Evaluation of forest areas and land use/cover (LULC) changes with a combination of remote sensing, intensity analysis and CA-Markov modelling

Abstract

Background: Land use and land cover change (LULC) is crucial for maintaining the integrity of ecosystems’ structure and function, and thus regular measurement and monitoring of LULC are necessary.

Methods: In this study, the temporal and spatial changes in forest areas and land cover in the province of Sinop, located in the north of Turkey, were analysed by intensity analysis for two 10-year periods from 2002-2012 to 2022, and 2032 and 2042 forecast LULC maps were generated using the cellular automata CA-Markov model. In the study, datasets were prepared using forest type maps and Landsat images, and the images were classified using various classification techniques.

Results: The results indicated that forest areas increased by 23% (37,823.38 ha) from 2002 to 2022, with the mixed forest category showing a decrease of 22% (12,245.43 ha) within this. In non-forest areas, a significant increase of 72% was observed in the settlement category, while a decrease of 63% was noted in the agricultural category. According to the intensity analysis, the rate of change in LULC is faster from 2002 to 2012 than from 2012 to 2022. In both periods, the settlement and agricultural categories have predominantly targeted each other’s losses. According to the simulation results of land use/cover from 2022 to 2042, a 0.50% increase in total forest area, a 2.87% increase in settlements, and a decrease of 2.65% and 0.71% in agriculture and water classes, respectively, are anticipated.

Conclusions: The overall results suggest that it can contribute to setting an appropriate development goal, especially for forest planners and policymakers, to regulate land use changes to achieve higher carbon stocks and maintain balance in global climate scenarios.