Spatiotemporal analysis of urban sprawling using change detection: a case study of Shaki district, Azerbaijan
Abstract
Introduction. The contemporary globalized world characterizes the rapid population growth, its significant concentration in cities, and an increase in the urban population. Currently, many socio-cultural, economic, environmental, and other challenges are arising in modern cities. Cities are therefore emerging from the common understanding and displaying new characteristics: reduced density, dispersed development, poor accessibility and monofunction. However, the concentration of population in cities also brings its own set of issues.
The purpose of article. The purpose of the study was to identify Shaki City's urban development process, and how its land use has evolved over time. It examines the population growth in the region and the increase in the specific weight of the urban population between 2016 and 2023, analyzing the population growth trend over a 20-year period. The direction and extent of urban land use has been studied by determining the relationship between the growth rate of the urban population and the extension of the urban area, and by analyzing the changes which have occurred during the period of land use.
Research methods. Statistical data has also been used for this purpose, together with data from the Azersky satellite. Machine Learning (ML), which is widely used in remote sensing systems, was applied, Support Vector Machine Learning (SVM), and image classification and processing were performed. On the basis of the obtained data, a comparative analysis of the previous and current conditions was carried out and the area of changes in the area between the classified areas was calculated. Simultaneously, the changes between categories during the use of the area and the recent changes in the direction of land use were shown. Classification performance has been assessed, user and producer accuracies have been determined and kappas have been calculated.
Main findings. The increase in the population of the Shaki district led to an increase in the specific weight of the urban population and the extension of the town to the south and south-east where the population previously lived sparsely. It is mainly due to construction of new housing estates in region, as well as construction of a central clinic, an ASAN service, and a regional education division. A 'flight to the centre' was observed, resulting in noticeable changes in the land use structure between 2016 and 2022, in line with the growth rate of urbanisation and economic development. The decoding of the distribution images of the region shows that there has been an increase in the area of settlements over the six-year period. By 2016, settlements cover 22.4 per cent of the city, and by 2022, the figure rises to 39 per cent. From 34% to 32.9%, the total area of forest reserves decreased.
Scientific novelty and practical value The article describes for the first time the urban sprawling and territorial transformations in Shaki district in the context of population growth by using change detection analyses. The practical value of the study is the possibility of using its algorithm and method to conduct similar studies in other cities of Azerbaijan. The results of the study are significant in the context of justifying regional measures to adapt urban expansion to population growth.
Downloads
References
Anderson, W.P.; Kanaroglou, P.S.; Miller, E.J. (1996). Urban Form, Energy and the Environment: A Review of Issues, Evidence and Policy. Urban Stud., 33, 7–35. [CrossRef].
Artunov, N. (2023). Remote Sensing Study of the Impact of Social-Economic Development on The Scale of Land Use in The Shaki District.International Journal of Social Science, Education, Communication and Economics (SINOMICS JOURNAL), 2(1), 27–40. https://doi.org/10.54443/sj.v2i1.110
Bayramov, E. B. (2016). Quantitative assessment of 2014–2015 land-cover changes in Azerbaijan using object-based classification of LANDSAT-8 time series. Model. Earth Syst. Environ. 2, 35. https://doi.org/10.1007/s40808-016-0088-8
Brears (2018). Natural Resource Management and the Circular Economy, Palgrave Studies in Natural Resource Management, XVI, 349, https://doi.org/10.1007/978-3-319-71888-0
Carruthers, J. (2002). The Impacts of State Growth Management Programmes: A Comparative Analysis. Urban Stud., 39, 1959–1982. [CrossRef]
Das, S.; Angadi, D.P. (2021). Assessment of urban sprawl using landscape metrics and Shannon’s entropy model approach in town level of Barrackpore sub-divisional region, India. Modeling Earth Syst. Environ., 7, 1071–1095. [CrossRef]
Demographic indicators of Azerbaijan (2023) Statistical Review, Baku, p 560, in Azerbaijan Azərbaycanın demoqrafik göstəriciləri. Statistik məcmuə, 560. https://www.stat.gov.az/source/demoqraphy/
Domingo, D.; Palka, G.; Hersperger, A.M. (2021). Effect of zoning plans on urban land-use change: A multi-scenario simulation forsupporting sustainable urban growth. Sustain. Cities Soc., 69, 102833. [CrossRef]
Efendiyev V., Nagiyev S. (2016). Geourbanistics, textbook for higher schools, "Baku University" publishing house, page 272. Baku /Əfəndiyev V., Nağıyev S. (2016). Geourbanistika, Ali məktəblər üçün dərslik, "Bakı Universiteti" nəşriyyatı, səh 272. Bakı [in Azerbaijan]
Efendiyev V.A. (2002). Urbanization and urban settlements in Azerbaijan, Baku, Baku University. 395. Əfəndiyev V.Ə. Urbanizasiya və Azərbaycanda şəhər yaşayış məntəqələri, Bakı, Bakı Universiteti. 395. [in Azerbaijan]
Ewing, R.; Pendall, R.; Chen, D. (2002). Measuring Sprawl and Its Impact; Smart Growth America: Washington, DC, USA.
