Regression modeling of reduction in spatial accuracy and detail for multiple geometric line simplification procedures

References

• Ai, T. (2007). The drainage network extraction from contour lines for contour line generalization. ISPRS Journal of Photogrammetry and Remote Sensing, 62(2), 93–103. doi: 10.1016/j.isprsjprs.2007.04.002
   Web of Science ®Google Scholar
• Ai, T., Ke, S., Yang, M., & Li, J. (2017). Envelope generation and simplification of polylines using Delaunay triangulation. International Journal of Geographical Information Science, 31(2), 297–319. doi: 10.1080/13658816.2016.1197399
   Web of Science ®Google Scholar
• Ai, T., Zhou, Q., Zhang, X., Huang, Y., & Zhou, M. (2014). A simplification of Ria coastline with geomorphologic characteristics preserved. Marine Geodesy, 37(2), 167–186. doi: 10.1080/01490419.2014.903215
   Web of Science ®Google Scholar
• Bayer, T. (2009). Automated building simplification using a recursive approach. In Advances in cartography and GIScience., (Vol. 1, pp. 121–146). Berlin, Heidelberg: Springer.
   Google Scholar
• Beard, K. (1991). Constraints on rule formation. In Map generalisation: Making rules for knowledge representation (pp. 121–135). UK: Longman Scientific & Technical.
   Google Scholar
• Biljecki, F., Ledoux, H., Stoter, J., & Zhao, J. (2014). Formalisation of the level of detail in 3D city modelling. Computers, Environment and Urban Systems, 48, 1–15. doi: 10.1016/j.compenvurbsys.2014.05.004
   Web of Science ®Google Scholar
• Buttenfield, B. P. (1987). Automating the identification of cartographic lines. Cartography and Geographic Information Science, 14(1), 7–20.
   Google Scholar
• Buttenfield, B. P. (1991). A rule for describing line feature geometry. In B. P. Buttenfield, and R. B. McMaster (Eds.), Map generalization: Making rules for knowledge representation, (pp. 150–171). London: Longman Scientific and Technical.
   Google Scholar
• Cheng, X., Wu, H., Ai, T., & Yang, M. (2017). Detail resolution: A new model to describe level of detail information of vector line data. In C. Zhou, F. Su, F. Harvey, and J. Xu (Eds.), Spatial data handling in big data era, advances in geographic information science, (pp. 167–177). Singapore: Springer.
   Google Scholar
• Damen, J., & Spaan, B. (2008). High quality building generalization by extending the morphological operators. In 12th ICA workshop on generalisation and multiple representation, 20–21 June 2008, (pp. 1–12). France: Montpellier.
   Google Scholar
• DCW (1992). Digital Chart of the World (DCW). Technical Report MIL-D-89009. Fairfax, VA: Defense Mapping Agency.
   Google Scholar
• Douglas, D., & Peucker, T. (1973). Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. The Canadian Cartographer, 10(2), 112–122. doi: 10.3138/FM57-6770-U75U-7727
   Google Scholar
• Dubuisson, M.-P., & Jain, A. (1994). A modified hausdorff distance for object matching. In Proceedings of 12th international conference on pattern recognition (Vol. 1, pp. 566–568). IEEE Comput. Soc. Press.
   Google Scholar
• Dutton, G. (1999). Scale, sinuosity, and point selection in digital line generalization. Cartography and Geographic Information Science, 26(1), 33–54. doi: 10.1559/152304099782424929
   Google Scholar
• Foerster, T., Stoter, J., & Lemmens, R. (2007). Towards automatic web-based generalisation processing: A case study. In Proceedings of the 11th ICA workshop on generalisation and multiple representation, Moscow, Russia, 2–3 August 2007, pp. 1–10.
   Google Scholar
• Jenks, G. F. (1981). Lines, computers, and human frailties. Annals of the Association of American Geographers, 71(1), 1–10. doi: 10.1111/j.1467-8306.1981.tb01336.x
   Web of Science ®Google Scholar
• Jones, C. B., & Abraham, I. (1986). Design considerations for a scale-independent database. In Proceedings of second international symposium on spatial data handling, Seattle (pp. 384–398), Washington, Seattle: International Geographical Union.
