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The evaluation, visualization of environmental data from long-term monitoring, and making them accessible in a processed form in user-friendly interfaces on the Internet are important tasks of our time. The pollution of groundwater resources in settlements is a global phenomenon, the mitigation of which requires a number of environmental measures. In this study, water quality changes following the construction of a sewerage network were examined in the course of long-term monitoring between 2013 and 2022, during which 40 municipal groundwater wells were regularly sampled. Classifying the monitoring data into pollution categories based on water quality index (WQI) and degree of contamination index (Cd), a high degree of contamination was found in the period before the installation of the sewerage network (2014), as the majority of the wells were classified as contaminated and heavily contaminated. In the monitoring period following the installation of the sewerage network, a significant positive change was found in the case of most of the water chemical parameters tested (EC, NH4+, NO2−, NO3−, PO43−). Based on interpolated maps, it was found that an increasing part of the area shows satisfactory or good water quality. This was confirmed by the discriminant analysis as well, as it is possible to determine with an accuracy of 80.4% whether the given sample originates from the period before or after the installation of the sewerage network based on the given water chemical parameters. However, 8 years after setting up the sewerage network, the concentration of inorganic nitrogen forms and organic matter remains high, indicating that the accumulated pollutants in the area are still present. To understand the dynamics of purification processes, additional, long-term monitoring is necessary. Making these data available to members of the society can contribute to appropriate environmental measures and strategies. [ABSTRACT FROM AUTHOR]

Featured Application: The SMARTerra decision support system provides high-resolution risk maps related to plant diseases and pests, enabling prompt and targeted intervention that minimizes environmental impact while minimizing economic losses. The prediction and monitoring of plant diseases and pests are key activities in agriculture. These activities enable growers to take preventive measures to reduce the spread of diseases and harmful insects. Consequently, they reduce crop loss, make pesticide and resource use more efficient, and preserve plant health, contributing to environmental sustainability. We illustrate the SMARTerra decision support system, which processes daily measured and predicted weather data, spatially interpolating them at high resolution across the entire Sardinia region. From these data, SMARTerra generates risk predictions for plant pests and diseases. Currently, models for predicting the risk of rice blast disease and the hatching of locust eggs are implemented in the infrastructure. The web interface of the SMARTerra platform allows users to visualize detailed risk maps and promptly take preventive measures. A simple notification system is also implemented to directly alert emergency responders. Model outputs by the SMARTerra infrastructure are comparable with results from in-field observations produced by the LAORE Regional Agency. The infrastructure provides a database for storing the time series and risk maps generated, which can be used by agencies and researchers to conduct further analysis. [ABSTRACT FROM AUTHOR]

Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75–0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates. [ABSTRACT FROM AUTHOR]

Heritage and culture tourism involve features that commemorate a valued past. Mining heritage tourism allows visitors to experience the past, guided by former mining landscapes and engaging interactively with material artifacts. This paper introduces the CoalHeritage European project, focusing on the promotion of coal mining heritage through the production and design of the European Visual Map Journal (EVMJ). The EVMJ is a user-friendly, web-based, interactive storytelling platform that supports the transfer of industrial and geoheritage from former coal mining areas. It aims to collect and disseminate heritage assets from post-mining coal areas, informing stakeholders and promoting these sites as tourist destinations. To further enhance public awareness, several ESRI StoryMaps web apps are being created to highlight specific features of each case study across Europe. The aim of this work is to introduce coal mining heritage as a new term, present the coal heritage platform and its importance for disseminating coal heritage aspects to the public, describe the methodology used for its design, and provide a brief overview of its evolving content. [ABSTRACT FROM AUTHOR]

Geographic information systems (GISs) based on WebGIS architectures have transformed geospatial data visualization and analysis, offering rapid access to critical information and enhancing decision making across sectors. This study conducted a bibliometric review of 358 publications using the Web of Science database. The analysis utilized tools, such as Bibliometrix (version R 4.3.0) and Biblioshiny (version 1.7.5), to study authors, journals, keywords, and collaborative networks in the field of information systems. This study identified two relevant clusters in the literature: (1) voluntary geographic information (VGI) and crowdsourcing, focusing on web integration for collaborative mapping through contributions from non-professionals and (2) GIS management for decision making, highlighting web-based architectures, open sources, and service-based approaches for storing, processing, monitoring, and sharing geo-referenced information. The journals, authors, and geographical distribution of the most important publications were identified. China, Italy, the United States, Germany, and India have excelled in the application of geospatial technologies in areas such as the environment, risk, sustainable development, and renewable energy. These results demonstrate the impact of web-based GISs on forest conservation, climate change, risk management, urban planning, education, public health, and disaster management. Future research should integrate AI, mobile applications, and geospatial data security in areas aligned with sustainable development goals (SDGs) and other global agendas. [ABSTRACT FROM AUTHOR]

Abstract Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75–0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates.

