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A Test of the Markov Prediction Model: The Case of Isparta

Year 2022, Volume: 7 Issue: Özel Sayı, 114 - 128, 30.04.2022
https://doi.org/10.30785/mbud.1024036

Abstract

Projections and predictions of urban growth provide information that can lead to a certain level of preparedness for making cities resilient and sustainable. To ascertain the degree of confidence in predicting urban growth, this paper back-tests the Cellular Automata (CA)-Markov Prediction Model (PM) by comparing the results of the model for 2010 and 2020 with the actual land-use patterns and growth of Isparta for the same years. The data used are Landsat images for 1990, 2000, 2010, and 2020. The images were classified and used to perform the CA-Markov PM. The findings show that successive changes in land use in Isparta display average proximity to the CA-Markov PM results, with strong positive correlations of 0.8559 in 2010 and 0.8494 in 2020. It is therefore attested that amongst other models the CA-Markov PM can be used as a mathematical model for simulating urban growth in Isparta.

Thanks

The authors acknowledged the comments from anonymous reviewers. The article complies with national and international research and publication ethics. Ethics committee permission was not required for the study. This article was presented in the “IArcSAS” 1st International Architectural Science and Application Symposium on 27-29 October 2021 as an abstract. It was later expanded for this Journal.

References

  • Ajiboye, J. O. (2021). Morphological Analysis of Urban growth control and management mechanisms: Abuja, Amsterdam and Ankara cases (Unpublished Master’s thesis). Department of City and Regional Planning, Suleyman Demirel University, Isparta, Turkey.
  • Ali, H. (2009). Land Use and Land Cover Change, Drivers and Its Impact: A Comparative Study from Kuhar Michael and Lenche Dima of Blue Nile and Awash Basins of Ethiopia; Cornell University: New York, NY, USA.
  • Baqa, M.F., Chen, F., Lu, L., Qureshi, S., Tariq, A., Wang, S., Jing, L., Hamza, S. & Li, Q. (2021). Monitoring and Modeling the Patterns and Trends of Urban Growth Using Urban Sprawl Matrix and CA-Markov Model: A Case Study of Karachi, Pakistan. Land, 10, 700. Access Address (12.12.2021): https://doi.org/ 10.3390/land10070700
  • Batty, M. & Longley, P. (1994). Fractal Cities: A Geometry of Form and Function. Academic Press, London, San Diego.
  • Batty, M. (2001). Models in planning: Technological imperatives and changing roles. International Journal of Applied Earth Observation and Geoinformation, 3(3), 252-266.
  • Batty, M. (2009). Urban modeling. In: R. Kitchin and N. Thrift (eds.), International Encyclopedia of Human Geography, Elsevier Science, London, 51–58.
  • Behera, M.D., Borate, S.N., Panda, S.N., Behera, P.R. & Roy, P.S. (2012). Modeling and analyzing the watershed dynamics using Cellular Automata (CA)–Markov model – A geo-information- based approach. Journal of Earth Syst. Sci. 121, 1011–1024. Access Address (17.12.2021): https://doi.org/10.1007/s12040-012-0207-5
  • Bhatta, B. (2010). Analysis of Urban Growth and Sprawl from Remote Sensing Data. Springer, Heidelberg, 172. Access Address (02.09.2021): https://doi.org/10.1007/978-3-642-05299-6
  • Brown, D.G., Walker, R., Manson, S. & Seto, K. (2004). Modeling land use and land cover change. In: G. Gutman, B.L. Turner, Eds. Land Change Science: Observing, Monitoring and Understanding Trajectories of Change on the Earth’s Surface. Dordrecht: Kluwer, 395-409. Access Address (14.8.2021): https://Doi:10.1007/978-1-4020-2562-4_23
  • Eastman, J. R. (2012). IDRISI Selva Manual. Worcester, M.A: Clark Labs, Clark University. 322p.
  • Eren, Ş. G. (2020). Tokyo: Solaris-güneş imparatorluğu’nun dirençli, kırılgan ve tehlikeli kenti. İdealkent, 10(28), 907-941.
