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ارزیابی و پیشبینی تغییرات پوشش/کاربری اراضی با استفاده از تصاویر ماهوارهای و مدل CA-Markov (موردمطالعه : منطقه 22 شهرداری تهران) | ||
| برنامه ریزی توسعه کالبدی | ||
| دوره 13، شماره 1 - شماره پیاپی 41، خرداد 1405، صفحه 15-30 اصل مقاله (1.55 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.30473/psp.2026.77866.2812 | ||
| نویسندگان | ||
| پروانه سبحانی* 1؛ افشین دانه کار2 | ||
| 1استادیار، گروه محیط زیست، دانشگاه لرستان، دانشکده منابع طبیعی، خرم آباد، ایران | ||
| 2استاد گروه محیط زیست، دانشگاه تهران، دانشکده منابع طبیعی، کرج، ایران | ||
| چکیده | ||
| تغییرات کاربری اراضی ناشی از توسعه فعالیتهای انسانی یکی از مهمترین تهدیدهای مناطق شهری به شمار میرود. ازاینرو، پژوهش حاضر با هدف بررسی روند تغییرات پوشش/کاربری اراضی منطقه ۲۲ شهرداری تهران طی دوره ۱۹۹۵ تا ۲۰۲۵ و پیشبینی الگوی تغییرات تا سال ۲۰۴۱ با استفاده از مدل ترکیبی CA–Markov انجام شد. ابتدا نقشههای پوشش/کاربری اراضی برای سالهای ۱۹۹۵ و ۲۰۲۵ تهیه و روند تغییرات کلاسهای مختلف اراضی تحلیل شد. سپس با بکارگیری مدل CA–Markov، تغییرات آینده شبیهسازی و اعتبار مدل با استفاده از ضریب کاپا ارزیابی شد. نتایج نشان داد اراضی انسانساخت از 11/2572 هکتار در سال ۱۹۹۵ به 46/2827 هکتار در سال ۲۰۲۵ افزایش یافته و بیشترین روند افزایشی را داشته است. در مقابل، اراضی بایر از 52/2780 به 8/2391 هکتار کاهش یافته است. همچنین، منابع آبی و پوششهای گیاهی روندی افزایشی و اراضی کشاورزی روند کاهشی را طی دوره مطالعه نشان میدهد. ضریب کاپای 88/0 نیز دقت مطلوب مدل را در پیشبینی تغییرات تأیید میکند. بر اساس نتایج شبیهسازی، اراضی انسانساخت تا سال ۲۰۴۱ به 4/2890 هکتار افزایش یافته و اراضی بایر به ۲۲۸۷ هکتار کاهش خواهد یافت. این روند بیانگر تداوم گسترش کاربریهای انسانساخت در سالهای آینده و تشدید فشار بر منابع سرزمینی در اثر رشد جمعیت و تمرکز فعالیتهای اقتصادی و کالبدی است. ازاینرو، کاهش پیامدهای نامطلوب تغییرات پوشش/کاربری اراضی مستلزم برنامهریزی کارآمد، مدیریت یکپارچه و بهرهبرداری پایدار از منابع سرزمینی است. یافتههای این پژوهش میتواند مبنایی برای تصمیمگیری، کنترل توسعه فعالیتهای انسانی و تدوین راهبردهای مدیریت شهری در راستای تحقق توسعه پایدار باشد. | ||
| کلیدواژهها | ||
| تغییرات مکانی-زمانی؛ پوشش/کاربری اراضی؛ دادههای سنجش از دوری؛ مدلسازی و پیشبینی؛ منطقه 22 شهرداری تهران | ||
| عنوان مقاله [English] | ||
| Assessment and prediction of land use/land cover changes using satellite images and CA-Markov model (Case study: District 22 of Tehran Municipality) | ||
| نویسندگان [English] | ||
| Parvaneh Sobhani1؛ Afshin Danehkar2 | ||
| 1Assistant Professor, Department of Environmental Science, Natural Resources Faculty, Lorestan University, Khorramabad, Iran. | ||
| 2Professor, Department of Environmental Science, Natural Resources Faculty, University of Tehran, Karaj, Iran | ||
| چکیده [English] | ||
| Introduction Land use changes driven by the expansion of human activities are among the most significant threats to urban areas. Methodology Accordingly, this study investigated the spatiotemporal dynamics of land cover/land use (LULC) changes in Tehran Municipality District 22 during 1995–2025 and predicted future change patterns up to 2041 using the integrated Cellular Automata–Markov (CA–Markov) model. LULC maps were produced for 1995 and 2025, and temporal changes in different land-use classes were analyzed. The CA–Markov model was then applied to simulate future land-use changes, and its performance was evaluated using the Kappa coefficient. Results The results indicated that built-up