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Land use and land cover (LULC) mapping is often undertaken by national mapping agencies, where these LULC products are used for different types of monitoring and reporting applications. Updating of LULC databases is often done on a multi-year cycle due to the high costs involved, so changes are only detected when mapping exercises are repeated. Consequently, the information on LULC can quickly become outdated and hence may be incorrect in some areas. In the current era of big data and Earth observation, change detection algorithms can be used to identify changes in urban areas, which can then be used to automatically update LULC databases on a more continuous basis. However, the change detection algorithm must be validated before the changes can be committed to authoritative databases such as those produced by national mapping agencies. This paper outlines a change detection algorithm for identifying construction sites, which represent ongoing changes in LU, developed in the framework of the LandSense project. We then use volunteered geographic information (VGI) captured through the use of mapathons from a range of different groups of contributors to validate these changes. In total, 105 contributors were involved in the mapathons, producing a total of 2778 observations. The 105 contributors were grouped according to six different user-profiles and were analyzed to understand the impact of the experience of the users on the accuracy assessment. Overall, the results show that the change detection algorithm is able to identify changes in residential land use to an adequate level of accuracy (85%) but changes in infrastructure and industrial sites had lower accuracies (57% and 75 %, respectively), requiring further improvements. In terms of user profiles, the experts in LULC from local authorities, researchers in LULC at the French national mapping agency (IGN), and first-year students with a basic knowledge of geographic information systems had the highest overall accuracies (86.2%, 93.2%, and 85.2%, respectively). Differences in how the users approach the task also emerged, e.g., local authorities used knowledge and context to try to identify types of change while those with no knowledge of LULC (i.e., normal citizens) were quicker to choose ‘Unknown’ when the visual interpretation of a class was more difficult.
A.-M. Olteanu-Raimond; L. See; M. Schultz; G. Foody; M. Riffler; T. Gasber; L. Jolivet; A. Le Bris; Y. Meneroux; L. Liu; M. Poupée; M. Gombert. Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change. Remote Sensing 2020, 12, 1186 .
AMA StyleA.-M. Olteanu-Raimond, L. See, M. Schultz, G. Foody, M. Riffler, T. Gasber, L. Jolivet, A. Le Bris, Y. Meneroux, L. Liu, M. Poupée, M. Gombert. Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change. Remote Sensing. 2020; 12 (7):1186.
Chicago/Turabian StyleA.-M. Olteanu-Raimond; L. See; M. Schultz; G. Foody; M. Riffler; T. Gasber; L. Jolivet; A. Le Bris; Y. Meneroux; L. Liu; M. Poupée; M. Gombert. 2020. "Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change." Remote Sensing 12, no. 7: 1186.
Traces collected by citizens using GNSS (Global Navigation Satellite System) devices during sports activities such as running, hiking or biking are now widely available through different sport-oriented collaborative websites. The traces are collected by citizens for their own purposes and frequently shared with the sports community on the internet. Our research assumption is that crowdsourced GNSS traces may be a valuable source of information to detect updates in authoritative datasets. Despite their availability, the traces present some issues such as poor metadata, attribute incompleteness and heterogeneous positional accuracy. Moreover, certain parts of the traces (GNSS points composing the traces) are results of the displacements made out of the existing paths. In our context (i.e., update authoritative data) these off path GNSS points are considered as noise and should be filtered. Two types of noise are examined in this research: Points representing secondary activities (e.g., having a lunch break) and points representing errors during the acquisition. The first ones we named secondary human behaviour (SHB), whereas we named the second ones outliers. The goal of this paper is to improve the smoothness of traces by detecting and filtering both SHB and outliers. Two methods are proposed. The first one allows for the detection secondary human behaviour by analysing only traces geometry. The second one is a rule-based machine learning method that detects outliers by taking into account the intrinsic characteristics of points composing the traces, as well as the environmental conditions during traces acquisition. The proposed approaches are tested on crowdsourced GNSS traces collected in mountain areas during sports activities.
Stefan S. Ivanovic; Ana-Maria Olteanu-Raimond; Sébastien Mustière; Thomas Devogele. A Filtering-Based Approach for Improving Crowdsourced GNSS Traces in a Data Update Context. ISPRS International Journal of Geo-Information 2019, 8, 380 .
AMA StyleStefan S. Ivanovic, Ana-Maria Olteanu-Raimond, Sébastien Mustière, Thomas Devogele. A Filtering-Based Approach for Improving Crowdsourced GNSS Traces in a Data Update Context. ISPRS International Journal of Geo-Information. 2019; 8 (9):380.