  • Eren, Ş. G. (2021). Sürdürülebilirlik Bağlamında Şehircilik ve Kentsel Büyüme Kavramları Üzerine Bir Analiz, Mimarlık Bilimleri ve Sürdürülebilirlik, İKSAD publishing house, Eds. Şebnem Ertaş Beşir, Meryem Bihter Bingül Bulut, İrem Bekar, 197-264. ISBN: 978-625-8061-43-7.
  • Eren, Ş. G. & Ajiboye, J. O. (2020). Isparta Bicycle Route: The Conflict between Private and Public Interests. International Congress of Architecture and Planning, Konya, Turkey (ICONARCH IV), Conference Proceedings, 759-788.
  • Fan, F., Weng, Q. & Wang, Y. (2007). Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors, 7, 1323–1342.
  • Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F.A., Coe, M.T., Daily, G.C., Gibbs, H. K., Helkowski, J.H., Holloway, T., Howard, E.A, Kucharik, C.J., Monfreda, C.,
  • Patz, J.A., Prentice, I.C., Ramakutty, N. & Snyder, P.K. (2005). Global consequences of land use. Science, 309(5734), 570-574.
  • Gashaw, T., Tulu, T., Argaw, M. & Worqlul, A.W. (2017). Evaluation and prediction of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia. Environmental Systems Research, 6(1), 17.
  • Gecena, R. & Sarpb, G. (2008). Road detection from high and low-resolution satellite images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37. 355-358.
  • Gibson, G. R. (2012). War and Agriculture: Three Decades of Agricultural Land Use and Land Cover Change in Iraq; University Libraries, Virginia Polytechnic Institute, and State University: Blacksburg, VA, USA.
  • Guan, D., Li, H., Inohae, T., Su, W., Nagaie, T. & Hokao, K. (2011). Modeling urban land-use change by the integration of cellular automaton and Markov model. Ecological Modelling. 222(20), 3761-3772. ISSN 0304-3800. Access Address (05.11.2021): https://doi.org/10.1016 /j. ecolmodel.2011.09.009.
  • Iacono, M., Levinson, D., El-Geneidy, A. & Wasfi, R. (2012). A Markov chain model of land-use change in twin cities, 1958-2005. Journal of Land Use, Mobility, and Environment. 8(3), 1-24. Access Address (10.11.2021): Doi:10.6092/1970-9870/2985
  • Jadawala, S.S., Shukla, S.H. & Tiwari, P.S. (2021). Cellular automata and Markov chain based urban growth prediction, International Journal of Environment and Geoinformatics (IJEGEO), 8(3): 337-343. doi.10.30897/ijegeo.781574
  • Jafari, M., Majedi, H., Monavari, S.M., Alesheikh, A.A. & Zarkesh, M.K. (2016). Dynamic simulation of urban expansion through a CA Markov Model Case study: Hyrcanian region, Gilan, Iran, European Journal of Remote Sensing, 49 (1), 513-529, DOI: 10.5721/EuJRS20164927
  • Kresl, P. K. (2007). Planning Cities for the Future: The Success and Failures of Urban Economic Strategies in Europe. Edward Elgar Publishing, Incorporated. ISBN: 9781847204332
  • 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. Access Address (12. 07.2021): https://doi.org/10.1371/journal.pone.0200493
  • Memarian, H., Balasundram, S.K., Talib, J.B., Sung, C.T.B., Sood, A.M. & Abbaspour, K. (2012). Validation of CA-Markov for Simulation of Land Use and Cover Change in the Langat Basin, Malaysia. Journal of Geographic Information System, 4(6), 542–54.
  • Mustafa A., Heppenstall A., Omrani H., Saadi I., Cools M. & Teller J. (2018). Modeling built-up expansion and densification with multinomial logistic regression, cellular automata, and genetic algorithm computers. Environmental Urban System. 67, 147–156. Access Address (13.11.2021): https://doi.org/10.1016/j.compenvurbsys.2017.09.009
  • Ozturk, D. (2015). Urban growth simulation of Atakum (Samsun, Turkey) using cellular automata-Markov chain and multi-layer perceptron-Markov chain models. Remote Sensing, 7(5), 5918–5950. Access Address (03.08.2021): https://doi.org/10.3390/rs70505918
  • Parsa, V. A., Yavari, A. & Nejadi, A. (2016). Spatio-temporal analysis of land use/land cover pattern changes in Arasbaran Biosphere Reserve: Iran. Modeling Earth Systems and Environment, 2, 1–13.
