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This study explores how combining virtual reality (VR) and augmented reality (AR) with geographic information systems (GIS) revolutionizes data visualization. It traces the historical development of these technologies and highlights key milestones that paved the way for this study's objectives. While existing platforms like Esri's software and Google Earth VR show promise, they lack complete integration for immersive GIS visualization. This gap has led to the need for a dedicated workflow to integrate selected GIS data into a game engine for visualization purposes. This study primarily utilizes QGIS for data preparation and Unreal Engine for immersive visualization. QGIS handles data management, while Unreal Engine offers advanced rendering and interactivity for immersive experiences. To tackle the challenge of handling extensive GIS datasets, this study proposes a workflow involving tiling, digital elevation model generation, and transforming GeoTIFF data into 3D objects. Leveraging QGIS and Three.js streamlines the conversion process for integration into Unreal Engine. The resultant virtual reality application features distinct stations, enabling users to navigate, visualize, compare, and animate GIS data effectively. Each station caters to specific functionalities, ensuring a seamless and informative experience within the VR environment. This study also delves into augmented reality applications, adapting methodologies to address hardware limitations for smoother user experiences. By optimizing textures and implementing augmented reality functionalities through modules Swift, RealityKit, and ARKit, this study extends the immersive GIS experience to iOS devices. In conclusion, this research demonstrates the potential of integrating virtual reality, augmented reality, and GIS, pushing data visualization into new realms. The innovative workflows and applications developed serve as a testament to the evolving landscape of spatial data interpretation and engagement. [ABSTRACT FROM AUTHOR]

This study explores how combining virtual reality (VR) and augmented reality (AR) with geographic information systems (GIS) revolutionizes data visualization. It traces the historical development of these technologies and highlights key milestones that paved the way for this study’s objectives. While existing platforms like Esri’s software and Google Earth VR show promise, they lack complete integration for immersive GIS visualization. This gap has led to the need for a dedicated workflow to integrate selected GIS data into a game engine for visualization purposes. This study primarily utilizes QGIS for data preparation and Unreal Engine for immersive visualization. QGIS handles data management, while Unreal Engine offers advanced rendering and interactivity for immersive experiences. To tackle the challenge of handling extensive GIS datasets, this study proposes a workflow involving tiling, digital elevation model generation, and transforming GeoTIFF data into 3D objects. Leveraging QGIS and Three.js streamlines the conversion process for integration into Unreal Engine. The resultant virtual reality application features distinct stations, enabling users to navigate, visualize, compare, and animate GIS data effectively. Each station caters to specific functionalities, ensuring a seamless and informative experience within the VR environment. This study also delves into augmented reality applications, adapting methodologies to address hardware limitations for smoother user experiences. By optimizing textures and implementing augmented reality functionalities through modules Swift, RealityKit, and ARKit, this study extends the immersive GIS experience to iOS devices. In conclusion, this research demonstrates the potential of integrating virtual reality, augmented reality, and GIS, pushing data visualization into new realms. The innovative workflows and applications developed serve as a testament to the evolving landscape of spatial data interpretation and engagement.

Sustainable development goal (SDG) 3 promotes well-being and healthy lives for people of all ages. However, based on the literature, one of the main challenges to achieving SDG 3 is inequality in access to health care. In order to support the efforts of the local government of the province to contribute to the achievement of SDG thru equitable access to health care, this study measured the spatial accessibility of healthcare facilities in Marinduque, Philippines. It used distance-based (i.e., travel-time) and area-based (i.e., enhanced two-step floating catchment analysis or E2SFCA) metrics. The distance from each healthcare facility to different villages in the province was established using QGIS and Google Maps. The distance traveled was measured using three (3) modes of transportation: tricycle, jeepney, and private vehicle. The E2SFCA scores were calculated for different population groups: the general population, women, children, and the elderly. Based on the results, island villages and those areas in the inner portion of the province lack physical access to healthcare facilities. Such a limitation was apparent in the distance- and area-based accessibility metrics. Among the population group considered in this study, the women population showed the lowest accessibility scores. [ABSTRACT FROM AUTHOR]

Sustainable development goal (SDG) 3 promotes well-being and healthy lives for people of all ages. However, based on the literature, one of the main challenges to achieving SDG 3 is inequality in access to health care. In order to support the efforts of the local government of the province to contribute to the achievement of SDG thru equitable access to health care, this study measured the spatial accessibility of healthcare facilities in Marinduque, Philippines. It used distance-based (i.e., travel-time) and area-based (i.e., enhanced two-step floating catchment analysis or E2SFCA) metrics. The distance from each healthcare facility to different villages in the province was established using QGIS and Google Maps. The distance traveled was measured using three (3) modes of transportation: tricycle, jeepney, and private vehicle. The E2SFCA scores were calculated for different population groups: the general population, women, children, and the elderly. Based on the results, island villages and those areas in the inner portion of the province lack physical access to healthcare facilities. Such a limitation was apparent in the distance- and area-based accessibility metrics. Among the population group considered in this study, the women population showed the lowest accessibility scores.

