Abstract
Despite all distortions and incompleteness present in Sketch maps, they can be used for different purposes such as collecting and searching spatial data and organizing the spatial knowledge of individuals. Since the prerequisite for all of these cases is matching sketches with existing data in spatial databases or metric maps, several studies have been conducted in this field. These studies generally focus on the relationships between routes, landmarks, and regions, while data sources do not necessarily contain all of these data. Also, the subject of the incompleteness of data and evaluation of the results has been less considered in previous studies. Therefore, in this paper, a new solution for matching routes from sketches to metric maps is presented. The proposed solution uses the Genetic Algorithm to measure the similarities between routes in two phases, and in each phase, a set of geometric/topological criteria is considered to improve the matching. The proposed algorithm is implemented to match routes of 25 sketches with the routes in a metric map. The average \(F_{{{\text{Measure}}}}\) of matching is 45.59%. The results show that by considering the specific conditions (not availability of descriptive data of routes and geometric/descriptive information of landmarks), this paper has been able to take an important step toward finding an acceptable solution for the matching problem. The proposed methods can be used to deal with the incompleteness of the thematic information in metric maps.
Similar content being viewed by others
References
Al-Salman, R., Dylla, F., Fogliaroni, P. (2012). Matching Geo-Spatial Information by Qualitative Spatial Relations, ACM SIGSPATIAL GEOCROWD 12
Bajpai P, Kumar DM (2008) Genetic algorithm: an approach to solve global optimization problems. Ind J Comput Sci Eng 1(3):199–206
Biedla T, Held M, Huber S, Kaaser D, Palfrader P (2015) A simple algorithm for computing positively weighted straight skeletons of monotone polygons. Inf Process Lett 115(2015):243–247
Blades M (1990) The reliability of data collected from sketch maps. J Environ Psychol 10:327–339
Blaser A (1999) prototype application sketcho technical report. University of Maine. National Centre of Geographic Information and Analysis, Orno
Chipofya M , Schultz C , Schwering A (2015) A metaheuristic approach for efficient and effective sketch-to-metric map alignment. Int J Geogr Inf Sci https://doi.org/10.1080/13658816.2015.1090000
Chipofya M, Schwering A, Binor T (2013) Matching qualitative spatial scene descriptions a la Tabu. University of Munster, Germany, Institute for Geoinformatics
Cohn AG, Hazarika SM (2001) Qualitative spatial representation and reasoning: an overview. Fundam Inform 43:2–32
Deep K, Thakur M (2007) A new crossover operator for real coded genetic algorithms. Appl Math Comput 188:895–911
Egenhofer MJ (1996) Spatial-query-by-sketch. Burnett M, Citrin W IEEE symposium on visual languages, vol 96. IEEE, Boulder, Colorado, pp 60–67
Garey MR, Johnson DS (1978) Computers and intractability: a guide to the theory of NP-completeness. W. H. Freeman & Co., New York, NY, USA (0716710455)
Haarslev V, Moller R, Wessel M (2000) Visual spatial query languages: a semantics using description logic. Springer-Verlag, London (Diagrammatic Representation and Reasoning)
Herrera F, Lozano M, Verdegay JL (1998) Tackling real coded genetic algorithms: operators and tools for behavioral analysis. Artif Intell Rev 12:265–319
Holland JH (1975) Adaptation in Natural and Artificial Systems. University of Michigan press, Ann Arbor
Huynh NT, Doherty ST (2007) Digital sketch-map drawing as an instrument to collect data about spatial cognition. Cartogr Int J Geogr Inf Geovis 42(4):285–296. https://doi.org/10.3138/carto.42.4.285
