. Together with the other risk factors of social vulnerability and exposure, a comprehensive spatial risk map can be created automatically for individual regions using open-source components. In addition, GIS and statistical tools enable further analysis and visualization for decision-making by the relevant stakeholders. The methodology was validated through the examination of a first case study conducted in the post-mining region of the southern Ruhr area in Germany. The methodology and tool created significant results in two test scenarios, and will be tested and improved using other European mining sites during the next stages of the project. Full article

Children’s playgrounds are an important component providing opportunities for children’s play. Few studies, however, have explored the unequal geographic provision of these valuable spaces. This work addressed this research gap by identifying the key data and methods required to analyse children’s playground provision at both global and national geographic scales. The aims of the paper were twofold: It firstly explored the potential for mapping children’s playground provision at a global scale and validated such an approach using finer spatial scales. Secondly, the unequal provision of playgrounds was investigated at a national scale in England, UK using open data sources. Relationships with the size of the settlement and deprivation were also explored. The work used a range of secondary datasets through applying quantitative GIS and statistical approaches. The results demonstrated that, due to data quality issues, a world approach to map playground provision was not currently viable. At a national scale, results highlighted substantial inequality in provision, with some settlements in England experiencing five times the number of children per playground, despite being broadly comparable in terms of population. Deprived settlements in England tended to have fewer, smaller, and further-away playgrounds. The patterns were most stark in the largest settlements. London, however, was consistently an exception to these patterns, where deprived areas tended to have more and closer playgrounds. Acknowledging the numerous competing different metrics to measure provision of children’s playgrounds, the research generated a framework for bringing together a wide range of interrelated data into a condensed form for comparison. Thus, the approach facilitated the identification of interventions within different contexts in order to reduce inequalities in playground provision and bolster children’s democratic right to the city for play. Full article

Landslides are a major global threat, endangering lives, infrastructure, and economies. This paper introduces the Geohazard plugin, an open-source tool for QGIS, designed to support medium–small-scale landslide analysis and management. The plugin integrates several algorithms, including the Groundmotion–C index for evaluating SAR data reliability, Landslide–Shalstab for assessing shallow landslide susceptibility, and Rockfall–Droka for estimating rockfall invasion areas and the rockfall relative (spatial) hazard. An application example is provided for each module to facilitate validation and discussion. A case study from the Western Italian Alps highlights the practical application of the Rockfall–Droka modules, showcasing their potential to identify critical zones by integrating the results on affected areas, process intensity, and preferential paths. Emphasis is given to the calibration of model parameters, a critical aspect of the analysis, achieved through a back-analysis of a rockfall event that occurred in June 2024. The Geohazard plugin streamlines geohazard assessments, providing land managers with actionable insights for decision-making and risk mitigation strategies. This user-friendly GIS tool contributes to enhancing resilience in landslide-prone regions. Full article

Cesium is an open-source 3D virtual earth engine based on WebGL and one of the most widely used 3D GIS engines. The 3DTiles rendering parameters in Cesium improve rendering efficiency but involve numerous data types and complex interdependencies, making simultaneous optimization challenging. In this paper, we proposed a multi-strategy probabilistic discrete differential evolution algorithm (MSPDDE) for finding the optimal values of the rendering parameters of Cesium 3DTiles model, which increases the search space and improves the convergence speed by introducing multiple mutation strategies. These strategies effectively reduce the probability of falling into local optimality due to too many parameters and deal with discrete variables in the rendering parameters by applying a probabilistic discretization strategy to the discrete variables so that MSPDDE is able to find all the rendering parameter optima of Cesium 3DTiles. Under three different sizes of 3DTiles model cases, the rendering model time using the optimal parameter configurations found by the algorithm is reduced by 28.84%, 27.89%, and 13.32%, respectively, compared with the default parameter configurations of Cesium, which shortens the time of rendering 3DTiles models by Cesium. Full article