The conservation of a primary importance historical building requires organization, management, continuous updating, comparison, and visualization of a large amount of data of different nature and origin. In relation to these aspects the use of a GIS brings various advantages including single and univocal management of the entire amount of existing data in a relational, dynamic, updatable and queryable way. The integration of a mobile solution permits the updating of the dataset and checking on site all information. The workflow presented uses opensource solutions, desktop and mobile, which allows the creation of an unconventional lithological Field Mapping activity: starting from photo interpretation and in situ survey, all the coating materials (stone, etc.) of some monuments of primary historical and cultural interest have been mapped (i.e., Duomo di Firenze, Duomo di Prato). The product can be considered as a lithological cartography, vertically oriented, processed by field surveys, geognostic surveys and photo interpretation. All combined to create a “lithological” mapping of the coatings of the various monuments; the advantage is a new approach for conservation and restoration of Cultural Heritage. The proposed workflow involves a mobile solution, opensource, that allows the verification and management of the database in the field.

Processing is an object-oriented Python framework for the popular open source Geographic Information System QGIS, which provides a seamless integration of geoprocessing tools from a variety of different software libraries. In this paper, we present the development history, software architecture and features of the Processing framework, which make it a versatile tool for the development of geoprocessing algorithms and workflows, as well as an efficient integration platform for algorithms from different sources. Using real-world application examples, we furthermore illustrate how the Processing architecture enables typical geoprocessing use cases in research and development, such as automating and documenting workflows, combining algorithms from different software libraries, as well as developing and integrating custom algorithms. Finally, we discuss how Processing can facilitate reproducible research and provide an outlook towards future development goals.

Unmanned Aerial Vehicle (UAV) imagery allows for a new way of obtaining geographic information. In this work, a Geographical Information System (GIS) open source application was developed in QGIS software that estimates several parameters and metrics on tree crown through image analysis techniques (image segmentation and image classification) and fractal analysis. The metrics that have been estimated were: area, perimeter, number of trees, distance between trees and a missing tree check. This methodology was tested on three different plantations: olive, eucalyptus and vineyard. The application developed is free, open source and takes advantage of QGIS integration with external software. Several tools available from Orfeo Toolbox and Geographic Resources Analysis Support System (GRASS) GIS were employed to generate a classified raster image which allows calculating the metrics referred before. The application was developed in the Python 2.7 language. Also, some functions, modules and classes from the QGIS Application Programming Interface (API) and PyQt4 API were used. This new plugin is a valuable tool, which allowed for automatizing several parameters and metrics on tree crown using GIS analysis tools, while considering data acquired by UAV. [ABSTRACT FROM AUTHOR]

A geographic information system (GIS) was used to introduce and test a new method for quantitatively characterizing topographic change. Borrowing from classic Newtonian mechanics, the concept of a body’s center of mass is applied to the geomorphic landscape, and the barrier island environment in particular, to evaluate the metric’s potential as a proxy for detecting, tracking and visualizing change. Two barrier islands along North Carolina’s Outer Banks are used to test this idea: Core Banks, uninhabited and largely-undeveloped, and Hatteras Island, altered by the presence of a protective dune system. Findings indicate that for Core Banks, the alongshore change in the center of mass is in accord with dominate littoral transport and wind conditions. Cross-shore change agrees with independent estimates for the island migration rates. This lends credence to our assertion that the mass center metric has the potential to be a viable proxy for describing wholesale barrier migration and would be a valuable addition to the already-established ocean shoreline and subaerial volume metrics. More research is, however, required to demonstrate efficacy.