Heritage and culture tourism involve features that commemorate a valued past. Mining heritage tourism allows visitors to experience the past, guided by former mining landscapes and engaging interactively with material artifacts. This paper introduces the CoalHeritage European project, focusing on the promotion of coal mining heritage through the production and design of the European Visual Map Journal (EVMJ). The EVMJ is a user-friendly, web-based, interactive storytelling platform that supports the transfer of industrial and geoheritage from former coal mining areas. It aims to collect and disseminate heritage assets from post-mining coal areas, informing stakeholders and promoting these sites as tourist destinations. To further enhance public awareness, several ESRI StoryMaps web apps are being created to highlight specific features of each case study across Europe. The aim of this work is to introduce coal mining heritage as a new term, present the coal heritage platform and its importance for disseminating coal heritage aspects to the public, describe the methodology used for its design, and provide a brief overview of its evolving content.

Landslides represent a growing threat among the various morphological processes that cause damage to territories. To address this problem and prevent the associated risks, it is essential to quickly find adequate methodologies capable of predicting these phenomena in advance. The following study focuses on the implementation of an experimental WebGIS infrastructure designed and built to predict the susceptibility index of a specific presumably at-risk area in real time (using specific input data) and in response to extreme weather events (such as heavy rain). The climate data values are calculated through an innovative and experimental atmospheric simulator developed by the authors, which is capable of providing data on meteorological variables with high spatial precision. To this end, the terrain is represented through cellular automata, implementing a suitable neural network useful for producing the desired output. The effectiveness of this methodology was tested on two debris flow events that occurred in the Calabria region, specifically in the province of Reggio Calabria, in 2001 and 2005, which caused extensive damage. The (forecast) results obtained with the proposed methodology were compared with the (known) historical data, confirming the effectiveness of the method in predicting (and therefore signaling the possibility of an imminent landslide event) a higher susceptibility index than the known one and one provided (to date) by the Higher Institute for Environmental Protection and Research (ISPRA), validating the result obtained through the actual subsequent occurrence of a landslide event in the area under investigation. Therefore, the method proposed today is not aimed at predicting the local movement of a small landslide area, but is primarily aimed at predicting the change or improving the variation of the landslide susceptibility index to compare the predicted value with the current one provided by the relevant bodies (ISPRA), thus signaling an alert for the entire area under investigation.

The Soprintendenza Speciale di Roma is developing a new application to set up a 'Map of the Archaeological Potential of Rome' within the SITAR platform. The research group is developing a solid system for the Rome Archaeological Potential Map, which is based on the great documentary heritage included in the system, i.e. 25,000 archaeological partitions and over 10,000 cores collected and processed. With a view to a participatory philosophy, this tool will be implemented through the input of data entered by individual users of the platform. The final elaboration will soon be available on the SITAR webgis. [ABSTRACT FROM AUTHOR]

To solve the problems in the traditional railway engineering surveying process, including unsound project management system, difficulty in resource allocation between projects, lack of the number of person and equipment in the project, and lack of intuitive overall data for production projects and outdated information technology means. This paper developed a railway surveying production management system based on J2EE business construction mode and Vue front-end and back-end separation technology, making the use of the open-source WebGIS framework Leaflet as the basis for visualizing maps. Combining with images, maps, vector features and other data, the system realized the locating, information querying, and whole-process management of person, equipment, and vehicles in the production projects. It utilized spatial analysis functions to assist in decision-making for the scheduling of person and equipment near project areas, fully utilizing production elements. The application testing was conducted on the refined measurement network resurvey project of the Xi'an - Yan'an high-speed railway Tongchuan section to verify the integrity and usability of the system throughout the process of starting, planning, allocating. The research indicates that the system effectively enhances the management efficiency of surveying production projects by standardizing the production system process and realize the information management of production projects. [ABSTRACT FROM AUTHOR]

Monitoring and evaluation of soil ecological environments are very important to ensure saline–alkali soil health and the safety of agricultural products. It is of foremost importance to, within a regional ecological risk-reduction strategy, develop a useful online system for soil ecological assessment and prediction to prevent people from suffering the threat of sudden disasters. However, the traditional manual or empirical parameter adjustment causes the mismatch of the hyperparameters of the model, which cannot meet the urgent need for high-performance prediction of soil properties using multi-dimensional data in the WebGIS system. To this end, this study aims to develop a saline–alkali soil ecological monitoring system for real-time monitoring of soil ecology in the Yellow River Delta, China. The system applied advanced web-based GIS, including front-end and back-end technology stack, cross-platform deployment of machine learning models, and a database embedded in multi-source environmental variables. The system adopts a five-layer architecture and integrates functions such as data statistical analysis, soil health assessment, soil salt prediction, and data management. The system visually displays the statistical results of air quality, vegetation index, and soil properties in the study area. It provides users with ecological risk assessment functions to analyze heavy metal pollution in the soil. Specially, the system introduces a tree-structured Parzan estimator (TPE)-optimized machine learning model to achieve accurate prediction of soil salinity. The TPE–RF model had the highest prediction accuracy (R2 = 94.48%) in the testing set in comparison with the TPE–GBDT model, which exhibited a strong nonlinear relationship between environmental variables and soil salinity. The system developed in this study can provide accurate saline–alkali soil information and health assessment results for government agencies and farmers, which is of great significance for agricultural production and saline–alkali soil ecological protection. [ABSTRACT FROM AUTHOR]

