Prediction of Land Use Changes Using the CA-Markov and LCM Models in the Kozehtopraghi Watershed in the Province of Ardabil

Document Type : Research

Authors

1 M.Sc. Graduated in Remote Sensing and GIS, Department of Literature and Humanities, Faculty of Natural Geography, Mohaghegh Ardabili University, Ardabil, Iran

2 Assistant Professor, Department of Literature and Humanities, Faculty of Natural Geography, University of Mohaghegh Ardabili, Ardabil, Iran

3 Associate Professor, Department of Natural Resources and Member of Water Management Research Institute, Faculty of Agricultural Technology and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract

Simulation and monitoring of future trends of land use changes is an important challenge for researchers and decision makers. This study uses the spatio-temporal models to simulate and evaluate the future trend in land use changes of the Kozehtopraghi Watershed in the Province of Ardabil. Landsat ETM+ (2000), TM (2010) and OLI (2018) images were used. The CA-Markov model was used to simulate land use changes in the future period (the year 2036). To assess the validity of a CA-Markov model, the predicted land use map of 2018 was compared with the classified map of 2018. Based on the Kappa accuracy coefficient with the value of 0.8, the accuracy of the simulated results was acceptable. The land use map of 2036 has been predicted using the CA-Markov model. In order to analyze and detect the changes in 2000 to 2036, the LCM model was employed. The results showed that the areas of irrigated farming, pastures and orchards will increase by 80.52, 36.90, and 5.76 percent, respectively. On the other hand, the rainfed agriculture and water bodies areas will decrease by 43.43 and 91.40 percent, respectively. In addition, based on the results of the change process, extreme changes in rainfed agriculture, orchard, pasture and irrigated agriculture will happen in the central, south-west, south-west and downstream parts of the Kozehtopraghi Watershed.

