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Predicting the land use and land cover change using Markov model: A catchment level analysis of the Bhagirathi-Hugli River

  • Sanat Das
  • Rajib SarkarEmail author
Article

Abstract

Land use and land cover are important biophysical factors which have a major role in different terrestrial processes on the earth. Land use and land cover change are a vital element of global environmental change. It is very essential for regional development and land use management towards sustainable development. The different time’s period satellite images in the study area have been studied to understand temporal as well as the spatial variability of land use and land cover (LULC) change. In this, an attempt was made to adopt the Markov model for obtaining and investigating the dynamics of land use change. Markov model was used as a stochastic model to make quantitative comparisons of the land-use changes between time periods extending from 2001 to 2010. Model performance was evaluated between the empirical LULC map obtained extracted from Landsat 8 (2017) image and the simulated LULC map obtained from the Markov model. The future land use distribution in the year 2019 and 2028 was acquired using a Markov model. This result shows that the Markov model and geospatial technology together are able to effectively capture the spatiotemporal trend in the landscape pattern in this study area.

Keywords

LULC Maximum likelihood Kappa statistics Markov model Transition matrix Validation 

Notes

Acknowledgements

The authors like to acknowledge USGS for providing data for the study and also like to thank the Department of Geography, Adamas University for providing necessary facility to conduct the study. We also like to thank anonymous reviewers and the editor for their comments and suggestions for improving the manuscript.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Copyright information

© Korean Spatial Information Society 2019

Authors and Affiliations

  1. 1.Department of GeographyAdamas UniversityKolkataIndia

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