Special Issue "Geoinformatics in Citizen Science"

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

Deadline for manuscript submissions: closed (31 March 2018)

Special Issue Editor

Guest Editor
Dr. Gloria Bordogna

CNR IREA, via Bassini 15, 20133 Milano, Italy
Website | E-Mail
Interests: fuzzy logic and soft computing for the representation and management of imprecision and uncertainty of textual and geographic information; Volunteered Geographic Information user-driven quality assessment in citizen science; Crowdsourced information spatio-temporal analytics; Information retrieval on the Web; Flexible Query Languages for Information Retrieval; ill-defined environmental knowledge representation and management; multisource geographic information fusion

Special Issue Information

Dear Colleagues,

It is with great pleasure that I announce a call for papers for a Special Issue on "Geoinformatics in Citizen Science".

"Citizen Science" indicates an increasing collaborative practice to carry out scientific projects by the involvement of a large number of volunteer citizens who are called to perform some specific tasks. The diffusion of citizen science is testified by the growth of the European Citizen Science Association (ECSA) and the USA (Citizen Science Association), which enhances the participation by the general public in scientific processes, mainly by initiating and supporting citizen science projects.

This old practice, primarily born within the naturalistic field to enrich museum collections, with the advent of the Web and smart mobile devices connected to the Internet, has changed by sharply increasing both the quantity, the timeliness, and the worldwide provenance of volunteers, as well as the quantity, types and quality of their contributions.

These large changes make it possible to adopt this practice to a variety of new purposes, such as for monitoring processes varying in both space and time, thus constituting a new challenge for science, which calls for powerful means to process very large amounts of geoinformation.

In fact, geoinformation is a major dimension of the contributions provided by volunteers: Most citizen science projects in the naturalistic and environmental fields exploit Volunteer Geographic Information (VGI), that is, volunteers are asked to provide information of various types and nature, such as textual notes, pictures, measurements of properties relative to target objects or events, by associating a geographic reference with their observations which allow scientists studying the geographic distribution and changes of the habitats and environment. Other projects need to collect and analyze the geographic distributions of volunteers who declared diseases in order to study pandemics.

Thus, citizen science needs geoinformatics in order to easily collect information from the field, to filter such information with respect to its reliability and quality, and to cross-analyze it with respect to geoinformation from other sources (remote sensing, in situ sensors data, etc.) for the purpose of the projects.

On the other hand, geoinformatic research can fruitfully exploit citizen science projects to tackle novel issues, such as reliability assessment methods of volunteers, quality assessment of their contributions, spatial cross-analysis copying the uncertainty and imprecision of geoinformation, interoperable sharing of VGI, and to test newly defined methods with real data.

This Special Issue is dedicated to exploring current experiences and trends with regards to the conceptual, methodological, and technological approaches defined and used in citizen science projects for processing and analyzing geoinformation and of the social aspects related with their application. We call for original papers from researchers worldwide, both in geoinformatic communities and citizen science associations and projects.

Gloria Bordogna
Guest Editor

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.

Keywords

  • Geoinformation in Citizen Science
  • VGI in Citizen Science
  • Crowdsourced Geoinformation Collection and Analysis

Published Papers (10 papers)

