Verification and Upgrading the Land Use Change Prediction Model by Controlling the Growth of Development in the CA-MC (Case Study Area: Gharesou Basin)

Document Type : Original Article

Authors

Assist. Profe. Faculty of natural resources and environmental science, University of Birjand, Iran

Abstract

Human activities are one of the factors that have a significant impact on the land use change patterns, and these changes are in most cases inconsistent with the environment. Therefore, land-use prediction models for sustainable land-use planning are a requirement. In this research, using the Cellular Automata Markov Chain model, modeling of land use change for the Gharehsou basin has been improved to predict the future. Promotion of the Markov chain model has been done by entering the population growth rate and per capita requirements of each land use in the model. Validation of the upgraded model by comparing the map of the predicted land use change for 2014 and the results of the upgraded model have been reviewed. The results of the comparison of these two maps showed that the results of the upgraded model were much more similar to the current situation since the population growth rate and, consequently, per capita needed for urban development are the most important driving force to disrupt the ratio of changes in a timely trend. Therefore, considering this factor in the Markov chain model more flexibility and great results closer to reality, which is practical in the Gharehsou basin. Finally, the upgraded CA-Markov chain model was used to predict the 2030 basin.

Keywords

References

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Environmental Researches
Volume 12, Issue 23
Recerches
September 2021
Pages 105-116

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