242
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Is the radial distance really a distance? An analysis of its properties and interest for the matching of polygon features

ORCID Icon, , ORCID Icon & ORCID Icon
Pages 438-475 | Received 18 Mar 2022, Accepted 07 Sep 2022, Published online: 23 Sep 2022

References

  • Adoram, M., and Lew, M.S., 1999. Irus: image retrieval using shape. In: Proceedings IEEE International Conference on Multimedia Computing and Systems. New York: IEEE, vol. 2, 597–602.
  • Al-Bakri, M., and Fairbairn, D., 2012. Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources. International Journal of Geographical Information Science, 26 (8), 1437–1456. doi:10.1080/13658816.2011.636012.
  • Angel, S., Parent, J., and CIVCO, D.L., 2010. Ten compactness properties of circles: measuring shape in geography. The Canadian Geographer/Le Géographe Canadien, 54 (4), 441–461. doi:10.1111/j.1541-0064.2009.00304.x.
  • Arkin, E.M., et al., 1991. An efficiently computable metric for comparing polygonal shapes. New York: IEEE.
  • Basaraner, M., and Cetinkaya, S., 2017. Performance of shape indices and classification schemes for characterising perceptual shape complexity of building footprints in GIS. International Journal of Geographical Information Science, 31 (10), 1952–1977. doi:10.1080/13658816.2017.1346257.
  • Buttenfield, B.P., and McMaster, R. B. 1991. Map generalization: making rules for knowledge representation. London: Longman Scientific & Technical, Chapter 9, 150–171.
  • Chang, C.C., Hwang, S., and Buehrer, D.J., 1991. A shape recognition scheme based on relative distances of feature points from the centroid. Pattern Recognition, 24 (11), 1053–1063.
  • Cohen, S.D., and Guibas, L.J., 1997. Shape-based image retrieval using geometric hashing. In: Proceedings of the ARPA image understanding workshop. Burlington, MA: Morgan Kaufmann Publishers, 669–674.
  • Costes, B., and Perret, J., 2019. A hidden Markov model for matching spatial networks. Journal of Spatial Information Science, 2019 (18), 57–89.
  • Douglas, D.H., and Peucker, T.K., 1973. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica: The International Journal for Geographic Information and Geovisualization, 10 (2), 112–122.
  • Fan, H., et al., 2014. Quality assessment for building footprints data on openstreetmap. International Journal of Geographical Information Science, 28 (4), 700–719.
  • Fonte, C.C., et al., 2015. VGI QUALITY CONTROL. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3/W5, 317–324. Available from: http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W5/317/2015/.
  • Fonte, C.C., et al., 2017. Using openstreetmap to create land use and land cover maps: development of an application. In: C. Campelo, C. Elízio, M. Bertolotto and P. Corcoran, eds. Volunteered geographic information and the future of geospatial data. Hershey, PA: IGI Global, 113–137. doi:10.4018/978-1-5225-2446-5.ch007.
  • Foody, G.M., 2009. Sample size determination for image classification accuracy assessment and comparison. International Journal of Remote Sensing, 30 (20), 5273–5291. doi:10.1080/01431160903130937.
  • Fu, Z.L., Shao, S.W., and Tong, C.Y., 2010. Multi-scale area entity shape matching based on tangent space. Computer Engineering, 17, 74.
  • Goodchild, M., 2007. Citizens as sensors: the world of volunteered geography. GeoJournal, 69 (4), 211–221.
  • Hangouët, J.F., 2006. Spatial data quality assessment and documentation. Wiley, 211–235.
  • Ivanovic, S., et al., 2019a. A filtering-based approach for improving crowdsourced GNSS traces in a data update context. ISPRS International Journal of Geo-Information, 8 (9), 380. Available from: https://www.mdpi.com/2220-9964/8/9/380.
  • Ivanovic, S.S., et al., 2019b. Potential of crowdsourced traces for detecting updates in authoritative geographic data. In: P. Kyriakidis, D. Hadjimitsis, D. Skarlatos and A. Mansourian, eds. Geospatial technologies for local and regional development. Cham: Springer International Publishing, 205–221. Series Title: Lecture Notes in Geoinformation and Cartography, doi:10.1007/978-3-030-14745-7\_12.
  • Kim, W.Y., and Kim, Y.S., 2000. A region-based shape descriptor using Zernike moments. Signal Processing: Image Communication, 16 (1–2), 95–102.
