Evaluation and prediction of future vegetation status in Dasht-e Fahleh region of Fars province using Markov model

Subject Areas : Climatology

Mohammad Javad Behi ¹ , Mohammad Hossein Mokhtari ² , Gholamhossein Moradi ³ , Mohammad Ali Saremi Naeini ⁴

1 - PHD candidate, Department of Natural Resources and Desert Studies, Yazd University, Iran
2 - Assiss. Prof., faculty of Natural Resources and Desert Studies, Yazd University, Iran (corresponding author)
3 - 3- Assiss. Prof., faculty of Natural Resources and Desert Studies, Yazd University, Iran
4 - 3- Assiss. Prof., faculty of Natural Resources and Desert Studies, Yazd University, Iran

Received: 2021-08-15 Accepted : 2021-11-21 Published : 2022-01-21

Keywords: Time series, Desert, Trend, remote sensing, Google Earth Engine,

Abstract :

The purpose of this study is to evaluate the temporal and spatial changes of vegetation in Mullah Fahleh of Firoozabad region of Fars province. The standard vegetation index data of Landsat 5, 7 and 8 satellites, the precipitation data and Palmer index, which are available as a remote sensing product, were extracted for 1992 to 2020 from the Google Earth Engine. Markov chain method was used to predict future vegetation changes. Using data from 1992 and 2002, the model was first run for 2020 and based on its acceptable performance (the kappa index of 75%), prediction was extended to 2030. The results showed an improving trend in vegetation status, so that the dense cover will increase from 4% in the initial period to 19% in 2030. The results of this study can help rangeland managers in the region to better exploit the region's natural resources and prevent the destruction of this ecosystem.

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