The Application of CA–MLP–ANN in Assessing Urbanisation in Quaternary Catchment X22J of Mpumalanga, South Africa

Abstract

Quaternary catchment X22J boasts ecological biodiversity, making ecotourism one of the thriving industries in the catchment. However, recent population growth and the migration from rural areas to urban areas have increased urbanisation. Therefore, this study aimed to assess and predict the trajectory of urban growth. Through the random forest algorithm in Google Earth Engine, this study analysed urban use in 1990, 2007 and 2024. The classification achieved an overall score of 0.89, 0.96 and 0.91 for 1990, 2007 and 2024, respectively. In addition, the Kappa coefficient varied between 0.85, 0.83 and 0.87 for 1990, 2007 and 2024. The CA–MLP–ANN algorithm was applied for the prediction of 2040 urban changes, leading to the model achieving a score of an overall Kappa coefficient of 0.52 and 74% correctness. Overall, the study predicted an increase of 4.01% in built-up areas from 2024 to 2040, maintaining the increasing trend from 1990. Consequently, a loss of 11% was observed in agricultural lands and a loss of 0.17 in waterbodies by 2040.