ISPRS International Journal of Geo-Information

Editorial

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208 KiB

Open AccessEditorial

Highlighting Current Trends in Volunteered Geographic Information

by David Jonietz, Vyron Antonio, Linda See and Alexander Zipf

ISPRS Int. J. Geo-Inf. 2017, 6(7), 202; https://doi.org/10.3390/ijgi6070202 - 4 Jul 2017

Cited by 16 | Viewed by 7207

Abstract

Volunteered Geographic Information (VGI) is a growing area of research. This Special Issue aims to capture the main trends in VGI research based on 16 original papers, and distinguishes between two main areas, i.e., those that deal with the characteristics of VGI and [...] Read more.

Volunteered Geographic Information (VGI) is a growing area of research. This Special Issue aims to capture the main trends in VGI research based on 16 original papers, and distinguishes between two main areas, i.e., those that deal with the characteristics of VGI and those focused on applications of VGI. The topic of quality assessment and assurance dominates the papers on VGI characteristics, whereas application-oriented work covers three main domains: human behavioral analysis, natural disasters, and land cover/land use mapping. In this Special Issue, therefore, both the challenges and the potentials of VGI are addressed. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

Research

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4662 KiB

Open AccessArticle

Generating Up-to-Date and Detailed Land Use and Land Cover Maps Using OpenStreetMap and GlobeLand30

by Cidália Costa Fonte, Marco Minghini, Joaquim Patriarca, Vyron Antoniou, Linda See and Andriani Skopeliti

ISPRS Int. J. Geo-Inf. 2017, 6(4), 125; https://doi.org/10.3390/ijgi6040125 - 22 Apr 2017

Cited by 64 | Viewed by 11608

Abstract

With the opening up of the Landsat archive, global high resolution land cover maps have begun to appear. However, they often have only a small number of high level land cover classes and they are static products, corresponding to a particular period of [...] Read more.

With the opening up of the Landsat archive, global high resolution land cover maps have begun to appear. However, they often have only a small number of high level land cover classes and they are static products, corresponding to a particular period of time, e.g., the GlobeLand30 (GL30) map for 2010. The OpenStreetMap (OSM), in contrast, consists of a very detailed, dynamically updated, spatial database of mapped features from around the world, but it suffers from incomplete coverage, and layers of overlapping features that are tagged in a variety of ways. However, it clearly has potential for land use and land cover (LULC) mapping. Thus the aim of this paper is to demonstrate how the OSM can be converted into a LULC map and how this OSM-derived LULC map can then be used to first update the GL30 with more recent information and secondly, enhance the information content of the classes. The technique is demonstrated on two study areas where there is availability of OSM data but in locations where authoritative data are lacking, i.e., Kathmandu, Nepal and Dar es Salaam, Tanzania. The GL30 and its updated and enhanced versions are independently validated using a stratified random sample so that the three maps can be compared. The results show that the updated version of GL30 improves in terms of overall accuracy since certain classes were not captured well in the original GL30 (e.g., water in Kathmandu and water/wetlands in Dar es Salaam). In contrast, the enhanced GL30, which contains more detailed urban classes, results in a drop in the overall accuracy, possibly due to the increased number of classes, but the advantages include the appearance of more detailed features, such as the road network, that becomes clearly visible. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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1808 KiB

Open AccessArticle

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

by Vuokko Heikinheimo, Enrico Di Minin, Henrikki Tenkanen, Anna Hausmann, Joel Erkkonen and Tuuli Toivonen

ISPRS Int. J. Geo-Inf. 2017, 6(3), 85; https://doi.org/10.3390/ijgi6030085 - 16 Mar 2017

Cited by 203 | Viewed by 17421

Abstract

Protected area management and marketing require real-time information on visitors’ behavior and preferences. Thus far, visitor information has been collected mostly with repeated visitor surveys. A wealth of content-rich geographic data is produced by users of different social media platforms. These data could [...] Read more.