areas exhibited the greatest increase, expanding from 2,572.11 ha in 1995 to 2,827.46 ha in 2025. In contrast, bare areas declined from 2,780.52 ha to 2,391.80 ha during the same period. Water areas and vegetation cover showed increasing trends, whereas agricultural areas continuously decreased throughout the study period. A Kappa coefficient of 0.88 confirmed the high predictive accuracy of the CA–Markov model. According to the simulation results, built-up areas are projected to increase to 2,890.40 ha by 2041, while bare areas are expected to decline to 2,287 ha. Discussion and Conclusion These findings indicate the continued expansion of built-up areas, increasing pressure on land resources due to population growth and the concentration of economic and urban development activities. Therefore, mitigating the adverse impacts of LULC change requires effective planning, integrated land management, and sustainable resource utilization. The findings provide a scientific basis for decision-making and urban management strategies to support sustainable urban development. | ||
| کلیدواژهها [English] | ||
| Spatial-temporal changes, Land use/ land cover, Remote sensing data, Modeling and prediction, District 22 of Tehran Municipality | ||
| مراجع | ||
|
Aslami, F., Ghorbani, A., Sobhani, B. & Panahandeh, M. (2015). Comparing artificial neural network, support vector machine and object-based methods in preparation land use/cover mapsusing landSat-8 images, Journal of RS and GIS Techniques in Natural Resources, 6(3), 1-14. https://doi.org/10.1007/s44274-024-00008-6
Awewomom, J., Dzeble, F., Takyi, Y. D., Ashie, W. B., Ettey, E. N. Y. O., Afua, P. E., & Akoto, O. (2024). Addressing global environmental pollution using environmental control techniques: a focus on environmental policy and preventive environmental management. Discover Environment, 2(1), 8. https://doi.org/10.1024/32274-674-0079-10
Bikis, A., Engdaw, M., Pandey, D., & Pandey, B. K. (2025). The impact of urbanization on land use land cover change using geographic information system and remote sensing: a case of Mizan Aman City Southwest Ethiopia. Scientific Reports, 15(1), 12014. https://doi.org/10.1038/s41598-025-96639-1
Danehkar, A., & Sobhani, P. (2024). Ecological potential evaluation and balance measurement of macro-land use in the urban set of Tehran-Alborz. Geographical planning of space quarterly journal, 14(4), 37-57. (In Persian). https://doi.org/10.30488/gps.2024.466071.3759
Duan, X., Haseeb, M., Tahir, Z., Mahmood, S. A., & Tariq, A. (2025). Analyzing and predicting land use and land cover dynamics using multispectral high-resolution imagery and hybrid CA-Markov modeling. Land use policy, 157, 107655. https://doi.org/10.1016/j.landusepol.2025.107655
Forotan, S., Shariat, M., Kheir Khah Zarkesh, M. M., & Sarvar, R. (2020). Investigating the trend of land use changes in Rey city using remote sensing data. Research and Technology of Environment, 5(7), 55–65. (In Persian) https://doi.org/10.1016/j.landusepol.2025.107655
Gabisa, M., Kabite, G., & Mammo, S. (2025). Land use and land cover change trends, drivers and its impacts on ecosystem services in burayu sub city, Ethiopia. Frontiers in Environmental Science, 13, 1557000. https://doi.org/ 10.3389/fenvs.2025.1557000
