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There has been enormous progress in geospatial data acquisition in the last decade. Centralized data collection, mainly by land surveying offices and local government agencies, has changed dramatically to voluntary data provision by citizens. Among a broad list of initiatives dealing with user generated geospatial information, OpenStreetMap (OSM) i...
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... the other hand, in order to determine VGI quality in quantitative terms, a comparison with official data of a higher quality (data produced by accepted quality standards) is required. In this study, the reference map at a scale of 1:2000 that was produced by the Municipality of Tehran, in Shapefile format, has been used as ground-truth data (Figure 3). Overlaying the OpenStreetMap (OSM) map with the reference map. ...
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... the fuzzy logic is employed to integrate them. Visually comparing Figure 3, which presents an overlay of the OSM map with a reference map, with Figure 11, which shows integrated quality metric in each tile, can illustrate the ability of the proposed method to evaluate the consistency of an OSM map with a reference map. ...
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In this work, a prototype GIS-based platform to integrate Volunteered Geographic Information from various sources with other spatial data is presented, aiming at assisting civil protection authorities in emergency response situations. The platform is now in the implementation phase, and this paper covers some aspects about its development and preli...
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... Commonly used reference data include officially published data, measured data and remote sensing image data (Barrington-Leigh, Millard-Ball, and Ali 2017;Hecht, Kunze, and Hahmann 2013;Zhou 2018). The selection of quality elements is mainly based on data completeness, positioning accuracy, etc (Borkowska and Pokonieczny 2022;Forghani and Reza Delavar 2014;Husen, Idris, and Ishak 2018). which are widely considered factors in most countries. ...
... Die zusammengetragenen Daten des OSM-Projektes waren in den vergangenen 15 Jahren häufig Bestandteil von Vergleichsstudien zur Ermittlung der Datenqualität in Deutschland (Zielstra & Zipf, 2010, Neis et al., 2011, Großbritannien (Haklay, 2010), Frankreich (Girres & Touya, 2010) und einigen weiteren Ländern (z. B. Forghani & Delavar, 2014;Tian et al., 2019). Bei den Untersuchungen kann generell zwischen einer intrinsischen und extrinsischen Vorgehensweise unterschieden werden. ...
Für Deutschland sind vermehrt offene Geodaten aus dem Bereich der öffentlichen Verwaltung und anderen gemeinnützigen Projekten erhältlich. Die Datensätze können von unterschiedlicher Qualität sein, wobei eine Kombination vereinzelt nützlich erscheint. Die in diesem Beitrag vorgestellte Methode zur Untersuchung wechselseitiger Einflüsse von Datensätzen hinsichtlich ihrer Qualität zeigt, dass die Methode geeignet ist. Das Ergebnis zeigt am Fallbeispiel der verwendeten Standorte der Landespolizei für Deutschland allerdings, dass die aufgestellte These jedoch nicht bestätigt werden kann. Bei der Untersuchung zeigen Qualitätsmerkmale in Bezug auf die thematische Genauigkeit die größten Unterschiede, wodurch die beiden Datensätze bzw. deren Institutionen nicht voneinander profitieren können.
... To address these challenges, researchers have used novel methods to evaluate VGI quality based both on measures and indicators (Antoniou & Skopeliti, 2015). For example, there are several cases where the quality of VGI was tested against reference data (see e.g., Fan et al., 2014;Forghani & Delavar, 2014;Dorn et al., 2015;Zhang & Malczewski, 2017;Touya et al., 2017). However, as explained, the direct evaluation of VGI data against reference data is not always possible due to data availability or differences in scope and scale between two types of datasets. ...
Climate change is linked to the increase of natural disasters occurrence over the world. The increasing frequency of wildfire events constitutes a threat toward ecology, economy, and human lives. Hence, accurate information extracted from detailed burnt area cartography plays a primary role in the ecosystems’ preparation. Geoinformation has enabled rapid and low-cost Earth Observation data acquisition and their processing in cloud-based platforms such as Google Earth Engine (GEE). In the present study, a GEE-based approach that exploits machine learning (ML) techniques and ESA’s Sentinel-2 imagery is developed with the purpose of automating the mapping of burnt areas. As a case study is used an area located in the outskirts of Athens in Greece, on which it was occurred one of the largest wildfires in the summer of 2021. A Sentinel-2 image, obtained from GEE immediately after the fire event, was combined with ML classifiers for the purpose of mapping the burnt area at the fire-affected site. Validation of the derived products was based on the error matrix and the Copernicus Rapid Mapping operational product available for this fire event. Our study results clearly demonstrated the importance of rapid and accurate burnt area mapping exploiting sophisticated algorithms such as ML, when applied to Sentinel-2 imagery. Our findings provide valuable information regarding random forests and support vector machines classifiers through comparisons during their implementation as well as the potential of automated mapping in cloud-based platforms such as GEE. All in all, burnt area mapping is very valuable toward preparation activities regarding postfire management in future fire incidents.
