Editorial

5 pages, 239 KiB

Open AccessEditorial

OSM Science—The Academic Study of the OpenStreetMap Project, Data, Contributors, Community, and Applications

by A. Yair Grinberger, Marco Minghini, Levente Juhász, Godwin Yeboah and Peter Mooney

ISPRS Int. J. Geo-Inf. 2022, 11(4), 230; https://doi.org/10.3390/ijgi11040230 - 30 Mar 2022

Cited by 12 | Viewed by 3657

This paper is an Editorial for the Special Issue titled “OpenStreetMap as a multidisciplinary nexus: perspectives, practices and procedures”. The Special Issue is largely based on the talks presented in the 2019 and 2020 editions of the Academic Track at the State of [...] Read more.

This paper is an Editorial for the Special Issue titled “OpenStreetMap as a multidisciplinary nexus: perspectives, practices and procedures”. The Special Issue is largely based on the talks presented in the 2019 and 2020 editions of the Academic Track at the State of the Map conferences. As such, it represents the most pressing and relevant issues and topics considered by the academic community in relation to OpenStreetMap (OSM)—a global project and community aimed to create and maintain a free and editable database and map of the world. In this Editorial, we survey the papers included in the Special Issue, grouping them into three research perspectives: applications of OSM for studies within other disciplines, OSM data quality, and dynamics in OSM. This survey reveals that these perspectives, while being distinct, are also interrelated. This calls for the formalization of an ‘OSM science’ that will provide the conceptual grounds to advance the scientific study of OSM, not as a set of individualized efforts but as a unified approach. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

Research

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29 pages, 5165 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Bridges and Barriers: An Exploration of Engagements of the Research Community with the OpenStreetMap Community

by A. Yair Grinberger, Marco Minghini, Godwin Yeboah, Levente Juhász and Peter Mooney

ISPRS Int. J. Geo-Inf. 2022, 11(1), 54; https://doi.org/10.3390/ijgi11010054 - 12 Jan 2022

Cited by 2 | Viewed by 3557

Abstract

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the [...] Read more.

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify possible causal structures explaining how these patterns may emerge within the context of a specific research group. Results indicate that academic papers generally show few signs of engagement and adopt data-oriented perspectives on the OSM project and product. The interviews expose that more complex perspectives and deeper engagement exist within the research group to which the interviewees belong, e.g., engaging in OSM mapping and direct interactions based on specific points-of-contact in the OSM community. Several conclusions and recommendations emerge, most notably: that every engagement with OSM includes an interpretive act which must be acknowledged and that the academic community should act to triangulate its interpretation of the data and OSM community by diversifying their engagement. This could be achieved through channels such as more direct interactions and inviting members of the OSM community to participate in the design and evaluation of research projects and programmes. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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22 pages, 1000 KiB

Open AccessArticle

On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness

by Alexander Bustamante, Laura Sebastia and Eva Onaindia

ISPRS Int. J. Geo-Inf. 2021, 10(5), 301; https://doi.org/10.3390/ijgi10050301 - 05 May 2021

Cited by 7 | Viewed by 2937

Abstract

Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek [...] Read more.

Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek to analyze the representativeness of the open and collaborative platform OpenStreetMap (OSM) to the international tourism scene. For this study, we selected eight parameters indicative of the tourism development of each country, such as the number of beds or cultural sites, and we extracted the OSM objects representative of these indicators. Then, we performed a statistical and regression analysis of the OSM data to compare and model the data emitted by WEF with data from OSM. Our aim is to analyze the tourist representativeness of the OSM data with respect to official reports to better understand when OSM data can be used to complement the official information and, in some cases, when official information is scarce or non-existent, to assess whether the OSM information can be a substitute. Results show that OSM data provide a fairly accurate picture of official tourism statistics for most variables. We also discuss the reasons why OSM data is not so representative for some variables in some specific countries. All in all, this work represents a step towards the exploitation of open and collaborative data for tourism. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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25 pages, 38533 KiB

