Special Issue "Volunteered Geographic Information: Analysis, Integration, Vision, Engagement (VGI-ALIVE)"

Special Issue Editors

Guest Editor
Dr. Peter Mooney

Department of Computer Science, Maynooth University, Maynooth, Ireland
Website | E-Mail
Interests: volunteered geographic information (VGI); citizen science; geospatial data mining and knowledge extraction; free and open source software for geomatics (FOSS4G)
Guest Editor
Dr. Franz-Benjamin Mocnik

University of Heidelberg, Germany
Website | E-Mail
Guest Editor
Prof. Dr. Alexander Zipf

GIScience Research Group, Institute of Geography, University of Heidelberg, Berliner Strasse 48, 69120 Heidelberg, Germany
Website | E-Mail
Interests: volunteered geographic information; crowdsourcing; citizen science; location based services; SDI
Guest Editor
Dr. Jamal Jokar Arsanjani

Geographic Information Science, Department of Planning and Development, Aalborg University Copenhagen, A.C. Meyers Vænge 15, DK-2450 Copenhagen, Denmark
Website | E-Mail
Phone: 93562323
Interests: volunteered geographic information (VGI); big (geo) data; crowdsourced mapping; citizen science; geocomputation; digital earth; remote sensing and spatio-temporal monitoring of environment; data fusion; (geo)data quality
Guest Editor
Dr. Hartwig H. Hochmair

University of Florida, United States
Website | E-Mail
Guest Editor
Ms. Kiran Zahra

University of Zurich, Switzerland
Website | E-Mail

Special Issue Information

Dear Colleagues,

The steady rise of data volume shared on already-established and new Volunteered Geographic Information (VGI) and social media platforms calls for advanced analysis methods of user contribution patterns, leads to continued challenges in data fusion, and provides also new opportunities for rapid data analysis for event detection and VGI data quality assessment. Questions regarding the future of VGI and social media platforms include the prospect of continued user growth, engagement of new user groups, further expansion of VGI to educational activities, and closing data gaps in geographically underrepresented areas.

Although some papers for this Special Issue will be drawn from a related one day VGI-ALIVE workshop at the AGILE 2018 conference, other original submissions aligned with this area of research are also highly welcome. The workshop evolves around a wide range of VGI and social/media research topics including cross-platform data contributions, innovative VGI analysis approaches, current data fusion methods, data interoperability, real-world applications, and the use of VGI and social media use in education. Contributions that discuss future challenges of VGI and social media, may it be on the legal or technical side, that formulate a vision for VGI and social media usage and analysis for the near future, and that demonstrate analysis workflows or the integration of VGI into education are also welcome. This Special Issue offers an outlet for publishing papers relevant to the scope of this workshop. Papers will be reviewed on a continuing basis until the submission deadline.

Article processing fees of IJGI can be waived for a limited number of papers, where priority is given to papers presented during the VGI-ALIVE workshop at the AGILE 2018 conference and early submissions. Please contact the Guest Editors for more information.

Special issue topics include (but are not limited to):

  • Activity patterns and collaboration across multiple VGI and social media platforms
  • (Quasi) real-time analysis of VGI and social media content
  • Technical and legal aspects of crowd-sourced data fusion
  • Opportunities, challenges, and limitations for the future of VGI
  • VGI and social media analysis in geographic areas with sparse data coverage
  • Novel methods of VGI data quality assessment
  • Mobility patterns from VGI and social media
  • User engagement and VGI education
  • Closing the gaps in VGI data coverage

Dr. Peter Mooney
Dr. Franz-Benjamin Mocnik
Prof. Dr. Alexander Zipf
Dr. Jamal Jokar Arsanjani
Dr. Hartwig H. Hochmair
Ms. Kiran Zahra
Guest Editors

Manuscript Submission Information

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Published Papers (4 papers)