... the previous studies on OSM data quality evaluation, some scholars have made relevant research on OSM building data quality evaluation by using the general qualitative and quantitative VGI data inspection methods. The completeness, semantic accuracy, positional accuracy and shape accuracy of the OSM dataset was evaluated by comparing OSM building data with official reference data (Brovelli & Zamboni, 2018;Fan et al., 2014;Forghani & Delavar, 2014;Hecht et al., 2013;Kunze et al., 2013). These data quality evaluation methods and quality indicators mentioned above are used for inspecting all of the OSM datasets in the study area, which consumed much manpower and material resources hence greatly increasing the inspection cost and reducing the inspection efficiency. ...
With the development of Volunteered Geographical Information (VGI) data, the OpenStreetMap has high research value in terms of project activity, social influence, urban development, application scope, and historical richness and the number of buildings or roads is increasing every day. However, how to evaluate the quality of a large amount OpenStreetMaps efficiently and accurately is still not fully understood. This article presents the development of an approach regarding multilevel stratified spatial sampling based on slope knowledge and official 1:1000 thematic maps as the reference dataset for OpenStreetMap data quality inspection of Hong Kong. This multilevel stratified spatial sampling plan is as follows: (1) The terrain characteristics of Hong Kong are fully considered by dividing grids into quality estimate strata based on the slope information; (2) Spatial sampling for the selection of grids or objects is used; (3) A more reliable sampling subset is made, regarding the representation of the entire OpenStreetMap dataset of Hong Kong. This sampling plan displays a 10% higher sampling accuracy, but without increasing the sample size, particularly as regards building completeness inspection compared with simple random sampling and systematic random sampling. This research promotes further applications of the Open-Street-Map dataset, thus enabling us to have a better understanding of the OpenStreetMap data quality in urban areas.
... To address these challenges, researchers have used novel methods to evaluate VGI quality based both on measures and indicators (Antoniou & Skopeliti, 2015). For example, there are several cases where the quality of VGI was tested against reference data (see e.g., Fan et al., 2014;Forghani & Delavar, 2014;Dorn et al., 2015;Zhang & Malczewski, 2017;Touya et al., 2017). However, as explained, the direct evaluation of VGI data against reference data is not always possible due to data availability or differences in scope and scale between two types of datasets. ...
... If formal data is available in a region, an appropriate approach for data evaluation is to compare formal data and collected data through VGI. This approach was applied by Forghani and Delavar in Tehran (Forghani & Delavar, 2014). Also, Teimoory et al. used the formal data to evaluate the reliability of OSM data regarding their history (Teimoory et al., 2021). ...
Currently, online maps are of the most innovative and significant sources of information in people's daily life. However, quality assessment of volunteered geographic information (VGI) data raises some challenges. This research aims to analyze the VGI participants' level of expertise through evaluation of their background information. Towards this goal, an android application was developed to test users' knowledge and cognition about some selected regions of city as well as their background information. In order to evaluate the quality of information expressed by participants, some changes were made in Tehran's online map, and users were asked to identify the changes and to guess the vanished attributes. Statistical and ANN approaches were applied for analysis. The results demonstrated that the ANN was able to predict the percentage of correct answers of a new volunteer with mean squared error of 0.2. This research suggests that users' age and familiarity with the specific region in the city play more significant roles in their expertise in using online maps and in probable participating in VGI.
... Launched in 2004, OSM serves as a platform to produce user generated spatial data following the crowdsourcing approach and aims at involving the general public in data collection to close existing spatial data gaps. As a consequence, the frontend of OSM is a free editable and therefore constantly changing map of the world (Forghani & Delavar, 2014). As. ...
OpenStreetMap (OSM) is known as the most successful application of VGI. The fact that it is based on user generated content often leads to the common assumption, that OSM data is neutral. These assumptions are legitimate but the vast majority of OSM contributors are mid-aged, white, male users. Accordingly, OSM data represents the worldview of a delimited social group and therefore lags behind its actual potential regarding the richness and quality of data with regard to diversity. To overcome this, new and diverse user groups have to be recruited. It is therefore necessary to identify the challenges and barriers specific new user groups face. This paper elucidates these mechanisms based on literature. Subsequently, we present a study with teacher training students, which identifies challenges of new OSM users. The results indicate that there are three dimensions of potential barriers: the complexity of OSM, the user experience in OSM and the user interface of OSM.