Open AccessArticle

Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process: Evidence from Slums in Africa and Asia

by Godwin Yeboah, João Porto de Albuquerque, Rafael Troilo, Grant Tregonning, Shanaka Perera, Syed A. K. Shifat Ahmed, Motunrayo Ajisola, Ornob Alam, Navneet Aujla, Syed Iqbal Azam, Kehkashan Azeem, Pauline Bakibinga, Yen-Fu Chen, Nazratun Nayeem Choudhury, Peter J. Diggle, Olufunke Fayehun, Paramjit Gill, Frances Griffiths, Bronwyn Harris, Romaina Iqbal, Caroline Kabaria, Abdhalah Kasiira Ziraba, Afreen Zaman Khan, Peter Kibe, Lyagamula Kisia, Catherine Kyobutungi, Richard J. Lilford, Jason J. Madan, Nelson Mbaya, Blessing Mberu, Shukri F. Mohamed, Helen Muir, Ahsana Nazish, Anne Njeri, Oladoyin Odubanjo, Akinyinka Omigbodun, Mary E. Osuh, Eme Owoaje, Oyinlola Oyebode, Vangelis Pitidis, Omar Rahman, Narjis Rizvi, Jo Sartori, Simon Smith, Olalekan John Taiwo, Philipp Ulbrich, Olalekan A. Uthman, Samuel I. Watson, Ria Wilson and Rita Yusuf Show full author list Hide full author list

ISPRS Int. J. Geo-Inf. 2021, 10(4), 265; https://doi.org/10.3390/ijgi10040265 - 14 Apr 2021

Cited by 24 | Viewed by 9680

Abstract

This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare [...] Read more.

This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare access of slum residents in the Global South. Descriptive statistics and qualitative analysis were employed to examine the following research question: What is the spatial data quality of collaborative remote mapping achieved by volunteer mappers in morphologically complex urban areas? Findings show that the completeness achieved by remote mapping largely depends on the morphology and characteristics of slums such as building density and rooftop architecture, varying from 84% in the best case, to zero in the most difficult site. The major scientific contribution of this study is to provide evidence on the spatial data quality of remotely mapped data through volunteer mapping efforts in morphologically complex urban areas such as slums; the results could provide insights into how much fieldwork would be needed in what level of complexity and to what extent the involvement of local volunteers in these efforts is required. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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25 pages, 4733 KiB

Open AccessArticle

Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

by Christina Ludwig, Robert Hecht, Sven Lautenbach, Martin Schorcht and Alexander Zipf

ISPRS Int. J. Geo-Inf. 2021, 10(4), 251; https://doi.org/10.3390/ijgi10040251 - 09 Apr 2021

Cited by 33 | Viewed by 12979

Abstract

Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) [...] Read more.

Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its spatial resolution of 10 m fails to capture fine-grained urban structures, while in OSM green spaces are not mapped consistently and with the same level of completeness everywhere. To address these limitations, we propose to fuse these data sets under explicit consideration of their uncertainties. The Sentinel-2 derived Normalized Difference Vegetation Index was fused with OSM data using the Dempster–Shafer theory to enhance the detection of small vegetated areas. The distinction between public and private green spaces was achieved using a Bayesian hierarchical model and OSM data. The analysis was performed based on land use parcels derived from OSM data and tested for the city of Dresden, Germany. The overall accuracy of the final map of public urban green spaces was 95% and was mainly influenced by the uncertainty of the public accessibility model. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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24 pages, 16000 KiB

Open AccessArticle

The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses

by Moritz Schott, Asher Yair Grinberger, Sven Lautenbach and Alexander Zipf

ISPRS Int. J. Geo-Inf. 2021, 10(3), 164; https://doi.org/10.3390/ijgi10030164 - 14 Mar 2021

Cited by 11 | Viewed by 7182

Abstract

The collaborative nature of activities in Web 2.0 projects leads to the formation of online communities. To reinforce this community, these projects often rely on happenings centred around data creation and curation activities. We suggest an integrated framework to directly assess online community [...] Read more.

