Search Results (32)

Effective management of urban development requires robust decision-support tools, including land suitability analysis and its visual communication. This study introduces and evaluates seven 3D geovisualization methods—Horizontal Planes, Point Cloud, 3D Surface, Vertical Planes, 3D Graduated Symbols, Prism Map, and Voxels—for visualizing land suitability for residential development in Jihlava, Czechia. Using five raster-based data layers derived from a multi-criteria evaluation (Urban Planner methodology) across three time horizons (2023, 2028, 2033), the visualizations were implemented in ArcGIS Online and assessed by 19 domain experts via a structured questionnaire. The evaluation focused on clarity, usability, and accuracy in interpreting land suitability values, with the methods being rated on a five-point scale. Results show that the Horizontal Planes method was rated highest in terms of interpretability and user satisfaction, while 3D Surface and Vertical Planes were considered the least effective. The study demonstrates that visualization methods employing visual variables (e.g., color and transparency) are better suited for land suitability communication. The methodological contribution lies in systematically comparing 3D visualization techniques for thematic spatial data, providing guidance for their application in planning practice. The results are primarily intended for urban planners, designers, and local government representatives as supportive tools for efficient planning of future built-up area development. Full article

This article explores the potential of the Unreal Engine as a tool for creating realistic 3D visualizations of large-scale areas (1000 km² and more) using GIS datasets. Unlike small-scale visualizations, large-scale visualizations are rare and often not public, which presents significant problems since they present different challenges and require different approaches. This article presents several relevant scientific studies and projects that have successfully used game engines for similar purposes. This case study focuses on the computational techniques used in Unreal Engine for the 3D visualization of GIS data and the potential application of Unreal Engine in large-scale geo-visualizations. It explores the potential for using GIS data within a game engine, including plug-ins that provide additional functionality for working with GIS data, such as the Vitruvio plug-in to implement procedural modeling of buildings. The case study is applied to GIS datasets of the historical Vltava Valley covering an area of 1670 km² to demonstrate the unique challenges of using Unreal Engine to create realistic visualizations of large-scale historical landscapes. The resulting visualizations are presented. The practical application of this research provides insights into the potential of the Unreal Engine as a tool for creating realistic 3D visualizations of large-scale historical areas. Full article

This study aims to create virtual reality (VR) geovisualizations using 3D point clouds obtained from airborne LiDAR technology. These visualizations were used to map the current state of river channels and tributaries in the Thessalian Plain, Greece, following severe flooding in the summer of 2023. The study area examined in this paper is the embankments enclosing the tributaries of the Pineios River in the Thessalian Plain region, specifically between the cities of Karditsa and Trikala in mainland Greece. This area was significantly affected in the summer of 2023 when flooding the region’s rivers destroyed urban elements and crops. The extent of the impact across the entire Thessalian Plain made managing the event highly challenging to the authorities. High-resolution 3D mapping and VR geovisualization of the embarkments encasing the main rivers and the tributaries of the Thessalian Plain essentially provides information for planning the area’s restoration processes and designing prevention and mitigation measures for similar disasters. The proposed methodology consists of four stages. The first and second stages of the methodology present the design of the data acquisition process with airborne LiDAR, aiming at the high-resolution 3D mapping of the sites. The third stage focuses on data processing, cloud point classification, and thematic information creation. The fourth stage is focused on developing the VR application. The VR application will allow users to immerse themselves in the study area, observe, and interact with the existing state of the embankments in high resolution. Additionally, users can interact with the 3D point cloud, where thematic information is displayed describing the classification of the 3D cloud, the altitude, and the RGB color. Additional thematic information in vector form, providing qualitative characteristics, is also illustrated in the virtual space. Furthermore, six different scenarios were visualized in the 3D space using a VR app. Visualizing these 3D scenarios using digital twins of the current antiflood infrastructure provides scenarios of floods at varying water levels. This study aims to explore the efficient visualization of thematic information in 3D virtual space. The goal is to provide an innovative VR tool for managing the impact on anthropogenic infrastructures, livestock, and the ecological capital of various scenarios of a catastrophic flood. Full article

