Predicting Land Use/Land Cover changes in Da Nang based on CA-ANN Model and Satellite Image Data

Da Nang City, a rapidly urbanizing area in Central Vietnam, is experiencing significant changes in Land Use/Land Cover (LULC). This study aims to monitor and predict LULC changes in the Da Nang area up to the year 2035. The use of free, open-source, and highly consistent data, combined with JavaScript programming on the Google Earth Engine (GEE) platform and machine learning algorithms, allowed for fast and efficient data processing. The study employed the Random Forest (RF) algorithm to classify six land cover types from Landsat-8 satellite imagery, achieving high classification accuracy with a Kappa coefficient exceeding 0.8. These classification results were then used for the future LULC change prediction model. To simulate and predict LULC changes for 2035, an integrated model of Cellular Automata (CA) and Artificial Neural Network (ANN) was applied to the Da Nang area. The CA-ANN model addresses the limitations of traditional statistical models (such as Markov Chain) by integrating spatial control factors and neighborhood influences. The prediction results clearly indicate an expansive trend in urban development; the residential area is forecasted to increase, reaching 6.22% by 2035, while the agricultural cultivation area shows a notable decrease of approximately 2.81% compared to 2015. The research affirms the superior efficiency of the integrated CA-ANN model for predicting LULC changes in fast-developing areas. These detailed and continuous multi-year results can effectively support fields such as spatial planning, land management, real estate, environmental resource management, and contribute to the development of Da Nang.

How to Cite

Dang, T.Thanh and Hoang, T.Thi 2026. Predicting Land Use/Land Cover changes in Da Nang based on CA-ANN Model and Satellite Image Data (in Vietnamese). Journal of Mining and Earth Sciences. 67, 3 (Jun, 2026), 116-130. DOI:https://doi.org/10.46326/JMES.2026.67(3).10.

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