The collaborative nature of activities in Web 2.0 projects leads to the formation of online communities. To reinforce this community, these projects often rely on happenings centred around data creation and curation activities. We suggest an integrated framework to directly assess online community member performance in a quantitative manner and applied it to the case study of OpenStreetMap. A set of mappers who participated in both field and remote mapping-related happenings was identified. To measure the effects of happenings, we computed attributes characterising the mappers’ contribution behaviour before and after the happenings and tested for significant impacts in relation to a control group. Results showed that newcomers to OpenStreetMap adopted a contribution behaviour similar to the contribution behaviour typical for the respective happening they attended: When contributing after the happening, newcomers who attended a remote mapping event tended to concentrate on creating new data with lower quality but high quantity in places foreign to their home region; newcomers who attended a field mapping event updated and enhanced existing local data with high accuracy. The behaviour of advanced mappers stayed largely unaffected by happenings. Unfortunately, our results did not reveal a positive effect on the community integration of newcomers through happenings. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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19 pages, 3450 KiB

Open AccessArticle

A Contributor-Focused Intrinsic Quality Assessment of OpenStreetMap in Mozambique Using Unsupervised Machine Learning

by Aphiwe Madubedube, Serena Coetzee and Victoria Rautenbach

ISPRS Int. J. Geo-Inf. 2021, 10(3), 156; https://doi.org/10.3390/ijgi10030156 - 11 Mar 2021

Cited by 12 | Viewed by 4235

Abstract

Anyone can contribute geographic information to OpenStreetMap (OSM), regardless of their level of experience or skills, which has raised concerns about quality. When reference data is not available to assess the quality of OSM data, intrinsic methods that assess the data and its [...] Read more.

Anyone can contribute geographic information to OpenStreetMap (OSM), regardless of their level of experience or skills, which has raised concerns about quality. When reference data is not available to assess the quality of OSM data, intrinsic methods that assess the data and its metadata can be used. In this study, we applied unsupervised machine learning for analysing OSM history data to get a better understanding of who contributed when and how in Mozambique. Even though no absolute statements can be made about the quality of the data, the results provide valuable insight into the quality. Most of the data in Mozambique (93%) was contributed by a small group of active contributors (25%). However, these were less active than the OSM Foundation’s definition of active contributorship and the Humanitarian OpenStreetMap Team (HOT) definition for intermediate mappers. Compared to other contributor classifications, our results revealed a new class: contributors who were new in the area and most likely attracted by HOT mapping events during disaster relief operations in Mozambique in 2019. More studies in different parts of the world would establish whether the patterns observed here are typical for developing countries. Intrinsic methods cannot replace ground truthing or extrinsic methods, but provide alternative ways for gaining insight about quality, and they can also be used to inform efforts to further improve the quality. We provide suggestions for how contributor-focused intrinsic quality assessments could be further refined. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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32 pages, 15184 KiB

Open AccessEditor’s ChoiceArticle

Development after Displacement: Evaluating the Utility of OpenStreetMap Data for Monitoring Sustainable Development Goal Progress in Refugee Settlements

by Jamon Van Den Hoek, Hannah K. Friedrich, Anna Ballasiotes, Laura E. R. Peters and David Wrathall

ISPRS Int. J. Geo-Inf. 2021, 10(3), 153; https://doi.org/10.3390/ijgi10030153 - 10 Mar 2021

Cited by 13 | Viewed by 4535

Abstract

In 2015, 193 countries declared their commitment to “leave no one behind” in pursuit of 17 Sustainable Development Goals (SDGs). However, the world’s refugees have been routinely excluded from national censuses and representative surveys, and, as a result, have broadly been overlooked in [...] Read more.

