Prediction of Land Use and Land Cover Changes from 2018 to 2042 Using CA-Markov: A Case Study from Türkiye

Abstract

Aim of study: To determine the potential changes that may occur in land use classes in Akyaz & imath; Forest Enterprise for 2030 and 2042. Area of study: Akyaz & imath; Forest Enterprise was selected as the study area. Material and method: In this study, the Coordination of Information on the Environment (CORINE) land use land cover (LULC) datasets for the years 2006, 2012 and 2018 were used. The Markov model derived transition area and transition probability matrices (TPM) for 2018 based on the LULC maps derived from CORINE for 2006 and 2012. These matrices were used to predict LULC classes in 2018 through a 10-year simulation using the CA-Markov module. Main results: A comparison was made between the projected LULC classes map and the land use class map derived from the 2018 CORINE data, and a similarity rate of 91.1% was found. For the 24 years from 2018 to 2042, the total forest area is predicted to increase by 3.8% or 581.5 ha. Research highlights: The forecasted outcomes acquired for the future can aid in developing revised forest management strategies, particularly in ensuring the long-term viability of forest ecosystems.