[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 12, Issue 2 (1-2023) ::
JGST 2023, 12(2): 167-175 Back to browse issues page
Spatial Analysis in curved spaces with Non-Euclidean Geometry
Mohammad Reza Malek *
Abstract:   (276 Views)
The ultimate goal of spatial information, both as part of technology and as science, is to answer questions and issues related to space, place, and location. Therefore, geometry is widely used for description, storage, and analysis. Undoubtedly, one of the most essential features of spatial information is geometric features, and one of the most obvious types of analysis is the geometric type and quantitative measures on such data. Most of the geometric analyzes and measurements used in different sections are based on Euclidean geometry.

In other words, most of the known geometric analyzes are based on the assumption that only one line parallel to another line can be drawn from a point outside the line. Therefore, for example, the sum of the internal angles of a triangle should be 180 degrees, and regular tessellation in the plane is possible with only three types of regular polygons. In non-Euclidean geometries, the mentioned assumption and the results of following it are violated and no longer valid. The purpose of this research is to explain the need to use Non-Euclidean geometry. In this research, it is practically shown that location-based social networks or sensor networks can be addressed in the context of non-Euclidean geometry. This research also shows that the geometry governing the location-based social network is a hyperbolic geometry with negative curvature. This fact can be very effective to solve the problems such as routing and clustering. Moreover, the use of Non-Euclidean tessellations is a suitable tool for providing the user's current location service on the map in mobile and ubiquitous GIS.


 
Article number: 12
Keywords: Ubiquitous GIS, Location Based Social Network, Non-Euclidean Geometry, Curvature, Hyperbolic geometry
Full-Text [PDF 576 kb]   (140 Downloads)    
Type of Study: Research | Subject: GIS
References
1. Kreveld, M. van (2020). Geometric Primitives and Algorithms. The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2020 Edition), John P. Wilson (ed.). DOI: 10.22224/gistbok/2020.2.6. [DOI:10.22224/gistbok/2020.2.6]
2. Panigrahi N. (2014). "Computational Geometry and Its Application to GIS", CRC Press, ISBN 13: 9781482223149. [DOI:10.1201/b17147-8]
3. Coxeter H. S. M. (1998):"Non-Euclidean Geometry", Sixth Edition, The Mathematical Association of America. ISBN 0883855224.
4. Wolfe H. E. (2014):"Introduction To Non-Euclidean Geometry", Nabu Press, ISBN 13: 978-1294451495..
5. Hilbert D. (1950):"The Foundations of Geometry", translated by: E. I. Townsend, Illinois.
6. Ryan P.J. (2006):"Euclidean and Non-Euclidean Geometry An Analytic Approach", Cambridge University Press, 15th Printing.
7. Dunham, D. (2012):" M.C. Escher's Use of the Poincaré Models of Hyperbolic Geometry", In: Bruter, C. (eds) Mathematics and Modern Art. Springer Proceedings in Mathematics, vol 18. Springer, https://doi.org/10.1007/978-3-642-24497-1_7 [DOI:10.1007/978-3-642-24497-1_7.]
8. Escher M.C. (Accessed: 2022):"Circle Limit IV", https://mcescher.com/gallery/mathematical/#.
9. Nickel, M., & Kiela, D. (2017):"Poincaré embeddings for learning hierarchical representations", Advances in neural information processing systems, 30.
10. Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., & Vandergheynst, P. (2017):"Geometric deep learning: going beyond euclidean data", IEEE Signal Processing Magazine, 34(4), 18-42. [DOI:10.1109/MSP.2017.2693418]
11. Baryshnikov Y. (Accessed; 2022):"Online Presentation", https://faculty.math.illinois.edu/~ymb/talks/m499/m499.html#/.
12. Stahl S. (2008):" A Gateway to Modern Geometry: The Poincaré Half-plane", Jones and Bartlett Publishers, ISBN 9780763753818.
13. Gullberg J. (1997):" Mathematics From the Birth of Numbers", Norton, ISBN 978-0-393-04002-9.
14. Aggarwal C.C. (2011):"Social Network Data Analytics", Springer Verlag, ISBN: 978-1-4419-8462-3. [DOI:10.1007/978-1-4419-8462-3_1]
15. Popescu-Pampu P. (2016):"What is the Genus?", Springer Verlag, ISBN 978-3-319-423. [DOI:10.1007/978-3-319-42312-8]
16. Coxeter H. S. M. (1973):" Poincaré's Proof of Euler's Formula",. Ch. 9 in Regular Polytopes, 3rd ed. New York: Dover, pp. 165-172.
17. Do Carmo M. (1976):" Differential Geometry of Curves and Surfaces", Prentice Hall.
18. Kumar, Hradesh & Kumar, Sanjeev. (2015):" Investigating Social Network as Complex Network and Dynamics of User Activities", International Journal of Computer Applications, 125(7), 13-18. 10.5120/ijca2015905952. [DOI:10.5120/ijca2015905952]
19. Gao, H., Tang, J., Liu, H.(2012):" Exploring social-historical ties on location-based social networks", In: Proceedings of the Sixth International Conference on Weblogs and Social Media.
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Malek M R. Spatial Analysis in curved spaces with Non-Euclidean Geometry. JGST 2023; 12 (2) :167-175
URL: http://jgst.issge.ir/article-1-1122-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 12, Issue 2 (1-2023) Back to browse issues page
نشریه علمی علوم و فنون نقشه برداری Journal of Geomatics Science and Technology