Keywords

References

Abuelaish B, Camacho O, Maria Teresa. 2016. Scenario of land use and land cover change in the Gaza strip using remote sensing and GIS models. Arab Journal of Geosciences, 9(274): 1–14.
Aburas M, Abdullah H, Ahmad-Mohd Sanusi S. 2018. Simulating and monitoring future land-use trends using Ca-Markov and LCM models. 9th IGRSM International Conference and Exhibition on Geospatial & Remote Sensing (IGRSM 2018), 24–25 April, Kuala Lumpur, Malaysia 169: 1–10.
Afifi MA. 2018. Modelling of land use changes using Markov Chain model, a case study: Shiraz. Geographic Science Research. 20(56): 142–158. (In Persian).
Akyurek O, Koc E, Akbaba F. 2018. Land use/ land cover change detection using multi-temporal satellite dataset: A case study in Istanbul new airport. Geo-information for Disaster Management, 3(4): 18–21.
Ansari A, Golabi M. 2019. Prediction of spatial land use changes based on LCM in a GIS environment for desert wetlands. International Soil and Water Conservation Research. 7(1): 64–70.
Armenteras D, Murcia U, Gonzalez T, Baron O, Arias J. 2019. Scenarios of land use and land cover change for NW Amazonia: Impact on forest intactness. Global Ecology Land Conservation, 17: 1–13.
Azizi Ghaklati S, Rangzan K, Taghizadeh A, Ahmadi Sh. 2014. LCM logistic regression modeling of land-use changes in Kouhmare Sorkhi, Fars province. Iranian Journal of Forest and Polar Research. 22(4): 585–596. (In Persian)
Behera M, Borate S, Panda S, Behera P, Roy P. 2012. Modeling and analyzing the watershed dynamics using cellular automata CA-Markov model a geo-information based model. Earth System Science. 121(4): 1011–1024.
Borana S, Yadav S. 2017. Modelling and prediction of land use changes in Jodhpur city using multi-layer perceptron Markov techniques. Research in Engineering, 7(11): 14–21.
Simioni DJ, Guasselli AL. 2018. Simulation of changes in land use/land cover in wetlands through CA-Markov model. Revista Brasileira de Geogrfia. 11(6): 2057–2066.
Ebrahimi H, Rasouli A, Ahmadpour A. 2018. Modelling of land use dynamics using object oriented image processing and CA-Markov model. Geographic Information, 27 (108): 137–149. (In Persian)
Fatollahi Roudbari S, Khanmohamadi M, Nasir Ahmadi K. 2018. Modelling of land use changes with using of LCM model: Case study, Neka Township. Natural Ecosystems of Iran, 9(1): 53–69. (In Persian)
Hegazy I, Kaloop M. 2015. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqalia governate Egypt. Sustainable Built Environment, pp. 1–8.
Heydarian P, Rangzan K, Maleki S, Taghizadeh A. 2013, Land use change detection using post classification comparison Landsat satellite images (Case study: land of Tehran), RS & GIS for Natural Resource. 4(4): 1–10.
HUA A. 2017. Application of CA-Markov model and land use/land cover changes in Malacca river watershed, Malaysia. Applied Ecology and Environmental Research. 15 (4): 605–922.
Ignacio Barredo J, Bosque-Sendra J. 1998. Comparison of multi criteria evaluation methods in geographical methods integrated in Geographical Information System to allocate urban areas. Geographical Systems. 5(4): 313–327.
Ildoromi A, Nori H, Naderi M, Aghabeigi Amin S, Zeinivand H. 2017. Land use change prediction using Markov Chain and CA-Markov model. Watershed Management Research, 8(16): 232–240.
Ishaq Shan A. Sumit U, Mehraj D, Dinkumar V. 2017. Land use/land cover change detection and analysis in Aglar watershed. Applied Science and Technology, 24(1): 1–11.
Jasim Hadi S, Shafri H, Mahir M. 2014. Modelling LULC for the period 2010–2030 using GIS and remote sensing. 7th IGRSM International Remote Sensing & GIS Conference and Exhibition 22–23 April, Kuala Lumpur, Malaysia, 20: 1–12.
Keshtkar H, Voit WA. 2016. Spatiotemporal analysis of landscape change using an integrated Markov chain and cellular automata models, Earth System and Environment, 2(10): 1-13.
Koranteng A, Niedzwiecki T. 2015. Modelling forest loss and other land use change dynamics in Ashanti region of Ghana. Folia Forestalia Polonica, 57(2): 69–111.
Li X, Wang M, Liu X, Chen Z, Wei X, Che W. 2018. MCR-Modified C-Markov model for the simulation of urban expansion. Sustainbility, 10 (3116): 1–18.
Meneses B, Reis E, Vale M, Reis R. 2018. Modelling land use and land cover changes in Portugal, A multi-scale and multi-temporal approach. Finisterra (Revista Portuguesa de Geografia). 107: 3–26.
Memarian H, Balasundram SK, Bin Talib J, Teh Boon Song Ch, Mohd Sood A, Abbaspour K. 2012. Validation of CA-Markov for simulation of land use and land cover change in the Langat basin, Malaysia. Geographic Information System, 4(6): 542–554.
Misagh N, Neisani Samani N, Tomanian A. 2018. Urban growth simulation of Tabriz using CA-Markov model and multi criteria evaluation. Human Geography Research, 5(1): 217–231. (In Persian)
Mishra V, Mohang K, Kumar Rai P. 2014. Prediction of land use changes based on land change modeler (LCM) using Remote Sensing. Geographical Institute, 64(1): 111–127.
