An assessment of physical development prediction in Shiraz (Iran) and its relationship with geomorphological factors
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Abstract
The development of cities and their environmental impacts have adverse consequences. However, it is possible to move toward sustainable development through knowledge and awareness of the urban areas, investigation, application, and optimal use of modern technologies and sciences. The current study examined the land-use changes of the city of Shiraz using remote sensing (RS) and geographical information system (GIS) to estimate the increase in the urban area, the reduction in agricultural and horticultural lands, the abuse of rangelands, and unauthorized construction in mountainous areas during 2000-2018. City development was determined in the time interval of 2025 using the maximum likelihood algorithm, supervised method, and Markov chain model. The relationship between land use and geomorphological factors was examined using the OLS method, the results of which showed an increase in the area of built-in land use and a decrease in the area of barren and agricultural lands in Shiraz during 2000-2018. Over the 7-year period, the area of built-in (36%), horticultural and agricultural (11%), barren (19%), and rangeland (46%) land use will change. According to the output of the OLS method, distance from the fault and distance from the channel had the highest impact on urban development risk compared to other parameters with the probability of 83% and 72% and error of 0.007 and 0.008, respectively.
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References
Farid, Y. (1996). New Attitudes in the Context of Urban Geography. Journal of Geographical Research, Tehran, 33, 5-14.
Seif al-Dini, F. (2002). A dictionary of urban and regional planning. Shiraz, Iran: Shiraz University Pres 1-507.
Chengtai D. (1999). Urban geomorphology in Chinese, 391.
Abedini, M., & Moghimi, E. (2012). the role of geomorphological bottlenecks in the physical development of metropolis of Tabriz for optimal use. Geography and environmental planning, 23(1), 147-166.
Bullard, R. D., Johnson, G.S., & Torres, A.O. (2000). Sprawl City: Race, Politics, and Planning in Atlanta, Island Press, Island, Washington, DC.
Herold, M., Goldstein, N. C., & Clarke, K. C. (2003). The spatiotemporal form of urban growth: measurement, analysis and modeling. Remote sensing of Environment, 86(3), 286-302.
Nasiri, A., Shirocova, V. A., & Zareie, S. (2019). Zoning of groundwater quality for plain Garmsar in Iran. Water Resources, 46(4), 624-629. https://doi.org/10.1134/S009780781904002X
Nasiri, A., Shafiei, N., & Farzin Kia, R. (2021). Investigation of Fahlian aquifer subsidence and its effect on groundwater loss. Arabian Journal of Geosciences, 14(7), 1-12. https://doi.org/10.1007/s12517-021-06917-7
Alansi, A. W., Amin, M. S. M., Halim, G. A., Shafri, H. Z. M., Thamer, A. M., Waleed, A. R. M., ... & Ezrin, M. H. (2009). The effect of development and land use change on rainfall-runoff and runoff-sediment relationships under humid tropical condition: Case study of Bernam watershed Malaysia. European Journal of Scientific Research, 31(1), 88-105. http://psasir.upm.edu.my/id/eprint/17077
Guan, D., Gao, W., Watari, K., & Fukahori, H. (2008). Land use change of Kitakyushu based on landscape ecology and Markov model. Journal of Geographical Sciences, 18(4), 455-468. https://doi.org/10.1007/s11442-008-0455-0
Václavík, T., & Rogan, J. (2009). Identifying trends in land use/land cover changes in the context of post-socialist transformation in central Europe: a case study of the greater Olomouc region, Czech Republic. GIScience & Remote Sensing, 46(1), 54-76. https://doi.org/10.2747/1548-1603.46.1.54
Tiwari, K., & Khanduri, K. (2011). Land use/land cover change detection in Doon valley (Dehradun tehsil), Uttarakhand: using GIS & Remote sensing technique. International journal of Geomatics and Geosciences, 2(1), 34-41.
Sarwar, M. I., Billa, M., & Paul, A. (2016). Urban land use change analysis using RS and GIS in Sulakbahar ward in Chittagong city, Bangladesh. International Journal of Geomatics and Geosciences, 7, 1-10.
de Oliveira Silveira, E. M., de Menezes, M. D., Júnior, F. W. A., Terra, M. C. N. S., & de Mello, J. M. (2017). Assessment of geostatistical features for object-based image classification of contrasted landscape vegetation cover. Journal of Applied Remote Sensing, 11(3), 036004. https://doi.org/10.1117/1.JRS.11.036004.
Huo, L. Z., Boschetti, L., & Sparks, A. M. (2019). Object-based classification of forest disturbance types in the conterminous United States. Remote Sensing, 11(5), 477. https://doi.org/10.3390/rs11050477.
Fan, F., Wang, Y., & Wang, Z. (2008). Temporal and spatial change detecting (1998–2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images. Environmental monitoring and assessment, 137(1), 127-147. https://doi.org/10.1007/s10661-007-9734-y
Erfanian, M., Hossein, K. M., Alijanpour, A. (2013). Introduction to OLS and GWR Multivariate Regression Methods in Spatial Modeling of Land Use Effects on Water Quality. Journal of Watershed Management Promotion and Development, 1(1).