Protected area management and marketing require real-time information on visitors’ behavior and preferences. Thus far, visitor information has been collected mostly with repeated visitor surveys. A wealth of content-rich geographic data is produced by users of different social media platforms. These data could potentially provide continuous information about people’s activities and interactions with the environment at different spatial and temporal scales. In this paper, we compare social media data with traditional survey data in order to map people’s activities and preferences using the most popular national park in Finland, Pallas-Yllästunturi National Park, as a case study. We compare systematically collected survey data and the content of geotagged social media data and analyze: (i) where do people go within the park; (ii) what are their activities; (iii) when do people visit the park and if there are temporal patterns in their activities; (iv) who the visitors are; (v) why people visit the national park; and (vi) what complementary information from social media can provide in addition to the results from traditional surveys. The comparison of survey and social media data demonstrated that geotagged social media content provides relevant information about visitors’ use of the national park. As social media platforms are a dynamic source of data, they could complement and enrich traditional forms of visitor monitoring by providing more insight on emerging activities, temporal patterns of shared content, and mobility patterns of visitors. Potentially, geotagged social media data could also provide an overview of the spatio-temporal activity patterns in other areas where systematic visitor monitoring is not taking place. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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7829 KiB

Open AccessArticle

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

by Guillaume Touya, Vyron Antoniou, Ana-Maria Olteanu-Raimond and Marie-Dominique Van Damme

ISPRS Int. J. Geo-Inf. 2017, 6(3), 80; https://doi.org/10.3390/ijgi6030080 - 14 Mar 2017

Cited by 45 | Viewed by 8059

Abstract

With the development of location-aware devices and the success and high use of Web 2.0 techniques, citizens are able to act as sensors by contributing geographic information. In this context, data quality is an important aspect that should be taken into account when [...] Read more.

With the development of location-aware devices and the success and high use of Web 2.0 techniques, citizens are able to act as sensors by contributing geographic information. In this context, data quality is an important aspect that should be taken into account when using this source of data for different purposes. The goal of the paper is to analyze the quality of crowdsourced data and to study its evolution over time. We propose two types of approaches: (1) use the intrinsic characteristics of the crowdsourced datasets; or (2) evaluate crowdsourced Points of Interest (POIs) using external datasets (i.e., authoritative reference or other crowdsourced datasets), and two different methods for each approach. The potential of the combination of these approaches is then demonstrated, to overcome the limitations associated with each individual method. In this paper, we focus on POIs and places coming from the very successful crowdsourcing project: OpenStreetMap. The results show that the proposed approaches are complementary in assessing data quality. The positive results obtained for data matching show that the analysis of data quality through automatic data matching is possible but considerable effort and attention are needed for schema matching given the heterogeneity of OSM and the representation of authoritative datasets. For the features studied, it can be noted that change over time is sometimes due to disagreements between contributors, but in most cases the change improves the quality of the data. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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1397 KiB

Open AccessArticle

On Data Quality Assurance and Conflation Entanglement in Crowdsourcing for Environmental Studies

by Didier G. Leibovici, Julian F. Rosser, Crona Hodges, Barry Evans, Michael J. Jackson and Chris I. Higgins

ISPRS Int. J. Geo-Inf. 2017, 6(3), 78; https://doi.org/10.3390/ijgi6030078 - 11 Mar 2017

Cited by 22 | Viewed by 6400

Abstract

Volunteer geographical information (VGI), either in the context of citizen science or the mining of social media, has proven to be useful in various domains including natural hazards, health status, disease epidemics, and biological monitoring. Nonetheless, the variable or unknown data quality due [...] Read more.

Volunteer geographical information (VGI), either in the context of citizen science or the mining of social media, has proven to be useful in various domains including natural hazards, health status, disease epidemics, and biological monitoring. Nonetheless, the variable or unknown data quality due to crowdsourcing settings are still an obstacle for fully integrating these data sources in environmental studies and potentially in policy making. The data curation process, in which a quality assurance (QA) is needed, is often driven by the direct usability of the data collected within a data conflation process or data fusion (DCDF), combining the crowdsourced data into one view, using potentially other data sources as well. Looking at current practices in VGI data quality and using two examples, namely land cover validation and inundation extent estimation, this paper discusses the close links between QA and DCDF. It aims to help in deciding whether a disentanglement can be possible, whether beneficial or not, in understanding the data curation process with respect to its methodology for future usage of crowdsourced data. Analysing situations throughout the data curation process where and when entanglement between QA and DCDF occur, the paper explores the various facets of VGI data capture, as well as data quality assessment and purposes. Far from rejecting the usability ISO quality criterion, the paper advocates for a decoupling of the QA process and the DCDF step as much as possible while still integrating them within an approach analogous to a Bayesian paradigm. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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7195 KiB

Open AccessArticle

Crowdsourcing User-Generated Mobile Sensor Weather Data for Densifying Static Geosensor Networks

by Shay Sosko and Sagi Dalyot

ISPRS Int. J. Geo-Inf. 2017, 6(3), 61; https://doi.org/10.3390/ijgi6030061 - 24 Feb 2017

Cited by 21 | Viewed by 6631

Abstract

Static geosensor networks are comprised of stations with sensor devices providing data relevant for monitoring environmental phenomena in their geographic perimeter. Although early warning systems for disaster management rely on data retrieved from these networks, some limitations exist, largely in terms of insufficient [...] Read more.

