Evaluating and predicting land use changes (Case study: Lahijan City)

Document Type : Research article

Authors

1 Faculty Member

2 دانشگاه پیام نور تهران

3 دانشگاه گیلان

Abstract

In recent years, land use changes in different cities of Iran have caused problems such as rising earth temperatures, environmental pollution, declining agricultural lands, and so on. The increasing population of urban dwellers in Lahijan in recent decades has caused land use changes, and assessment of these changes in recent decades and predicting future changes is a necessity of the present study. By using remote sensing technology, the extent of land use changes can be examined. In this study, satellite images of Lahijan city from USGS site by using Landsat 5-TM satellite in May 1999, 2008 and Landsat 8-OLI satellite in May 2018, at intervals of about 10 years, have been prepared. Classification of satellite images has been done by using clustering method in GIS software. Then, the raster images are converted to vector images to calculate the cluster’s area. Finally, the forecast for land use changes in 2028 was done using the Markov chain model in TerrSet software. The comparison of the area of land cover and built environment areas in Markov's forecast for 2028 shows a significant increase in built environment compared to natural environment with land cover. The forecast shows that the area of built environment in Lahijan in 2028 is 1329 hectares and the area of land cover is 87 hectares.

Keywords


ابراهیمی، حمید، رسولی، علی‌اکبر و احمد احمدپور (1396). «مدل‌سازی تغییرات دینامیک کاربری اراضی با استفاده از پردازش شیء‌گرای تصاویر ماهواره‌ای و مدل CA-Markov (مطالعة موردی: شهر شیراز)»، فصلنامة علمی-پژوهشی اطلاعات جغرافیایی، شمارة 108، صص 137-149.
آذری، مهدی (1390). مدل‌سازی گسترش فیزیکی شهرها جهت نیل به توسعة پایدار شهری با استفاده از سلول‌های خودکار (مطالعة موردی شهر مراغه) پایان‌نامة کارشناسی‌ارشد رشتة جغرافیا و برنامه‌ریزی شهری، استاد راهنما: محسن احدنژاد، زنجان: دانشگاه زنجان.
خواجه برج‌سفیدی، آرمان و علی سلطانی (1392). «شبیه‌سازی و تحلیل الگوی رشد شهری کلان‌شهر اهواز با استفاده از مدل ترکیبی مارکوف-سلول‌های خودکار (Marcov-CA)»، صفه، شمارة 62، صص 63-76.
دژکام، صادق، جباریان امیری، بهمن و علی‌اصغر درویش‌صفت (1394). «پیش‌بینی تغییرات کاربری و پوشش زمین در شهرستان رشت با استفاده از مدل سلول‌های خودکار و زنجیرة مارکوف»، پژوهش‌های محیط‌زیست، شمارة 11، صص 193-204.
رمضانی نفیسه و جعفری رضا (1393). «آشکارسازی تغییرات کاربری و پوشش اراضی در افق ۱۴۰۴ با استفاده از مدل زنجیره ای CA مارکوف (مطالعه موردی: اسفراین)»، فصلنامه تحقیقات جغرافیایی، دوره 29، شماره 4، صص 83-96.
صادقیان، عماد و سید زین‌العابدین حسینی (1394). بررسی و پیش‌بینی تغییرات پوشش و کاربری اراضی با استفاده از مدل سلول‌های خودکار مارکوف، اولین همایش علمی-پژوهشی افق‌های نوین در علوم جغرافیا و برنامه‌ریزی، معماری و شهرسازی ایران، انجمن علمی توسعه و ترویج علوم و فنون بنیادین، تهران.
عزیزی، اصغر، افراخته، حسن و فرهاد عزیزپور (1397). «تحلیلی بر تزاحم فضایی در ناحیة گردشگری روستایی برغان»، نشریة تحلیلفضاییمخاطراتمحیطی، شمارة 4، صص 1-20.
Alexander, P., Rounsevell, M. D., Dislich, C., Dodson, J. R., Engström, K., & Moran, D. (2015). Drivers for Global Agricultural Land Use Change: The Nexus of Diet, Population, Yield and Bioenergy. Global Environmental Change35, 138-147.
Al-Sharif, A. A., & Pradhan, B. (2014). Monitoring and Predicting Land Use Change in Tripoli Metropolitan City Using an Integrated Markov Chain and Cellular Automata Models in GIS. Arabian Journal of Geosciences7(10), 4291-4301.
