An Investigation into the Completeness of, and the Updates to, OpenStreetMap Data in a Heterogeneous Area in Brazil

Camboim, Silvana Philippi; Bravo, João Vítor Meza; Sluter, Claúdia Robbi

doi:10.3390/ijgi4031366

Cited by 53 publications

(56 citation statements)

References 31 publications

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“…In this paper, we contribute towards this issue by focusing primarily on the coverage offered by VGI platforms in Kenya. By contributing this first case study of its type in the African continent, we augment the very limited literature [16,46] on this topic and help advance our understanding of the value of citizen-contributed data for developing countries, as well as of the challenges associated with this evolving paradigm of geospatial data collection for such communities.…”

Section: Discussionmentioning

confidence: 99%

“…However, besides the work of Haklay [46] in Haiti and Camboim et al [16] in Brazil, to the authors' knowledge, no other studies currently exist for comparing such data for developing countries. In Haklay [46], this preliminary study used the same method as in Haklay [43] to calculate road completeness, comparing the road coverage between OSM and Map Maker data obtained after the 2010 Haitian earthquake.…”

Section: Introductionmentioning

confidence: 95%

“…Map Maker, on the other hand, showed greater coverage in some of the more rural areas near the northern and southwestern parts of the country. The same measure of completeness was used by Camboim et al [16], along with three additional completeness measures (road length, number of buildings and attribute completeness) and two temporal measures (number of editors per region and days past last change) to assess the quality of VGI for urban and rural areas in Curitiba, Brazil. That study showed higher completeness and temporal values in areas with larger population densities.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Mahabir

Stefanidis

Croitoru

et al. 2017

IJGI

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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 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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Mahabir

Stefanidis

Croitoru

et al. 2017

IJGI

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“…However, very few studies have reported on the fitness-of-use of the dataset in developing countries [56,[90][91][92][93] using established quality indicators. The established methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data [14].…”

Section: Semantic Accuracymentioning

confidence: 99%

Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox

Sehra

Singh

2017

Future Internet

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OpenStreetMap (OSM) is a recent emerging area in computational science. There are several unexplored issues in the quality assessment of OSM. Firstly, researchers are using various established assessment methods by comparing OSM with authoritative dataset. However, these methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data. In such a scenario, the intrinsic quality indicators can be used to assess the quality. Secondly, a framework for data assessment specific to different geographic information system (GIS) domains is not available. In this light, the current study presents an extension of the Quantum GIS (QGIS) processing toolbox by using existing functionalities and writing new scripts to handle spatial data. This would enable researchers to assess the completeness of spatial data using intrinsic indicators. The study also proposed a heuristic approach to test the road navigability of OSM data. The developed models are applied on Punjab (India) OSM data. The results suggest that the OSM project in Punjab (India) is progressing at a slow peace, and contributors' motivation is required to enhance the fitness of data. It is concluded that the scripts developed to provide an intuitive method to assess the OSM data based on quality indicators can be easily utilized for evaluating the fitness-of-use of the data of any region.

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“…An example of such dataset is one based on old but accurate cadastral data, in which newer buildings have been supplemented with other acquisition techniques such as footprints digitized from aerial images. Such approaches may result in data of variable accuracy and differing LODs, a phenomenon inherent to volunteered geoinformation (Camboim, Bravo, & Sluter, 2015;Fan, Zipf, Fu, & Neis, 2014;Senaratne, Mobasheri, Ali, Capineri, & Haklay, 2017;Touya & Brando-Escobar, 2013;Uden & Zipf, 2013). Because such data are becoming increasingly used for spatial analyses (Wendel, Murshed, Sriramulu, & Nichersu, 2016), it is worthwhile to investigate for which portions of the dataset caution should be exercised due to lower reliability than in other parts of the dataset.…”

Section: Introductionmentioning

confidence: 99%

The effect of acquisition error and level of detail on the accuracy of spatial analyses

Biljecki

Heuvelink

Ledoux

et al. 2017

Cartography and Geographic Information Science

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There has been a great deal of research about errors in geographic information and how they affect spatial analyses. A typical GIS process introduces various types of errors at different stages, and such errors usually propagate into errors in the result of a spatial analysis. However, most studies consider only a single error type thus preventing the understanding of the interaction and relative contributions of different types of errors. We focus on the level of detail (LOD) and positional error, and perform a multiple error propagation analysis combining both types of error. We experiment with three spatial analyses (computing gross volume, envelope area, and solar irradiation of buildings) performed with procedurally generated 3D city models to decouple and demonstrate the magnitude of the two types of error, and to show how they individually and jointly propagate to the output of the employed spatial analysis. The most notable result is that in the considered spatial analyses the positional error has a much higher impact than the LOD. As a consequence, we suggest that it is pointless to acquire geoinformation of a fine LOD if the acquisition method is not accurate, and instead we advise focusing on the accuracy of the data. ARTICLE HISTORY

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An Investigation into the Completeness of, and the Updates to, OpenStreetMap Data in a Heterogeneous Area in Brazil

Cited by 53 publications

References 31 publications

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

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

Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox

The effect of acquisition error and level of detail on the accuracy of spatial analyses

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