Securing combat equipment for urgent special missions, such as rescue, fire protection, chemical prevention, and military operations, is crucial in technical logistics. Rapid preparation and mobilisation of forces in response to the reality of the tasks are essential. A software system that stores a complete database of equipment, human resources, and navigation maps is required. This article explores the application of Open Source WebGIS technologies, such as Geoserver, PostGIS, OpenLayer, GraphHopper, and Python, in experimentally building management software for searching equipment, units, and navigation. It supports decision-making by allowing users to select the optimal response plan based on digital maps. The software integrates spatial analysis and routing techniques to locate units with suitable equipment, either nearest or within a specified radius. Users can thereby determine the optimal route from the selected unit to the mobilisation site. Testing with fire prevention data in Hanoi city showed that the search results for the optimal route are precisely equivalent to those provided by current Google Maps. This research has initially mastered data and technology to proactively update and manage data in areas lacking industry-specific information that existing software does not cover.

Mine ecological environment monitoring and governance is a critical requirement for national ecological civilization construction and the dual carbon goal. The informatization and intelligent construction of the mine ecological environment have become an important part of Digital China driven by the new generation of information technology, and it is also an inevitable trend in the development of the current era. However, existing mine ecological environment monitoring systems are still in the primary stage with a single theme, incomplete elements, basic measurement, and local management, and they cannot meet the demand for multi-element, long-term, high-frequency monitoring and analysis of the mine ecological environment. To address this problem, the quantitative remote sensing monitoring and intelligent analysis system for the mine ecological environment under B/S architecture is proposed, called Mine Ecology Remote Eyes. The development requirements, technical framework, key technologies, and core functions of the system are further described in detail. The system utilizes satellite remote sensing technology and other monitoring methods to obtain and aggregate mine ecological big data from different sources, forming a map of mine distribution and data resource services. Using quantitative remote sensing to invert ecological parameters of mine environments, a set of long-term and multi-element monitoring products can be generated. These products cover various ecological elements such as human activities, natural geographical conditions, and “vegetation-soil-water-atmosphere” parameters. The system provides a range of tools for GIS spatial and temporal analysis, statistical analysis, and comprehensive quantitative evaluation. With these tools, users can monitor spatial changes in ecological parameters such as land use and normalized difference vegetation index (NDVI) in mining areas along with mining activities, as well as query and visualize historical statistical values of ecological elements such as soil water content and suspended solids concentration in water under different spatiotemporal locations or regions. Additionally, the system enables comprehensive quantitative evaluation of the quality of the mine ecological environment taking into account multiple ecological elements. Finally, the system generates a monitoring report on ecological disturbance and governance of the mine. The application of Mine Ecology Remote Eyes will facilitate the change monitoring, data management, intelligent analysis, and decision-making applications of the mine ecological environment. This system has the potential to improve the efficiency and intelligence level of monitoring and governance of the mine ecological environment, and provides a reference for promoting the informatization of ecological civilization.

El inventario del patrimonio arquitectónico debe enfrentarse a problemas de gestión y almacenamiento de grandes cantidades de información en formatos heterogéneos, además de la necesidad de organizar y administrar la información generada por el trabajo colaborativo entre los diferentes técnicos que participan en el proceso de documentación. La solución implica la creación de una base normalizada para planificar y ejecutar el registro digital de la documentación gráfica. Con este fin, se presenta un Sistema de Información del Patrimonio Arquitectónico Mudéjar de Aragón, con el propósito de integrar bajo un soporte común, toda la documentación e información gráfica disponible del elemento patrimonial, con el propósito de elaborar un inventario para su conservación y divulgación. Se plantea la implementación de una herramienta que permita la difusión y explotación de la información por parte de diferentes usuarios a través de un portal web que integre un visor cartográfico (WebGIS) y el acceso a un gestor de nube de puntos basado en WebGL.

Landslides represent a growing threat among the various morphological processes that cause damage to territories. To address this problem and prevent the associated risks, it is essential to quickly find adequate methodologies capable of predicting these phenomena in advance. The following study focuses on the implementation of an experimental WebGIS infrastructure designed and built to predict the susceptibility index of a specific presumably at-risk area in real time (using specific input data) and in response to extreme weather events (such as heavy rain). The climate data values are calculated through an innovative and experimental atmospheric simulator developed by the authors, which is capable of providing data on meteorological variables with high spatial precision. To this end, the terrain is represented through cellular automata, implementing a suitable neural network useful for producing the desired output. The effectiveness of this methodology was tested on two debris flow events that occurred in the Calabria region, specifically in the province of Reggio Calabria, in 2001 and 2005, which caused extensive damage. The (forecast) results obtained with the proposed methodology were compared with the (known) historical data, confirming the effectiveness of the method in predicting (and therefore signaling the possibility of an imminent landslide event) a higher susceptibility index than the known one and one provided (to date) by the Higher Institute for Environmental Protection and Research (ISPRA), validating the result obtained through the actual subsequent occurrence of a landslide event in the area under investigation. Therefore, the method proposed today is not aimed at predicting the local movement of a small landslide area, but is primarily aimed at predicting the change or improving the variation of the landslide susceptibility index to compare the predicted value with the current one provided by the relevant bodies (ISPRA), thus signaling an alert for the entire area under investigation. [ABSTRACT FROM AUTHOR]

