Special Issue "Free and Open Source Tools for Geospatial Analysis and Mapping"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 31 March 2019

Special Issue Editors

Guest Editor
Dr. Paolo Dabove

Department of Environment, Land, and Infrastructure Engineering (DIATI), Politecnico di Torino, 10129 Turin, Italy
Website | E-Mail
Interests: surveying and mapping
Guest Editor
Dr. Bianca Federici

Department of Civil, Chemical and Environmental Engineering (DICCA), University of Genoa, 16145 Genoa, Italy
Website | E-Mail
Interests: remote sensing and GIS

Special Issue Information

Dear Colleagues,

Recent years have been characterized by rapid developments in various fields of geospatial analysis and mapping. The use of Free and Open Source Software (FOSS) has developed rapidly at both commercial and academic research levels.

This Special Issue brings together scientists, developers and advanced users in software development, geographical data acquisition, processing and visualization, aiming to encourage cooperation and diffusion in the various fields where open source technologies are nowadays used.

With this Special Issue on "Free and Open Source Tools for Geospatial Analysis and Mapping", we address research methods, as well as applications on the design, implementation, characterization and use of free and open-source software for geospatial and environmental analysis, positioning, mapping, photogrammetry, remote sensing and spatial information science. This includes the development of new and innovative technological concepts based on free and open source software for scientific research, as well as for education and business projects.

Prospective authors are cordially invited to contribute to this Special Issue by submitting an article containing original research.

Dr. Paolo Dabove
Dr. Bianca Federici
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Research

