The Experts below are selected from a list of 3723 Experts worldwide ranked by ideXlab platform
Alexander Zipf - One of the best experts on this subject based on the ideXlab platform.
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INTEGRATION OF AUTHORITATIVE AND Volunteered Geographic Information FOR UPDATING URBAN MAPPING: CHALLENGES AND POTENTIALS
ISPRS - International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2020Co-Authors: V. O. Fernandes, E. N. Elias, Alexander ZipfAbstract:Abstract. This paper provides a bibliometric review between integration of authoritative and Volunteered Geographic Information for the purpose of cartographic updating of urban mappings. The adopted methodology was through a bibliometric survey of the literature published by Web of Science and Science Direct. The period was evaluated from 2005 to 2020 and the keywords used were: integration of authoritative data, Volunteered Geographic Information, VGI, large scale topographic mapping, Authoritative urban mapping. The number of publications found was small for the topic that deals with this integration, totalizing 14 articles at Web of Science and 23 at Science Direct. 38% of them were published in the International Journal of Geo Information (ISPRS), 16% in the International Journal of Geographical Information Science. 5% were published in the Cartography and Geographic Information Science and the Computer Geosciences respectively. The other 36% is shown in several other journals, approximately 3% each. Regarding the origin of publications, 25% are in Germany (University of Heidelberg), 14% in the UK (New Castle University), 13% in China (Wuhan University), 11% in Canada (Calgary University), and other countries show percentages between 3% and 5%. Among the research, areas are physical geography, remote sensing, computer science, Information science, engineering, and public administration. Among themes addressed in the articles, potentials can be pointed out as existence of models which institutions can implement management of Information received collaboratively, existence of several methodologies for quality control of this Information so that they can be integrated into authoritative data that are called as data conflation. Methodologies for handling big data and semantic interoperability, as well as automation of processes. This data potential is not only on platforms such as OpenStreetMap, but also on data collected through scraping from social networks such as twitter, sites, and others. Among the challenges, there are still somethings to investigate regarding consideration of temporal, historic, political, and economic aspects, as well as the consideration of legal aspects. The integration of this Volunteered Geographic Information is necessary, mainly in cities with economic and cultural difficulties to maintain their mapping up to date, as well as the difficulty of accessing Information that allows access to authoritative data.
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Volunteered Geographic Information research in the first decade: a narrative review of selected journal articles in GIScience
International Journal of Geographical Information Science, 2020Co-Authors: Yingwei Yan, Chen-chieh Feng, Wei Huang, Hongchao Fan, Yi-chen Wang, Alexander ZipfAbstract:More than 10 years have passed since the coining of the term Volunteered Geographic Information (VGI) in 2007. This article presents the results of a review of the literature concerning VGI. A tota...
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Highlighting Current Trends in Volunteered Geographic Information
ISPRS International Journal of Geo-Information, 2017Co-Authors: David Jonietz, Vyron Antonio, Linda See, Alexander ZipfAbstract: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.
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deepvgi deep learning with Volunteered Geographic Information
The Web Conference, 2017Co-Authors: Jiaoyan Chen, Alexander ZipfAbstract:Recently, deep learning has been widely studied to recognize ground objects with satellite imageries. However, finding ground truths especially for developing and rural areas is quite hard and manually labeling a large set of training data is costly. In this work, we propose an ongoing research named DeepVGI which aims at deeply learning from satellite imageries with the supervision of Volunteered Geographic Information (VGI). VGI data from OpenStreetMap (OSM) and a crowdsourcing mobile application named MapSwipe which allows volunteers to label images with buildings or roads for humanitarian aids are utilized. Meanwhile, an active learning framework with deep neural networks is developed by incorporating both VGI data with more complete supervision knowledge. Our experiments show that DeepVGI can achieve high building detection performance for humanitarian mapping in rural African areas.
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completeness of citizen science biodiversity data from a Volunteered Geographic Information perspective
Geo-spatial Information Science, 2017Co-Authors: Clemens Jacobs, Alexander ZipfAbstract:AbstractObservations of living organisms by citizen scientists that are reported to online portals are a valuable source of Information. They are also a special kind of Volunteered Geographic Information (VGI). VGI data have issues of completeness, which arise from biases caused by the opportunistic nature of the data collection process. We examined the completeness of bird species represented in citizen science observation data from eBird and iNaturalist in US National Parks (NPs). We used approaches for completeness estimation which were developed for data from OpenStreetMap, a crowdsourced map of the world. First, we used an extrinsic approach, comparing species lists from citizen science data with National Park Service lists. Second, we examined two intrinsic approaches using total observation numbers in NPs and the development of the number of new species being added to the data-set over time. Results from the extrinsic approach provided appropriate completeness estimations to evaluate the intrinsic ...