  • Peng, W. & Berry, E. M., (2019). The Concept of Food Security. In: Ferranti, P., Berry, E.M., Anderson, J.R. (Eds.), Encyclopedia of Food Security and Sustainability, 2, 1–7. ISBN: 9780128126875
  • Perveen, S., Kamruzzaman, M. & Yigitcanlar, T. (2017). Developing Policy Scenarios for Sustainable Urban Growth Management: A Delphi Approach. Sustainability, 9, 1787. Access Address (10.10.2021): doi:10.3390/su9101787
  • Pooyandeh, M., Mesgari, S., Alimohammadi, A. & Shad, R. (2007). A comparison between complexity and temporal GIS models for Spatio-temporal urban applications. In: O. Gervasi and M. Gavrilova (eds.), ICCSA 2007, LNCS 4706, Part II, Springer, 308–321.
  • Porter, J. R., Xie, L., Challinor, A.J., Cochrane, K., Howden, S. M., Iqbal, M. M., Lobell, D. B. & Travasso, M. I. (2014). Food security and food production systems. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL, (Eds.). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA, 485-533.
  • Raven, J., Stone, B., Mills, G., Towers, J., Katzschner, L., Leone, M., Gaborit, P., Georgescu, M. & Hariri, M. (2018). Urban planning and design. In: Rosenzweig, C., W. Solecki, P. Romero-Lankao, S. Mehrotra, S. Dhakal, and S. Ali Ibrahim (Eds.), Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network. Cambridge University Press. New York. 139–172.
  • Regmi, R., Saha, S. & Balla, M. (2014). Geospatial analysis of land use land cover changes predictive modeling at Phewa Lake Watershed of Nepal. International Journal of Current Engineering and Technology., 4(4), 2617–2627.
  • Rossiter, D. G. (2004). Technical Note: Statistical methods for accuracy assessment of classified thematic maps. Enschede (NL): International Institute for Geo-information Science and Earth Observation (ITC).
  • Santé, I., García, A. M., Miranda, D. & Crecente, R. (2010). Cellular automata models for the simulation of real urban processes: A review and analysis. Landscape and Urban Planning, 96(2), 108-122.
  • Senthilnathan, S. (2019). The usefulness of Correlation Analysis. Access Address (10.12.2021): https://ssrn.com/abstract=3416918 or http://dx.doi.org/10.2139/ssrn.3416918
  • Schubert, D. (2019) Cities, and plans – the past defines the future, Planning Perspectives, 34 (1), 3-23, Access Address (07.10.2021): DOI: 10.1080/02665433.2018.1541758
  • Singh, S. K., Mustak, S., Srivastava, P. K., Szabó, S. & Islam, T. (2015). Predicting spatial and decadal LULC changes through cellular automata Markov chain models using earth observation datasets and geo-information. Environmental Processes. 2, 61–78. Access Address (03.09.2021): https://doi.org/10.1007/s40710-015-0062-x
  • Thompson, E. M., Greenhalgh, P., Muldoon-Smith, K., Charlton, J. & Dolník, M. (2016). Planners in the Future City: Using City Information Modelling to Support Planners as Market Actors. Urban Planning, 1, 79–94. Access Address (08.08.2021): https://doi.org/10.17645/up.v1i1.556
  • Torrens, P. M. (2000). How Cellular Models of Urban Systems Work (1. Theory). Working Paper Series 28, Centre for Advanced Spatial Analysis, London, UK.
  • Türkiye Nüfusu (2021). Access Address: https://www.nufusune.com/isparta-nufusu. Access Date: (12.09.2021)
  • USGS Earth Explorer (2021). https://earthexplorer.usgs.gov/
  • Vitousek, P. M. (1994). Beyond global warming: ecology and global change. Ecology, 75(7),1861‐187.
  • Wang, L., Sousa, W. P. & Gong, P. (2004). Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery. International Journal of Remote Sensing, 25(24), 5655-5668.
  • Wu, Q., Li, H., Wang, R., Paulussen, J., He, Yong., Wang, M., Wang, B. & Wang, Z. (2006). Monitoring and predicting land-use change in Beijing using remote sensing and GIS, Landscape and Urban Planning, 78(4), 322-333. Access Address (10.11.2021): doi.org/10.1016/j.landurbplan. 2005.10.002.
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Markov Tahmin Modelinin Testi: Isparta Örneği