Static geosensor networks are comprised of stations with sensor devices providing data relevant for monitoring environmental phenomena in their geographic perimeter. Although early warning systems for disaster management rely on data retrieved from these networks, some limitations exist, largely in terms of insufficient coverage and low density. Crowdsourcing user-generated data is emerging as a working methodology for retrieving real-time data in disaster situations, reducing the aforementioned limitations, and augmenting with real-time data generated voluntarily by nearby citizens. This paper explores the use of crowdsourced user-generated sensor weather data from mobile devices for the creation of a unified and densified geosensor network. Different scenario experiments are adapted, in which weather data are collected using smartphone sensors, integrated with the development of a stabilization algorithm, for determining the user-generated weather data reliability and usability. Showcasing this methodology on a large data volume, a spatiotemporal algorithm was developed for filtering on-line user-generated weather data retrieved from WeatherSignal, and used for simulation and assessment of densifying the static geosensor weather network of Israel. Geostatistical results obtained proved that, although user-generated weather data show small discrepancies when compared to authoritative data, with considerations they can be used alongside authoritative data, producing a densified and augmented weather map that is detailed and continuous. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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2717 KiB

Open AccessArticle

Whistland: An Augmented Reality Crowd-Mapping System for Civil Protection and Emergency Management

by Gioele Luchetti, Adriano Mancini, Mirco Sturari, Emanuele Frontoni and Primo Zingaretti

ISPRS Int. J. Geo-Inf. 2017, 6(2), 41; https://doi.org/10.3390/ijgi6020041 - 7 Feb 2017

Cited by 24 | Viewed by 8561

Abstract

The prevention and correct management of natural disaster event sequences play a key role in saving human lives. The availability of embedded and mobile smart computing systems opens new roads for the management of land and infrastructures by civil protection operators. To date, [...] Read more.

The prevention and correct management of natural disaster event sequences play a key role in saving human lives. The availability of embedded and mobile smart computing systems opens new roads for the management of land and infrastructures by civil protection operators. To date, research has explored the use of social networks for the management of disasters connected to meteorological/hydrogeological events or earthquakes, but without emphasis on the importance of an integrated system. The main feature of the Whistland system proposed in this paper is to make synergistic use of augmented reality (AR), crowd-mapping (CM), social networks, the Internet of Things (IoT) and wireless sensor networks (WSN) by exploiting technologies and frameworks of Web 2.0 and GIS 2.0 to make informed decisions about the chain of events. The Whistland system is composed of a geo-server, a mobile application with AR and an analytics dashboard. The geo-server acts as the hub of the sensor and social networks. The abstracted concept in this sense is the transformation of the user domain into “intelligent sensors” for the whole scope of crisis management. The social network integration is made through an efficient pointer-like mechanism that keeps the storage requirement low through a mobile application based on an augmented reality engine and provides qualitative information that sensors are unable to capture. Real-time analyses, geo-searches and the capability to examine event histories with an augmented reality engine all help the stakeholders to understand better the state of the resources under observation/monitoring. The system has been extensively tested in the programmed maintenance of river basins, where it is necessary to log maintenance activities in order to keep the riverbank clean: a significant use-case in many countries affected by hydro-geological instability. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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16350 KiB

Open AccessArticle

Authoritative and Volunteered Geographical Information in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi, Kenya

by Ron Mahabir, Anthony Stefanidis, Arie Croitoru, Andrew T. Crooks and Peggy Agouris

ISPRS Int. J. Geo-Inf. 2017, 6(1), 24; https://doi.org/10.3390/ijgi6010024 - 20 Jan 2017

Cited by 38 | Viewed by 11613

Abstract

With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until [...] Read more.