In 2015, 193 countries declared their commitment to “leave no one behind” in pursuit of 17 Sustainable Development Goals (SDGs). However, the world’s refugees have been routinely excluded from national censuses and representative surveys, and, as a result, have broadly been overlooked in SDG evaluations. In this study, we examine the potential of OpenStreetMap (OSM) data for monitoring SDG progress in refugee settlements. We collected all available OSM data in 28 refugee and 26 nearby non-refugee settlements in the major refugee-hosting country of Uganda. We created a novel SDG-OSM data model, measured the spatial and temporal coverages of SDG-relevant OSM data across refugee settlements, and compared these results to non-refugee settlements. We found 11 different SDGs represented across 92% (21,950) of OSM data in refugee settlements, compared to 78% (1919 nodes) in non-refugee settlements. However, most data were created three years after refugee arrival, and 81% of OSM data in refugee settlements were never edited, both of which limit the potential for long-term monitoring of SDG progress. In light of our findings, we offer suggestions for improving OSM-driven SDG monitoring in refugee settlements that have relevance for development and humanitarian practitioners and research communities alike. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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17 pages, 3092 KiB

Open AccessArticle

The Sketch Map Tool Facilitates the Assessment of OpenStreetMap Data for Participatory Mapping

by Carolin Klonner, Maximilian Hartmann, Rebecca Dischl, Lily Djami, Liana Anderson, Martin Raifer, Fernanda Lima-Silva, Lívia Castro Degrossi, Alexander Zipf and João Porto de Albuquerque

ISPRS Int. J. Geo-Inf. 2021, 10(3), 130; https://doi.org/10.3390/ijgi10030130 - 03 Mar 2021

Cited by 9 | Viewed by 7766

Abstract

A worldwide increase in the number of people and areas affected by disasters has led to more and more approaches that focus on the integration of local knowledge into disaster risk reduction processes. The research at hand shows a method for formalizing this [...] Read more.

A worldwide increase in the number of people and areas affected by disasters has led to more and more approaches that focus on the integration of local knowledge into disaster risk reduction processes. The research at hand shows a method for formalizing this local knowledge via sketch maps in the context of flooding. The Sketch Map Tool enables not only the visualization of this local knowledge and analyses of OpenStreetMap data quality but also the communication of the results of these analyses in an understandable way. Since the tool will be open-source and several analyses are made automatically, the tool also offers a method for local governments in areas where historic data or financial means for flood mitigation are limited. Example analyses for two cities in Brazil show the functionalities of the tool and allow the evaluation of its applicability. Results depict that the fitness-for-purpose analysis of the OpenStreetMap data reveals promising results to identify whether the sketch map approach can be used in a certain area or if citizens might have problems with marking their flood experiences. In this way, an intrinsic quality analysis is incorporated into a participatory mapping approach. Additionally, different paper formats offered for printing enable not only individual mapping but also group mapping. Future work will focus on advancing the automation of all steps of the tool to allow members of local governments without specific technical knowledge to apply the Sketch Map Tool for their own study areas. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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21 pages, 18887 KiB

Open AccessEditor’s ChoiceArticle

Worldwide Detection of Informal Settlements via Topological Analysis of Crowdsourced Digital Maps

by Satej Soman, Anni Beukes, Cooper Nederhood, Nicholas Marchio and Luís M. A. Bettencourt

ISPRS Int. J. Geo-Inf. 2020, 9(11), 685; https://doi.org/10.3390/ijgi9110685 - 16 Nov 2020

Cited by 22 | Viewed by 10587

Abstract

The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion [...] Read more.

The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMICs) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities—from individual neighborhoods to global regions—that can coordinate local community knowledge with political agency, technical capability, and further research. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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20 pages, 5525 KiB

Open AccessArticle

Leveraging OSM and GEOBIA to Create and Update Forest Type Maps

by Melanie Brauchler and Johannes Stoffels

ISPRS Int. J. Geo-Inf. 2020, 9(9), 499; https://doi.org/10.3390/ijgi9090499 - 21 Aug 2020

Cited by 5 | Viewed by 3303

Abstract

Up-to-date information about the type and spatial distribution of forests is an essential element in both sustainable forest management and environmental monitoring and modelling. The OpenStreetMap (OSM) database contains vast amounts of spatial information on natural features, including forests (landuse=forest). The [...] Read more.