  • Liu, C., et al., 2015. A progressive buffering method for road map update using openstreetmap data. ISPRS International Journal of Geo-Information, 4 (3), 1246–1264. Available from: https://www.mdpi.com/2220-9964/4/3/1246.
  • Liu, L., et al., 2021. A data fusion-based framework to integrate multi-source vgi in an authoritative land use database. International Journal of Digital Earth, 14 (4), 480–509. doi:10.1080/17538947.2020.1842524.
  • Lokhat, I., and Touya, G., 2016. Enhancing building footprints with squaring operations. Journal of Spatial Information Science, 2016 (13), 33–60.
  • Maidaneh Abdi, I., Le Guilcher, A., and Olteanu-Raimond, A.M., 2020. A regression model of spatial accuracy prediction for openstreetmap buildings. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 5 (4), 39–47.
  • Meng, Q., and Lu, Y., 2014. A fast multi-scale polygon features update approach based on features matching. In: 2014 The Third International Conference on Agro-Geoinformatics. New York: IEEE, 1–5.
  • Müller, M., 2007. Dynamic time warping in information retrieval for music and motion. Springer, 69–84.
  • Mustière, S., and Devogele, T., 2008. Matching networks with different levels of detail. GeoInformatica, 12 (4), 435–453.
  • Olteanu-Raimond, A.M., et al., 2020. Use of automated change detection and VGI sources for identifying and validating urban land use change. Remote Sensing, 12 (7), 1186. Available from: https://www.mdpi.com/2072-4292/12/7/1186.
  • Olteanu-Raimond, A.M., Mustière, S., and Ruas, A., 2015. Knowledge formalization for vector data matching using belief theory. Journal of Spatial Information Science, 10, 21–46. Available from: http://josis.org/index.php/josis/article/view/194.
  • Premaratne, P., and Premaratne, M., 2014. Image matching using moment invariants. Neurocomputing, 137, 65–70.
  • Ripley, B.D., 2009. Stochastic simulation. vol. 316. Hoboken, NJ: John Wiley & Sons.
  • Schultz, M., et al., 2017. Open land cover from openstreetmap and remote sensing. International Journal of Applied Earth Observation and Geoinformation, 63, 206–213. Available from: https://www.sciencedirect.com/science/article/pii/S0303243417301605.
  • See, L., et al., 2016. Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information. ISPRS International Journal of Geo-Information, 5 (5), 55. Available from: http://www.mdpi.com/2220-9964/5/5/55.
  • Senaratne, H., et al., 2017. A review of volunteered geographic information quality assessment methods. International Journal of Geographical Information Science, 31 (1), 139–167.
  • Van Damme, M.D., Olteanu-Raimond, A.M., and Méneroux, Y., 2019. Potential of crowdsourced data for integrating landmarks and routes for rescue in mountain areas. International Journal of Cartography, 5 (2–3), 195–213. doi:10.1080/23729333.2019.1615730.
  • van Winden, K., Biljecki, F., and van der Spek, S., 2016. Automatic update of road attributes by mining GPS tracks. Transactions in GIS, 20 (5), 664–683. doi:10.1111/tgis.12186.
  • Vauglin, F., and Bel Hadj Ali, A., 1998. Geometric matching of polygonal surfaces in giss. In: Proc. ASPRS Annual Meeting. ASPRS.
  • Visvalingam, M., and Whyatt, J.D., 1993. Line generalisation by repeated elimination of points. The Cartographic Journal, 30 (1), 46–51.
  • Walter, V., and Fritsch, D., 1999. Matching spatial data sets: a statistical approach. International Journal of Geographical Information Science, 13 (5), 445–473.
  • Xavier, E.M.A., Ariza-López, F.J., and Ureña Cámara, M.A., 2016. A survey of measures and methods for matching geospatial vector datasets. ACM Computing Surveys, 49 (2), 1–34. doi:10.1145/2963147.
  • Yan, Y., et al., 2020. Volunteered geographic information research in the first decade: a narrative review of selected journal articles in giscience. International Journal of Geographical Information Science, 34 (9), 1765–1791. doi:10.1080/13658816.2020.1730848.
  • Zhang, D., and Lu, G., 2004. Review of shape representation and description techniques. Pattern Recognition, 37 (1), 1–19. Available from: https://www.sciencedirect.com/science/article/pii/S0031320303002759.
  • Zielstra, D., and Hochmair, H.H., 2011. Comparative study of pedestrian accessibility to transit stations using free and proprietary network data. Transportation Research Record: Journal of the Transportation Research Board, 2217 (1), 145–152. doi:10.3141/2217-18.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.