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Research

Open AccessFeature PaperArticle CS Projects Involving Geoinformatics: A Survey of Implementation Approaches
ISPRS Int. J. Geo-Inf. 2018, 7(8), 312; https://doi.org/10.3390/ijgi7080312
Received: 30 March 2018 / Revised: 4 June 2018 / Accepted: 25 June 2018 / Published: 2 August 2018
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Abstract
In the last decade, citizen science (CS) has seen a renewed interest from both traditional science and the lay public as testified by a wide number of initiatives, projects, and dedicated technological applications. One of the main reasons for this renewed interest lies
[...] Read more.
In the last decade, citizen science (CS) has seen a renewed interest from both traditional science and the lay public as testified by a wide number of initiatives, projects, and dedicated technological applications. One of the main reasons for this renewed interest lies in the fact that the ways in which citizen science projects are designed and managed have been significantly improved by the recent advancements in information and communications technologies (ICT), especially in the field of geoinformatics. In this research work, we investigate currently active citizen science projects that involve geoinformation to understand how geoinformatics is actually employed. To achieve this, we define eight activities typically carried out during the implementation of a CS initiative as well as a series of approaches for each activity, in order to pinpoint distinct strategies within the different projects. To this end, a representative set of ongoing CS initiatives is selected and surveyed. The results show how CS projects address the various activities, and report which strategies and technologies from geoinformatics are massively or marginally used. The quantitative results are presented, supported by examples and descriptions. Finally, cues and critical issues coming from the research are discussed. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle A New Method for the Assessment of Spatial Accuracy and Completeness of OpenStreetMap Building Footprints
ISPRS Int. J. Geo-Inf. 2018, 7(8), 289; https://doi.org/10.3390/ijgi7080289
Received: 29 April 2018 / Revised: 14 July 2018 / Accepted: 20 July 2018 / Published: 24 July 2018
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Abstract
OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data, widely used in many projects as an alternative to or integrated with authoritative data. One of the main criticisms against this dataset is that, being a collaborative product created mainly by
[...] Read more.
OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data, widely used in many projects as an alternative to or integrated with authoritative data. One of the main criticisms against this dataset is that, being a collaborative product created mainly by citizens without formal qualifications, its quality has not been assessed and therefore its usage can be questioned for some applications. This paper provides a map matching method to check the spatial accuracy of the building footprint layer, based on a comparison with a reference dataset. Moreover, from the map matching and a similarity check, buildings can be detected and therefore an index of completeness can also be computed. This process has been applied in Lombardy, a region in Northern Italy, covering an area of 23,900 km2 and comprising respectively about 1 million buildings in OSM and 2.8 million buildings in the authoritative dataset. The results of the comparison show that the positional accuracy of the OSM buildings is at least compatible with the quality of the reference dataset at the scale of 1:5000 since the average deviation, with respect to the authoritative map, is below the expected tolerance of 3 m. The analysis of completeness, given in terms of the number of buildings appearing in the authoritative dataset and not present in OSM, shows an average percentage in the whole region equal to 57%. However, worth noting that the opposite, namely the number of buildings in OSM and not in the reference dataset, is not zero, but corresponds to 9%. The OSM building map can therefore be considered to be a valid base map for direct use (territorial frameworks, map navigation, urban analysis, etc.) and for derived use (background for the production of thematic maps) in all those cases where an accuracy corresponding to 1:5000 is required. Moreover it could be used for integrating the authoritative map at this scale (or smaller) where it is not complete and a rigorous quality certification in terms of metric precision is not required. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle A Citizen Science Approach for Collecting Toponyms
ISPRS Int. J. Geo-Inf. 2018, 7(6), 222; https://doi.org/10.3390/ijgi7060222
Received: 30 March 2018 / Revised: 1 June 2018 / Accepted: 13 June 2018 / Published: 16 June 2018
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Abstract
The emerging trends and technologies of surveying and mapping potentially enable local experts to contribute and share their local geographical knowledge of place names (toponyms). We can see the increasing numbers of toponyms in digital platforms, such as OpenStreetMap, Facebook Place Editor, Swarm
[...] Read more.
The emerging trends and technologies of surveying and mapping potentially enable local experts to contribute and share their local geographical knowledge of place names (toponyms). We can see the increasing numbers of toponyms in digital platforms, such as OpenStreetMap, Facebook Place Editor, Swarm Foursquare, and Google Local Guide. On the other hand, government agencies keep working to produce concise and complete gazetteers. Crowdsourced geographic information and citizen science approaches offer a new paradigm of toponym collection. This paper addresses issues in the advancing toponym practice. First, we systematically examined the current state of toponym collection and handling practice by multiple stakeholders, and we identified a recurring set of problems. Secondly, we developed a citizen science approach, based on a crowdsourcing level of participation, to collect toponyms. Thirdly, we examined the implementation in the context of an Indonesian case study. The results show that public participation in toponym collection is an approach with the potential to solve problems in toponym handling, such as limited human resources, accessibility, and completeness of toponym information. The lessons learnt include the knowledge that the success of this approach depends on the willingness of the government to advance their workflow, the degree of collaboration between stakeholders, and the presence of a communicative approach in introducing and sharing toponym guidelines with the community. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform
ISPRS Int. J. Geo-Inf. 2018, 7(5), 187; https://doi.org/10.3390/ijgi7050187
Received: 28 March 2018 / Revised: 24 April 2018 / Accepted: 7 May 2018 / Published: 12 May 2018
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Abstract
Although air pollution is one of the most significant environmental factors posing a threat to human health worldwide, air quality data are scarce or not easily accessible in most European countries. The current work aims to develop a centralized air quality data hub
[...] Read more.
Although air pollution is one of the most significant environmental factors posing a threat to human health worldwide, air quality data are scarce or not easily accessible in most European countries. The current work aims to develop a centralized air quality data hub that enables citizens to contribute to air quality monitoring. In this work, data from official air quality monitoring stations are combined with air pollution estimates from sky-depicting photos and from low-cost sensing devices that citizens build on their own so that citizens receive improved information about the quality of the air they breathe. Additionally, a data fusion algorithm merges air quality information from various sources to provide information in areas where no air quality measurements exist. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle Coupling Traditional Monitoring and Citizen Science to Disentangle the Invasion of Halyomorpha halys
ISPRS Int. J. Geo-Inf. 2018, 7(5), 171; https://doi.org/10.3390/ijgi7050171
Received: 28 March 2018 / Revised: 19 April 2018 / Accepted: 30 April 2018 / Published: 4 May 2018
Cited by 1 | PDF Full-text (2184 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
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
[...] Read more.
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. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle Obstacles and Opportunities of Using a Mobile App for Marine Mammal Research
ISPRS Int. J. Geo-Inf. 2018, 7(5), 169; https://doi.org/10.3390/ijgi7050169
Received: 30 March 2018 / Revised: 24 April 2018 / Accepted: 28 April 2018 / Published: 3 May 2018
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Abstract
This study investigates the use of a mobile application, Whale mAPP, as a citizen science tool for collecting marine mammal sighting data. In just over three months, 1261 marine mammal sightings were observed and recorded by 39 citizen scientists in Southeast Alaska. The
[...] Read more.
This study investigates the use of a mobile application, Whale mAPP, as a citizen science tool for collecting marine mammal sighting data. In just over three months, 1261 marine mammal sightings were observed and recorded by 39 citizen scientists in Southeast Alaska. The resulting data, along with a preliminary and post-Whale mAPP questionnaires, were used to evaluate the tool’s scientific, educational, and engagement feasibility. A comparison of Whale mAPP Steller sea lion distribution data to a scientific dataset were comparable (91% overlap) given a high enough sample size (n = 73) and dense spatial coverage. In addition, after using Whale mAPP for two weeks, citizen scientists improved their marine mammal identification skills and self-initiated further learning, representing preliminary steps in developing an engaging citizen science project. While the app experienced high initial enthusiasm, maintaining prolonged commitment represents one of the fundamental challenges for this project. Increasing participation with targeted recruitment and sustained communication will help combat the limitations of sample size and spatial coverage. Overall, this study emphasizes the importance of early evaluation of the educational and scientific outcomes of a citizen science project, so that limitations are recognized and reduced. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle OSM Data Import as an Outreach Tool to Trigger Community Growth? A Case Study in Miami
ISPRS Int. J. Geo-Inf. 2018, 7(3), 113; https://doi.org/10.3390/ijgi7030113
Received: 1 January 2018 / Revised: 26 February 2018 / Accepted: 12 March 2018 / Published: 15 March 2018
Cited by 1 | PDF Full-text (6748 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents the results of a study that explored if and how an OpenStreetMap (OSM) data import task can contribute to OSM community growth. Different outreach techniques were used to introduce a building import task to three targeted OSM user groups. First,
[...] Read more.
This paper presents the results of a study that explored if and how an OpenStreetMap (OSM) data import task can contribute to OSM community growth. Different outreach techniques were used to introduce a building import task to three targeted OSM user groups. First, existing OSM members were contacted and asked to join the data import project. Second, several local community events were organized with Maptime Miami to engage local mappers in OSM contribution activities. Third, the import task was introduced as an extra credit assignment in two GIS courses at the University of Florida. The paper analyzes spatio-temporal user contributions of these target groups to assess the effectiveness of the different outreach techniques for recruitment and retention of OSM contributors. Results suggest that the type of prospective users that were contacted through our outreach efforts, and their different motivations play a major role in their editing activity. Results also revealed differences in editing patterns between newly recruited users and already established mappers. More specifically, long-term engagement of newly registered OSM mappers did not succeed, whereas already established contributors continued to import and improve data. In general, we found that an OSM data import project can add valuable data to the map, but also that encouraging long-term engagement of new users, whether it be within the academic environment or outside, proved to be challenging. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data