Mohammad Yari F. Puor Khabaz H, Aghdar H, Tavakoli M. 2019. Prediction of land use changes in Behbahan city for the years 1392 to 1406 with using of LCM model. Geographical Space, 19(65): 37–56. (In Persian)
Mondal M, Surabuddin.Sharma N, Kappas M, Gorg P. 2019. CA-Markov modeling of land use land cover dynamics and sensitivity analysis to identify sensitive parameters. Remote Sensing and Spatial Information Sciences, 2(3): 723–729.
Mujion T, Indra D, Harmantyo P, Rukmana NZ. 2017. Simulation of land use change and effect on potential deforestation using Markov chain-Cellular Automata. AIP Conference Proceedings, the 18th International Conference on Positron Annihilation. 1862(1): 1–9.
Mukhopdhaya S. 2016. Land use and land cover change modelling using CA-Markov case study: Deforestation analysis of Doon valley. Agroecology and Natural Resource Management, 3(1): 1–5.
Munthali M, Botai J, Davis N, Ade la Abiodun M. 2019. Multi-temporal analysis of land use and land cover change detection for Dedza district of Malawi using Geospatial techniques. Applied Engineering, 14(5): 1151–1162.
Nouri J, Gharagozlu A, Arjmandi R, Faryadi S, Adl M. 2014. Predicting urban land use changes using a CA-Markov model. Arab Journal of Geosciences, 39(7): 5565–5573.
Omar N, Sanusi S, Hussin W, Samat N, Mohammed K. 2014. Markov-CA model using analytical hirareny process and multi regression technique. Earth and Environmental Science, 20: 1–18.
Onwuka S, Eneche P, Ismail N, 2017. Geospatial modeling and prediction of land use/cover dynamics in Onitsha metropolis, Nigeria: a sub-pixel approach. Applied Science & Technology, 22(6): 1–18.
Patil S, Jamgade M. 2019. Land change prediction using Markov change Multi-Layer Perceptron in Navi Mumbai, Maharashtra, India. Innovative Technology and Exploring Engineering (IJITEE), 8(10): 484–490.
Powell, Thomas WR. Lenton Timothy M. 2013. Scenarios for future biodiversity loss due to multiple drivers reveal conflict between mitigating climate change and preserving biodiversity. Environmental Research Letters. 8: 1–9.
Reddy C, Singh S, Dadhwal V, Jhacs R, Diwakar P. 2017. Predictive modelling of the spatial pattern of past and future forest cover change in India. Earth System Science, 126(8): 1–16.
Riyand Moe, I. Kure, Sh. Fajar Januriyadi, N. Farid, M. Udo, K. Kazama, S. Koshimura, Sh. 2017. Future projection of flood inundation considering land-use changes and land subsidence in Jakarta, Indonesia. Hydrological Research Letters, 11(2): 99–105.
Sadoddin A, Sheikh VB, Mostafazadeh R, Halili M.G. 2010. Analysis of Vegetation-based management scenarios using MCDM in the Ramian Watershed, Iran. International Journal of Plan Production, 4(1): 51-62
Saifullah K, Barus B, Ruatiadi E. 2017. Spatial modelling of land use/cover change (LULC) in south Tangerang city, Banten. IOP Conference Series: Earth and Environmental Science, 54(1): 1–11.
Samie A, Deng X, Jia S, Chen D. 2017. Scenario-based simulation on dynamics of land-use-land-cover change in Punjab, Pakistan. Sustaninability, 9(8): 1–17.
Sarabuddin Mondal M, Sharma N, Kappas M, Garg P. 2019. CA Markov modeling of land use/land cover dynamics and sensitivity analysis, Identify sensitive parameters. Remote Sensing and Spatial Information Science, 2 (13): 723–729.
Schaldach R, Alcamo J, Heisterman M. 2006. The multiple-scale land use change model LandSHIFT: A scenario analysis of land use change consequence in Africa. Proceedings of the iEMSs Third Biennal Meeting: Summit on Environmental Modelling and Software, Burlington, USA. 196: 1–7.
Siregar V, Prabowo N, Agus S, Subarno T. 2018. The effect of atmospheric correction on object base image classification using SPOT-7 imagery: a case study in the Harapan and Kelapa Islands. IOP Conference Series: Earth and Environmental Science, 2nd International Conference on Marine Science: Better Insight for the Healthy Ocean 6–7 September, Indonesia 176: 1–11.
Sundara Kumar K, Udaya Bhaskar P, Padmakumari K. 2015. Application of land change modeling for prediction of future of land use land cover: A case study of Vijayawda city, Advanced Technology in Engineering and Science, 3(1): 773–783.
Thanh Huong N, Thuy Phuong N. 2018. Land use/land cover change prediction in Dak Nong province based on remote sensing and Markov chain model and Cellular Automata. Vietnamese Environment, 9(3): 132–144.
Wang J, Wang H, Ning S, Hiroshi I. 2018. Predicting future land cover change and its impact on streamflow and sediment load in a trans-boudary river basin. International Association Hydrological Science, 379: 217–222.
Yirsaw E, Wu W, Shi X, Temesgeh H, Bekele B. 2017. Land use and land cover change modeling and the prediction of subsequent changes in ecosystem service values in a coastal area of China, The Su-Xi-Change region. Sustainability, 9 (1204): 2–17.

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History

  • Receive Date: 07 October 2019
  • Revise Date: 09 December 2019
  • Accept Date: 17 December 2019

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