Year 2022, Volume: 7 Issue: Özel Sayı, 114 - 128, 30.04.2022
https://doi.org/10.30785/mbud.1024036

Abstract

Kentsel büyüme ve arazi kullanımı değişikliklerinin öngörülmesi ve tahmini, kentlerin dayanıklı ve sürdürülebilir hale getirilmesinde belirli düzeyde hazırlıklı olmayı sağlayan bilgiler sunar. Kentsel büyümeyi ve arazi kullanım değişikliklerini tahmin etmede modellerin kullanımının uygunluk düzeyini tespit etmek için bu makale, 2010 ve 2020 yılları için Hücresel Otomatlar (CA)-Markov Tahmin Modelini (PM) Isparta kentinin gerçek arazi kullanım kalıpları ve büyümesinin geriye dönük bir testini aynı yıllar için yapmaktadır. Çalışma için kullanılan veriler 1990, 2000, 2010 ve 2020 Landsat görüntüleridir. Görüntüler sınıflandırılmış ve CA-Markov PM'nin uygulamasında kullanılmıştır. Bulgular, Isparta'nın arazi kullanımındaki ardışık değişikliklerin CA-Markov PM sonuçlarıyla ortalama yakınlık derecesine ve sırasıyla 2010 yılı için 0.8559 ve 2020 yılı için 0.8494'lük güçlü bir pozitif korelasyona sahip olduğunu göstermektedir. Bu nedenle; diğer modeller arasından CA-Markov PM'nin, matematiksel bir model olarak, Isparta kentinin kentsel büyümenin simülasyonunda kullanılabileceği belirlenmiştir.