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The COVID-19 pandemic has had a profound impact worldwide and continues to spread due to various mutations of the virus. Many governmental and nonprofit agencies at different levels have quickly developed COVID-19 dashboards to disseminate information on the pandemic to the public. However, most of these systems have mainly distributed "plain" information (e.g. cases, death counts, vaccination), and rarely provided insights that can be gained from spatiotemporal analyses, such as the detection of emerging clusters. The results from these analyses hold tremendous potential for health policymakers as they try to identify ways to slow down transmission. We present a web-based geographic framework to detect and visualize space-time clusters of COVID-19. Our tightly coupled framework integrates the prospective space-time scan statistics and local indicators of spatial association (LISA) with novel 2D and 3D interactive visuals in a cyber environment (). We illustrate the applicability of our approach using COVID-19 data for the continental US. Our framework is portable to other regions that may experience infectious diseases but is also flexible to handle data of different spatial and temporal granularities. This paper fits within an effort to integrate space-time analytics for the monitoring of infectious diseases in web environment, ultimately improving health surveillance systems. [ABSTRACT FROM AUTHOR]

In times of the COVID-19 pandemic, teachers on all levels have had to adapt to an online or hybrid teaching environment. People in geography, a discipline that traditionally values field trips to connect theory to practice, have had to find online alternatives for educational activities that normally would have taken place in the field. This has led to several innovative practices, which, however, have only to a limited degree been purposively tested for efficacy because of the ad-hoc, enforced nature of the required changes. This project deals with this issue by studying, through student workshops dealing with the creation of online didactic walking routes in two cities, how students can obtain specific geographical competences such as interpreting different historical layers that collectively shape the current urban fabric through online cartography. We found that students reported clear improvements in geographical reasoning skills, regarding both GIS and heritage interpretation. There were no clear patterns regarding the role of familiarity with the studied city for the quality of the produced story maps. On final reflection, we argue that online cartographic exercises are a valuable addition to the geographers' educational toolkit to bounce forward to a more resilient, reflective educational practice after the pandemic. [ABSTRACT FROM AUTHOR]

In recent years the role of preventive archaeological investigations - and consequently that of archaeologists -in territorial and urban transformation became more and more important; On the other hand, the time allocated to archaeological investigation is often severely compressed: so, it is essential to exercise targeted and effective action and, even more so, to have in-depth knowledge of the context on which the project impacts. The National Geoportal for Archaeology is a useful tool, making archaeological data available for consultation and free reuse. Its usefulness is growing every day, thanks to recent provisions that provide for the use of the GNA as a standard for the delivery of minimum data for all archaeological investigations. [ABSTRACT FROM AUTHOR]

One of the most important obstacles for taking advantage of forest resources in the Italian Alps is represented by the high level of private properties fragmentation and by their small size. Thus, there is an urgent need for tools to support single or multi-forest owners to gain reliable and updated information on their forest stands so that the proper silvicultural activities following all the existing regulations can be adopted. The present research was aimed at promoting a shared management of small private forest properties in the mountainous area of Friuli Venezia Giulia (NE Italy) through the implementation of a new WebGIS tool to support forest decisions and management at different spatial scales. This new tool was developed updating and merging together different available information sources (e.g., tree species composition, the presence of protected areas, forest roads, etc.) with ad-hoc elaborated layers (e.g., standing volume, annual increment of volume, forest accessibility, etc.), also elaborating a cost analysis related to the different possible harvesting methods. The tool allows queries at the level of either a single or a group of cadastral parcels to obtain data in a format, which can be used for filling in the planning document requested by the regional authorities.

The prediction and monitoring of plant diseases and pests are key activities in agriculture. These activities enable growers to take preventive measures to reduce the spread of diseases and harmful insects. Consequently, they reduce crop loss, make pesticide and resource use more efficient, and preserve plant health, contributing to environmental sustainability. We illustrate the SMARTerra decision support system, which processes daily measured and predicted weather data, spatially interpolating them at high resolution across the entire Sardinia region. From these data, SMARTerra generates risk predictions for plant pests and diseases. Currently, models for predicting the risk of rice blast disease and the hatching of locust eggs are implemented in the infrastructure. The web interface of the SMARTerra platform allows users to visualize detailed risk maps and promptly take preventive measures. A simple notification system is also implemented to directly alert emergency responders. Model outputs by the SMARTerra infrastructure are comparable with results from in-field observations produced by the LAORE Regional Agency. The infrastructure provides a database for storing the time series and risk maps generated, which can be used by agencies and researchers to conduct further analysis.

