Geometric and semantic quality assessments of building features in OpenStreetMap for some areas of Istanbul

• Autorzy: Basaraner Melih

Identyfikatory

DOI

10.2478/pcr-2020-0010

• Języki publikacji: EN

Abstrakty

EN

Nowadays volunteered geographic information (VGI) and collaborative mapping projects such as OpenStreetMap (OSM) have gained popularity as they not only offer free data but also allow crowdsourced contributions. Spatial data entry in this manner creates quality concerns for further use of the VGI data. In this regard, this article focuses on the assessments of geometric and semantic quality of the OSM building features (BFs) against a large-scale topographic (TOPO) data belonging to some areas of Istanbul. The comparison is carried out based on the one-to-one matched BFs according to a geometric matching ratio. In geometric terms, various parameters of position (i.e. X, Y), size (i.e. area, perimeter and granularity), shape (i.e. convexity, circularity, elongation, equivalent rectangular index, rectangularity and roughness index), and orientation (i.e. orientation angle) elements are computed and compared. In semantic terms, BF type coherences are evaluated. According to the findings of geometric quality, the average positional difference was less than three meters. In addition, the perimeter values tended to decrease while area and granularity values tended to increase in OSM data against TOPO data. Those showed that the level of the detail of the OSM BFs was lower than TOPO BFs in general. This was also confirmed by the decreasing tendency of shape complexity according to the parameters of shape element. Orientation angle differences was often low except for some special cases. It was found that the scale of the OSM dataset, even though not homogenous, approximately corresponded to the lower limit of medium scale maps (i.e. 1:10,000) or a slightly smaller scale. According to the findings of semantic quality, in case of the presence of specific type definition, the coherence was rather high between OSM and TOPO BFs while the most OSM BFs did not have a specific type attribute. This study showed that the matching process needed some improvements while the followed approach was largely successful in the evaluation of the matched buildings from geometric and semantic aspects.

Słowa kluczowe

EN

OpenStreetMap; building features; geometric data quality; semantic data quality; topographic data

• Wydawca: Polskie Towarzystwo Geograficzne. Oddział Kartograficzny
• Czasopismo: Polish Cartographical Review
• Rocznik: 2020
• Tom: Vol. 52, No. 3
• Strony: 94--107
• Opis fizyczny: Bibliogr. 21 poz., mapy, rys., tab.

Twórcy

autor

Basaraner Melih

• Yildiz Technical University Department of Geomatic Engineering Division of Cartography, Istanbul, Turkey

Bibliografia

• Basaraner M., Cetinkaya S., 2017, Performance of shape indices and classification schemes for characterising perceptual shape complexity of building footprints in GIS. “Intern. Journal of Geogr. Inform. Science” Vol. 31, No. 10, pp. 1952-1977.
• Basiri A., Haklay M., Foody G., Mooney P., 2019, Crowdsourced geospatial data quality: challenges and future directions. “Intern. Journal of Geogr. Inform. Science” Vol. 33, No. 8, pp. 1588-1593.
• Basiri A., Jackson M. Amirian P. Pourabdollah A., Sester M., Winstanley A., Moore T., Zhang L., 2016, Quality assessment of OpenStreetMap data using trajectory mining. “Geo-spatial Inform. Science” Vol. 19, No. 1, pp. 56-68.
• Brovelli M.A., Zamboni G.A, 2018, New method for the assessment of spatial accuracy and completeness of OpenStreetMap building footprints. “ISPRS Intern. Journal of Geoinformation” Vol. 7, No. 8, p. 289.
• Cartwright W., 2012, Neocartography: opportunities, issues and prospects. “South African Journal of Geomatics” Vol. 1, No.1, pp. 14-31.
• Erden O.E., Basaraner M., 2019, Geometric quality analysis of building footprints from OpenStreet-Map data in comparison to topographic map data. In: International Symposium on Advanced Engineering Technologies (ISADET), 2-4 May 2019, Kahramanmaras, Turkey.
• Fan H., Zipf A., Fu Q., Neis P., 2014, Quality assessment for building footprints data on OpenStreetMap. “Intern. Journal of Geogr. Inform. Science” Vol. 28, No. 4, pp. 700-719.
• Fonte C.C., Antoniou V., Bastin L., Estima J., Arsanjani J.J., Bayas J.-C.L., See L., Vatseva R., 2017, Assessing VGI data quality. In: G. Foody, L. See, S. Fritz, P. Mooney, A.-M. Olteanu-Raimond, C.C. Fonte, V. Antoniou (eds.), Mapping and the citizen sensor, pp. 137-163. London: Ubiquity Press.
• Hecht R., Kunze C., Hahmann S., 2013, Measuring completeness of building footprints in OpenStreet-Map over space and time. “ISPRS Intern. Journal of Geoinformation” Vol. 2, No. 4, pp. 1066-1091.
• Jacobs K.T., Mitchell S.W., 2020, OpenStreetMap quality assessment using unsupervised machine learning methods. “Trans GIS” Vol. 24, No. 5, pp. 1280-1298.
• Kohlstock P., 2014, Kartographie - eine Einführung, 3. Auflage. Paderborn: Schöningh (UTB).
• Kresse W., Fadaie K., 2004, ISO standards for geographic information. Berlin: Springer.
• Li Z., 2007, Algorithmic foundation of multi-scale spatial representation. Boca Raton: CRC Press.
• Maidaneh Abdi I., Le Guilcher A., Olteanu-Raimond A.-M., 2020, A regression model of spatial accuracy prediction for OpenStreetMap buildings. “ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Inform. Sciences” Vol. V-4-2020, pp. 39-47.
• Nowak Da Costa J., 2016, Novel tool for examination of data completeness based on a comparative study of VGI data and official building datasets. “Geodetski Vestnik” Vol. 60, No. 3, pp. 495-508.
• See L., Estima J., Pődör A., Arsanjani J.J., Bayas J.-C.L.,Vatseva R., 2017, Sources of VGI for mapping. In: G. Foody, L. See, S. Fritz, P. Mooney, A.-M. Olteanu-Raimond., C.C. Fonte, V. Antoniou (eds.), Mapping and the citizen sensor, pp. 13-35. London: Ubiquity Press.
• Senaratne H., Mobasheri A., Ali A.L., Capineri C., Haklay M., 2017, A review of volunteered geographic information quality assessment methods. “Intern. Journal of Geogr. Inform. Science” Vol. 31, No. 1, pp. 139-167.
• Sui D., Goodchild M., Elwood S., 2013, Volunteered geographic information, the exaflood, and the growing digital divide. In: D. Sui, M. Goodchild, S. Elwood (eds.), Crowdsourcing geographic knowledge - volunteered geographic information (VGI) in theory and practice, pp. 1-12. New York: Springer.
• Xu Y., Chen Z., Xie Z., Wu L., 2017, Quality assessment of building footprint data using a deep auto-encoder network. “Intern. Journal of Geogr. Inform. Science” Vol. 31, No. 10, pp. 1929-1951.
• download.geofabrik.de/europe/turkey.html - Geofabrik downloads – Europe - Turkey (access 05.01.2020)
• iso.org/standard/32575.html - ISO 19157:2013 Geographic information - Data quality (access 03.12.2020)