Scott A. Hale - One of the best experts on this subject based on the ideXlab platform.
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Estimating Traffic Disruption Patterns with Volunteered Geographic Information.
Scientific reports, 2020Co-Authors: Chico Q. Camargo, Jonathan Bright, Graham Mcneill, Sridhar Raman, Scott A. HaleAbstract:Accurate understanding and forecasting of traffic is a key contemporary problem for policymakers. Road networks are increasingly congested, yet traffic data is often expensive to obtain, making informed policy-making harder. This paper explores the extent to which traffic disruption can be estimated using features from the Volunteered Geographic Information site OpenStreetMap (OSM). We use OSM features as predictors for linear regressions of counts of traffic disruptions and traffic volume at 6,500 points in the road network within 112 regions of Oxfordshire, UK. We show that more than half the variation in traffic volume and disruptions can be explained with OSM features alone, and use cross-validation and recursive feature elimination to evaluate the predictive power and importance of different land use categories. Finally, we show that using OSM's granular point of interest data allows for better predictions than the broader categories typically used in studies of transportation and land use.
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Estimating Traffic Disruption Patterns with Volunteered Geographic Information
arXiv: Computers and Society, 2019Co-Authors: Chico Q. Camargo, Jonathan Bright, Graham Mcneill, Sridhar Raman, Scott A. HaleAbstract:Accurate understanding and forecasting of traffic is a key contemporary problem for policymakers. Road networks are increasingly congested, yet traffic data is often expensive to obtain, making informed policy-making harder. This paper explores the extent to which traffic disruption can be estimated from static features from the Volunteered Geographic Information site OpenStreetMap (OSM). We use OSM features as predictors for linear regressions of counts of traffic disruptions and traffic volume at 6,500 points in the road network within 112 regions of Oxfordshire, UK. We show that more than half the variation in traffic volume and disruptions can be explained with static features alone, and use cross-validation and recursive feature elimination to evaluate the predictive power and importance of different land use categories. Finally, we show that using OSM's granular point of interest data allows for better predictions than the aggregate categories typically used in studies of transportation and land use.
Clodoveu A. Davis - One of the best experts on this subject based on the ideXlab platform.
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ThemeRise: a theme-oriented framework for Volunteered Geographic Information applications
Open Geospatial Data Software and Standards, 2018Co-Authors: Michele B. Pinheiro, Clodoveu A. DavisAbstract:Motivation Web 2.0 disseminated the possibility of engaging citizens in data collection initiatives, also known as Volunteered Geographic Information (VGI), a type of crowdsourcing. This project was conceived based on the need to quickly develop and publish Geographic data collection tools and resources that could be customized to any relevant theme and engage as many contributors as possible.
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ThemeRise: a theme-oriented framework for Volunteered Geographic Information applications
Open Geospatial Data Software and Standards, 2018Co-Authors: Michele B. Pinheiro, Clodoveu A. DavisAbstract:Motivation Web 2.0 disseminated the possibility of engaging citizens in data collection initiatives, also known as Volunteered Geographic Information (VGI), a type of crowdsourcing. This project was conceived based on the need to quickly develop and publish Geographic data collection tools and resources that could be customized to any relevant theme and engage as many contributors as possible. Implementation ThemeRise, a framework for generating VGI applications, was implemented with current and flexible technologies, which ensure its extensibility and evolution. The framework manages the structure and characteristics of data collection target themes individually, allowing for multi-thematic VGI initiative design. This perspective shift also allows a individualization of rewards for volunteer actions, so that the affinity of users to theme-related knowledge domains can be adequately considered and rewarded. As it currently stands, ThemeRise allows creating and publishing VGI resources in minutes, while preserving a sophisticated control over themes, contributions and user experience.
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GeoInfo - A Framework for Web and Mobile Volunteered Geographic Information Applications
2013Co-Authors: Clodoveu A. Davis, Hugo De Souza Vellozo, Michele B. PinheiroAbstract:dcc.ufmg.br Abstract. This paper proposes a framework to be used in the creation of various Volunteered Geographic Information applications, incorporating both Web-based tools and mobile applications (apps). The framework includes the elements required to customize the Information collection, while using a unified structure and interface across Web and mobile platforms. We demonstrate the use of the proposed framework in an application, named Strepitus, which gathers Information on noise sources, so that users can report abusive sources of noise disturbance. The framework's elements and the components of Strepitus are presented in tandem, so that the design decisions are made clear. We observe that the framework allows for a quick development of new VGI applications, and this is important for capturing data on phenomena of current interest for the users, thus helping to maximize the number of Volunteered contributions.
