Use of GLCM Entropy Parameter in the Analysis of Urban Function Spaces; Antalya City Example

Abstract

Urban spaces are concentrated in certain functions to meet the needs and desires of the urbanites. However, for each city, different functions and the value of the space to meet these functions are different. In this study, spatial entropy analysis of Antalya, the most important tourism city of our country, was carried out through GLCM Entropy analysis, one of the texture parameter methods. In the study, firstly, function areas and function spaces were determined. A 5-meter resolution satellite image for 2022 was obtained to perform texture parameter analyses. The satellite image was scaled to include the whole city and urban spaces with QGIS software, and then the general entropy values of the city were calculated with Definies software. Then, selected urban spaces with different functions were extracted from the satellite image and subjected to entropy analyses. According to the results obtained, the areas with the highest entropy difference for Antalya city were determined as airport and harbour, which are transportation and trade places. For Antalya, which has poor road access to the world due to geographical reasons, it is seen as an important determination in terms of analysis that the places representing air and sea connection come to the fore.

Keywords

• Urban Space
• Entropy
• Remote Sensing
• Texture Parameter

References

1. Acar, E., Özerdem, M. S. (2012). Kızıltepe Agricultural Classification of Kızıltepe Agricultural Field Images According to Crop Product Development (Kızıltepe Tarımsal Kızıltepe Tarımsal Alan İmgelerinin Ekinin Ürün Gelişimine Göre Sınıflandırılması). Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi, 5(1).
2. Alparslan, E., Aydöner, C., Yüce, H., Dönertaş, A. S. (2004). Determination of Changes in Coastal Area Texture of Marmara Sea in Istanbul Province by Landsat Satellite Image Analysis (İstanbul İli Marmara Denizi Kıyısal Alan Dokusu Değişikliklerin Landsat Uydu Görüntü Analizi ile Belirlenmesi). jiP, 1, 0.
3. Altan, İ. (1993). Concept of Space in Architecture (Mimarlikta Mekan Kavramı). Psikoloji Çalışmaları, 19, 75-88. Baraldi, A., Panniggiani, F. (1995). An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters. IEEE transactions on geoscience and remote sensing, 33(2), 293-304.
4. Barner, M., Cottineau, C., Molinero, C., Salat, H., Stanilov, K., Arcaute, E. (2017). Multiscale entropy in the spatial context of cities. arXiv preprint arXiv:1711.09817.
5. Batty, M. (1974). Urban Density and Entropy Functions. Journal of Cybernetics, 4(2), 41-55. doi:10.1080/01969727408546065
6. Bayartan, M. (2007). Urban Functions, Effects of Special Functions on Urban Development and Trabzon Example (Kentsel Fonksiyonlar, Özel Fonksiyonların Kentsel Gelişime Etkileri ve Trabzon Örneği). Karadeniz İncelemeleri Dergisi, 1(2), 123-136.
7. Belge, R. (2018). Geographical elements that make up Denizli city identity (Denizli kent kimliğini oluşturan coğrafi öğeler). Ege Coğrafya Dergisi, 27(2), 167-181.
8. Beliakov, G., James, S., Troiano, L. (2008). Texture recognition by using GLCM and various aggregation functions. Paper presented at the 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