With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until now, studies have focused primarily on developed countries, showing that VGI content can match or even surpass the quality of authoritative sources, with very few studies in developing countries. In this paper, we compare the quality of authoritative (data from the Regional Center for Mapping of Resources for Development (RCMRD)) and non-authoritative (data from OSM and Google’s Map Maker) road data in conjunction with population data in and around Nairobi, Kenya. Results show variability in coverage between all of these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards rural areas. Furthermore, OSM had higher content density in large slums, surpassing the authoritative datasets at these locations, while Map Maker showed better coverage in rural housing areas. These results suggest a greater need for a more inclusive approach using VGI to supplement gaps in authoritative data in developing nations. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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3168 KiB

Open AccessArticle

“Contextualized VGI” Creation and Management to Cope with Uncertainty and Imprecision

by Gloria Bordogna, Luca Frigerio, Tomáš Kliment, Pietro Alessandro Brivio, Laure Hossard, Giacinto Manfron and Simone Sterlacchini

ISPRS Int. J. Geo-Inf. 2016, 5(12), 234; https://doi.org/10.3390/ijgi5120234 - 8 Dec 2016

Cited by 9 | Viewed by 5009

Abstract

This paper investigates the causes of imprecision of the observations and uncertainty of the authors who create Volunteer Geographic Information (VGI), i.e., georeferenced contents generated by volunteers when participating in some citizen science project. Specifically, various aspects of imprecision and uncertainty of VGI [...] Read more.

This paper investigates the causes of imprecision of the observations and uncertainty of the authors who create Volunteer Geographic Information (VGI), i.e., georeferenced contents generated by volunteers when participating in some citizen science project. Specifically, various aspects of imprecision and uncertainty of VGI are outlined and, to cope with them, a knowledge-based approach is suggested based on the creation and management of “contextualized VGI”. A case study example in agriculture is reported where contextualized VGI can be created about in situ crops observations by the use of a smart app that supports volunteers by means of both an ontology and the representation of the context of the geo-localization. Furthermore, an approach to cope with both ill-defined knowledge and volunteer’s uncertainty or imprecise observations is defined based on a fuzzy ontology with uncertainty level-based approximate reasoning. By representing uncertainty and imprecision of VGI, users, i.e., consumers, can exploit quality checking mechanisms to filter VGI based on their needs. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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1034 KiB

Open AccessArticle

Tagging in Volunteered Geographic Information: An Analysis of Tagging Practices for Cities and Urban Regions in OpenStreetMap

by Nikola Davidovic, Peter Mooney, Leonid Stoimenov and Marco Minghini

ISPRS Int. J. Geo-Inf. 2016, 5(12), 232; https://doi.org/10.3390/ijgi5120232 - 5 Dec 2016

Cited by 29 | Viewed by 7928

Abstract

In Volunteered Geographic Information (VGI) projects, the tagging or annotation of objects is usually performed in a flexible and non-constrained manner. Contributors to a VGI project are normally free to choose whatever tags they feel are appropriate to annotate or describe a particular [...] Read more.

In Volunteered Geographic Information (VGI) projects, the tagging or annotation of objects is usually performed in a flexible and non-constrained manner. Contributors to a VGI project are normally free to choose whatever tags they feel are appropriate to annotate or describe a particular geographic object or place. In OpenStreetMap (OSM), the Map Features part of the OSM Wiki serves as the de-facto rulebook or ontology for the annotation of features in OSM. Within Map Features, suggestions and guidance on what combinations of tags to use for certain geographic objects are outlined. In this paper, we consider these suggestions and recommendations and analyse the OSM database for 40 cities around the world to ascertain if contributors to OSM in these urban areas are using this guidance in their tagging practices. Overall, we find that compliance with the suggestions and guidance in Map Features is generally average or poor. This leads us to conclude that contributors in these areas do not always tag features with the same level of annotation. Our paper also confirms anecdotal evidence that OSM Map Features is less influential in how OSM contributors tag objects. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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1224 KiB

Open AccessArticle

Towards a Protocol for the Collection of VGI Vector Data

by Peter Mooney, Marco Minghini, Mari Laakso, Vyron Antoniou, Ana-Maria Olteanu-Raimond and Andriani Skopeliti

ISPRS Int. J. Geo-Inf. 2016, 5(11), 217; https://doi.org/10.3390/ijgi5110217 - 17 Nov 2016

Cited by 34 | Viewed by 9628

Abstract

A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and [...] Read more.