Ghodousi, V., Nazam Far, H., & Rahmati, M. (2025). Land use changes and simulation of urban growth and development (Case study: Ardabil city). Journal of Sustainable Urban and Regional Development Studies, 6(3), 168–185. (In Persian) https://www.srds.ir/article_215756.html?lang=en
Huang, X., Wang, H., & Xiao, F. (2022). Simulating urban growth affected by national and regional land use policies: Case study from Wuhan, China. Land use policy: The International Journal Covering All Aspects of Land Use, (112), 71. https://doi.org/10.1016/j.landusepol.2021.105850
Ibarra-Bonilla, J. S., Villarreal-Guerrero, F., Prieto-Amparán, J. A., Santellano-Estrada, E., & Pinedo-Alvarez, A. (2021). Characterizing the impact of Land-Use/Land-Cover changes on a Temperate Forest using the Markov model. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 1013-1022. https://doi.org/10.1016/j.ejrs.2021.08.003
Kalfas, D., Kalogiannidis, S., Chatzitheodoridis, F., & Toska, E. (2023). Urbanization and land use planning for achieving the sustainable development goals (SDGs): A case study of Greece. Urban Science, 7(2), 43. https://doi.org/10.3390/urbansci7020043
Khan, A. R., Khan, A., Masud, S., & Rahman, R. M. (2021). Analyzing the Land Cover Change and Degradation in Sundarbans Mangrove Forest Using Machine Learning and Remote Sensing Technique. In Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part II 16 (pp. 429-438). Springer International Publishing. https://doi.org/10.1007/978-3-030-85099-9_35
Khazai, A., Abbaspour, M., BabeiKafaki, S., Taghavi, L., & Rashidi, Y. (2023). Investigating and predicting land use changes in the metropolis of Tehran using remote sensing technology. New Environmental Sciences, 21(2), 121–138. (In Persian) https://doi.org/10.48308/ENVS.2022.1226
Lidicker Jr, W. Z. (2020). A Scientist’s Warning to humanity on human population growth. Global Ecology and Conservation, 24, e01232. https://doi.org/10.1016/j.gecco.2020.e01232
Parizadi, T., Shamaei, A., & Khodabakhshi, S. F. (2024). Analyzing the structural-spatial transformations of Tehran’s hinterland and its future (Case study: Hinterland of District 22 of Tehran Municipality). Researches in Applied Geographical Sciences, 75(24), 330–352. (In Persian) https://doi.org/10.61186/jgs.24.75.24
Planning and Compilation of Provincial Spatial Planning Project. (2009). Tehran Province Planning Deputy. 1–73. (In Persian)
Raihan, A., & Tuspekova, A. (2022). Dynamic impacts of economic growth, energy use, urbanization, agricultural productivity, and forested area on carbon emissions: New insights from Kazakhstan. World Development Sustainability, 1, 100019. https://doi.org/10.1016/j.wds.2022.100019
Rana, M. S., & Sarkar, S. (2021). Prediction of urban expansion by using land cover change detection approach. Heliyon, 7(11). https://doi.org/10.1016/j.heliyon.2021.e08202
Saik, P., Koshkalda, I., Bezuhla, L., Stoiko, N., & Riasnianska, A. (2024). Achieving land degradation neutrality: land-use planning and ecosystem approach. Frontiers in Environmental Science, 12, 1446056. https://doi.org/10.3389/fenvs.2024.1446056
Saleem, A., Anwar, S., Nawaz, T., Fahad, S., Saud, S., Ur Rahman, T., & Nawaz, T. (2025). Securing a sustainable future: the climate change threat to agriculture, food security, and sustainable development goals. Journal of Umm Al-Qura University for Applied Sciences, 11(3), 595-611. https://doi.org/ 10.1007/s43994-025-00112-5