... Launched in 2004, OSM serves as a platform to produce user generated spatial data following the crowdsourcing approach and aims at involving the general public in data collection to close existing spatial data gaps. As a consequence, the frontend of OSM is a free editable and therefore constantly changing map of the world (Forghani & Delavar, 2014). As. ...
OpenStreetMap (OSM) is known as the most successful application of VGI. The fact that it is based on user-generated content often leads to the common assumption that OSM data is neutral. These assumptions are legitimate, but the vast majority of OSM contributors are middle-aged, white, male users. Accordingly, OSM data represents the worldview of a delimited social group and therefore lags behind its actual potential regarding the richness and quality of data with regard to diversity. To overcome this, new and diverse user groups have to be recruited. It is therefore necessary to identify the challenges and barriers specific new user groups face. This chapter elucidates these mechanisms based on literature. Subsequently, the authors present a study with teacher training students that identifies challenges of new OSM users. The results indicate that there are three dimensions of potential barriers: the complexity of OSM, the user experience in OSM, and the user interface of OSM.
... To evaluate completeness, researchers compared VGI with authoritative data. These studies are based on comparing the length in a grid map [Haklay, 2013, Zielstra andZipf, 2010;Forghani and Delavar, 2014], comparing the length or total area [Girres and Touya, 2010;Kalantari and La, 2015], or comparing VGI data with the ground truth [Mashhadi et al., 2014]. Consistency is measured by comparing different dataset objects with other objects of the same theme (intra-theme consistency) or objects of other themes (inter-theme consistency) [Girres andTouya, 2010, Antoniou andSkopeliti, 2015]. ...
Volunteered Geographic Information (VGI) phenomena offer an alternative or supplement to the authoritative mechanism of geospatial data acquisition. It aims to allow people without professional geospatial skills or knowledge to participate in the geospatial data collection. VGI has been boosted by recent advances in geospatial technology and applications. VGI applications have shown great potential in various areas such as disaster management and public health. However, VGI suffers from a lack of quality assurance, because VGI contributors may lack knowledge of the geospatial domain and credibility. Moreover, VGI data may have different levels of detail and precision, and may have been collected for different purposes. Appropriate VGI data for a specific application may be less appropriate for another application. End-users may use VGI data without being aware of its appropriateness to their requirements. This may cause a risk that arises when end-users inappropriately use, or be uncertain about using VGI data in their applications. This risk may undermine the VGI project, in which end-users are involved. This paper proposes an approach that aims to enhance VGI quality assurance by measuring the spatio-semantic similarity between user requirements and provided VGI, and to evaluate the fitness-for-use of VGI. The proposed approach is based on an algorithm to help VGI end-users to deal with the risks related to the quality of VGI data. The approach helps end-user make appropriate decisions about VGI data (e.g., considering or not considering VGI data and being careful when using VGI data).
... Geometric metrics use geometric characteristics of features such as position, length, perimeter, area, shape, or angle [57]. Among the most used metrics in this category are Euclidean [20,[58][59][60][61][62], Hausdorff [2,45,47,[63][64][65][66] and Fréchet [2,67,68] distances, shape similarity measures [2,49,51], and the degree of overlapping between features [2,27,69,70]. ...
One of the most significant challenges in cities concerns urban mobility. Urban mobility involves the use of different modes of transport, which can be individual or collective, and different organizations can produce their respective datasets that, usually, are used isolated from each other. The lack of an integrated view of the entire multimodal urban transportation network (MUTN) brings difficulties to citizens and urban planning. However, obtaining reliable and up-to-date spatial data is not an easy task. To address this problem, we propose a framework for creating a multimodal urban transportation network by integrating spatial data from heterogeneous sources. The framework standardizes the representation of different datasets through a common conceptual model for spatial data (schema matching), uses topological, geometric, and semantic information to find matches among objects from different datasets (data matching), and consolidated them into a single representation using data fusion techniques in a complementary, redundant and cooperative way. Spatial data integration makes it possible to use reliable data from official sources (possibly outdated and expensive to produce) and crowdsourced data (continuously updated and low cost to use). To evaluate the framework, a MUTN for the Brazilian city of Belo Horizonte was built integrating authoritative and crowdsourced data (OpenStreetMap, Foursquare, Facebook Places, Google Places, and Yelp), and then it was used to compute routes among eighty locations using four transportation possibilities: walk, drive, transit, and drive–walk. The time and distance of each route were compared against their equivalent from Google Maps, and the results point to a great potential for using the framework in urban computing applications that require an integrated view of the entire multimodal urban transportation network.