The PARSIFAL (Probabilistic Approach to pRovide Scenarios of earthquake Induced slope FAiLures) method was applied to the survey of post-earthquake landslides in central Italy for seismic microzonation purposes. In order to optimize time and resources, while also reducing errors, the paper-based method of survey data sheets was translated into digital formats using such instruments as Tablet PCs, GPS and open source software (QGIS). To the base mapping consisting of Technical Regional Map (Carta Tecnica Regionale—CTRs) at the scale of 1:10,000, layers were added with such sensitive information as the Inventory of Landslide Phenomena in Italy (Inventario dei Fenomeni Franosi in Italia—IFFI), for example. A database was designed and implemented in the SQLite/SpatiaLite Relational DataBase Management System (RDBMS) to store data related to such elements as landslides, rock masses, discontinuities and covers (as provided by PARSIFAL). To facilitate capture of the datum on the ground, data entry forms were created with Qt Designer. In addition to this, the employment of some QGIS plug-ins, developed for digital surveying and enabling of quick annotations on the map and the import of images from external cameras, was found to be of considerable use.

The studies of forest ecosystems from remotely-sensed data are of great interest to researchers because of ecosystem services provided by this ecosystem, including protection of soils and vegetation, climate stabilization, and regulation of the hydrological cycle. In this context, our study focused on the use of a spectral angle mapper (SAM) classification method for mapping species in the Azrou Forest, Central Middle Atlas, Morocco. A Sentinel-2A image combined with ground reference data were used in this research. Four classes (holm oak, cedar forest, bare soil, and others-unclassified) were selected; they represent, respectively, 27, 11, 24, and 38% of the study area. The overall accuracy of classification was estimated to be around 99.72%. This work explored the potential of the SAM classification combined with Sentinel-2A data for mapping land cover in the Azrou Forest ecosystem. [ABSTRACT FROM AUTHOR]

The brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), is an invasive pest that has expanded its range outside of its original confinements in Eastern Asia, spreading through the United States, Canada and most of the European and Eurasian countries. The invasiveness of this agricultural and public nuisance pest is facilitated by the availability of an array of suitable hosts, an r-selected life history and the release from natural enemies in the invaded zones. Traditional monitoring methods are usually impeded by the lack of time and resources to sufficiently cover large geographical ranges. Therefore, the citizen science initiative “BugMap” was conceived to complement and assist researchers in breaking down the behavior of this invasive pest via a user-friendly, freely available mobile application. The collected data were employed to forecast its predicted distribution and to identify the areas at risk in Trentino, Northern Italy. Moreover, they permitted the uncovering of the seasonal invasion dynamics of this insect, besides providing insight into its phenological patterns, life cycle and potential management methods. Hence, the outcomes of this work emphasize the need to further integrate citizens in scientific endeavors to resolve ecological complications and reduce the gap between the public and science.

Unmanned Aerial Vehicle (UAV) imagery allows for a new way of obtaining geographic information. In this work, a Geographical Information System (GIS) open source application was developed in QGIS software that estimates several parameters and metrics on tree crown through image analysis techniques (image segmentation and image classification) and fractal analysis. The metrics that have been estimated were: area, perimeter, number of trees, distance between trees, and a missing tree check. This methodology was tested on three different plantations: olive, eucalyptus, and vineyard. The application developed is free, open source and takes advantage of QGIS integration with external software. Several tools available from Orfeo Toolbox and Geographic Resources Analysis Support System (GRASS) GIS were employed to generate a classified raster image which allows calculating the metrics referred before. The application was developed in the Python 2.7 language. Also, some functions, modules, and classes from the QGIS Application Programming Interface (API) and PyQt4 API were used. This new plugin is a valuable tool, which allowed for automatizing several parameters and metrics on tree crown using GIS analysis tools, while considering data acquired by UAV.

Processing is an object-oriented Python framework for the popular open source Geographic Information System QGIS, which provides a seamless integration of geoprocessing tools from a variety of different software libraries. In this paper, we present the development history, software architecture and features of the Processing framework, which make it a versatile tool for the development of geoprocessing algorithms and workflows, as well as an efficient integration platform for algorithms from different sources. Using real-world application examples, we furthermore illustrate how the Processing architecture enables typical geoprocessing use cases in research and development, such as automating and documenting workflows, combining algorithms from different software libraries, as well as developing and integrating custom algorithms. Finally, we discuss how Processing can facilitate reproducible research and provide an outlook towards future development goals. [ABSTRACT FROM AUTHOR]

The studies of forest ecosystems from remotely-sensed data are of great interest to researchers because of ecosystem services provided by this ecosystem, including protection of soils and vegetation, climate stabilization, and regulation of the hydrological cycle. In this context, our study focused on the use of a spectral angle mapper (SAM) classification method for mapping species in the Azrou Forest, Central Middle Atlas, Morocco. A Sentinel-2A image combined with ground reference data were used in this research. Four classes (holm oak, cedar forest, bare soil, and others-unclassified) were selected; they represent, respectively, 27, 11, 24, and 38% of the study area. The overall accuracy of classification was estimated to be around 99.72%. This work explored the potential of the SAM classification combined with Sentinel-2A data for mapping land cover in the Azrou Forest ecosystem.