Fan, J.; Zhou, L. (2019). Three-dimensional intergovernmental competition and urban sprawl: Evidence from Chinese prefectural-level cities. Land Use Policy, 87, 104035. [CrossRef]
Fitawok, M.B.; Derudder, B.; Minale, A.S.; Van Passel, S.; Adgo, E.; Nyssen, J. (2020). Modeling the Impact of Urbanization on Land-Use Change in Bahir Dar City, Ethiopia: An Integrated Cellular Automata–Markov Chain Approach. Land, 9, 115.
Gavrilidis, A.A.; Nit,a, M.R.; Onose, D.A.; Badiu, D.L.; Nastase, I.I. (2019). Methodological framework for urban sprawl control through sustainable planning of urban green infrastructure. Ecol. Indic., 96, 67–78.
Guan, D.; He, X.; He, C.; Cheng, L.; Qu, S. (2020). Does the urban sprawl matter in Yangtze River Economic Belt, China? An integrated analysis with urban sprawl index and one scenario analysis model. Cities , 99, 102611.
Guite, L. (2019). Assessment of urban sprawl in Bathinda city, India. J. Urban Manag., 8, 195–205 [CrossRef].
İsmatova K (2005) Integration of geoinformation model with satellite remote sensing data for land cover mapping. In: Proceedings of the 31st international symposium on remote sensing of environment. Global monitoring for sustainability and security, Azerbaijan, Saint Petersburg, 20–24 May 2005.
Jensen, J.R. (1996) Introductory Digital Image Processing: A Remote Sensing Perspective. 2nd Edition, Prentice Hall, Inc., Upper Saddle River, NJ.
Landis, J.R. and Koch, G.G. (1977). A One-Way Components of Variance Model for Categorical Data. Biometrics, 33, 671-679. https://doi.org/10.2307/2529465
Liping C, Yujun S, Saeed S . (2018). Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China. PLoS ONE 13(7): e0200493. https://doi.org/10.1371/journal.pone.0200493.
Manakos I, Braun M (eds) (2014) Land use land cover mapping in Europe. Praxis and trends. Series: remote sensing and digital image processing, 18, 441. 112 illus., 79 illus. in color. Springer. Access via Springer
Mansour, S.; Al-Belushi, M.; Al-Awadhi. (2020). T. Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques. Land Use Policy, 91, 104414. [CrossRef].
Morar, C., Lukić, T., Valjarević, A., Niemets, L., Kostrikov, S., Sehida, K., Telebienieva, I., Kliuchko, L., Kobylin, P., & Kravchenko, K. (2022). Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine. Frontiers in Environmental Science, 10, 823129. https://doi.org/10.3389/fenvs.2022.823129
Menzori, I.D.; Sousa, I.C.N.d.; Gonçalves, L.M. (2021). Urban growth management and territorial governance approaches: A master plans conformance analysis. Land Use Policy, 105, 105436.
Niemets, K., Kravchenko, K., Kandyba, Y., Kobylin, P., & Morar, C. (2021). World cities in terms of the sustainable development concept. Geography and Sustainability, 2(4), 304-311. https://doi.org/10.1016/j.geosus.2021.12.003
Pashayev N.A, Ayyubov N.H, Eminov, Z.N. (2010). Economic, social and political geography of the Republic of Azerbaijan, Baku, . 410.//Paşayev N.Ə, Əyyubov N.H, Eminov,Z.N. (2010). Azərbaycan Respublikasının iqtisadi, sosial və siyasi coğrafiyası, Bakı, 410 [in Azerbaijan]
Rwanga, S.S. and Ndambuki, J.M. (2017). Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS. International Journal of Geosciences, 8, 611-622. https://doi.org/10.4236/ijg.2017.84033
Socio-economic development of regions. (2021), Statistical collection, Baku, 728. Regionların sosial-iqtisadi inkişafı. Statistik məcmuə, 728. [in Azerbaijan] https://www.stat.gov.az/source/regions/
Tan, R.; Zhang, T.; Liu, D.; Xu, H. (2021). How will innovation-driven development policy affect sustainable urban land use: Evidencefrom 230 Chinese cities. Sustain. Cities Soc., 72, 103021.
Torrens, P. (2008). A Toolkit for Measuring Sprawl. Appl. Spat. Anal. Policy, 1, 5–36. [CrossRef].
Wang, X.; Shi, R.; Zhou, Y. (2020). Dynamics of urban sprawl and sustainable development in China. Socio-Econ. Plan. Sci., 70, 100736. [CrossRef].
Wassie, S. (2020). Natural resource degradation tendencies in Ethiopia: a review. Environ Syst Res 9, 33. https://doi.org/10.1186/s40068-020-00194-1.
Whyte, W. (1958). The Exploding Metropolis; Doubleday: Garden City, NY, USA.
Zhou, D.; Li, Z.; Wang, S.; Tian, Y.; Zhang, Y.; Jiang, G. (2021). How does the newly urban residential built-up density differ across Chinese cities under rapid urban expansion? Evidence from residential FAR and statistical data from 2007 to 2016. Land Use Polic.
This work is licensed under a Creative Commons Attribution 4.0 International License.