   Google Scholar
• Jones, C. B., Kidner, D. B., Luo, L. Q., Bundy, G. L., & Ware, J. M. (1996). Database design for a multi-scale spatial information system. International Journal of Geographical Information Systems, 10(8), 901–920. doi: 10.1080/02693799608902116
   Web of Science ®Google Scholar
• Kilpeläinen, T. (2000). Maintenance of multiple representation databases for topographic data. The Cartographic Journal, 37(2), 101–107. doi: 10.1179/caj.2000.37.2.101
   Web of Science ®Google Scholar
• Kolbe, T. H., Gröger, G., & Plümer, L. (2005). CityGML: Interoperable access to 3D city models. In P. van Oosterom, S. Zlatanova, and E. M. Fendel, (Eds.), Geo-Information for disaster management, (pp. 883–899). Berlin, Heidelberg: Springer.
   Google Scholar
• Lemmens, M. (2011). Quality of geo-information. In Geo-Information, (pp. 211–227). Dordrecht, Netherlands: Springer.
   Google Scholar
• Li, Z. (2006). Algorithmic foundation of multi-scale spatial representation. Boca Raton, FL: CRC Press.
   Google Scholar
• Li, Z., & Openshaw, S. (1992). Algorithms for automated line generalization based on a natural principle of objective generalization. International Journal of Geographical Information Systems, 6(5), 373–389. doi: 10.1080/02693799208901921
   Web of Science ®Google Scholar
• Mackaness, W. A., & Ruas, A. (2007). Evaluation in the map generalisation process. In Generalisation of geographic information: Cartographic modelling and applications (pp. 89–111). Amsterdam: Elsevier.
   Google Scholar
• McMaster, R. B. (1986). A statistical analysis of mathematical measures for linear simplification. Cartography and Geographic Information Science, 13(2), 103–116.
   Google Scholar
• McMaster, R. B. (1987). Automated line generalization. Cartographica: The International Journal for Geographic Information and Geovisualization, 24(2), 74–111. doi: 10.3138/3535-7609-781G-4L20
   Google Scholar
• Meng, L., & Forberg, A. (2007). 3D Building generalisation. In Generalisation of geographic information: Cartographic modelling and applications (pp. 211–231). Amsterdam: Elsevier.
   Google Scholar
• Mitropoulos, V., & Nakos, B. (2011). A methodology on natural occurring lines segmentation and generalization. In Proceedings of 14th ICA workshop on generalisation and multiple representation, Paris, France (p. 7), Paris, France.
   Google Scholar
• Mustiere, S. (2005). Cartographic generalization of roads in a local and adaptive approach: A knowledge acquisition problem. International Journal of Geographical Information Science, 19(8–9), 937–955. doi: 10.1080/13658810509161245
   Web of Science ®Google Scholar
• Park, W., & Yu, K. (2011). Hybrid line simplification for cartographic generalization. Pattern Recognition Letters, 32(9), 1267–1273. doi: 10.1016/j.patrec.2011.03.013
   Web of Science ®Google Scholar
• Peters, R., Ledoux, H., & Meijers, M. (2014). A Voronoi-based approach to generating depth-contours for hydrographic charts. Marine Geodesy, 37(2), 145–166. doi: 10.1080/01490419.2014.902882
   Web of Science ®Google Scholar
• Plazanet, C., Affholder, J.-G., & Fritsch, E. (1995). The importance of geometric modeling in linear feature generalization. Cartography and Geographic Information Science, 22(4), 291–305. doi: 10.1559/152304095782540276
   Google Scholar
• Raposo, P. (2013). Scale-specific automated line simplification by vertex clustering on a hexagonal tessellation. Cartography and Geographic Information Science, 40(5), 427–443. doi: 10.1080/15230406.2013.803707
   Web of Science ®Google Scholar
• Ruas, A., & Bianchin, A. (2002). Echelle et niveau de detail. In A. Ruas (Ed.) Generalisation et representation multiple (pp. 25–44). Paris: Hermes Lavoisier.
