Using the Markov chain model to predict variations in pistachio plantations (A case study of Zeidabad, Sirjan Town)

Remote sensing is the key technology used to assess land use changes that serve as basic information in all planning. The current study uses the Markov chain model to investigate changes in the area under pistachio cultivation and explores its potential for predicting future variations in land use in Zeidabad, Sirjan. For this purpose, use is made of ETM+ Landsat 7 and OLI Landsat 8 sensor images taken in the years 2000, 2010, and 2019, all of which are classified into the two land use classes of vegetation (pistachio plantations) and non-vegetation (residential areas, riverbeds, barren land, and pastures). The results obtained indicate an upward trend in agricultural development, particularly in pistachio cultivation as the most dynamic land use, in the study region so that an increase of 1888.83 hectares (15.04%) is recorded for the total cultivated land. Similarly, an upward trend is recorded for changes in pistachio plantations during the years 2010 to 2019 so that 1685.07 hectares (11.66%) of land is shown to be added to the total land area under pistachio cultivation. Markov chain analysis of the period from 2010 to 2019 indicates a steady increase in pistachio cultivation in the study region by 2029.