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Research

Open AccessArticle Checking the Consistency of Volunteered Phenological Observations While Analysing Their Synchrony
ISPRS Int. J. Geo-Inf. 2018, 7(12), 487; https://doi.org/10.3390/ijgi7120487
Received: 21 October 2018 / Revised: 9 December 2018 / Accepted: 13 December 2018 / Published: 19 December 2018
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Abstract
The increasing availability of volunteered geographic information (VGI) enables novel studies in many scientific domains. However, inconsistent VGI can negatively affect these studies. This paper describes a workflow that checks the consistency of Volunteered Phenological Observations (VPOs) while considering the synchrony of observations
[...] Read more.
The increasing availability of volunteered geographic information (VGI) enables novel studies in many scientific domains. However, inconsistent VGI can negatively affect these studies. This paper describes a workflow that checks the consistency of Volunteered Phenological Observations (VPOs) while considering the synchrony of observations (i.e., the temporal dispersion of a phenological event). The geographic coordinates, day of the year (DOY) of the observed event, and the accumulation of daily temperature until that DOY were used to: (1) spatially group VPOs by connecting observations that are near to each other, (2) define consistency constraints, (3) check the consistency of VPOs by evaluating the defined constraints, and (4) optimize the constraints by analysing the effect of inconsistent VPOs on the synchrony models derived from the observations. This workflow was tested using VPOs collected in the Netherlands during the period 2003–2015. We found that the average percentage of inconsistent observations was low to moderate (ranging from 1% for wood anemone and pedunculate oak to 15% for cow parsley species). This indicates that volunteers provide reliable phenological information. We also found a significant correlation between the standard deviation of DOY of the observed events and the accumulation of daily temperature (with correlation coefficients ranging from 0.78 for lesser celandine, and 0.60 for pedunculate oak). This confirmed that colder days in late winter and early spring lead to synchronous flowering and leafing onsets. Our results highlighted the potential of synchrony information and geographical context for checking the consistency of phenological VGI. Other domains using VGI can adapt this geocomputational workflow to check the consistency of their data, and hence the robustness of their analyses. Full article
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Open AccessArticle Optimising Citizen-Driven Air Quality Monitoring Networks for Cities
ISPRS Int. J. Geo-Inf. 2018, 7(12), 468; https://doi.org/10.3390/ijgi7120468
Received: 31 August 2018 / Revised: 23 November 2018 / Accepted: 27 November 2018 / Published: 30 November 2018
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Abstract
Air quality has had a significant impact on public health, the environment and eventually on the economy of countries for decades. Effectively mitigating air pollution in urban areas necessitates accurate air quality exposure information. Recent advancements in sensor technology and the increasing popularity
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Air quality has had a significant impact on public health, the environment and eventually on the economy of countries for decades. Effectively mitigating air pollution in urban areas necessitates accurate air quality exposure information. Recent advancements in sensor technology and the increasing popularity of volunteered geographic information (VGI) open up new possibilities for air quality exposure assessment in cities. However, citizens and their sensors are put in areas deemed to be subjectively of interest (e.g., where citizens live, school of their kids or working spaces), and this leads to missed opportunities when it comes to optimal air quality exposure assessment. In addition, while the current literature on VGI has extensively discussed data quality and citizen engagement issues, few works, if any, offer techniques to fine-tune VGI contributions for an optimal air quality exposure assessment. This article presents and tests an approach to minimise land use regression prediction errors on citizen-contributed data. The approach was evaluated using a dataset (N = 116 sensors) from the city of Stuttgart, Germany. The comparison between the existing network design and the combination of locations selected by the optimisation method has shown a drop in spatial mean prediction error by 52%. The ideas presented in this article are useful for the systematic deployment of VGI air quality sensors, and can aid in the creation of higher resolution, more realistic maps for air quality monitoring in cities. Full article
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Open AccessArticle Change Detection for Building Footprints with Different Levels of Detail Using Combined Shape and Pattern Analysis
ISPRS Int. J. Geo-Inf. 2018, 7(10), 406; https://doi.org/10.3390/ijgi7100406
Received: 31 August 2018 / Revised: 4 October 2018 / Accepted: 9 October 2018 / Published: 13 October 2018
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Abstract
Crowd-sourced geographic information is becoming increasingly available, providing diverse and timely sources for updating existing spatial databases to facilitate urban studies, geoinformatics, and real estate practices. However, the discrepancies between heterogeneous datasets present challenges for automated change detection. In this paper, we identify
[...] Read more.
Crowd-sourced geographic information is becoming increasingly available, providing diverse and timely sources for updating existing spatial databases to facilitate urban studies, geoinformatics, and real estate practices. However, the discrepancies between heterogeneous datasets present challenges for automated change detection. In this paper, we identify important measurable factors to account for issues like boundary mismatch, large offset, and discrepancies in the levels of detail between the more current and to-be-updated datasets. These factors are organized into rule sets that include data matching, merge of the many-to-many correspondence, controlled displacement, shape similarity, morphology of difference parts, and the building pattern constraint. We tested our approach against OpenStreetMap and a Dutch topographic dataset (TOP10NL). By removing or adding some components, the results show that our approach (accuracy = 0.90) significantly outperformed a basic geometric method (0.77), commonly used in previous studies, implying a more reliable change detection in realistic update scenarios. We further found that distinguishing between small and large buildings was a useful heuristic in creating the rules. Full article
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Open AccessArticle Improving the Quality of Citizen Contributed Geodata through Their Historical Contributions: The Case of the Road Network in OpenStreetMap
ISPRS Int. J. Geo-Inf. 2018, 7(7), 253; https://doi.org/10.3390/ijgi7070253
Received: 17 April 2018 / Revised: 11 June 2018 / Accepted: 27 June 2018 / Published: 28 June 2018
Cited by 1 | PDF Full-text (11685 KB) | HTML Full-text | XML Full-text
Abstract
OpenStreetMap (OSM) has proven to serve as a promising free global encyclopedia of maps with an increasing popularity across different user communities and research bodies. One of the unique characteristics of OSM has been the availability of the full history of users’ contributions,
[...] Read more.
OpenStreetMap (OSM) has proven to serve as a promising free global encyclopedia of maps with an increasing popularity across different user communities and research bodies. One of the unique characteristics of OSM has been the availability of the full history of users’ contributions, which can leverage our quality control mechanisms through exploiting the history of contributions. Since this aspect of contributions (i.e., historical contributions) has been neglected in the literature, this study aims at presenting a novel approach for improving the positional accuracy and completeness of the OSM road network. To do so, we present a five-stage approach based on a Voronoi diagram that leads to improving the positional accuracy and completeness of the OSM road network. In the first stage, the OSM data history file is retrieved and in the second stage, the corresponding data elements for each object in the historical versions are identified. In the third stage, data cleaning on the historical datasets is carried out in order to identify outliers and remove them accordingly. In the fourth stage, through applying the Voronoi diagram method, one representative version for each set of historical versions is extracted. In the final stage, through examining the spatial relations for each object in the history file, the topology of the target object is enhanced. As per validation, a comparison between the latest version of the OSM data and the result of our approach against a reference dataset is carried out. Given a case study in Tehran, our findings reveal that the completeness and positional precision of OSM features can be improved up to 14%. Our conclusions draw attention to the exploitation of the historical archive of the contributions in OSM as an intrinsic quality indicator. Full article
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