   Google Scholar
• Samsonov, T. E., & Yakimova, O. P. (2017). Shape-adaptive geometric simplification of heterogeneous line datasets. International Journal of Geographical Information Science, 31(8), 1485–1520. doi: 10.1080/13658816.2017.1306864
   Web of Science ®Google Scholar
• Sarjakoski, T. L. (2007). Conceptual models of generalisation and multiple representation. In Generalisation of geographic information: Cartographic modelling and applications (pp. 11–35). Amsterdam: Elsevier.
   Google Scholar
• Shi, W., & Cheung, C. (2006). Performance evaluation of line simplification algorithms for vector generalization. The Cartographic Journal, 43(1), 27–44. doi: 10.1179/000870406X93490
   Web of Science ®Google Scholar
• Song, J., & Miao, R. (2016). A novel evaluation approach for line simplification algorithms towards vector map visualization. ISPRS International Journal of Geo-Information, 5(12), 223. doi: 10.3390/ijgi5120223
   Web of Science ®Google Scholar
• Stoter, J., Zhang, X., Stigmar, H., & Harrie, L. (2014). Evaluation in generalisation. In Abstracting geographic information in a data rich world: Methodologies and applications of map generalisation (pp. 259–297). Cham: Springer.
   Google Scholar
• Touya, G. (2013). Detecting level-of-detail inconsistencies in volunteered geographic information data sets. Cartographica: The International Journal for Geographic Information and Geovisualization, 48(2), 134–143. doi: 10.3138/carto.48.2.1836
   Google Scholar
• Touya, G., & Baley, M. (2017). Level of details harmonization operations in openstreetmap based large scale maps. In Citizen empowered mapping (Vol. 18, pp. 3–25). Cham: Springer International Publishing AG.
   Google Scholar
• Touya, G., Duchêne, C., & Ruas, A. (2010). Collaborative generalisation: Formalisation of generalisation knowledge to orchestrate different cartographic generalisation processes. In Theories and methods of spatio-temporal reasoning in geographic space (pp. 264–278). Berlin, Heidelberg: Springer.
   Google Scholar
• Touya, G., & Reimer, A. (2015). Inferring the scale of openstreetmap features. In OpenStreetMap in GIScience (pp. 81–99). Springer International Publishing.
   Google Scholar
• Veregin, H. (2000). Quantifying positional error induced by line simplification. International Journal of Geographical Information Science, 14(2), 113–130. doi: 10.1080/136588100240877
   Web of Science ®Google Scholar
• Visvalingam, M. (2016). The Visvalingam algorithm: Metrics, measures and heuristics. The Cartographic Journal, 53(3), 242–252. doi: 10.1080/00087041.2016.1151097
   Web of Science ®Google Scholar
• Visvalingam, M., & Whyatt, J. D. (1993). Line generalisation by repeated elimination of points. The Cartographic Journal, 30(1), 46–51. doi: 10.1179/caj.1993.30.1.46
   Web of Science ®Google Scholar
• Wang, Z., & Müller, J.-C. (1998). Line generalization based on analysis of shape characteristics. Cartography and Geographic Information Science, 25(1), 3–15. doi: 10.1559/152304098782441750
   Google Scholar
• Wang, Z., & Muller, J. C. (1993). Complex coastline generalization. Cartography and Geographic Information Science, 20(2), 96–106. doi: 10.1559/152304093782610333
   Google Scholar
• Weibel, R. (1996). A typology of constraints to line simplification. In Proceedings of 7th international symposium on spatial data handling, 12–16 August 1996, Delft, The Netherlands, pp. 533–546.
   Google Scholar
• Zhao, Z., & Saalfeld, A. (1997). Linear-time sleeve-fitting polyline. In Autocarto 13, ACSM/ASPRS'97 technical papers, Seattle, Washington, pp. 214–223.
   Google Scholar
• Zhou, S., & Jones, C. B. (2003). A multi-representation spatial data model. In G. Goos, J. Hartmanis, J. van Leeuwen, T. Hadzilacos, Y. Manolopoulos, J. Roddick, and Y. Theodoridis (Eds.), Advances in spatial and temporal databases (Vol. 2750, pp. 394–411). Berlin, Heidelberg: Springer.
   Google Scholar