Up-to-date information about the type and spatial distribution of forests is an essential element in both sustainable forest management and environmental monitoring and modelling. The OpenStreetMap (OSM) database contains vast amounts of spatial information on natural features, including forests (landuse=forest). The OSM data model includes describing tags for its contents, i.e., leaf type for forest areas (i.e., leaf_type=broadleaved). Although the leaf type tag is common, the vast majority of forest areas are tagged with the leaf type mixed, amounting to a total area of 87% of landuse=forests from the OSM database. These areas comprise an important information source to derive and update forest type maps. In order to leverage this information content, a methodology for stratification of leaf types inside these areas has been developed using image segmentation on aerial imagery and subsequent classification of leaf types. The presented methodology achieves an overall classification accuracy of 85% for the leaf types needleleaved and broadleaved in the selected forest areas. The resulting stratification demonstrates that through approaches, such as that presented, the derivation of forest type maps from OSM would be feasible with an extended and improved methodology. It also suggests an improved methodology might be able to provide updates of leaf type to the OSM database with contributor participation. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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17 pages, 4940 KiB

Open AccessArticle

Using OpenStreetMap Data and Machine Learning to Generate Socio-Economic Indicators

by Daniel Feldmeyer, Claude Meisch, Holger Sauter and Joern Birkmann

ISPRS Int. J. Geo-Inf. 2020, 9(9), 498; https://doi.org/10.3390/ijgi9090498 - 21 Aug 2020

Cited by 21 | Viewed by 6743

Abstract

Socio-economic indicators are key to understanding societal challenges. They disassemble complex phenomena to gain insights and deepen understanding. Specific subsets of indicators have been developed to describe sustainability, human development, vulnerability, risk, resilience and climate change adaptation. Nonetheless, insufficient quality and availability of [...] Read more.

Socio-economic indicators are key to understanding societal challenges. They disassemble complex phenomena to gain insights and deepen understanding. Specific subsets of indicators have been developed to describe sustainability, human development, vulnerability, risk, resilience and climate change adaptation. Nonetheless, insufficient quality and availability of data often limit their explanatory power. Spatial and temporal resolution are often not at a scale appropriate for monitoring. Socio-economic indicators are mostly provided by governmental institutions and are therefore limited to administrative boundaries. Furthermore, different methodological computation approaches for the same indicator impair comparability between countries and regions. OpenStreetMap (OSM) provides an unparalleled standardized global database with a high spatiotemporal resolution. Surprisingly, the potential of OSM seems largely unexplored in this context. In this study, we used machine learning to predict four exemplary socio-economic indicators for municipalities based on OSM. By comparing the predictive power of neural networks to statistical regression models, we evaluated the unhinged resources of OSM for indicator development. OSM provides prospects for monitoring across administrative boundaries, interdisciplinary topics, and semi-quantitative factors like social cohesion. Further research is still required to, for example, determine the impact of regional and international differences in user contributions on the outputs. Nonetheless, this database can provide meaningful insight into otherwise unknown spatial differences in social, environmental or economic inequalities. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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22 pages, 3087 KiB

Open AccessArticle

Change Detection from Remote Sensing to Guide OpenStreetMap Labeling

by Conrad M. Albrecht, Rui Zhang, Xiaodong Cui, Marcus Freitag, Hendrik F. Hamann, Levente J. Klein, Ulrich Finkler, Fernando Marianno, Johannes Schmude, Norman Bobroff, Wei Zhang, Carlo Siebenschuh and Siyuan Lu

ISPRS Int. J. Geo-Inf. 2020, 9(7), 427; https://doi.org/10.3390/ijgi9070427 - 02 Jul 2020

Cited by 11 | Viewed by 6175

Abstract

The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the latest remote sensing data in [...] Read more.