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Open AccessArticle A QGIS Tool for Automatically Identifying Asbestos Roofing
ISPRS Int. J. Geo-Inf. 2019, 8(3), 131; https://doi.org/10.3390/ijgi8030131
Received: 25 January 2019 / Revised: 10 February 2019 / Accepted: 24 February 2019 / Published: 6 March 2019
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Abstract
Exposure to asbestos fibers implies a long-term risk for human health; therefore, the development of information systems that are able to detect the extent and status of asbestos over a certain territory has become a priority. This work presents a tool (based on [...] Read more.
Exposure to asbestos fibers implies a long-term risk for human health; therefore, the development of information systems that are able to detect the extent and status of asbestos over a certain territory has become a priority. This work presents a tool (based on the geographic information system open source software, QGIS) that is conceived for automatically identifying buildings with asbestos roofing. The area under investigation is the metropolitan area around Prato (Italy). The performance analysis of this system was carried out by classifying images that were acquired by the WorldView-3 sensor. These images are available at a low cost when compared with those obtained by means of aerial surveys, and they provide adequate resolution levels for roofing classification. The tool, a QGIS plugin, has shown fairly good performance in identifying asbestos roofing, with some false negatives and some false positives when applying a per-pixel classification. A performance improvement is obtainable when considering the percentage of asbestos pixels that are contained in each roof of the analyzed image. This value is also available with the plugin. In the future, this tool should make it possible to monitor the asbestos roof removal process over time in the area of interest, in accordance with other image data that give evidence of such removals. Full article
(This article belongs to the Special Issue Free and Open Source Tools for Geospatial Analysis and Mapping)
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Open AccessArticle The CM SAF R Toolbox—A Tool for the Easy Usage of Satellite-Based Climate Data in NetCDF Format
ISPRS Int. J. Geo-Inf. 2019, 8(3), 109; https://doi.org/10.3390/ijgi8030109
Received: 5 February 2019 / Revised: 18 February 2019 / Accepted: 24 February 2019 / Published: 28 February 2019
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Abstract
The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) provides satellite-based climate data records of essential climate variables of the energy budget and water cycle. The data records are generally distributed in NetCDF format. To simplify the preparation, analysis, and visualization of [...] Read more.
The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) provides satellite-based climate data records of essential climate variables of the energy budget and water cycle. The data records are generally distributed in NetCDF format. To simplify the preparation, analysis, and visualization of the data, CM SAF provides the so-called CM SAF R Toolbox. This is a collection of R-based tools, which are optimized for spatial data with longitude, latitude, and time dimension. For analysis and manipulation of spatial NetCDF-formatted data, the functionality of the cmsaf R-package is implemented. This R-package provides more than 60 operators. The visualization of the data, its properties, and corresponding statistics can be done with an interactive plotting tool with a graphical user interface, which is part of the CM SAF R Toolbox. The handling, functionality, and visual appearance are demonstrated here based on the analysis of sunshine duration in Europe for the year 2018. Sunshine duration in Scandinavia and Central Europe was extraordinary in 2018 compared to the long-term average. Full article
(This article belongs to the Special Issue Free and Open Source Tools for Geospatial Analysis and Mapping)
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Open AccessArticle A Field Data Acquisition Method and Tools for Hazard Evaluation of Earthquake-Induced Landslides with Open Source Mobile GIS
ISPRS Int. J. Geo-Inf. 2019, 8(2), 91; https://doi.org/10.3390/ijgi8020091
Received: 29 November 2018 / Revised: 15 January 2019 / Accepted: 11 February 2019 / Published: 15 February 2019
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Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Free and Open Source Tools for Geospatial Analysis and Mapping)
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Open AccessArticle An Analysis of the Evolution, Completeness and Spatial Patterns of OpenStreetMap Building Data in China
ISPRS Int. J. Geo-Inf. 2019, 8(1), 35; https://doi.org/10.3390/ijgi8010035
Received: 24 October 2018 / Revised: 11 December 2018 / Accepted: 9 January 2019 / Published: 16 January 2019
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Abstract
OpenStreetMap (OSM) is a free map that can be created, edited, and updated by volunteers globally. The quality of OSM datasets is therefore of great concern. Extensive studies have focused on assessing the completeness (a quality measure) of OSM datasets in various countries, [...] Read more.
OpenStreetMap (OSM) is a free map that can be created, edited, and updated by volunteers globally. The quality of OSM datasets is therefore of great concern. Extensive studies have focused on assessing the completeness (a quality measure) of OSM datasets in various countries, but very few have been paid attention to investigating the OSM building dataset in China. This study aims to present an analysis of the evolution, completeness and spatial patterns of OSM building data in China across the years 2012 to 2017. This is done using two quality indicators, OSM building count and OSM building density, although a corresponding reference dataset for the whole country is not freely available. Development of OSM building counts from 2012 to 2017 is analyzed in terms of provincial- and prefecture-level divisions. Factors that may affect the development of OSM building data in China are also analyzed. A 1 × 1 km2 regular grid is overlapped onto urban areas of each prefecture-level division, and the OSM building density of each grid cell is calculated. Spatial distributions of high-density grid cells for prefecture-level divisions are analyzed. Results show that: (1) the OSM building count increases by almost 20 times from 2012 to 2017, and in most cases, economic (gross domestic product) and OSM road length are two factors that may influence the development of OSM building data in China; (2) most grid cells in urban areas do not have any building data, but two typical patterns (dispersion and aggregation) of high-density grid cells are found among prefecture-level divisions. Full article
(This article belongs to the Special Issue Free and Open Source Tools for Geospatial Analysis and Mapping)
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Open AccessArticle Shp2graph: Tools to Convert a Spatial Network into an Igraph Graph in R
ISPRS Int. J. Geo-Inf. 2018, 7(8), 293; https://doi.org/10.3390/ijgi7080293
Received: 4 June 2018 / Revised: 29 June 2018 / Accepted: 19 July 2018 / Published: 24 July 2018
Cited by 1 | PDF Full-text (3452 KB) | HTML Full-text | XML Full-text
Abstract
In this study, we introduce the R package shp2graph, which provides tools to convert a spatial network into an ‘igraph’ graph of the igraphR package. This conversion greatly empowers a spatial network study, as the vast array of graph [...] Read more.
In this study, we introduce the R package shp2graph, which provides tools to convert a spatial network into an ‘igraph’ graph of the igraphR package. This conversion greatly empowers a spatial network study, as the vast array of graph analytical tools provided in igraph are then readily available to the network analysis, together with the inherent advantages of being within the R statistical computing environment and its vast array of statistical functions. Through three urban road network case studies, the calculation of road network distances with shp2graph and with igraph is demonstrated through four key stages: (i) confirming the connectivity of a spatial network; (ii) integrating points/locations with a network; (iii) converting a network into a graph; and (iv) calculating network distances (and travel times). Throughout, the required R commands are given to provide a useful tutorial on the use of shp2graph. Full article
(This article belongs to the Special Issue Free and Open Source Tools for Geospatial Analysis and Mapping)
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Open AccessFeature PaperTechnical Note HidroMap: A New Tool for Irrigation Monitoring and Management Using Free Satellite Imagery
ISPRS Int. J. Geo-Inf. 2018, 7(6), 220; https://doi.org/10.3390/ijgi7060220
Received: 7 May 2018 / Revised: 31 May 2018 / Accepted: 12 June 2018 / Published: 15 June 2018
Cited by 2 | PDF Full-text (6544 KB) | HTML Full-text | XML Full-text
Abstract
Proper control and planning of water resource use, especially in those catchments with large surface, climatic variability and intensive irrigation activity, is essential for a sustainable water management. Decision support systems based on useful tools involving main stakeholders and hydrological planning offices of [...] Read more.
Proper control and planning of water resource use, especially in those catchments with large surface, climatic variability and intensive irrigation activity, is essential for a sustainable water management. Decision support systems based on useful tools involving main stakeholders and hydrological planning offices of the river basins play a key role. The free availability of Earth observation products with high temporal resolution, such as the European Sentinel-2B, has allowed us to combine remote sensing with cadastral and agronomic data. This paper introduces HidroMap to the scientific community, an open source tool as a geographic information system (GIS) organized in two different modules, desktop-GIS and web-GIS, with complementary functions and based on PostgreSQL/PostGIS database. Through an effective methodology HidroMap allows monitoring irrigation activity, managing unregulated irrigation, and optimizing available fluvial surveillance resources using satellite imagery. This is possible thanks to the automatic download, processing and storage of satellite products within field data provided by the River Surveillance Agency (RSA) and the Hydrological Planning Office (HPO). The tool was successfully validated in Duero Hydrographic Basin along the 2017 summer irrigation period. In conclusion, HidroMap comprised an important support tool for water management tasks and decision making tackled by Duero Hydrographic Confederation which can be adapted to any additional need and transferred to other river basin organizations. Full article
(This article belongs to the Special Issue Free and Open Source Tools for Geospatial Analysis and Mapping)
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