The inventory of architectural heritage must deal with problems of managing and storing large amounts of information in heterogeneous formats, in addition to the necessity to organize and manage the information generated by the collaborative work between the different technicians involved in the documentation process. The solution involves the creation of a standardized base to plan and execute the digital recording of graphic documentation. To this end, an Information System of the Mudejar Architectural Heritage of Aragon is presented, with the purpose of integrating under a common support, all the documentation and graphic information available on the heritage element, with the purpose of preparing an inventory for its conservation and dissemination. The implementation of a tool that allows the dissemination and exploitation of information by different users through a web portal that integrates a cartographic viewer (WebGIS) and access to a point cloud manager based on WebGL is proposed. [ABSTRACT FROM AUTHOR]

Underground coal mining will inevitably cause serious ground deformation, and therefore, preventive mining-induced deformation analysis (MIDA) is of great importance in assisting mining planning and decision-making. Current web-based Geographic Information System (webGIS)-based applications usually use 2D GIS data and lack a holistic framework. This study presents a multi-scalar oblique photogrammetry-supported unified 3D webGIS framework for MIDA applications to fill this gap. The developed web platform uses multiple open-source JavaScript libraries, and the prototype system provides user-friendly interfaces for GIS data collecting and corresponding database establishment, geo-visualization and query, dynamic prediction, and spatial overlapping analysis within the same framework. The proposed framework was tested and evaluated in the Qianyingzi mining area in eastern China. The results demonstrated that multi-scalar oblique photogrammetry balances data quality and acquisition efficiency and provides a good source of GIS datasets, and the web-based platform has a good absolute and relative spatial accuracy verified by two types of validation data. Practical application results proved the feasibility and reliability of the system. The developed web-based MIDA prototype system attains an appealing performance and can be easily extended to similar geoscience applications. [ABSTRACT FROM AUTHOR]

Scientific studies concentrated in Antarctica hold great value and importance for humanity. Research projects are conducted in various disciplines on the continent, where nearly 100 research stations from 30 countries are established. Despite the challenges posed by Antarctica's natural structure, unique environment, difficult working conditions, and limited logistics opportunities, scientific research conducted there is indispensable due to the valuable information it offers. In pursuit of accessing this information, Turkish Antarctic expeditions have been organized since 2017. In this study, a polar data center was established through a web-based geographic information system (WebGIS), a significant infrastructure for the continuity of scientific studies. The implemented projects and raw/processed data from previous expeditions in diverse subjects and disciplines, including geology, geophysics, geography, hydrology, meteorology, oceanography, glaciology, atmospheric physics, chemistry, microbiology, and remote sensing, were incorporated into this information system. Studies in Antarctica have primarily focused on observing the effects of global warming, necessitating the monitoring of past and current data related to sea ice, sea level, and coastal changes. The data also encompasses seismic, volcanic, tectonic, and Global Navigation Satellite System (GNSS) monitoring. As suggested by the Antarctic Treaty, a user-friendly website was designed and made accessible for research projects, data, and publications. An entity relationship diagram was created for the fields to be included in the database. These fields were structured as tables using structured query language (SQL) queries in PgAdmin. A workspace and storage area were created in GeoServer, and a connection was established with PostGIS. Layers of spatial and nonspatial data from the PgAdmin application were added to the GeoServer workspace. The data transferred to GeoServer were presented in an OpenLayers web map with Web Map Service (WMS) and Web Feature Service (WFS) according to Open Geospatial Consortium (OGC) standards. Additionally, a mini web map was designed using the desktop Quantum GIS (QGIS) application and GIS Cloud collaboration, displaying GNSS and meteorological (weather) observation stations on the continent. A dynamic web project was employed for coding in Eclipse software, where backend coding was done with JavaScript. SQL was used as a part of the backend to integrate data from the database per request. Frontend coding for the website's visual side was completed with HTML, CSS, and JavaScript. As a result, a WebGIS platform was developed where researchers can register, add projects, and publications, and view data on a map. Users can download, analyze, and utilize the available data. The data center's existence underscores the importance of polar science and serves as an incentive for further research. [ABSTRACT FROM AUTHOR]

Here we show the SAVEMEDCOASTS-2 web-based geographic information system (webGIS) that supports land planners and decision makers in considering the ongoing impacts of Relative Sea Level Rise (RSLR) when formulating and prioritizing climate-resilient adaptive pathways for the Mediterranean coasts. The webGIS was developed within the framework of the SAVEMEDCOASTS and SAVEMEDCOASTS-2 projects, funded by the European Union, which respond to the need to protect people and assets from natural disasters along the Mediterranean coasts that are vulnerable to the combined effects of Sea Level Rise (SLR) and Vertical Land Movements (VLM). The geospatial data include available or new high-resolution Digital Terrain Models (DTM), bathymetric data, rates of VLM, and multi-temporal coastal flooding scenarios for 2030, 2050, and 2100 with respect to 2021, as a consequence of RSLR. The scenarios are derived from the 5th Assessment Report (AR5) provided by the Intergovernmental Panel on Climate Change (IPCC) and encompass different Representative Concentration Pathways (RCP2.6 and RCP8.5) for climate projections. The webGIS reports RSLR scenarios that incorporate the temporary contribution of both the highest astronomical tides (HAT) and storm surges (SS), which intensify risks to the coastal infrastructure, local community, and environment. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency of submarine pipeline inspection, and manage inspection data more reasonably and effectively, so as to analyze and predict pipeline health status more scientifically, an efficient and intelligent submarine pipeline inspection management platform was constructed by using WebGIS and 3D visualization technology. The platform has functions such as automatic management of job flow, visual monitoring of job site, intelligent analysis and visual display of inspection data. The results of applications show that the platform is advanced and reliable, and can enable the submarine pipeline inspection system to be automated, visualized and intelligent. The improvement and promotion of the platform will be of great significance to ensure the high efficiency and low fault operation of China′s submarine pipelines.

