In the heart of the Vietnamese Mekong Delta, a silent transformation has been unfolding over the past three decades, one that has significant implications for agriculture, urban development, and the energy sector. A groundbreaking study led by Tran The Dinh from the Department of Geography at An Giang University and Vietnam National University Ho Chi Minh City has shed light on these changes, using cutting-edge machine learning techniques to analyze land use and land cover (LULC) dynamics in the Long Xuyen Quadrangle (LXQ).
The study, published in *Environmental Challenges* (known in Vietnamese as *Thách thức Môi trường*), employed three widely-used machine learning classifiers—Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Trees (CART)—to evaluate LULC changes from 1990 to 2023. The research leveraged Landsat imagery and the Google Earth Engine (GEE) platform to achieve unprecedented accuracy in mapping these transformations.
“Our findings reveal a dramatic shift in the landscape of the LXQ,” said Dinh. “The Random Forest classifier, in particular, demonstrated exceptional accuracy, outperforming the other classifiers with an overall accuracy of 95.90% and a Kappa coefficient of 0.951.”
The results are stark: wetlands in the region have shrunk by a staggering 89%, from 2593.96 km² in 1990 to just 293.74 km² in 2023. Concurrently, arable cropland has more than doubled, expanding by approximately 100% from 1996.81 km² to 3994.39 km². Urban areas have also seen significant growth, driven by socio-economic factors such as agricultural intensification and urbanization.
These changes are not just environmental; they have profound commercial implications, particularly for the energy sector. Wetlands play a crucial role in carbon sequestration and biodiversity conservation, both of which are increasingly important for sustainable energy practices. The loss of wetlands could exacerbate climate change impacts, affecting energy infrastructure and operations.
“Understanding these dynamics is crucial for developing sustainable land management practices,” Dinh emphasized. “Our study highlights the need for wetland preservation, careful urban planning, and sustainable agricultural practices to mitigate adverse ecological impacts.”
The study’s use of advanced geospatial technologies and machine learning sets a new standard for monitoring and understanding LULC dynamics. As the Mekong Delta continues to develop rapidly, the insights from this research could shape future policies and practices, ensuring a balance between economic growth and environmental sustainability.
For the energy sector, this research underscores the importance of integrating ecological considerations into planning and development. By preserving wetlands and promoting sustainable land use, companies can mitigate risks and contribute to long-term environmental health.
As Dinh noted, “The future of the Mekong Delta—and regions like it—depends on our ability to adapt and innovate. This study is a step in that direction, but it’s just the beginning.”