A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and Commercial Surveying Companies (CSC). However, there are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC make use of robust and standardised data collection protocols whilst VGI projects often provide guidelines rather than rigorous data collection specifications. The proposed protocol addresses formalising the collection and creation of vector data in VGI projects in three principal ways: by manual vectorisation; field survey; and reuse of existing data sources. This protocol is intended to be generic rather than being linked to any specific VGI project. We believe that this is the first protocol for VGI vector data collection that has been formally described in the literature. Consequently, this paper shall serve as a starting point for on-going development and refinement of the protocol. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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3071 KiB

Open AccessArticle

Evaluating Trade Areas Using Social Media Data with a Calibrated Huff Model

by Yandong Wang, Wei Jiang, Senbao Liu, Xinyue Ye and Teng Wang

ISPRS Int. J. Geo-Inf. 2016, 5(7), 112; https://doi.org/10.3390/ijgi5070112 - 12 Jul 2016

Cited by 45 | Viewed by 8013

Abstract

Delimitating trade areas is a major business concern. Today, mobile communication technologies make it possible to use social media data for this purpose. Few studies however, have focused on methods to extract suitable samples from social media data for trade area delimitation. In [...] Read more.

Delimitating trade areas is a major business concern. Today, mobile communication technologies make it possible to use social media data for this purpose. Few studies however, have focused on methods to extract suitable samples from social media data for trade area delimitation. In our case study, we divided Beijing into regular grid cells and extracted activity centers for each social media user. Ten sample sets were obtained by selecting users based on the retail agglomerations they visited and aggregating user activity centers to each grid cell. We calculated distance and visitation frequency attributes for each user and each grid cell. The distance value of a grid cell is the average distance of user activity centers in this grid cell to a retail agglomeration. The visitation frequency of a grid cell refers to the average count of visits to retail agglomerations by user activity centers for a cell. The calculated attribute values of 10 sets were input into a Huff model and the delimitated trade areas were evaluated. Results show that sets obtained by aggregating user activity centers have a better delimitating effect than sets obtained without aggregation. Differences in the distribution and intensity of trade areas also became apparent. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessArticle

Volunteered Geographic Information System Design: Project and Participation Guidelines

by José-Pablo Gómez-Barrón, Miguel-Ángel Manso-Callejo, Ramón Alcarria and Teresa Iturrioz

ISPRS Int. J. Geo-Inf. 2016, 5(7), 108; https://doi.org/10.3390/ijgi5070108 - 5 Jul 2016

Cited by 21 | Viewed by 10816

Abstract

This article sets forth the early phases of a methodological proposal for designing and developing Volunteered Geographic Information (VGI) initiatives based on a system perspective analysis in which the components depend and interact dynamically among each other. First, it focuses on those characteristics [...] Read more.

This article sets forth the early phases of a methodological proposal for designing and developing Volunteered Geographic Information (VGI) initiatives based on a system perspective analysis in which the components depend and interact dynamically among each other. First, it focuses on those characteristics of VGI projects that present different goals and modes of organization, while using a crowdsourcing strategy to manage participants and contributions. Next, a tool is developed in order to design the central crowdsourced processing unit that is best suited for a specific project definition, associating it with a trend towards crowd-based or community-driven approaches. The design is structured around the characterization of different ways of participating, and the task cognitive demand of working on geo-information management, spatial problem solving and ideation, or knowledge acquisition. Then, the crowdsourcing process design helps to identify what kind of participants are needed and outline subsequent engagement strategies. This is based on an analysis of differences among volunteers’ participatory behaviors and the associated set of factors motivating them to contribute, whether on a crowd or community-sourced basis. From a VGI system perspective, this paper presents a set of guidelines and methodological steps in order to align project goals, processes and volunteers and thus successfully attract participation. This methodology helps establish the initial requirements for a VGI system, and, in its current state, it mainly focuses on two components of the system: project and participants. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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6663 KiB

Open AccessArticle

Guided Classification System for Conceptual Overlapping Classes in OpenStreetMap

by Ahmed Loai Ali, Nuttha Sirilertworakul, Alexander Zipf and Amin Mobasheri

ISPRS Int. J. Geo-Inf. 2016, 5(6), 87; https://doi.org/10.3390/ijgi5060087 - 7 Jun 2016

Cited by 19 | Viewed by 10210

Abstract

The increased development of Volunteered Geographic Information (VGI) and its potential role in GIScience studies raises questions about the resulting data quality. Several studies address VGI quality from various perspectives like completeness, positional accuracy, consistency, etc. They mostly have consensus on the [...] Read more.