In the context of rural revitalization strategies and humans’ increasing leisure pursuits, rural tourism has begun to act as a new development path of rural economic growth and industrial transformation. This phenomenon generally occurs in rural areas around metropolitan areas, manifesting as the transformation or reconstruction of rural spaces. As a result, many new types of tertiary industry spaces utilizing rural land for leisure activities have emerged. We analyze the connotations of rural spatial and industrial transformation from the perspective of spatial production and innovatively propose that the transformed space is an ecological product, which includes three types in practice: industrial space, consumption space, and residential space. This study facilitates urban–rural integration and common prosperity. Given the lack of analysis of rural ecological products, especially rural spatial ecological products (e.g., rural B&Bs and other tertiary industry spaces), this study aims to explore the value expression and driving factors of rural spatial ecological products based on geo-visual (spatially visualizing) analytical tools looking at 10361 B&Bs in Jiangsu and Zhejiang Provinces of China as typical examples. Our results show that (1) the value of rural spatial ecological products is reflected in the price that urban consumers are willing to pay for rural natural landscapes, which constitutes an ecological premium; and (2) the prices of rural spatial ecological products are strikingly different at multiple spatial scales, and this difference is related to the local ecological resources. This study provides insights into the rational allocation of the limited resources required for rural construction, which helps optimize the spatial planning of rural ecotourism and enhance the gametogenous development momentum of rural areas. At the same time, this study theoretically expands the research results of cultural ecosystem services. Full article

This article presents the development of a geo-visualization tool, which provides police officers or any other type of law enforcement officer with the ability to conduct the spatiotemporal predictive geo-visualization of criminal activities in short and continuous time horizons, according to the real events that are happening: that is, for those geographical areas, time slots, and dates that are of interest to users, with the ability to consider individual events or groups of events. This work used real data collected by the Colombian National Police (PONAL); it constitutes a tool that is especially effective when applied to Real-Time Systems for crime deterrence, prevention, and control. For its creation, the spatial and temporal correlation of the events is carried out and the following deep learning techniques are employed: CNN-1D (Convolutional Neural Network-1D), MLP (multilayer perceptron), LSTM (long short-term memory), and the classical technique of VAR (vector autoregression), due to its appropriate performance in the multi-step and multi-parallel forecasting of multivariate time series with sparse data. This tool was developed with Open-Source Software (OSS) as it is implemented in the Python programming language with the corresponding machine learning libraries. It can be implemented with any geographic information system (GIS) and used in relation to other types of activities, such as natural disasters or terrorist activities. Full article

Geovisualization tools can supplement the statistical analyses of landscape-level wildfire behavior by enabling the discovery of nuanced information regarding the relationships between fire spread, topography, fuels, and weather. The objectives of this study were to develop and evaluate the effectiveness of geovisualization tools for analyzing wildfire behavior and specifically to apply those tools to study portions of the Thomas and Detwiler wildfire events that occurred in California in 2017. Fire features such as active fire fronts and rate of spread (ROS) vectors derived from repetitive airborne thermal infrared (ATIR) imagery sequences were incorporated into geovisualization tools hosted in a web geographic information systems application. This geovisualization application included ATIR imagery, fire features derived from ATIR imagery (rate of spread vectors and fire front delineations), growth form maps derived from NAIP imagery, and enhanced topographic rasters for visualizing changes in local topography. These tools aided in visualizing and analyzing landscape-level wildfire behavior for study portions of the Thomas and Detwiler fires. The primary components or processes of fire behavior analyzed in this study were ROS, spotting, fire spread impedance, and fire spread over multidirectional slopes. Professionals and researchers specializing in wildfire-related topics provided feedback on the effectiveness and utility of the geovisualization tools. The geovisualization tools were generally effective for visualizing and analyzing (1) fire spread over multidirectional slopes; (2) differences in spread magnitudes within and between sequences over time; and (3) the relative contributions of fuels, slope, and weather at any given point within the sequences. Survey respondents found the tools to be moderately effective, with an average effectiveness score of 6.6 (n = 5) for the visualization tools on a scale of 1 (ineffective) to 10 (effective) for postfire spread analysis and visualizing fire spread over multidirectional slopes. The results of the descriptive analysis indicate that medium- and fine-scale topographic features, roads, and riparian fuels coincided with cases of fire spread impedance and exerted control over fire behavior. Major topographic features such as ridges and valleys slowed, or halted, fire spread consistently between study areas. The relationships between spotting, fuels, and topography were inconclusive. Full article