Arsanjani, J. J., Helbich, M., Kainz, W., & Boloorani, A. D. (2013). Integration of Logistic Regression, Markov Chain and Cellular Automata Models to Simulate Urban Expansion. International Journal of Applied Earth Observation and Geoinformation21, 265-275.
Azari, M. (2012). Modeling the Physical Expansion of Cities to Achieve Sustainable Urban Development Using Cellular Automata (Case Study of Maragheh City) (Master's Thesis in Geography and Urban Planning). Supervisor: Ahadnejad, M., Zanjan: Zanjan University. (In Persian)
Azizi, A., Afrakhteh, H., & Azizpour, F. (2018). An Analysis of Spatial Conflict in Borgan Rural Tourism Area. Journal of Spatial Analysis of Environmental Hazards, 5(4), 1-20. https://doi.org/10.29252/jsaeh.5.4.1. (In Persian)
Das, M., & Ghosh, S. K. (2017). Measuring Moran's I in a Cost-Efficient Manner to Describe a Land-Cover Change Pattern in Large-Scale Remote Sensing Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing10(6), 2631-2639.
Dejkam, S., Jabarian, A. B., & Darvish Sefat, A. A. (2015). Predicting Land Use Change and Land Cover in Rasht City Using Automatic Cell Model and Markov Chain. Environmental Researches, 6(11), 193-204. (In Persian)
Ebrahimy, H., Rasuly, A., & Ahmadpour, A. (2019). Modeling Dynamic Changes of Land Use with Object Based Image Analysis and CA-Markov Approach (Case Study: Shiraz City). Scientific- Research Quarterly of Geographical Data (SEPEHR), 27(108), 137-149. https://doi.org/10.22131/sepehr.2019.34625. (In Persian)
Fu, P., & Weng, Q. (2016). A Time Series Analysis af Urbanization Induced Land Use and Land Cover Change and Its Impact on Land Surface Temperature with Landsat Imagery. Remote Sensing of Environment175, 205-214.
Gašparović, M., Zrinjski, M., & Gudelj, M. (2019). Automatic Cost-Effective Method for Land Cover Classification (ALCC). Computers, Environment and Urban Systems76, 1-10.
Halmy, M. W. A., Gessler, P. E., Hicke, J. A., & Salem, B. B. (2015). Land Use/Land Cover Change Detection and Prediction in the North-Western Coastal Desert of Egypt Using Markov-CA. Applied Geography63, 101-112.
Hamad, R., Balzter, H., & Kolo, K. (2018). Predicting Land Use/Land Cover Changes Using a CA-Markov Model Under Two Different Scenarios. Sustainability10(10), 3421.
Huang, J., Wu, Y., Gao, T., Zhan, Y., & Cui, W. (2015). An Integrated Approach Based on Markov Chain and Cellular Automata to Simulation of Urban Land Use Changes. Applied Mathematics & Information Sciences9(2), 1-7.
Keesstra, S., Nunes, J., Novara, A., Finger, D., Avelar, D., Kalantari, Z., & Cerdà, A. (2018). The Superior Effect of Nature Based Solutions in Land Management for Enhancing Ecosystem Services. Science of the Total Environment610, 997-1009.
Khajeh Borj Sefidi, A., & Soltani, A. (2013), Simulation and Analysis of Ahvaz Metropolitan’s Urban Growth Pattern Using Combined Model of Markov Chain and Cellular Automata (Marcov-CA). Sofeh, 62, 63-76. (In Persian)
Khawaldah, H. A. (2016). A Prediction of Future Land Use/Land Cover in Amman Area Using GIS-Based Markov Model and Remote Sensing. Journal of Geographic Information System8(3), 412-427.
Liu, X., Liang, X., Li, X., Xu, X., Ou, J., Chen, Y., ... & Pei, F. (2017). A Future Land Use Simulation Model (FLUS) for Simulating Multiple Land Use Scenarios by Coupling Human and Natural Effects. Landscape and Urban Planning168, 94-116.
Mantyka-Pringle, C. S., Visconti, P., Di Marco, M., Martin, T. G., Rondinini, C., & Rhodes, J. R. (2015). Climate Change Modifies Risk of Global Biodiversity Loss Due to Land-Cover Change. Biological Conservation187, 103-111.
Mas, J. F., Kolb, M., Paegelow, M., Olmedo, M. C., & Houet, T. (2014). Modelling Land Use/Cover Changes: A Comparison of Conceptual Approaches and Softwares. https://doi.org/10.1016/j.envsoft.2013.09.010.