Michele B. Pinheiro - One of the best experts on this subject based on the ideXlab platform.
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ThemeRise: a theme-oriented framework for Volunteered Geographic Information applications
Open Geospatial Data Software and Standards, 2018Co-Authors: Michele B. Pinheiro, Clodoveu A. DavisAbstract:Motivation Web 2.0 disseminated the possibility of engaging citizens in data collection initiatives, also known as Volunteered Geographic Information (VGI), a type of crowdsourcing. This project was conceived based on the need to quickly develop and publish Geographic data collection tools and resources that could be customized to any relevant theme and engage as many contributors as possible.
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ThemeRise: a theme-oriented framework for Volunteered Geographic Information applications
Open Geospatial Data Software and Standards, 2018Co-Authors: Michele B. Pinheiro, Clodoveu A. DavisAbstract:Motivation Web 2.0 disseminated the possibility of engaging citizens in data collection initiatives, also known as Volunteered Geographic Information (VGI), a type of crowdsourcing. This project was conceived based on the need to quickly develop and publish Geographic data collection tools and resources that could be customized to any relevant theme and engage as many contributors as possible. Implementation ThemeRise, a framework for generating VGI applications, was implemented with current and flexible technologies, which ensure its extensibility and evolution. The framework manages the structure and characteristics of data collection target themes individually, allowing for multi-thematic VGI initiative design. This perspective shift also allows a individualization of rewards for volunteer actions, so that the affinity of users to theme-related knowledge domains can be adequately considered and rewarded. As it currently stands, ThemeRise allows creating and publishing VGI resources in minutes, while preserving a sophisticated control over themes, contributions and user experience.
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GeoInfo - A Framework for Web and Mobile Volunteered Geographic Information Applications
2013Co-Authors: Clodoveu A. Davis, Hugo De Souza Vellozo, Michele B. PinheiroAbstract:dcc.ufmg.br Abstract. This paper proposes a framework to be used in the creation of various Volunteered Geographic Information applications, incorporating both Web-based tools and mobile applications (apps). The framework includes the elements required to customize the Information collection, while using a unified structure and interface across Web and mobile platforms. We demonstrate the use of the proposed framework in an application, named Strepitus, which gathers Information on noise sources, so that users can report abusive sources of noise disturbance. The framework's elements and the components of Strepitus are presented in tandem, so that the design decisions are made clear. We observe that the framework allows for a quick development of new VGI applications, and this is important for capturing data on phenomena of current interest for the users, thus helping to maximize the number of Volunteered contributions.
Chico Q. Camargo - One of the best experts on this subject based on the ideXlab platform.
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Estimating Traffic Disruption Patterns with Volunteered Geographic Information.
Scientific reports, 2020Co-Authors: Chico Q. Camargo, Jonathan Bright, Graham Mcneill, Sridhar Raman, Scott A. HaleAbstract:Accurate understanding and forecasting of traffic is a key contemporary problem for policymakers. Road networks are increasingly congested, yet traffic data is often expensive to obtain, making informed policy-making harder. This paper explores the extent to which traffic disruption can be estimated using features from the Volunteered Geographic Information site OpenStreetMap (OSM). We use OSM features as predictors for linear regressions of counts of traffic disruptions and traffic volume at 6,500 points in the road network within 112 regions of Oxfordshire, UK. We show that more than half the variation in traffic volume and disruptions can be explained with OSM features alone, and use cross-validation and recursive feature elimination to evaluate the predictive power and importance of different land use categories. Finally, we show that using OSM's granular point of interest data allows for better predictions than the broader categories typically used in studies of transportation and land use.
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Estimating Traffic Disruption Patterns with Volunteered Geographic Information
arXiv: Computers and Society, 2019Co-Authors: Chico Q. Camargo, Jonathan Bright, Graham Mcneill, Sridhar Raman, Scott A. HaleAbstract:Accurate understanding and forecasting of traffic is a key contemporary problem for policymakers. Road networks are increasingly congested, yet traffic data is often expensive to obtain, making informed policy-making harder. This paper explores the extent to which traffic disruption can be estimated from static features from the Volunteered Geographic Information site OpenStreetMap (OSM). We use OSM features as predictors for linear regressions of counts of traffic disruptions and traffic volume at 6,500 points in the road network within 112 regions of Oxfordshire, UK. We show that more than half the variation in traffic volume and disruptions can be explained with static features alone, and use cross-validation and recursive feature elimination to evaluate the predictive power and importance of different land use categories. Finally, we show that using OSM's granular point of interest data allows for better predictions than the aggregate categories typically used in studies of transportation and land use.