Surface motion is a complex, dynamic phenomenon that draws significant scientific attention. This study focuses on the development of a cartographic toolset for the visualization of space-borne Persistent Scatterer Interferometry (PSI) surface motion measurements. The entire archive of Sentinel-1 Synthetic Aperture Radar (SAR) imagery over the broader Thessaloniki (Greece) area has been exploited to derive the PSI measurements utilizing the Surface motioN mAPPING (SNAPPING) service on the Geohazards Exploitation Platform (GEP). A collection of web map applications, interactive visualization tools, and an animated map were developed based on state-of-the-art approaches. This geo-visualization toolset consists of the following: (i) Three web map applications exploring PSI velocity rates, PSI time series, and a comparison of PSI with geodetic leveling data; (ii) Two interactive map tools focusing on 3D visualization of PSI time series and estimating velocity rates for predefined temporal frames; and (iii) An animated map of PSI time series. The utilization of the aforementioned visualization toolset provided useful conclusions about the variety of land displacement that occurs in different subareas of Northern Greece from different causes. More specifically, certain subareas with significant subsidence rates range from −2 mm/year up to −18 mm/year from 2015 to 2020. The magnitude of displacement and the underlying causes (subsidence, faults, landslides, human processes, etc.) varies across different subareas. On the other hand, a subarea of uplift trend exists in the north of the city of Thessaloniki with displacements up to 5 mm/year for the period between 2015–2020, despite being constrained by the fact that the geo-visualization platform is able to display SNAPPING PSI measurements from any location around the world, making it a useful tool for global exploration. The platform’s contents are available through a user-friendly graphical interface and are mostly addressed to domain experts as well as end-users. Opposed to similar approaches where static 2D maps and velocity rates web applications are presented through this platform, users can monitor and study the dynamic behavior of surface motion to a spatiotemporal extent more thoroughly. Full article

Pervasiveness of alcohol products and their promotion in the urban landscape may normalize alcohol consumption. This study aims to utilize geovisualization-based methods to assess attitudes towards different levels of alcohol exposure in the urban environment. We selected a typical downtown location, Lavapiés Square in Madrid, Spain, to conduct our study. First, we designed and created realistic 3D models simulating three different urban scenes with varying degrees of exposure to alcohol in the environment. Second, we used a survey on 159 adults to explore the level of acceptance of, attitudes towards, and perceptions of alcohol exposure in each scene. Participants reported a higher level of comfort in the scene with null alcohol exposure compared with the other scenes (p < 0.001). Acceptance towards alcohol exposure decreased as the level of alcohol elements increased in the scenes (p < 0.01). Acceptance also decreased when children were present in the scenes (p < 0.01). This study demonstrated that geovisualization tools provide a useful and well-suited approach to analyze perceptions of the alcohol environment. The use of geovisualization can help understand attitudes and perceptions towards the alcohol environment and may offer a way to simulate different scenarios prior to development or retrofitting. Full article