9. Beyazıt, E., Güneş, M. (2020). Globalization and Urban Identity: Erosion of Urban Values in the Process of Globalization (Küreselleşme ve Kent Kimliği: Kentsel Değerlerin Küreselleşme Sürecinde Aşınması). Journal of Academic Value Studies, 3(9), 323-331.
10. Bostancı, S. H., Ocakçı, M. (2009). Evaluating the design qualities of city silhouettes with the entropy approach (Kent siluetlerine ilişkin tasarım niteliklerinin, entropi yaklaşımı ile değerlendirilmesi). İTÜDERGİSİ/a, 8(2).
11. Budak, S., Kavanoz, S. (2019). The Process of Highlighting Small Settlements with Their Local and Unique Values: Urban Tourism in the Age of Globalization (Küçük Yerleşimlerin Yerel ve Özgün Değerleriyle Öne Çıkarılma Süreci: Küreselleşme Çağında Kent Turizmi). SİYASAL: Journal of Political Sciences, 28, 117-140. doi:10.26650/siyasal.2019.28.2.0043
12. Cabral, P., Augusto, G., Tewolde, M., Araya, Y. (2013). Entropy in Urban Systems. Entropy, 15(12), 5223-5236. Chen, Y., Wang, J., Feng, J. (2017). Understanding the fractal dimensions of urban forms through spatial entropy. Entropy, 19(11), 600.
13. Coutrot, A., Manley, E., Goodroe, S., Gahnstrom, C., Filomena, G., Yesiltepe, D., Hornberger, M. (2022). Entropy of city street networks linked to future spatial navigation ability. Nature, 604(7904), 104-110.
14. Çalışkan, A., Emrullah, A., Yılmaz, K. (2012). Palm Recognition System with GLCM Based K-NN Classifier Model (GLCM Tabanlı K-NN Sınıflandırıcı Modeli ile Avuç İçi Tanıma Sistemi). Batman Üniversitesi Yaşam Bilimleri Dergisi, 1(2), 1-10.
15. Demirhan, A., Güler, İ. (2010). Image Segmentation with Self-Organizing Map Networks and Gray Level Co-Occurrence Matrices (Özörgütlemeli Harita Ağlari Ve Gri Düzey Eş Oluşum Matrisleri Ile Görüntü Bölütleme). Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 25(2).
16. Duman, Y., Bilgili, A. (2022). The Impact of Cities on Climate Change: The Importance of Cities and Successful Application Examples in Combating Climate Change (Kentlerin İklim Değişikliği Üzerine Etkisi: İklim Değişikliği İle Mücadelede Kentlerin Önemi ve Başarılı Uygulama Örnekleri). Vizyoner Yönetim, 119-136.
17. Ekinoglu, H., Kubat, A. S., Plunz, R. (2017). Modeling spatial wholeness in cities using information entropy theory. A| Z ITU Journal of the Faculty of Architecture, 14(3), 67-81.
18. Gehl, J. (2020). Cities For People (İnsan için kentler): Koç Üniversitesi.
19. Gudmundsson, A., Mohajeri, N. (2013). Entropy and order in urban street networks. Scientific reports, 3(1), 3324.
20. Haralick, R. M. (1979). Statistical and structural approaches to texture. Proceedings of the IEEE, 67(5), 786-804.
21. Haralick, R. M., Shanmugam, K., Dinstein, I. (1973). Textural Features for Image Classification. Ieee Transactions on Systems Man and Cybernetics, Smc3(6), 610-621. doi: 10.1109/Tsmc.1973. 4309314
22. Horng, M.-H. (2003). Texture feature coding method for texture classification. Optical Engineering, 42(1), 228-238.
23. Hu, Y., Zhao, C.-x., Wang, H.-n. (2008). Directional analysis of texture images using gray level co-occurrence matrix. Paper presented at the 2008 IEEE Pacific-Asia workshop on computational intelligence and industrial application.
24. Judd, D. R., Fainstein, S. S. (1999). The tourist city: Yale University Press.
25. Kapur, J. N., Sahoo, P. K., Wong, A. K. (1985). A new method for gray-level picture thresholding using the entropy of the histogram. Computer vision, graphics, and image processing, 29(3), 273-285.
26. Karakurt, E. (2006). Suggestions for organizing urban space: modern urban planning approach and postmodern urban planning approach (Kentsel mekanı düzenleme önerileri: modern kent planlama anlayışı ve postmodern kent planlama anlayışı). Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi(26), 1-25.
27. Konuk, G. (1992). Urban design as a synthesis of time and space (Zaman ve mekanın bir sentezi olarak kentsel tasarım). Kentsel Tasarım ve Uygulamalar Sempozyumu, 66-81.
28. Li, X., Claramunt, C. (2006). A spatial entropy‐based decision tree for classification of geographical information. Transactions in GIS, 10(3), 451-467.
29. Löfstedt, T., Brynolfsson, P., Asklund, T., Nyholm, T., Garpebring, A. (2019). Gray-level invariant Haralick texture features. PloS one, 14(2), e0212110.