The increased development of Volunteered Geographic Information (VGI) and its potential role in GIScience studies raises questions about the resulting data quality. Several studies address VGI quality from various perspectives like completeness, positional accuracy, consistency, etc. They mostly have consensus on the heterogeneity of data quality. The problem may be due to the lack of standard procedures for data collection and absence of quality control feedback for voluntary participants. In our research, we are concerned with data quality from the classification perspective. Particularly in VGI-mapping projects, the limited expertise of participants and the non-strict definition of geographic features lead to conceptual overlapping classes, where an entity could plausibly belong to multiple classes, e.g., lake or pond, park or garden, marsh or swamp, etc. Usually, quantitative and/or qualitative characteristics exist that distinguish between classes. Nevertheless, these characteristics might not be recognizable for non-expert participants. In previous work, we developed the rule-guided classification approach that guides participants to the most appropriate classes. As exemplification, we tackle the conceptual overlapping of some grass-related classes. For a given data set, our approach presents the most highly recommended classes for each entity. In this paper, we present the validation of our approach. We implement a web-based application called Grass&Green that presents recommendations for crowdsourcing validation. The findings show the applicability of the proposed approach. In four months, the application attracted 212 participants from more than 35 countries who checked 2,865 entities. The results indicate that 89% of the contributions fully/partially agree with our recommendations. We then carried out a detailed analysis that demonstrates the potential of this enhanced data classification. This research encourages the development of customized applications that target a particular geographic feature. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessArticle

Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data

by Vyron Antoniou, Cidália Costa Fonte, Linda See, Jacinto Estima, Jamal Jokar Arsanjani, Flavio Lupia, Marco Minghini, Giles Foody and Steffen Fritz

ISPRS Int. J. Geo-Inf. 2016, 5(5), 64; https://doi.org/10.3390/ijgi5050064 - 13 May 2016

Cited by 60 | Viewed by 11004

Abstract

Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI), which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for [...] Read more.

Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI), which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-tagged photographs and then consider what elements would be essential, desirable, or unnecessary for the aforementioned use cases. Geo-tagged photographs were then extracted from Flickr, Panoramio and Geograph for an area of London, UK, and classified based on their usefulness for land cover mapping including an analysis of the accompanying metadata. Finally, we discuss protocols for geo-tagged photographs for use of VGI in relation to land cover applications. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessArticle

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

by Linda See, Peter Mooney, Giles Foody, Lucy Bastin, Alexis Comber, Jacinto Estima, Steffen Fritz, Norman Kerle, Bin Jiang, Mari Laakso, Hai-Ying Liu, Grega Milčinski, Matej Nikšič, Marco Painho, Andrea Pődör, Ana-Maria Olteanu-Raimond and Martin Rutzinger

ISPRS Int. J. Geo-Inf. 2016, 5(5), 55; https://doi.org/10.3390/ijgi5050055 - 27 Apr 2016

Cited by 351 | Viewed by 29902

Abstract

Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial [...] Read more.

Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessReview

Volunteered Geographic Information in Natural Hazard Analysis: A Systematic Literature Review of Current Approaches with a Focus on Preparedness and Mitigation

by Carolin Klonner, Sabrina Marx, Tomás Usón, João Porto de Albuquerque and Bernhard Höfle

ISPRS Int. J. Geo-Inf. 2016, 5(7), 103; https://doi.org/10.3390/ijgi5070103 - 25 Jun 2016

Cited by 70 | Viewed by 11615

Abstract

With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural [...] Read more.

With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural hazard analysis. Our systematic literature review aims at identifying current research and directions for future research in terms of Volunteered Geographic Information (VGI) within natural hazard analysis. Focusing on both the preparedness and mitigation phase results in eleven articles from two literature databases. A qualitative analysis for in-depth information extraction reveals auspicious approaches regarding community engagement and data fusion, but also important research gaps. Mainly based in Europe and North America, the analysed studies deal primarily with floods and forest fires, applying geodata collected by trained citizens who are improving their knowledge and making their own interpretations. Yet, there is still a lack of common scientific terms and concepts. Future research can use these findings for the adaptation of scientific models of natural hazard analysis in order to enable the fusion of data from technical sensors and VGI. The development of such general methods shall contribute to establishing the user integration into various contexts, such as natural hazard analysis. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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