Monitoring and evaluation of soil ecological environments are very important to ensure saline–alkali soil health and the safety of agricultural products. It is of foremost importance to, within a regional ecological risk-reduction strategy, develop a useful online system for soil ecological assessment and prediction to prevent people from suffering the threat of sudden disasters. However, the traditional manual or empirical parameter adjustment causes the mismatch of the hyperparameters of the model, which cannot meet the urgent need for high-performance prediction of soil properties using multi-dimensional data in the WebGIS system. To this end, this study aims to develop a saline–alkali soil ecological monitoring system for real-time monitoring of soil ecology in the Yellow River Delta, China. The system applied advanced web-based GIS, including front-end and back-end technology stack, cross-platform deployment of machine learning models, and a database embedded in multi-source environmental variables. The system adopts a five-layer architecture and integrates functions such as data statistical analysis, soil health assessment, soil salt prediction, and data management. The system visually displays the statistical results of air quality, vegetation index, and soil properties in the study area. It provides users with ecological risk assessment functions to analyze heavy metal pollution in the soil. Specially, the system introduces a tree-structured Parzan estimator (TPE)-optimized machine learning model to achieve accurate prediction of soil salinity. The TPE–RF model had the highest prediction accuracy (R2 = 94.48%) in the testing set in comparison with the TPE–GBDT model, which exhibited a strong nonlinear relationship between environmental variables and soil salinity. The system developed in this study can provide accurate saline–alkali soil information and health assessment results for government agencies and farmers, which is of great significance for agricultural production and saline–alkali soil ecological protection.

This paper focuses on the reconstruction of the social and economic conditions of the Grand Duchy of Tuscany in the mid eighteen thirties on the basis of recent geohistorical information. To perform this reconstruction, we georeferenced information relating to the nineteenth-century factories and shops recorded in the Land Registry. To date, this aspect has received little attention when considering the historiographic traditions of this area, firmly rooted in a sharecropping system based on the three main Mediterranean agricultural products. The use of geostatistical tools allowed us to determine the height and slope of each of the geometries in the two geodatabases. We were also able to create positive spatial data autocorrelations, determine specific production and trading areas and thus determine the anthropisation levels of these territories in the outlying areas of the State. The online publication of these geographical databases on the cartographic portal of the Tuscany Region through a dedicated WebGIS was the last phase of our study. Considering both the number and density of geometries surveyed, our work is an extraordinary example of how geohistorical research may be combined with new technologies for the purpose of studying geohistorical content and disseminating it to the general public.

This paper presents the development procedure and significance of a web mapping application designed for disseminating, exploring, and analyzing Kaupert’s 19th-century Maps of Attica, Greece. The application facilitates historical and geographical study by providing access to high-resolution map images and overlaying multiple vector layers of geospatial data. The paper outlines the methods used to create the application, which includes the process of interpreting, digitizing, and organizing the original mapped data, georeferencing the historical cartographic sheets, and developing the web-based mapping application. The results of this work include a comprehensive and interactive digital reference tool for studying the ancient topography of Attica, as well as a framework for future research. Overall, this work highlights the potential of digital technologies to transform the way we approach and study historical maps and other cultural artifacts.

The analysis of the 2002 Prestige tanker accident showed how public misinformation can worsen marine pollution incidents, rendering their management suboptimal as these evolve, thus raising the issue of appropriately informing and educating coastal and island populations who are at risk. Two decades later, developments in electronic platforms, including Geographic Information Systems (GIS), the Automatic Identification System (AIS) for ship signal transmission, and social media, provide a set of means for public monitoring of such incidents, creating the possibility to antagonise effectively erroneous or malevolent information, which can hinder efficient actions for containing marine pollution risks even without active training of the populations concerned. The authors, in the framework of the development of the Marine Coastal Observatory and Risk Management project "AEGIS+", have developed E-S.A.V.E., an online innovative platform that (a) meets the needs of different users as revealed by a survey run across groups of them, (b) uses a suitable Geographic Information System (GIS) environment, (c) cooperates with public authorities, for the reliable update of automated systems, and (d) employs an artificial intelligence (AI)-supported tool for social media monitoring; the platform also provides educational resources and information on national and international resources on marine environmental protection and sustainable maritime logistics. [ABSTRACT FROM AUTHOR]