Chicago/Turabian StyleStefan S. Ivanovic; Ana-Maria Olteanu-Raimond; Sébastien Mustière; Thomas Devogele. 2019. "A Filtering-Based Approach for Improving Crowdsourced GNSS Traces in a Data Update Context." ISPRS International Journal of Geo-Information 8, no. 9: 380.
Accurate and up-to-date information on land use and land cover (LULC) is needed to develop policies on reducing soil sealing through increased urbanization as well as to meet climate targets. More detailed information about building function is also required but is currently lacking. To improve these datasets, the national mapping agency of France, Institut de l’Information Géographique et Foréstière (IGN France), has developed a strategy for updating their LULC database on a update cycle every three years and building information on a continuous cycle using web, mobile, and wiki applications. Developed as part of the LandSense project and eventually tapping into the LandSense federated authentication system, this paper outlines the data collection campaigns, the key concepts that have driven the system architecture, and a description of the technologies developed for this solution. The campaigns have only just begun, so there are only preliminary results to date. Thus far, feedback on the web and mobile applications has been positive, but still requires a further demonstration of feasibility.
Ana-Maria Olteanu-Raimond; Laurence Jolivet; Marie-Dominque Van Damme; Timothée Royer; Ludovic Fraval; Linda See; Tobias Sturn; Mathias Karner; Inian Moorthy; Steffen Fritz. An Experimental Framework for Integrating Citizen and Community Science into Land Cover, Land Use, and Land Change Detection Processes in a National Mapping Agency. Land 2018, 7, 103 .
AMA StyleAna-Maria Olteanu-Raimond, Laurence Jolivet, Marie-Dominque Van Damme, Timothée Royer, Ludovic Fraval, Linda See, Tobias Sturn, Mathias Karner, Inian Moorthy, Steffen Fritz. An Experimental Framework for Integrating Citizen and Community Science into Land Cover, Land Use, and Land Change Detection Processes in a National Mapping Agency. Land. 2018; 7 (3):103.
Chicago/Turabian StyleAna-Maria Olteanu-Raimond; Laurence Jolivet; Marie-Dominque Van Damme; Timothée Royer; Ludovic Fraval; Linda See; Tobias Sturn; Mathias Karner; Inian Moorthy; Steffen Fritz. 2018. "An Experimental Framework for Integrating Citizen and Community Science into Land Cover, Land Use, and Land Change Detection Processes in a National Mapping Agency." Land 7, no. 3: 103.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Production of Topographic Maps with VGI: Quality Management and Automation. Mapping and the Citizen Sensor 2017, 61 -91.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Production of Topographic Maps with VGI: Quality Management and Automation. Mapping and the Citizen Sensor. 2017; ():61-91.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Production of Topographic Maps with VGI: Quality Management and Automation." Mapping and the Citizen Sensor , no. : 61-91.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Citizen Science and Citizens’ Observatories: Trends, Roles, Challenges and Development Needs for Science and Environmental Governance. Mapping and the Citizen Sensor 2017, 351 -376.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Citizen Science and Citizens’ Observatories: Trends, Roles, Challenges and Development Needs for Science and Environmental Governance. Mapping and the Citizen Sensor. 2017; ():351-376.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Citizen Science and Citizens’ Observatories: Trends, Roles, Challenges and Development Needs for Science and Environmental Governance." Mapping and the Citizen Sensor , no. : 351-376.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Visualisation and Communication of VGI Quality. Mapping and the Citizen Sensor 2017, 197 -222.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Visualisation and Communication of VGI Quality. Mapping and the Citizen Sensor. 2017; ():197-222.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Visualisation and Communication of VGI Quality." Mapping and the Citizen Sensor , no. : 197-222.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. The Future of VGI. Mapping and the Citizen Sensor 2017, 377 -390.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. The Future of VGI. Mapping and the Citizen Sensor. 2017; ():377-390.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "The Future of VGI." Mapping and the Citizen Sensor , no. : 377-390.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Assessing VGI Data Quality. Mapping and the Citizen Sensor 2017, 137 -163.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Assessing VGI Data Quality. Mapping and the Citizen Sensor. 2017; ():137-163.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Assessing VGI Data Quality." Mapping and the Citizen Sensor , no. : 137-163.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Mapping and the Citizen Sensor. Mapping and the Citizen Sensor 2017, 1 -12.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Mapping and the Citizen Sensor. Mapping and the Citizen Sensor. 2017; ():1-12.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Mapping and the Citizen Sensor." Mapping and the Citizen Sensor , no. : 1-12.
Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. The Impact of the Contribution Micro-environment on Data Quality: The Case of OSM. Mapping and the Citizen Sensor 2017, 165 -196.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. The Impact of the Contribution Micro-environment on Data Quality: The Case of OSM. Mapping and the Citizen Sensor. 2017; ():165-196.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "The Impact of the Contribution Micro-environment on Data Quality: The Case of OSM." Mapping and the Citizen Sensor , no. : 165-196.
Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. VGI in National Mapping Agencies: Experiences and Recommendations. Mapping and the Citizen Sensor 2017, 299 -326.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. VGI in National Mapping Agencies: Experiences and Recommendations. Mapping and the Citizen Sensor. 2017; ():299-326.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "VGI in National Mapping Agencies: Experiences and Recommendations." Mapping and the Citizen Sensor , no. : 299-326.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Motivating and Sustaining Participation in VGI. Mapping and the Citizen Sensor 2017, 93 -117.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Motivating and Sustaining Participation in VGI. Mapping and the Citizen Sensor. 2017; ():93-117.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Motivating and Sustaining Participation in VGI." Mapping and the Citizen Sensor , no. : 93-117.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Integrating Spatial Data Infrastructures (SDIs) with Volunteered Geographic Information (VGI) for creating a Global GIS platform. Mapping and the Citizen Sensor 2017, 273 -297.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Integrating Spatial Data Infrastructures (SDIs) with Volunteered Geographic Information (VGI) for creating a Global GIS platform. Mapping and the Citizen Sensor. 2017; ():273-297.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Integrating Spatial Data Infrastructures (SDIs) with Volunteered Geographic Information (VGI) for creating a Global GIS platform." Mapping and the Citizen Sensor , no. : 273-297.
Linda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. Sources of VGI for Mapping. Mapping and the Citizen Sensor 2017, 13 -35.
AMA StyleLinda See, Giles Foody, Steffen Fritz, Peter Mooney, Ana-Maria Olteanu-Raimond, Cidália Costa Fonte, Vyron Antoniou. Sources of VGI for Mapping. Mapping and the Citizen Sensor. 2017; ():13-35.
Chicago/Turabian StyleLinda See; Giles Foody; Steffen Fritz; Peter Mooney; Ana-Maria Olteanu-Raimond; Cidália Costa Fonte; Vyron Antoniou. 2017. "Sources of VGI for Mapping." Mapping and the Citizen Sensor , no. : 13-35.
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.
Guillaume Touya; Vyron Antoniou; Ana-Maria Olteanu-Raimond; Marie-Dominique Van Damme. Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations. ISPRS International Journal of Geo-Information 2017, 6, 80 .
AMA StyleGuillaume Touya, Vyron Antoniou, Ana-Maria Olteanu-Raimond, Marie-Dominique Van Damme. Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations. ISPRS International Journal of Geo-Information. 2017; 6 (3):80.
Chicago/Turabian StyleGuillaume Touya; Vyron Antoniou; Ana-Maria Olteanu-Raimond; Marie-Dominique Van Damme. 2017. "Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations." ISPRS International Journal of Geo-Information 6, no. 3: 80.
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.
Peter Mooney; Marco Minghini; Mari Laakso; Vyron Antoniou; Ana-Maria Olteanu-Raimond; Andriani Skopeliti. Towards a Protocol for the Collection of VGI Vector Data. ISPRS International Journal of Geo-Information 2016, 5, 217 .
AMA StylePeter Mooney, Marco Minghini, Mari Laakso, Vyron Antoniou, Ana-Maria Olteanu-Raimond, Andriani Skopeliti. Towards a Protocol for the Collection of VGI Vector Data. ISPRS International Journal of Geo-Information. 2016; 5 (11):217.
Chicago/Turabian StylePeter Mooney; Marco Minghini; Mari Laakso; Vyron Antoniou; Ana-Maria Olteanu-Raimond; Andriani Skopeliti. 2016. "Towards a Protocol for the Collection of VGI Vector Data." ISPRS International Journal of Geo-Information 5, no. 11: 217.
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.
Linda See; Peter Mooney; Giles M. 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; Martin Rutzinger. Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information. ISPRS International Journal of Geo-Information 2016, 5, 55 .
AMA StyleLinda See, Peter Mooney, Giles M. 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, Martin Rutzinger. Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information. ISPRS International Journal of Geo-Information. 2016; 5 (5):55.
Chicago/Turabian StyleLinda See; Peter Mooney; Giles M. 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; Martin Rutzinger. 2016. "Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information." ISPRS International Journal of Geo-Information 5, no. 5: 55.