Myint, S. W., & Wang, L. (2006). Multicriteria Decision Approach for Land Use Land Cover Change Using Markov Chain Analysis and a Cellular Automata Approach. Canadian Journal of Remote Sensing32(6), 390-404.
Newbold, T., Hudson, L. N., Hill, S. L., Contu, S., Lysenko, I., Senior, R. A., ..., & Day, J. (2015). Global Effects of Land Use on Local Terrestrial Biodiversity. Nature520(7545), 45-50.
Ramezani, N. &  Jafari, R. (2014). Land use/cover change detection in 2025 with CA-Markov chain model (case study: Esfarayen). Geographical Research, 29(4), 83-96.
Razavi, B. S. (2014). Predicting the Trend of Land Use Changes Using Artificial Neural Network and Markov Chain Model (Case Study: Kermanshah City). Research Journal of Environmental and Earth Sciences6(4), 215-226.
Rimal, B., Zhang, L., Keshtkar, H., Haack, B., Rijal, S., & Zhang, P. (2018). Land Use/Land Cover Dynamics and Modeling of Urban Land Expansion by the Integration of Cellular Automata and Markov Chain. ISPRS International Journal of Geo-Information7(4), 154.
Sadeghian, E., & Hosseini, S. Z. A. A. (2015). Study and Prediction of Land Change and Land Use Changes Using Markov Automated Cell Models. First Scientific Research Conference on New Horizons in Geography and Planning, Architecture and Urban Planning, Scientific Association of the Development and Promotion of Fundamental Science and Technology, Tehran. (In Persian)
Sedlák, P., Komárková, J., Jech, J., & Mašín, O. (2019). Low-Cost UAV as a Source of Image Data for Detection of Land Cover Changes. Journal of Information Systems Engineering and Management4(3), 1-9.
Selwood, K. E., Mcgeoch, M. A., & Mac Nally, R. (2015). The Effects of Climate Change and Land Use Change on Demographic Rates and Population Viability. Biological Reviews90(3), 837-853.
Sun, H., Forsythe, W., & Waters, N. (2007). Modeling Urban Land Use Change and Urban Sprawl: Calgary, Alberta, Canada. Networks and Spatial Economics7(4), 353-376.
Tang, J., Wang, L., & Yao, Z. (2007). Spatio-Temporal Urban Landscape Change Analysis Using the Markov Chain Model and a Modified Genetic Algorithm. International Journal of Remote Sensing28(15), 3255-3271.
Tattoni, C., Ciolli, M., & Ferretti, F. (2011). The Fate of Priority Areas for Conservation in Protected Areas: A Fine-Scale Markov Chain Approach. Environmental Management47(2), 263-278.
Yang, X., Zheng, X. Q., & Lv, L. N. (2012). A Spatiotemporal Model of Land Use Change Based on Ant Colony Optimization, Markov Chain and Cellular Automata. Ecological Modelling233, 11-19.
Zali, N., & Abizadeh, S. (2013). Analyzing Urban Green Space Function Emphasizing Green Space Features in District 2 of Tabriz Metropolis in Iran. Anuario Do Instituto De Geociencias, 36(1). https://pdfs.semanticscholar.org/9bde/2a9d3cb42b15062932af0808dcbce0fd5729.pdf
Zali, N., Abizadeh, S., & Baghernia, A. (2013). New Urbanism and Urban Design: Tools for Changing Behavioral Patterns of the Citizens. Internatıonal Journal of Natural and Engineering Sciences, 7(1), 31-36.
Zali, N., Rabbani, T., & Vahidi Motti, V. (2015). Application of Prospective Structural Analysis for Identification of Strategic Variables in the Future Development of Baneh City in Iran. European Spatial Research and Policy, 22(1), 153-171.
Zali, N., Rahimpoor, M., Saed Benab, S., Molavi, M., & Mohammadpour, S. (2016). The Distribution of Public Services from the Perspective of Sustainable Spatial Equality in the Tabriz Metropolitan in Iran. Ema-Journal of Land Use, Mobility and Environment, 9(3), 287-304.