Modelling land use/cover change in Lake Mogan and surroundings using CA-Markov Chain Analysis

Abstract

Aim : Lake Mogan, having high ecological and cultural significance, has been under intense pressure of urbanization and industrialization due to its location on the periphery of the capital Ankara. In this study, we analyzed data from satellite remote sensing, Geographic Information System and Cellular Automata Markov Chain modelling to predict land use/cover changes in Lake Mogan and surrounding areas. Methodology : Three images recorded in 1975 and 1999 (air photos) and 2009 (Quickbird image) were used to detect the land use/cover changes over the time. An object-based supervised classification approach to simulate changes in the study area for the future was performed. Land use/cover changes for the year 2029 was modelled using Cellular Automata Markov Chain Analysis with the support of suitability analysis. Results: The results indicated that most of the agricultural areas will be converted into settlements over the next 40 years. Modelling results for 2029 also showed that land degradation activities are likely to continue in the future. Interpretation :According to model on land use changes in Lake Mogan and surrounding areas, there is an immediate need to take long-term measures for sustainable land development based on the regional scales, preferably on the basin level.