Simulating the spatiotemporal changes of forest extent for the Chehelchay watershed (Golestan province), using integrated CA-Markov model | ||
| تحقیقات جنگل و صنوبر ایران | ||
| Article 9, Volume 20, Issue 2 - Serial Number 48, June 2012, Pages 285-273 PDF (393.72 K) | ||
| Document Type: Research article | ||
| DOI: 10.22092/ijfpr.2012.107279 | ||
| Authors | ||
| Arash Zare Garizi* 1; Vahedberdi Sheikh2; Amir Sadoddin2; Abdolrassoul Salman Mahiny3 | ||
| 1PhD student of Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources | ||
| 2Assistant professor, Faculty of Rangeland and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources | ||
| 3Associate professor, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agriculture Sciences and Natural Resources | ||
| Abstract | ||
| The importance of land-use/ land-cover (LULC) as a dynamic factor and effective on environmental conditions, makes it necessary to get precise quantitative and qualitative information from it and to identify its changes through short time periods. Modeling LULC changes provides useful information for better understanding of the changes process, determining driving forces and predicting areas under change conditions. In this study, the integrated CA-Markov model was used to simulate forest cover changes in the Chehelchay Water catchment at minodasht area of Golestan province of Iran. CA-Markov is a combined Cellular Automata/Markov chain land cover prediction procedure that adds an element of spatial contiguity to the stochastic Markov chain analysis. Landsat images of 1987 and 2009 and land-use map of 2001 were used to derive forest extent maps of the Chehelchay Water catchment and characterize changes through time. To investigate the relationships between forest extent changes and some environmental and human-related factors and to produce transition suitability maps, a logistic regression analysis was applied between forest extent changes as response variable and the deriving factors as explanatory variables. Future LULC types for 2009 were then predicted using CA–Markov model, based on the land-cover changes between 1987 and 2001. In order to evaluate the modeling results, prediction for 2009 was compared with the observed 2009 land cover map. The computed accuracy coefficient indicated high efficiency of CA-Markov for simulating forest extent changes in the Chehelchay Water catchment (Kappa = 0.92). Finally, assuming current trends in LULC changes continue, forest cover map for the year 2020 was developed. The results indicate that there will be a notable decrease in forest area. | ||
| Keywords | ||
| Forest extent changes; Logistic regression; Markov chains; Cellular Automata; the Chehelchay Watershed | ||
| References | ||
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