30. Marchettini, N., Pulselli, F., Tiezzi, E. (2006). Entropy and the city. WIT Trans. Ecol. Environ, 93, 263-272.
31. Ökmen, M., Parlak, B. (2008). Turkish Urban Administrations from Modernization to Globalization: Basic Characteristics, Problems and Projections (Modernleşmeden Küreselleşmeye Türk Kent Yönetimleri: Temel Nitelikler, Sorunlar ve Projeksiyonlar). Karamanoğlu Mehmetbey Üniversitesi Sosyal ve Ekonomik Araştırmalar Dergisi, 2008(2), 199-259.
32. Ölmez, E. (2021). Entropy approach in remote sensing and GIS applications in the analysis of historical places: "Example of the Ancient City of Xanthos" (Tarihsel mekanların analizinde uzaktan algılama ve CBS uygulamalarında entropi yaklaşımı:" Ksanthos Antik Kenti Örneği"). Akdeniz Üniversitesi Fen Bilimleri Enstitüsü, Master Thesis.
33. Özen, İ., Aptoula, E. (2016). Texture Description Based on Co-occurrence of Morphological Features (Biçimbilimsel Özniteliklerin Eş-Oluşumlarına Dayalı Doku Betimleme). Paper presented at the 18. Akademik Bilişim Konferansı, Aydın.
34. Öztürk, D. (2017). Examining Urban Sprawl with Shannon Entropy and Fractal Analysis: Samsun Example (Shannon Entropi ve Fraktal Analiz ile Kentsel Yayılmanın İncelenmesi: Samsun Örneği). Türkiye Harita Bilimsel ve Teknik Kurultayı, 3(6).
35. Pender, L., Sharpley, R. (2005). The Management of Tourism: SAGE Publications.
36. Pesaresi, M. (2000). Texture analysis for urban pattern recognition using fine-resolution panchromatic satellite imagery. Geographical and Environmental Modelling, 4(1), 43-63.
37. Purvis, B., Mao, Y., Robinson, D. (2019). Entropy and its Application to Urban Systems. Entropy, 21(1), 56.
38. Rasmussen, S. E. (1969). Towns and buildings: described in drawings and words (Vol. 112): Mit Press.
39. Ratti, C., Richens, P. (1999). Urban Texture Analysis With Image Processing Techniques. Paper presented at the Computers in Building: Proceedings of the CAADfutures’ 99 Conference. Proceedings of the Eighth International Conference on Computer Aided Architectural Design Futures held at Georgia Institute of Technology, Atlanta, Georgia, USA on June 7–8, 1999.
40. Rondinel-Oviedo, D. R., Keena, N. (2023). Entropy and Cities: A Bibliographic Analysis towards More Circular and Sustainable Urban Environments. Entropy, 25(3). doi:ARTN 532.10.3390/e25030532
41. Salihoğlu, T. (2020). Determining the Boundaries of Central Areas in Istanbul with the Help of GIS (CBS Yardımıyla İstanbul’daki Merkez Alanların Sınırlarının Belirlenmesi). Geomatik, 5(3), 201-208.
42. Sarı, S., Türk, T. (2021). An investigation of urban development with geographical information systems: 100-year change of Sivas City, Turkey. International Journal of Engineering and Geosciences, 6(1), 51-63.
43. Sathyamoorthy, D. (2013). Çoklu ölçekli sayısal yükseklik modellerinden çıkarılan fizyografik detaylara ait yüzey doku özelliklerinin gri düzey eş-oluşum matrisi ile analizi. Jeodezi ve Jeoinformasyon Dergisi(107), 59-69.
44. Shiozaki, A. (1986). Edge extraction using entropy operator. Computer vision, graphics, and image processing, 36(1), 1-9.
45. Tang, J., Zhang, S., Chen, X., Liu, F., Zou, Y. (2018). Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city—China. Physica A: Statistical Mechanics and its Applications, 493, 430-443.
46. Tümtaş, S., Ergun, C. (2016). Globalization and Its Effects on Cities (Küreselleşme ve Kentlere Etkileri). Süleyman Demirel Üniversitesi Fen-Edebiyat Fakültesi Sosyal Bilimler Dergisi(37), 135-150.
47. Verzosa, L. C. O., Gonzalez, R. M. (2010). Remote sensing, geographic information systems and Shannon’s entropy: Measuring urban sprawl in a mountainous environment: na.
48. Wang, C., Zhao, H. (2018). Spatial heterogeneity analysis: Introducing a new form of spatial entropy. Entropy, 20(6), 398.
49. Yeh, A. G.-O., Li, X. (2001). Measurement and monitoring of urban sprawl in a rapidly growing region using entropy. Photogrammetric engineering and remote sensing.
50. Zaim, A., Sawalha, A., Quweider, M., Iglesias, J., Tang, R. (2006). A new method for iris recognition using gray-level coccurence matrix. Paper presented at the 2006 IEEE International Conference on Electro/Information Technology.