CA-Markov chain for simulation and prediction of LULC and assessing the status of water pollution in Manzala Lake after recent development

Abstract

AbstractThe Egyptian government recently undertook a large-scale national dredging project to improve the properties and productivity of the northern lakes. Manzala Lake has a distinctive ecological system that offers locals a variety of ecological services. This study was occurred using an integrating approach of remote sensing and Markov modeling to determine the land use/cover (LULC) change of Manzala Lake’s components. The physiochemical characteristics of the water were also measured. Six LULC classes namely; water, crops, vegetation, urban areas, bare lands, and, sabkha were detected in and around the lake in three different years (1998, 2010, and 2022). The LULC transition was studied and predicted using the CA-Markov model. The area of surface water, flooded vegetation, sabkha, and urban areas were increased by the year of 2022. The bare lands were declined more comparing with the past periods. The new developments in Manzala Lake made more changes in the LULC of lake ecosystems. Also, it is an indication to exploitation the bare areas around lakes into new urban areas. The obtained results were necessary for the revised management plan. It is essential for managing the lakes’ land resources, and vital to carefully consider the development strategies to determine how these projects will influence on the environment and biodiversity. In addition, to what extent this lake productivity will improve and help in the recovery of Egypt’s national income.