Tailings ponds, essential components of mining operations worldwide, present considerable potential hazards downstream in the event of tailings dam failures. In recent years, instances of tailings dam failures, carrying potential environmental safety hazards, have occasionally occurred on a global scale due to the limited technical approaches available for safety supervision of tailings ponds. In this study, an innovative WebGIS-based unmanned aerial vehicle oblique photography (UAVOP) method was developed to analyze the storage capacity change and dam failure risk of tailings ponds. Its applicability was then validated by deploying it at a tailings pond in Yunfu City, Guangdong Province, China. The results showed that the outcomes of two phases of real-scene 3D images met the specified accuracy requirements with an RSME of 0.147–0.188 m in the plane and 0.198–0.201 m along the elevation. The storage capacities of phase I and phase II tailings ponds were measured at 204,798.63 m3 and 148,291.27 m3, respectively, with a storage capacity change of 56,031.51 m3. Moreover, the minimum flood control dam widths, minimum free heights, and dam slope ratios of the tailings pond were determined to comply with the flood control requirements, indicating a low risk of dam failure of the tailings pond. This pilot case study demonstrated the performance of the UAVOP in evaluating storage capacity change and dam failure risk for tailings ponds. It not only enhanced the efficiency of dynamic safety supervision of tailings ponds but also offered valuable references for globally analogous research endeavors. [ABSTRACT FROM AUTHOR]

The paper introduces the Oil-Slick Hub (OSH), a computational platform to facilitate the data visualization of a large database of petroleum signatures observed on the surface of the ocean with synthetic aperture radar (SAR) measurements. This Internet platform offers an information search and retrieval system of a database resulting from >20 years of scientific projects that interpreted ~15 thousand offshore mineral oil "slicks": natural oil "seeps" versus operational oil "spills". Such a Digital Mega-Collection Database consists of satellite images and oil-slick polygons identified in the Gulf of Mexico (GMex) and the Brazilian Continental Margin (BCM). A series of attributes describing the interpreted slicks are also included, along with technical reports and scientific papers. Two experiments illustrate the use of the OSH to facilitate the selection of data subsets from the mega collection (GMex variables and BCM samples), in which artificial intelligence techniques—machine learning (ML)—classify slicks into seeps or spills. The GMex variable dataset was analyzed with simple linear discriminant analyses (LDAs), and a three-fold accuracy performance pattern was observed: (i) the least accurate subset (~65%) solely used acquisition aspects (e.g., acquisition beam mode, date, and time, satellite name, etc.); (ii) the best results (>90%) were achieved with the inclusion of location attributes (i.e., latitude, longitude, and bathymetry); and (iii) moderate performances (~70%) were reached using only morphological information (e.g., area, perimeter, perimeter to area ratio, etc.). The BCM sample dataset was analyzed with six traditional ML methods, namely naive Bayes (NB), K-nearest neighbors (KNN), decision trees (DT), random forests (RF), support vector machines (SVM), and artificial neural networks (ANN), and the most effective algorithms per sample subsets were: (i) RF (86.8%) for Campos, Santos, and Ceará Basins; (ii) NB (87.2%) for Campos with Santos Basins; (iii) SVM (86.9%) for Campos with Ceará Basins; and (iv) SVM (87.8%) for only Campos Basin. The OSH can assist in different concerns (general public, social, economic, political, ecological, and scientific) related to petroleum exploration and production activities, serving as an important aid in discovering new offshore exploratory frontiers, avoiding legal penalties on oil-seep events, supporting oceanic monitoring systems, and providing valuable information to environmental studies. [ABSTRACT FROM AUTHOR]

The habous institution is playing a considerable religious and socio-economic role in the history of Morocco. Thanks to the revenues derived from habous property, the country was able to acquire numerous social and religious facilities. These resources financed the construction of several mosques and medersas, and ensured the functioning of numerous charitable and general utility works. The habous property is vast and heterogeneous in terms of typologies and functions, it includes agricultural land, urban land plots, and also buildings, a substantial number of which has a heritage value. However, data concerning habous land and real estate is scarce. There are no precise, general and easily consultable databases that bring together data relating to this heritage and enable decision-makers to understand its potential and the way in which this potential can be optimized. In this perspective, several researches have been interested in the elaboration of geographic information systems for the management of land and real estate assets, except that no work has approached such a rich, diversified and heterogeneous heritage as the habous heritage, nor has it presented a complete framework ensuring an extensive characterization of the real estate assets, taking into account the different states of the land: agricultural, serviced or built, the natural, regulatory and patrimonial context of the assets, as well as their technical and functional aspects. To overcome this deficiency, we have designed our own database and we have forged our own classification and coding tools based on an approach that constantly relates different scales of observation and investigation to grasp the complexity and importance of the habous heritage, and explore areas of its development. In this work we have built a Geographic Information System (GIS), composed of a database connected to QGIS and GIS Web in order to store, manage and visualize data related to the habous heritage. The whole infrastructure has been developed and implemented using open-source software. Tests to evaluate the efficiency and the relevance of the results of our information system have been carried out. We tried to show how this system could, from the interpretation and the interrogation of the collected data, be a decision support tool in the management of the habous property. [ABSTRACT FROM AUTHOR]