The vegetation indices (VIs) estimated from remotely sensed data are simple and based on effective algorithms for quantitative and qualitative evaluations of the dynamics of biophysical crop variables such as vegetation cover, leaf area, vigor and development, and many others. Over the last decade, many VIs have been proposed and validated to enhance the vegetation signal by reducing the noise from effects produced either by the soil or by vegetation such as brightness, shadows, color, etc. VIs are commonly calculated from satellite images such as ones from Landsat and Sentinel-2 because of their medium resolution and free availability. However, despite the VIs being fairly simple algorithms, it can take hours to calculate them for an established agricultural area, mainly due to the pre-processing of the images (including atmospheric corrections, the detection of clouds and shadows), size and download time of the images, and the capacity of the computer equipment used. Time increases as the number of images increases. In this sense, the free to use Google Earth Engine (GEE) platform was here used to develop an application called VICAL to calculate 23 VIs map (VIs commonly used in agricultural applications) and time series of any agricultural area in the world with images (cloud-free) from Landsat and Sentinel-2 data. It was found that VICAL can calculate these 23 VIs accurately, and shows the potential of the GEE cloud-based tools using multispectral dataset to assess many spectral VIs. This tool is very beneficial for researchers with poor access to satellite data or in institutions with a lack of computational infrastructure to handle the large volumes of satellite datasets, since it is not necessary for the user writing a single line of code. The VICAL is open-access image analysis platform that can be modified to carry out more complex analysis or adapt it to a specific VI application. Full article

The interaction between humans and nature dramatically reveals the role of sudden and destructive events in the progressive and never-ending trend of depletion of the territorial dimension of the Belìce Valley (Valle del Belìce, Sicily, Italy). If on the one hand a tragic event, such as the earthquake of 1968, that destroyed towns and villages in the Belìce Valley, represented a moment of pain and suffering for local communities and their territories, on the other, more than 50 years after the event, we are able to shed light on the reaction to the earthquake effects through an in-depth analysis of the heritage of the physical and immaterial rubble. Our research is aimed at framing, through special geovisual tools, the paths of this rebuilding process and to verify whether the “new” interaction of humans and nature has reached an acceptable balance. After introducing the concept of landscape and investigating some local manifestations within the Belìce Valley, we tackle the technical question of re-photography as a powerful and quick method for observing the territorial changes that occurred after the earthquake. This approach is based on the collection of historical photographs and, subsequently, onsite activities for the creation of a contemporary archive of images. The method used for comparing the images was that of re-photographic overlapping, a useful technique to compare different moments of the history of a landscape and to analyze the effectiveness of the process of rebuilding. Finally, this analysis introduces us to a new perspective where in our opinion, it is possible to frame some features of the Belìce Valley and some more general aspects that are useful for other territories hit by destructive events and having to face choices related to the future of their communities. Full article

Urban green infrastructure (UGI) has a key role in improving human and environmental health in cities and contributes to several services related to climate adaptation. Accurate localization and quantification of pervious surfaces and canopy cover are envisaged to implement UGI, address sustainable spatial planning, and include adaptation and mitigation strategies in urban planning practices. This study aims to propose a simple and replicable process to map pervious surfaces and canopy cover and to investigate the reliability and the potential planning uses of UGI maps. The proposed method combines the normalized difference vegetation index (NDVI), extracted from high-resolution airborne imagery (0.20 m), with digital elevation models to map pervious surfaces and canopy cover. The approach is tested in the Municipality of Trento, Italy, and, according to a random sampling validation, has an accuracy exceeding 80%. The paper provides a detailed map of green spaces in the urban areas, describing quantity and distribution, and proposes a synthesis map expressed as a block-level degree of pervious surfaces and canopy cover to drive urban transformations. The proposed approach constitutes a useful tool to geovisualize critical areas and to compare levels of pervious surfaces and canopy cover in the municipal area. Acknowledging the role of green areas in the urban environment, the paper examines the potential applications of the maps in the policy cycle, such as land use management and monitoring, and in climate-related practices, and discusses their integration into the current planning tools to shift towards performative rather than prescriptive planning. Full article

The provision of webGIS-based water quality data services has become a priority area for both the public and administrative sectors in the context of the pandemic emergency associated with the global spread of COVID-19. Current geographic, monitoring and decision supporting systems, typically based on web-based geospatial information, greatly facilitate the sharing of spatial and temporal data from environmental databases and real-time analyses. In the present study, different water quality indices are determined, compared and geovisualized, during which the changes in the quality of the shallow groundwater resources of a settlement are examined in the period (2011–2019) in an eastern Hungarian settlement. Another objective of the research is to determine three water quality indices (Water Quality Index, CCME Water Quality Index, Contamination degree) and categorize water samples based on the same input spatial and temporal data using self-developed freely available geovisualization tools. Groundwater quality was assessed by using different water quality indices. Significant pollution of the groundwater in the time period before the installation of a sewage network was shown. Regarding water quality, significant positive changes were shown based on all three water quality indices in the years after installing a sewage network (2015–2019). The presence of pollution apart from the positive changes suggests that the purification processes will last for a long time. Full article