Sang, L., Zhang, C., Yang, J., Zhu, D. &Yun, W. (2011). Simulation of land use spatial pattern of towns and villages based on CA-Markov model, Mathematical and Computer Modelling, 54(4), 938-943. https://doi.org/10.1016/j.mcm.2010.11.019
Satari, M. H., Sarvar, R., & Mahdavi, M. (2023). Analysis and evaluation of environmental impacts of urban land use changes in the Tehran metropolis region. Journal of Geographical Studies of Arid Regions, 14(15), 60–81. (In Persian) https://doi.org/10.22034/jargs.2023.376032.1001
Setiawan, O., Rahayu, A. A. D., Samawandana, G., Tata, H. L., Dharmawan, I. W. S., Rachmat, H. H., & Khotimah, H. (2024). Unraveling land use land cover change, their driving factors, and implication on carbon storage through an integrated modelling approach. The Egyptian Journal of Remote Sensing and Space Sciences, 27(4), 615-627. https://doi.org/10.1016/j.ejrs.2024.09.005
Shivanna, K. R. (2022). Climate change and its impact on biodiversity and human welfare. Proceedings of the Indian National Science Academy, 88(2), 160-171. https://doi.org/ 10.1007/s43538-022-00073-6
Sobhani, P. (2024). Urban development impacts on natural ecosystems in urban protected areas of Tehran province, Iran. Heliyon, 10 (2024) e40572. https://doi.org/10.1016/j.heliyon.2024.e40572
Sobhani, P., & Danehkar, A. (2024). Modeling and predicting land use changes using the hybrid CA-ANN model in the mangrove forests of Khamir and Qeshm. Iranian Remote Sensing and GIS, 16(4), 95–114. (In Persian). https://doi.org/10.48308/GISJ.2024.233850.1189
Sobhani, P., & Danehkar, A. (2025). Analysis of the Ecological Network Structure and Continuity of Biological Function in the Tehran-Alborz Urban Complex. Quarterly Journal of Urban and Regional Development Planning, 10(33), 217-241. (In Persian). https://doi.org/10.22054/urdp.2025.83888.1685
Sobhani, P., & Danehkar, A. (2026). Urban Sustainable Development Strategies in the Tehran-Alborz Region. Journal of Sustainable Urban & Regional Development Studies (JSURDS), 7(3), 52-71. (In Persian). https://www.srds.ir/article_243680_en.html
Sobhani, P., Esmaeilzadeh, H., & Mostafavi, H. (2021). Simulation and impact assessment of future land use and land cover changes in two protected areas in Tehran, Iran. Sustainable Cities and Society, 75, 103296. https://doi.org/10.1016/j.scs.2021.103296
Tal, A. (2025). The environmental impacts of overpopulation. Encyclopedia, 5(2), 45. https://doi.org/ 10.3390/encyclopedia5020045
Taloor, A. K., Sharma, S., Parsad, G., & Jasrotia, R. (2024). Land use land cover simulations using integrated CA-Markov model in the Tawi Basin of Jammu and Kashmir India. Geosystems and Geoenvironment, 3(2), 100268. https://doi.org/10.1016/j.geogeo.2024.100268
Tehran Metropolitan Area and Surrounding Cities Project. (1999). Center for Urban and Architectural Studies and Research. 1–89. (In Persian)
Waśniewski, A., Hościło, A., & Aune-Lundberg, L. (2023). The impact of selection of reference samples and DEM on the accuracy of land cover classification based on Sentinel-2 data. Remote Sensing Applications: Society and Environment, 32, 101035. https://doi.org/10.1016/j.rsase.2023.101035
Zafar, Z., Zubair, M., Zha, Y., Fahd, S., & Nadeem, A. A. (2024). Performance assessment of machine learning algorithms for mapping of land use/land cover using remote sensing data. The Egyptian Journal of Remote Sensing and Space Sciences, 27(2), 216-226. https://doi.org/10.1016/j.ejrs.2024.02.004 | ||
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