References

  • Ajiboye, J. O. (2021). Morphological Analysis of Urban growth control and management mechanisms: Abuja, Amsterdam and Ankara cases (Unpublished Master’s thesis). Department of City and Regional Planning, Suleyman Demirel University, Isparta, Turkey.
  • Ali, H. (2009). Land Use and Land Cover Change, Drivers and Its Impact: A Comparative Study from Kuhar Michael and Lenche Dima of Blue Nile and Awash Basins of Ethiopia; Cornell University: New York, NY, USA.
  • Baqa, M.F., Chen, F., Lu, L., Qureshi, S., Tariq, A., Wang, S., Jing, L., Hamza, S. & Li, Q. (2021). Monitoring and Modeling the Patterns and Trends of Urban Growth Using Urban Sprawl Matrix and CA-Markov Model: A Case Study of Karachi, Pakistan. Land, 10, 700. Access Address (12.12.2021): https://doi.org/ 10.3390/land10070700
  • Batty, M. & Longley, P. (1994). Fractal Cities: A Geometry of Form and Function. Academic Press, London, San Diego.
  • Batty, M. (2001). Models in planning: Technological imperatives and changing roles. International Journal of Applied Earth Observation and Geoinformation, 3(3), 252-266.
  • Batty, M. (2009). Urban modeling. In: R. Kitchin and N. Thrift (eds.), International Encyclopedia of Human Geography, Elsevier Science, London, 51–58.
  • Behera, M.D., Borate, S.N., Panda, S.N., Behera, P.R. & Roy, P.S. (2012). Modeling and analyzing the watershed dynamics using Cellular Automata (CA)–Markov model – A geo-information- based approach. Journal of Earth Syst. Sci. 121, 1011–1024. Access Address (17.12.2021): https://doi.org/10.1007/s12040-012-0207-5
  • Bhatta, B. (2010). Analysis of Urban Growth and Sprawl from Remote Sensing Data. Springer, Heidelberg, 172. Access Address (02.09.2021): https://doi.org/10.1007/978-3-642-05299-6
  • Brown, D.G., Walker, R., Manson, S. & Seto, K. (2004). Modeling land use and land cover change. In: G. Gutman, B.L. Turner, Eds. Land Change Science: Observing, Monitoring and Understanding Trajectories of Change on the Earth’s Surface. Dordrecht: Kluwer, 395-409. Access Address (14.8.2021): https://Doi:10.1007/978-1-4020-2562-4_23
  • Eastman, J. R. (2012). IDRISI Selva Manual. Worcester, M.A: Clark Labs, Clark University. 322p.
  • Eren, Ş. G. (2020). Tokyo: Solaris-güneş imparatorluğu’nun dirençli, kırılgan ve tehlikeli kenti. İdealkent, 10(28), 907-941.
  • Eren, Ş. G. (2021). Sürdürülebilirlik Bağlamında Şehircilik ve Kentsel Büyüme Kavramları Üzerine Bir Analiz, Mimarlık Bilimleri ve Sürdürülebilirlik, İKSAD publishing house, Eds. Şebnem Ertaş Beşir, Meryem Bihter Bingül Bulut, İrem Bekar, 197-264. ISBN: 978-625-8061-43-7.
  • Eren, Ş. G. & Ajiboye, J. O. (2020). Isparta Bicycle Route: The Conflict between Private and Public Interests. International Congress of Architecture and Planning, Konya, Turkey (ICONARCH IV), Conference Proceedings, 759-788.
  • Fan, F., Weng, Q. & Wang, Y. (2007). Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors, 7, 1323–1342.
  • Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F.A., Coe, M.T., Daily, G.C., Gibbs, H. K., Helkowski, J.H., Holloway, T., Howard, E.A, Kucharik, C.J., Monfreda, C.,
  • Patz, J.A., Prentice, I.C., Ramakutty, N. & Snyder, P.K. (2005). Global consequences of land use. Science, 309(5734), 570-574.
  • Gashaw, T., Tulu, T., Argaw, M. & Worqlul, A.W. (2017). Evaluation and prediction of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia. Environmental Systems Research, 6(1), 17.
  • Gecena, R. & Sarpb, G. (2008). Road detection from high and low-resolution satellite images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37. 355-358.
  • Gibson, G. R. (2012). War and Agriculture: Three Decades of Agricultural Land Use and Land Cover Change in Iraq; University Libraries, Virginia Polytechnic Institute, and State University: Blacksburg, VA, USA.
  • Guan, D., Li, H., Inohae, T., Su, W., Nagaie, T. & Hokao, K. (2011). Modeling urban land-use change by the integration of cellular automaton and Markov model. Ecological Modelling. 222(20), 3761-3772. ISSN 0304-3800. Access Address (05.11.2021): https://doi.org/10.1016 /j. ecolmodel.2011.09.009.
  • Iacono, M., Levinson, D., El-Geneidy, A. & Wasfi, R. (2012). A Markov chain model of land-use change in twin cities, 1958-2005. Journal of Land Use, Mobility, and Environment. 8(3), 1-24. Access Address (10.11.2021): Doi:10.6092/1970-9870/2985
  • Jadawala, S.S., Shukla, S.H. & Tiwari, P.S. (2021). Cellular automata and Markov chain based urban growth prediction, International Journal of Environment and Geoinformatics (IJEGEO), 8(3): 337-343. doi.10.30897/ijegeo.781574
  • Jafari, M., Majedi, H., Monavari, S.M., Alesheikh, A.A. & Zarkesh, M.K. (2016). Dynamic simulation of urban expansion through a CA Markov Model Case study: Hyrcanian region, Gilan, Iran, European Journal of Remote Sensing, 49 (1), 513-529, DOI: 10.5721/EuJRS20164927
  • Kresl, P. K. (2007). Planning Cities for the Future: The Success and Failures of Urban Economic Strategies in Europe. Edward Elgar Publishing, Incorporated. ISBN: 9781847204332