Jacobs LF (2003) The evolution of the cognitive map. Brain Behav Evol 62:128–139. https://doi.org/10.1159/000072443
Jan S, Schwering A (2015) SketchMapia: a framework for qualitative alignment of sketch maps and metric maps. AGILE, Lisbon
Jan S, Schwering A, Chipofya M, Binor T (2014) Qualitative representations of extended spatial objects in sketch maps Lecture Notes in Geoinformation and Cartography, Springer International Publishing Switzerland https://doi.org/10.1007/978-3-319-03611-3_3
Jan S, Schwering A, Schultz C, Chipofya M (2017) Cognitively plausible representations for the alignment of sketch and geo-referenced maps. J Spat Inf Sci Number 14:31–59. https://doi.org/10.5311/JOSIS.2017.14.294
Jan S, Schwering A, Wang J, Chipofya M (2013) Ordering: A Reliable Qualitative Information for The Alignment of Sketch and Metric Maps, In: Proceedings of the 2013 IEEE Canadian Conference on Electrical & Computer Engineering, 0-7802-xxxx-x/02/$10
Kopczynski M (2006) Efficient spatial queries with sketches In: ISPRS Technical Commission II Symposium Vienna pp. 19–24
Lopez A, Caffò AO, Postma A, Bosco A (2020a) How to separate coordinate and categorical spatial relation components in integrated spatial representations: A new methodology for analysing sketch maps. Scand J Psychol https://doi.org/10.1111/sjop.12633
Lopez A, Postma A, Bosco A (2020b) Categorical & coordinate spatial information: Can they be disentangled in sketch maps?. J Environ Psychol 68 https://doi.org/10.1016/j.jenvp.2020.101392
Malhotra, R., Singh, N. & Singh, Y. (2011). Genetic Algorithms: Concepts, Design for Optimization of Process Controllers. Computer and Information Science. Vol. 4, No. 2
Metz HM (2007) Sketch maps: helping students get the big picture. J Geogr 89(3):114–118. https://doi.org/10.1080/00221349008979610
Microsoft Bing Maps Imagery Service: Editor Application API’s Terms of Use, Last Updated: November 2010, https://blog.openstreetmap.org/wp-content/uploads/2010/11/4540180-Bing-Maps-Imagery-Editor-API-License-Final.pdf
Moratz, R., Lücke, D., & Mossakowski, T. (2009) Oriented straight line segment algebra: Qualitative spatial reasoning about oriented objects. CoRR, abs/0912.5533
Nedas KN, Egenhofer MJ (2008) Spatial-scene similarity queries. Trans. GIS 12:661–681. https://doi.org/10.1111/j.1467-9671.2008.01127.x
OpenStreetMap website: https://www.openstreetmap.org/#map=16/33.2906/57.5159&layers=N
Schwering A, Wang J, Chipofya M, Jan S, Li R, Broelemann K (2014) SketchMapia: qualitative representations for the alignment of sketch and metric maps. Spat Cogn Comput 14(3):220–254. https://doi.org/10.1080/13875868.2014.917378
Thoresen S (2007) An efficient solution to inexact graph matching with application to computer vision Norwegian University of Science and Technology, Department of Computer and Information Science. 978-82-471-3604-1
Thorndyke PW (1981) Distance estimation from cognitive maps. Cogn Psychol 13:526–550
Wallgrün JO, Wolter D, Richter K (2010) Qualitative matching of spatial information. ACM GIS 10:300–3008
Wang J (2009) How human schematization and systematic errors take effect on sketch map formalizations s (Master’s thesis), University of Munster Institute for Geoinformatics
Wang J, Schwering A (2015) Invariant spatial information in sketch maps __ a study of survey sketch maps of urban areas. J Spat Inf Sci 11:31–52. https://doi.org/10.5311/JOSIS.2015.11.225
Wang J, Mülligann C, Schwering, A (2011) An empirical study on relevant aspects for sketch map alignment University of Muenster, Germany Institute for Geoinformatics
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zare Zardiny, A., Hakimpour, F. Route Matching in Sketch and Metric Maps. J Geogr Syst 23, 381–405 (2021). https://doi.org/10.1007/s10109-020-00343-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10109-020-00343-1