There is much interest in being able to combine crowdsourced data. One of the critical issues in information sciences is how to combine data or information that are discordant or inconsistent in some way. Many previous approaches have taken a majority rules approach under the assumption that most people are correct most of the time. This paper analyses crowdsourced land cover data generated by the Geo-Wiki initiative in order to infer the land cover present at locations on a 50 km grid. It compares four evidence combination approaches (Dempster-Shafer, Bayes, Fuzzy Sets and Possibility) applied under a geographically weighted kernel with the geographically weighted average approach applied in many current Geo-Wiki analyses. A geographically weighted approach uses a moving kernel under which local analyses are undertaken. The contribution (or salience) of each data point to the analysis is weighted by its distance to the kernel centre, reflecting Tobler's 1st law of geography. A series of analyses were undertaken using different kernel sizes (or bandwidths). Each of the geographically weighted evidence combination methods generated spatially distributed measures of belief in hypotheses associated with the presence of individual land cover classes at each location on the grid. These were compared with GlobCover, a global land cover product. The results from the geographically weighted average approach in general had higher correspondence with the reference data and this increased with bandwidth. However, for some classes other evidence combination approaches had higher correspondences possibly because of greater ambiguity over class conceptualisations and / or lower densities of crowdsourced data. The outputs also allowed the beliefs in each class to be mapped. The differences in the soft and the crisp maps are clearly associated with the logics of each evidence combination approach and of course the different questions that they ask of the data. The results show that discordant data can be combined (rather than being removed from analysis) and that data integrated in this way can be parameterised by different measures of belief uncertainty. The discussion highlights a number of critical areas for future research.
Alexis Comber; Cidália Fonte; Giles Foody; Steffen Fritz; Paul Harris; Ana-Maria Olteanu-Raimond; Linda See. Geographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information. GeoInformatica 2016, 20, 503 -527.
AMA StyleAlexis Comber, Cidália Fonte, Giles Foody, Steffen Fritz, Paul Harris, Ana-Maria Olteanu-Raimond, Linda See. Geographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information. GeoInformatica. 2016; 20 (3):503-527.
Chicago/Turabian StyleAlexis Comber; Cidália Fonte; Giles Foody; Steffen Fritz; Paul Harris; Ana-Maria Olteanu-Raimond; Linda See. 2016. "Geographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information." GeoInformatica 20, no. 3: 503-527.
The perspective of European National Mapping Agencies (NMA) on the role of citizen sensing in map production was explored. The NMAs varied greatly in their engagement with the community generating volunteered geographic information (VGI) and in their future plans. From an assessment of NMA standard practices, it was evident that much VGI was acquired with a positional accuracy that, while less than that typically acquired by NMAs, actually exceeded the requirements of the nominal data capture scale used by most NMAs. Opportunities for VGI use in map revision and updating were evident, especially for agencies that use a continuous rather than cyclical updating policy. Some NMAs had also developed systems to engage with citizen sensors and examples are discussed. Only rarely was VGI used to collect data on features beyond the standard set used by the NMAs. The potential role of citizen sensing and so its current scale of use by NMAs is limited by a series of concerns, notably relating to issues of data quality, the nature and motivation of the contributors, legal issues, the sustainability of data source, and employment fears of NMA staff. Possible priorities for future research and development are identified to help ensure that the potential of VGI in mapping is realized.
Ana-Maria Olteanu-Raimond; Glen Hart; Giles Foody; Guillaume Touya; Tobias Kellenberger; Demetris Demetriou. The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies. Transactions in GIS 2016, 21, 74 -90.
AMA StyleAna-Maria Olteanu-Raimond, Glen Hart, Giles Foody, Guillaume Touya, Tobias Kellenberger, Demetris Demetriou. The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies. Transactions in GIS. 2016; 21 (1):74-90.
Chicago/Turabian StyleAna-Maria Olteanu-Raimond; Glen Hart; Giles Foody; Guillaume Touya; Tobias Kellenberger; Demetris Demetriou. 2016. "The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies." Transactions in GIS 21, no. 1: 74-90.
Mobile phone operators produce enormous amounts of data. In this paper we present applications performed with a dataset (communication events + handover and Location Area Up-date) collected by the operator Orange from 31 March to 11 April 2009 for the whole Paris Region. Trips are deduced from the spatio-temporal trajectory of devices through a hypothesis of stationarity within a Location Area in order to define activities. Trips are then aggregated in an origin-destination matrix which is compared with traditional data (census data and household travel survey).
Patrick Bonnel; Etienne Hombourger; Ana-Maria Olteanu-Raimond; Zbigniew Smoreda. Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations. Transportation Research Procedia 2015, 11, 381 -398.
AMA StylePatrick Bonnel, Etienne Hombourger, Ana-Maria Olteanu-Raimond, Zbigniew Smoreda. Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations. Transportation Research Procedia. 2015; 11 ():381-398.
Chicago/Turabian StylePatrick Bonnel; Etienne Hombourger; Ana-Maria Olteanu-Raimond; Zbigniew Smoreda. 2015. "Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations." Transportation Research Procedia 11, no. : 381-398.