Analysis of Land Use/land Cover Changes and Prediction of Future Changes With Land Change Modeler: Case of Belek, Turkey

Abstract

In the areas declared to be a tourism center, a rapid tourism-related development occurs depending on the investments in tourism, which causes a dramatic land use and land cover changes. Determining, monitoring, and modeling of land use and land cover changes are required in order to ensure the conservation-use balance and sustainability within such vulnerable areas that are under the development pressure. This study consists of four steps. In the first step, the Landsat images dated 1985, 2000, and 2021 were classified using the maximum likelihood method and the land use and land cover of Belek Tourism Center located in Turkey were determined. The second step included the identification of areal and spatial changes between the land use and land cover classes for the periods between 1985 and 2000, 2000 and 2021, and 1985 and 2021. In the third step, the land use and land cover changes in Belek Tourism Center for 2040 were modeled using the Land Change Modeler. Last step evaluated the relationship between the modeled spatial development pattern and the current planning decisions. According to the results obtained through a 36-year research, the rates of settlement, forest, and water body areas have increased by 11.91%, 13.67%, and 0.82%, respectively whereas the rates of barren land and agricultural areas have reduced by 22.25% and 4.15%, respectively. The land use map modeled for 2040 predicts the settlement areas to expand by 5.46% and the agricultural areas to shrink by 4.21% by comparison with 2021.

Integrated use of the CA-Markov model and the Trends.Earth module to enhance the assessment of land cover degradation: Application in the Upper Zambezi Basin, southern Africa

“…Several approaches for detecting and predicting land cover and land use (LCLU) changes exist, among which the artificial neural network (ANN), cellular automata (CA), and Markov chain (MC) models appear to be the most commonly utilised (Lukas et al, 2023;Burak Akdeniz & Sag, 2022;Wang et al, 2021;Näschen et al, 2019a;Hamad et al, 2018a;Halmy et al, 2015;Singh et al, 2015;Corner et al, 2014;Memarian et al, 2012). Some studies have used a combination of the CA-Markov models and the ANN to better prediction outcomes for particular landscapes (Hu et al, 2018).…”