A geographic information system (GIS) was used to introduce and test a new method for quantitatively characterizing topographic change. Borrowing from classic Newtonian mechanics, the concept of a body's center of mass is applied to the geomorphic landscape, and the barrier island environment in particular, to evaluate the metric's potential as a proxy for detecting, tracking and visualizing change. Two barrier islands along North Carolina's Outer Banks are used to test this idea: Core Banks, uninhabited and largely-undeveloped, and Hatteras Island, altered by the presence of a protective dune system. Findings indicate that for Core Banks, the alongshore change in the center of mass is in accord with dominate littoral transport and wind conditions. Cross-shore change agrees with independent estimates for the island migration rates. This lends credence to our assertion that the mass center metric has the potential to be a viable proxy for describing wholesale barrier migration and would be a valuable addition to the already-established ocean shoreline and subaerial volume metrics. More research is, however, required to demonstrate efficacy. [ABSTRACT FROM AUTHOR]

The conservation of a primary importance historical building requires organization, management, continuous updating, comparison, and visualization of a large amount of data of different nature and origin. In relation to these aspects the use of a GIS brings various advantages including single and univocal management of the entire amount of existing data in a relational, dynamic, updatable and queryable way. The integration of a mobile solution permits the updating of the dataset and checking on site all information. The workflow presented uses opensource solutions, desktop and mobile, which allows the creation of an unconventional lithological Field Mapping activity: starting from photo interpretation and in situ survey, all the coating materials (stone, etc.) of some monuments of primary historical and cultural interest have been mapped (i.e., Duomo di Firenze, Duomo di Prato). The product can be considered as a lithological cartography, vertically oriented, processed by field surveys, geognostic surveys and photo interpretation. All combined to create a "lithological" mapping of the coatings of the various monuments; the advantage is a new approach for conservation and restoration of Cultural Heritage. The proposed workflow involves a mobile solution, opensource, that allows the verification and management of the database in the field. [ABSTRACT FROM AUTHOR]

High-resolution satellite images must undergo a geometric rectification process in order to be used for metrical purposes. This operation, called orthorectification, is necessary because of deformations mainly due to camera distortions and acquisition geometry. To correctly orthorectify an image, it is necessary to accurately reconstruct the photogrammetric-acquisition characteristics and the image position with respect to a reference system connected to the ground. This operation, called orientation, can be done using various mathematical models such as rigorous, rational polynomial function (RPF), and rational polynomial coefficient, or, according to some authors, rapid positioning coefficient (RPC) models. Orientation and orthorectification are usually performed within specific commercial software, but in QGIS, these complex operations can be performed using the open libraries of the Orfeo Tool Box (OTB). Unfortunately, instructions given by OTB developers lead to scarce results. In fact, the procedure proposed in OTB does not allow for the full exploitation of the potential of RPC models, on which OTB itself is based. As OTB is open-source software, a plugin was developed to overcome these limitations and exploit its full potential. In fact, OTB interfaces are unfortunately essential, and some necessary functions are missing. Therefore, a new QGIS plugin was developed in order to run the entire process in the most photogrammetrically and statistically correct way, and, at the same time, to simplify the relative procedures. [ABSTRACT FROM AUTHOR]

The PARSIFAL (Probabilistic Approach to pRovide Scenarios of earthquake Induced slope FAiLures) method was applied to the survey of post-earthquake landslides in central Italy for seismic microzonation purposes. In order to optimize time and resources, while also reducing errors, the paper-based method of survey data sheets was translated into digital formats using such instruments as Tablet PCs, GPS and open source software (QGIS). To the base mapping consisting of Technical Regional Map (Carta Tecnica Regionale—CTRs) at the scale of 1:10,000, layers were added with such sensitive information as the Inventory of Landslide Phenomena in Italy (Inventario dei Fenomeni Franosi in Italia—IFFI), for example. A database was designed and implemented in the SQLite/SpatiaLite Relational DataBase Management System (RDBMS) to store data related to such elements as landslides, rock masses, discontinuities and covers (as provided by PARSIFAL). To facilitate capture of the datum on the ground, data entry forms were created with Qt Designer. In addition to this, the employment of some QGIS plug-ins, developed for digital surveying and enabling of quick annotations on the map and the import of images from external cameras, was found to be of considerable use. [ABSTRACT FROM AUTHOR]