Urban development management in Dien Bien Phu City: An integrated approach using multi-source remote sensing, machine learning, and planning maps

Bui Thi Ngoc Lan, Nguyen Manh Hung, Vu Anh Tuan, Dao Duy Toan, Asami Hideki, Nguyen Cong Giang
Author affiliations

Authors

  • Bui Thi Ngoc Lan Faculty of Urban Management - Hanoi Architectural University
  • Nguyen Manh Hung 1-Vienam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam; 2-Graduate University of Science and Technology, VAST, Hanoi, Vietnam
  • Vu Anh Tuan Vienam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam
  • Dao Duy Toan Faculty of Bridge and Road, Hanoi University of Civil Engineering, Hanoi, Vietnam
  • Asami Hideki Former President of Nikken Sekkei Civil Engineering
  • Nguyen Cong Giang 1-Vienam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam; 2-Faculty of Architecture and Engineering, University of Phuong Dong

DOI:

https://doi.org/10.15625/2615-9783/24668

Keywords:

Sustainable urbanization, Urban planning, Remote sensing, Machine learning, Basin-type cities

Abstract

Sustainable urban development management in mountainous cities with complex basin topography is becoming a formidable challenge for urban planners amidst rapid urbanization. This study quantifies the land use/land cover (LULC) dynamics in Dien Bien Phu City from 2018 to 2025 using an integrated framework that combines multi-temporal Sentinel-2 imagery, Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM), and the Random Forest machine learning algorithm on the Google Earth Engine platform. The classification results achieved high reliability, with overall accuracy (OA) ranging from 94.2% to 98.8% and Kappa coefficients (Kappa) exceeding 0.96. Spatial analysis reveals a pronounced structural shift in land cover: built-up areas increased significantly from 8.8% in 2018 to 12.4% in 2025, while forest cover declined sharply from 35.1% to 26.7%. Notably, bare land accounted for a substantial proportion (14.1%) by 2025, potentially indicating land preparation activities and reflecting possible short-term fluctuations in plantation forest cover. The results further suggest that urban growth is transitioning from a historically monocentric pattern towards a more polycentric model, primarily expanding into southern and western corridors. By benchmarking these findings against the 2045 General Planning Vision, this study identifies potential conflict zones between urban expansion and ecological conservation in mountainous buffer areas. These findings provide a scientific basis for urban authorities to regulate land-use conversion, particularly in high-risk basin foothill zones, while simultaneously addressing the imbalance between infrastructure expansion and ecological preservation. In particular, the spatial delineation of urbanization pressures provides actionable guidance for establishing greenbelts and optimizing urban growth boundaries in accordance with the 2045 General Planning Vision, thereby enhancing the long-term climate resilience of basin-type cities under accelerating environmental change.

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Published

19-05-2026

How to Cite

Bui Thi, N. L., Nguyen Manh, H., Vu Anh , T., Dao Duy, T., Asami Hideki, & Nguyen Cong, G. (2026). Urban development management in Dien Bien Phu City: An integrated approach using multi-source remote sensing, machine learning, and planning maps. Vietnam Journal of Earth Sciences. https://doi.org/10.15625/2615-9783/24668

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