ISPRS Int. J. Geo-Inf. 2018, 7(3), 80; https://doi.org/10.3390/ijgi7030080
Received: 22 January 2018 / Revised: 16 February 2018 / Accepted: 21 February 2018 / Published: 25 February 2018
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Abstract
Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the
[...] Read more.
Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the accuracy with which they can label cases. Here, the potential to increase the accuracy of crowdsourced data on land cover identified from satellite remote sensor images through the use of weighted voting strategies is explored. Critically, the information used to weight contributions based on the accuracy with which a contributor labels cases of a class and the relative abundance of class are inferred entirely from the contributed data only via a latent class analysis. The results show that consensus approaches do yield a classification that is more accurate than that achieved by any individual contributor. Here, the most accurate individual could classify the data with an accuracy of 73.91% while a basic consensus label derived from the data provided by all seven volunteers contributing data was 76.58%. More importantly, the results show that weighting contributions can lead to a statistically significant increase in the overall accuracy to 80.60% by ignoring the contributions from the volunteer adjudged to be the least accurate in labelling. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle An Automatic User Grouping Model for a Group Recommender System in Location-Based Social Networks
ISPRS Int. J. Geo-Inf. 2018, 7(2), 67; https://doi.org/10.3390/ijgi7020067
Received: 29 December 2017 / Revised: 10 February 2018 / Accepted: 18 February 2018 / Published: 21 February 2018
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Abstract
Spatial group recommendation refers to suggesting places to a given set of users. In a group recommender system, members of a group should have similar preferences in order to increase the level of satisfaction. Location-based social networks (LBSNs) provide rich content, such as
[...] Read more.
Spatial group recommendation refers to suggesting places to a given set of users. In a group recommender system, members of a group should have similar preferences in order to increase the level of satisfaction. Location-based social networks (LBSNs) provide rich content, such as user interactions and location/event descriptions, which can be leveraged for group recommendations. In this paper, an automatic user grouping model is introduced that obtains information about users and their preferences through an LBSN. The preferences of the users, proximity of the places the users have visited in terms of spatial range, users’ free days, and the social relationships among users are extracted automatically from location histories and users’ profiles in the LBSN. These factors are combined to determine the similarities among users. The users are partitioned into groups based on these similarities. Group size is the key to coordinating group members and enhancing their satisfaction. Therefore, a modified k-medoids method is developed to cluster users into groups with specific sizes. To evaluate the efficiency of the proposed method, its mean intra-cluster distance and its distribution of cluster sizes are compared to those of general clustering algorithms. The results reveal that the proposed method compares favourably with general clustering approaches, such as k-medoids and spectral clustering, in separating users into groups of a specific size with a lower mean intra-cluster distance. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Open AccessArticle Experiences with Citizen-Sourced VGI in Challenging Circumstances
ISPRS Int. J. Geo-Inf. 2017, 6(12), 385; https://doi.org/10.3390/ijgi6120385
Received: 20 October 2017 / Revised: 20 November 2017 / Accepted: 22 November 2017 / Published: 26 November 2017
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Abstract
The article explores the process of Volunteered Geographic Information (VGI) collection by assessing the relative usability and accuracy of a range of different methods (smartphone GPS, tablet, and analogue maps) for data collection among different demographic and educational groups, and in different geographical
[...] Read more.
The article explores the process of Volunteered Geographic Information (VGI) collection by assessing the relative usability and accuracy of a range of different methods (smartphone GPS, tablet, and analogue maps) for data collection among different demographic and educational groups, and in different geographical contexts within a study area. Assessments are made of positional accuracy, completeness, and the experiences of citizen data collectors with reference to the official cadastral data and the land administration system. Ownership data were validated by crowd agreement. The outcomes of this research show the varying effects of volunteers, data collection method, geographical area, and application field, on geospatial data handling in the VGI arena. An overview of the many issues affecting the development and implementation of VGI projects is included. These are focused on the specific example of VGI data handling presented here: a case study area where instability and lack of resources are found alongside strong communities and a pressing need for more robust and effective official structures. The chosen example relates to the administration of land in an area of Iraq. Full article
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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