Volunteer-contributed geographic data (VGI) is an important source of geospatial big data that support research and applications. A major concern on VGI data quality is that the underlying observation processes are inherently biased. Detecting observation hot-spots thus helps better understand the bias. Enabled by the parallel kernel density estimation (KDE) computational tool that can run on multiple GPUs (graphics processing units), this study conducted point pattern analyses on tens of millions of iNaturalist observations to detect and visualize volunteers’ observation hot-spots across spatial scales. It was achieved by setting varying KDE bandwidths in accordance with the spatial scales at which hot-spots are to be detected. The succession of estimated density surfaces were then rendered at a sequence of map scales for visual detection of hot-spots. This study offers an effective geovisualization scheme for hierarchically detecting hot-spots in massive VGI datasets, which is useful for understanding the pattern-shaping drivers that operate at multiple spatial scales. This research exemplifies a computational tool that is supported by high-performance computing and capable of efficiently detecting and visualizing multi-scale hot-spots in geospatial big data and contributes to expanding the toolbox for geospatial big data analytics. Full article

Forests are an important natural resource and are instrumental in sustaining environmental sustainability. Burning biomass in forests results in greenhouse gas emissions, many of which are long-lived. Precise and consistent broad-scale monitoring of fire intensity is a valuable tool for analyzing climate and ecological changes related to fire. Remote sensing and geographic information systems provide an opportunity to improve current practice’s accuracy and performance. Spectral indices techniques such as normalized burn ratio (NBR) have been used to identify burned areas utilizing satellite data, which aid in distinguishing burnt areas using their standard spectral responses. For this research, we created a split-panel web-based Google Earth Engine app for the geo-visualization of the region severely affected by forest fire using Sentinel 2 weekly composites. Then, we classified the burn severity in areas affected by forest fires in Wolgan Valley, New South Wales, Australia, and the surrounding area through Difference Normalized Burn Ratio (dNBR). The result revealed that the region’s burnt area increased to 6731 sq. km in December. We also assessed the impact of long-term rainfall and land surface temperature (LST) trends over the study region to justify such incidents. We further estimated the effect of such incidents on air quality by analyzing the changes in the column number density of carbon monoxide and nitrogen oxides. The result showed a significant increase of about 272% for Carbon monoxide and 45% for nitrogen oxides. We conclude that, despite fieldwork constraints, the usage of different NBR and web-based application platforms may be highly useful for forest management to consider the propagation of fire regimes. Full article

In the context of rural revitalization strategies and humans’ increasing leisure pursuit, leisure agriculture starts to act as a new engine of rural economic growth and industrial upgradation. Unraveling the agri-leisure developmental regularity from a spatial perspective facilitates urban-rural integration and poverty alleviation in rural regions. Given the lack of spatially analyzing agri-leisure (e.g., sightseeing picking orchards) especially at the macro-spatial scale (e.g., the national scale), this study aims to explore the spatiality of leisure agriculture and its fundamental driving mechanisms based on geo-visual (spatially visualizing) analytical tools looking at 20,778 picking orchards in China. Results show that: (1) Picking orchards are distributed in the form of clusters with striking disparity at multiple spatial scales; (2) Five spatial agglomerations are found involving the regions around Beijing and Tianjin, Shandong hinterland, Henan hinterland, the core district of the Yangtze Delta, and the core district of the Pearl River Delta; (3) The driving mechanisms are revealed, and the spatial pattern of picking orchards is found to be largely influenced by morphology, distance to central cities, traffic conditions, economic level, and tourism resources. This study is conducive to optimizing the spatial planning of rural eco-tourism towards sustainable agro-development. Full article