  • 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. Access Address (12. 07.2021): https://doi.org/10.1371/journal.pone.0200493
  • Memarian, H., Balasundram, S.K., Talib, J.B., Sung, C.T.B., Sood, A.M. & Abbaspour, K. (2012). Validation of CA-Markov for Simulation of Land Use and Cover Change in the Langat Basin, Malaysia. Journal of Geographic Information System, 4(6), 542–54.
  • Mustafa A., Heppenstall A., Omrani H., Saadi I., Cools M. & Teller J. (2018). Modeling built-up expansion and densification with multinomial logistic regression, cellular automata, and genetic algorithm computers. Environmental Urban System. 67, 147–156. Access Address (13.11.2021): https://doi.org/10.1016/j.compenvurbsys.2017.09.009
  • Ozturk, D. (2015). Urban growth simulation of Atakum (Samsun, Turkey) using cellular automata-Markov chain and multi-layer perceptron-Markov chain models. Remote Sensing, 7(5), 5918–5950. Access Address (03.08.2021): https://doi.org/10.3390/rs70505918
  • Parsa, V. A., Yavari, A. & Nejadi, A. (2016). Spatio-temporal analysis of land use/land cover pattern changes in Arasbaran Biosphere Reserve: Iran. Modeling Earth Systems and Environment, 2, 1–13.
  • Peng, W. & Berry, E. M., (2019). The Concept of Food Security. In: Ferranti, P., Berry, E.M., Anderson, J.R. (Eds.), Encyclopedia of Food Security and Sustainability, 2, 1–7. ISBN: 9780128126875
  • Perveen, S., Kamruzzaman, M. & Yigitcanlar, T. (2017). Developing Policy Scenarios for Sustainable Urban Growth Management: A Delphi Approach. Sustainability, 9, 1787. Access Address (10.10.2021): doi:10.3390/su9101787
  • Pooyandeh, M., Mesgari, S., Alimohammadi, A. & Shad, R. (2007). A comparison between complexity and temporal GIS models for Spatio-temporal urban applications. In: O. Gervasi and M. Gavrilova (eds.), ICCSA 2007, LNCS 4706, Part II, Springer, 308–321.
  • Porter, J. R., Xie, L., Challinor, A.J., Cochrane, K., Howden, S. M., Iqbal, M. M., Lobell, D. B. & Travasso, M. I. (2014). Food security and food production systems. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL, (Eds.). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA, 485-533.
  • Raven, J., Stone, B., Mills, G., Towers, J., Katzschner, L., Leone, M., Gaborit, P., Georgescu, M. & Hariri, M. (2018). Urban planning and design. In: Rosenzweig, C., W. Solecki, P. Romero-Lankao, S. Mehrotra, S. Dhakal, and S. Ali Ibrahim (Eds.), Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network. Cambridge University Press. New York. 139–172.
  • Regmi, R., Saha, S. & Balla, M. (2014). Geospatial analysis of land use land cover changes predictive modeling at Phewa Lake Watershed of Nepal. International Journal of Current Engineering and Technology., 4(4), 2617–2627.
  • Rossiter, D. G. (2004). Technical Note: Statistical methods for accuracy assessment of classified thematic maps. Enschede (NL): International Institute for Geo-information Science and Earth Observation (ITC).
  • Santé, I., García, A. M., Miranda, D. & Crecente, R. (2010). Cellular automata models for the simulation of real urban processes: A review and analysis. Landscape and Urban Planning, 96(2), 108-122.
  • Senthilnathan, S. (2019). The usefulness of Correlation Analysis. Access Address (10.12.2021): https://ssrn.com/abstract=3416918 or http://dx.doi.org/10.2139/ssrn.3416918
  • Schubert, D. (2019) Cities, and plans – the past defines the future, Planning Perspectives, 34 (1), 3-23, Access Address (07.10.2021): DOI: 10.1080/02665433.2018.1541758
  • Singh, S. K., Mustak, S., Srivastava, P. K., Szabó, S. & Islam, T. (2015). Predicting spatial and decadal LULC changes through cellular automata Markov chain models using earth observation datasets and geo-information. Environmental Processes. 2, 61–78. Access Address (03.09.2021): https://doi.org/10.1007/s40710-015-0062-x
  • Thompson, E. M., Greenhalgh, P., Muldoon-Smith, K., Charlton, J. & Dolník, M. (2016). Planners in the Future City: Using City Information Modelling to Support Planners as Market Actors. Urban Planning, 1, 79–94. Access Address (08.08.2021): https://doi.org/10.17645/up.v1i1.556
  • Torrens, P. M. (2000). How Cellular Models of Urban Systems Work (1. Theory). Working Paper Series 28, Centre for Advanced Spatial Analysis, London, UK.
  • Türkiye Nüfusu (2021). Access Address: https://www.nufusune.com/isparta-nufusu. Access Date: (12.09.2021)
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There are 50 citations in total.

Details

Primary Language English
Subjects Urban and Regional Planning, Architecture
Journal Section Research Articles
Authors

Jesugbemi Olaoye Ajiboye 0000-0002-3529-7866

Şirin Gülcen Eren 0000-0002-2038-3905

Andrew Ayangeaor Ugese This is me 0000-0001-7883-9496

Publication Date April 30, 2022
Submission Date November 16, 2021
Published in Issue Year 2022 Volume: 7 Issue: Özel Sayı

Cite

APA Ajiboye, J. O., Eren, Ş. G., & Ugese, A. A. (2022). A Test of the Markov Prediction Model: The Case of Isparta. Journal of Architectural Sciences and Applications, 7(Özel Sayı), 114-128. https://doi.org/10.30785/mbud.1024036