The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the latest remote sensing data in combination with state-of-the-art computer vision methods to assist the OSM community in labeling work. This article reports our progress to utilize artificial neural networks (ANN) for change detection of OSM data to update the map. Furthermore, we aim at identifying geospatial regions where mappers need to focus on completing the global OSM dataset. Our approach is technically backed by the big geospatial data platform Physical Analytics Integrated Repository and Services (PAIRS). We employ supervised training of deep ANNs from vertical aerial imagery to segment scenes based on OSM map tiles to evaluate the technique quantitatively and qualitatively. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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20 pages, 10041 KiB

Open AccessArticle

Quality Verification of Volunteered Geographic Information Using OSM Notes Data in a Global Context

by Toshikazu Seto, Hiroshi Kanasugi and Yuichiro Nishimura

ISPRS Int. J. Geo-Inf. 2020, 9(6), 372; https://doi.org/10.3390/ijgi9060372 - 06 Jun 2020

Cited by 8 | Viewed by 4466

Abstract

Although the data obtained from volunteered geographic information (VGI) are inherently different from public surveys, the quantity of the data are vast and the quality of the data are often poor. To improve the quality of VGI data, the positional accuracy and diversity [...] Read more.

Although the data obtained from volunteered geographic information (VGI) are inherently different from public surveys, the quantity of the data are vast and the quality of the data are often poor. To improve the quality of VGI data, the positional accuracy and diversity and interaction of the number of users involved in the regional generation of the data are important. This research proposes a new approach for the accumulation of OpenStreetMap (OSM) data by using OSM Notes and attempts to analyze the geographical distribution and the characteristics of the contents of the contributions, quantitatively and qualitatively. Subsequently, the results demonstrated regional differences in OSM Notes, but it provided users with an understanding of the new features of quality management in OSM, even in regions where OSM activities are not necessarily active. In addition, it was also possible to discover new factors such as the time transition required for the correction and contribution of anonymous users. These results are expected to serve as a tool for users to communicate with each other to resolve data bugs that exist in OSM and provide future researchers with examples of user interaction in global OSM activities. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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20 pages, 3978 KiB

Open AccessEditor’s ChoiceArticle

Cartographic Vandalism in the Era of Location-Based Games—The Case of OpenStreetMap and Pokémon GO

by Levente Juhász, Tessio Novack, Hartwig H. Hochmair and Sen Qiao

ISPRS Int. J. Geo-Inf. 2020, 9(4), 197; https://doi.org/10.3390/ijgi9040197 - 26 Mar 2020

Cited by 23 | Viewed by 11097

Abstract

User-generated map data is increasingly used by the technology industry for background mapping, navigation and beyond. An example is the integration of OpenStreetMap (OSM) data in widely-used smartphone and web applications, such as Pokémon GO (PGO), a popular augmented reality smartphone game. As [...] Read more.

User-generated map data is increasingly used by the technology industry for background mapping, navigation and beyond. An example is the integration of OpenStreetMap (OSM) data in widely-used smartphone and web applications, such as Pokémon GO (PGO), a popular augmented reality smartphone game. As a result of OSM’s increased popularity, the worldwide audience that uses OSM through external applications is directly exposed to malicious edits which represent cartographic vandalism. Multiple reports of obscene and anti-semitic vandalism in OSM have surfaced in popular media over the years. These negative news related to cartographic vandalism undermine the credibility of collaboratively generated maps. Similarly, commercial map providers (e.g., Google Maps and Waze) are also prone to carto-vandalism through their crowdsourcing mechanism that they may use to keep their map products up-to-date. Using PGO as an example, this research analyzes harmful edits in OSM that originate from PGO players. More specifically, this paper analyzes the spatial, temporal and semantic characteristics of PGO carto-vandalism and discusses how the mapping community handles it. Our findings indicate that most harmful edits are quickly discovered and that the community becomes faster at detecting and fixing these harmful edits over time. Gaming related carto-vandalism in OSM was found to be a short-term, sporadic activity by individuals, whereas the task of fixing vandalism is persistently pursued by a dedicated user group within the OSM community. The characteristics of carto-vandalism identified in this research can be used to improve vandalism detection systems in the future. Full article

(This article belongs to the Special Issue OpenStreetMap as A Multi-Disciplinary Nexus: Perspectives, Practices and Procedures)

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