Evaluation of Markov Chain and Automated Cell Integrated Model in Simulation of Land Use Change and Land Cover of Gotvand Dam

فصلنامه آب و توسعه پایدار

Article 6, Volume 9, Issue 2 - Serial Number 24, September 2022, Pages 47-56   

Document Type: Applied Article

DOI: 10.22067/jwsd.v9i2.2112.1106

Authors

Mohammad Kianpoor kal khajh^{* 1}; Mehdi Pajouhesh²; Samad Emamgholizadeh³

¹Master of Water Structures, Shahroud University of Technology, Iran

²Associate Professor of Soil and Water Conservation, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Iran

³Professor of Water Structures, Faculty of Civil Engineering, Shahroud University of Technology, Iran

Abstract

For sustainable land use, it is necessary to reveal the changes in land use and land cover and to identify the factors affecting the changes. The use of remote sensing and GIS provides accurate and systematic information on surface phenomena. The purpose of this study is to evaluate the efficiency of the integrated model of automatic cell and Markov chain in simulating and predicting temporal and spatial changes of land use changes and land cover in Gotvand dam area. The Kappa coefficient was 0.92 for 1991, 0.97 for 2008, and 0.93 for 2020. The accuracy of the CA-MARKOV model for predicting changes in the second period was 85%. Pastures form the dominant cover of the study area. Also, pasture and barren lands have been destroyed and reduced in area, and the area of other uses has increased. The results of the change prediction matrix based on the map of 2008 and 2020 showed that between 2020 and 2050, 10.37% of water areas, 21.49% of built-up areas, 44.41% of agricultural lands, 25.85% of Barren lands, 41.10% of pastures and 18.15% of meadows will remain unchanged. The results of revealing the land use map of 2050 showed that 31.2% of water areas, 37.5% of built-up areas, 13.9% of agricultural lands, 32.37% of barren lands and 44.78% of pastures in the studied area. The results show the increase of cultivated area and the development of agricultural lands. Also, the results showed that the increase in population and expansion of urbanization in the region has caused the destruction of pastures.

Keywords

CA-MARKOV; Remote Sensing; Forecasting; Land Use; Accuracy Assessment

References

انصاری، ا. 1395. شناسایی کانون‌‌های برداشت و عوامل موثر در بروز طوفان‌‌های گرد و غبار در منطقه تالاب کویری میقان اراک. دانشگاه اراک. اراک.
رضایان، س.، جوزی، ع.، ایزدنیا، م.، مرشدی، ج. و مرادی مجد، ن. ۱۳۹۳. تأثیر تغییرات کاربری اراضی بر مورفولوژی رودخانه کارون (مطالعه موردی: محدوده سد گتوند تا تنگ عقیلی شوشتر). فصلنامه علوم محیطی، (۱)۱۲: 77-۸۶.
شکوهیده، ه.، پژوهش، م. و حیدری قهفرخی، ز. ۱۴۰۰. بررسی کارآیی مدل تلفیقی سلول‌های خودکار و زنجیره مارکوف در شبیه‌سازی الگوی مکانی - مانی سد کارون ۳. مرکز توسعه پژوهش‌های نوین، (۱)۷: 161-۱۷۷.
علی خواه اصل، م. و رضوانی، ف. ۱۳۹۷. پیش‌بینی تغییرات پوشش زمین در افق ۱۴۰۷ با استفاده مدل تلفیقی زنجیره‌ای مارکوف و سلول خودکار؛ مطالعه موردی: حوزه آبخیز مشرف به دریاچه بزنگان. فصلنامه تحقیقات جغرافیایی، (۳)۳۳: 74-۸۷.
نظریان، ا.ا.، قربانی، م. و کوهبانی، ح.ر. ۱۳۸۹. ارزیابی تغییرات کاربری اراضی حوضه آبخیز طالقان در دوره زمانی ۱۳۶۶ تا ۱۳۸۰. مجله علمی پژوهشی مرتعداری، (۳)۴: 440-۴۵۱.
Alabi A., Tobore A., Oyerinde G. and Senjobi B. 2021. Forest cover change in Onigambari reserve, Ibadan, Nigeria: Application of vegetation index and Markov chain techniques. The Egyptian Journal of Remote Sensing and Space Sciences, 24(3): 983-990
Camacho Olmedo M.T., Paegelow M., Mas J. and Escobar F. 2018. Geomatic approaches for modeling land change scenarios. In: Cartwright, W., Gartner, G., Meng, L., Peterson, M.P. (Eds.), Lecture Notes in Geoinformation and Cartography. Springer International Publishing AG. Cham, Switzerland.
Capitani C., Van Soesbergen A., Mukama K., Malugu I. and Mbilinyi et al. 2019. Scenarios of land use and land cover change and their multiple impacts on natural capital in Tanzania. Environ. Conserv, 46: 17–24.
Clarke K.C., Hoppen S. and Gaydos L. 1997. A self-modelling cellular automata model of historical urbanization in the San Francisco bay area. Environ. Plan, 24: 247– 261.
Du Y., Teillet P.M. and Cihlar, J. 2002. RAadiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection, Remote Sensing of Environment, 82: 123-134.
Gupta R. and Sharma L.K. 2020. Efficacy of spatial land Change modeler as a forecasting indicator for anthropogenic change dynamics over five decades: a case study of Shoolpaneshwar Wildlife Sanctuary, Gujarat, India. Ecol. Indic, 112: 106171.
Huang L. and Ni N. 2008. Object-Oriented classification of high resolution satellite image for better accuracy. Proceedings of the 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Shanghai, P. R. China.
Jie Z. 2011. Accuracy assessments and uncertainty analysis of spatially explicit modeling for land use/cover change and urbanization: A case in Beijing metropolitan area. SCIENCE CHINA Earth Sciences 2010, 53(2): 173-80.
Khoi D.D. and Murayama Y. 2010. Forecasting areas vulnerable to forest conversion in the Tam Dao National Park Region, Vietnam. Remote Sensing, 2(5): 1249–1272.
Kumar K.S., Kumari K.P. and Bhaskar P.U. 2016. Application of Markov Chain & Cellular Automata based model for prediction of Urban transitions. International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE. Chennai, India.
Li Z.T., Li M. and Xia, B.C. 2020. Spatio-temporal dynamics of ecological security pattern of the Pearl River Delta urban agglomeration based on LUCC simulation. Ecol. Indic, 114: 106319.
Memarian H., Balasundram S.K., Talib J.B., Sung C.T.B. Sood A.M. and 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): 542-554. 
Wang Q., Guan Q., Lin J., Luo H., Ten Z. and Ma Y. 2021. Simulating land use/land cover change in an arid region with the coupling models. Ecological Indicators, 122(2021): 107231. 
Wu J. and Hobbs R. 2002. Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landsc. Ecol, 17: 355–365.
Zhao Z., Zhang Y., Liu L., Liu F. and Zhang H. 2015. Recent changes in wetlands on the Tibetan Plateau: a review. J. Geogr. Sci, 25: 879–896.