Tourism is one of the most important factors in economic growth in Vietnam. However, it requires the balance between economics, social-cultures, and ecology because of their big impacts. In this paper, we propose a platform with mobile and web-based applications that can support smart and sustainable tourism in Vietnam for both local governments and visitors. The mobile application allows visitors to access location-based services to explore the visiting area, such as finding nearby natural attractions, as well as information to minimize the negative effects of tourism on the environment and the local community. It also enables users to report negative impacts to local government. The web application allows local authorities to monitor the status and trends of the habitant, natural environment, tourism infrastructure and activities in the area. The system uses geographic information systems (GIS) and remote sensing techniques to collect, analye and visualize various indicators of sustainability. The platform is developed with open-source technologies such as NodeJS, PostgreSQL, and Flutter. The paper demonstrates the feasibility and usefulness of the proposed platform through case studies in Hoa Binh and BacKan, two provinces have many attractive natural sites. [ABSTRACT FROM AUTHOR]

Kos is the third largest island of the Dodecanese, located in the southeastern Aegean Sea, Greece. The island's remarkable location both in a prominent geodynamic space and at a crossroads of East, West and South has endowed it with a unique wealth of geological, biological, cultural, and traditional heritage. Steep mountain ranges consisting of Alpine Mesozoic rocks alternate with low-altitude plateaus featuring marine and lacustrine sediments that contain fossils of past life. In addition, the transition of barren land to lush forests where numerous species of flora and fauna thrive is unique to Greek ecosystems. This environment hosted civilizations and activities that gradually led to the present-day cultural and religious state of the island, where people and nature coexist respectfully on one of the country's most favourite destinations. In an effort to further enhance the public's awareness of the geo-cultural heritage of Kos, an online ESRI Hub was created, featuring several individual ESRI StoryMaps web apps regarding each specific aspect of the island's heritage. The goal of this paper is to discuss the importance of using such means for disseminating geoscientific information to the public, to describe the methods used and to give a brief presentation of its content. [ABSTRACT FROM AUTHOR]

This paper presents the development procedure and significance of a web mapping application designed for disseminating, exploring, and analyzing Kaupert's 19th-century Maps of Attica, Greece. The application facilitates historical and geographical study by providing access to high-resolution map images and overlaying multiple vector layers of geospatial data. The paper outlines the methods used to create the application, which includes the process of interpreting, digitizing, and organizing the original mapped data, georeferencing the historical cartographic sheets, and developing the web-based mapping application. The results of this work include a comprehensive and interactive digital reference tool for studying the ancient topography of Attica, as well as a framework for future research. Overall, this work highlights the potential of digital technologies to transform the way we approach and study historical maps and other cultural artifacts. [ABSTRACT FROM AUTHOR]

Merapi Volcano is one of the active volcanoes in Indonesia, which is located in the Central Java and Yogyakarta Province. The eruption of Merapi Volcano is a threat to people living on the slopes of Merapi, especially on its denselypopulated southern flank. The purpose of this study was to build a webGIS to support volcanic hazard mitigation regarding Merapi Volcano and evaluate the webGIS system for determining the community’s perception. This research was the first to produce a product that is used by government agencies related to volcanic disaster mitigation. webGIS development was carried out using an open source platform. System evaluation was carried out using usability testing. The samples were obtained using systematic the random sampling method of respondents who lived in the villages on the southern flank of Merapi volcano. webGIS was built using LeafletJS and QGIS, combined with spatial data about the evacuation locations, health facilities, evacuation routes, government offices, educational facilities and worship facilities, with a basemap obtained from Openstreet Map and Google Satellite. WebGIS was equipped with a database query feature to make it easier for users to find geographical information. The usability testing results showed that as many as 83% of the respondents were very satisfied with the appearance and information of webGIS, while as many as 82% were very satisfied with the navigation offered via the webGIS display.

The Institute of Marine Sciences (ISMAR) and the Institute of Polar Sciences (ISP) of the Italian National Research Council (CNR) have gathered a substantial amount of heterogeneous geodata through the years in the Adriatic Sea, with different methodologies and for multiple scopes regarding geological, oceanographic, biological, anthropogenic aspects, and their interactions.To overcome challenges in datasets heterogeneity and fragmentation, a Marine Spatial Data Infrastructure (MSDI) has been set up, with the aim to integrate and preserve geodata, foster their reuse (e.g. the generation of scenarios for geological past and future developments by the application of numerical models), and ensure a good degree of FAIRness (FAIR: Findable, Accessible, Interoperable, and Reusable). The MSDI consists of a Spatial Relational Database Management System (RDBMS) based on specific data models designed following in part the INSPIRE Directive data specifications, a WebGIS, a metadata catalogue, and a cloud system. This paper shows the potentialities of this MSDI and discusses the main implementation steps, the elements that make up the infrastructure, the level of FAIRness reached, the main elements promoting FAIRness, and the gaps to be covered.Compliance with the FAIR principles represents a fundamental step to developing interoperability with European and international marine data management infrastructures for handling and exchanging multidisciplinary data.