Tạp chí
 
Năm 2026
 
Số 67, Kỳ 4, [08 - 2026] - Tiếng Anh

Assessing coastal urbanization and land use efficiency from multi-temporal optical imagery using machine learning: case study in Ha Long City

DOI:10.46326/JMES.2026.67(4).05

  • Cơ quan:

    1 Vietnam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam
    2 Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
    3 Faculty of Bridge and Road, Hanoi University of Civil Engineering, Hanoi, Vietnam
    4 Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Hanoi, Vietnam

  • *Tác giả liên hệ:
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  • Nhận bài: 18-01-2026
  • Sửa xong: 17-04-2026
  • Chấp nhận: 02-05-2026
  • Ngày đăng: 01-08-2026
Trang: 42 - 59
Lượt xem: 13
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Lượt tải: 1
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Tóm tắt:

Coastal cities are highly dynamic environments subject to intense pressures from urbanization, population growth, and environmental change, making spatiotemporal urban development analysis critical for sustainable planning. This study utilizes multi-temporal Landsat and Sentinel-2 imagery from 1995÷2025 to map land-use/land-cover (LULC) patterns and evaluate urban expansion in Ha Long City. A Random Forest classifier was applied using spectral features and key remote-sensing indices, including NDVI, NDBI, MNDWI, CMRI, and elevation data. Post-classification change detection was then conducted to identify major transitions from natural and agricultural surfaces to built-up areas. The classification results show high accuracy, particularly for built-up land, with F1-scores increasing from 0.88 in 1995 to 0.96-0.98 after 2010, indicating consistent producer’s and user’s accuracy for long-term monitoring. Over three decades, Ha Long’s urban land expanded from about 2,097 ha to more than 7,188 ha, raising the regional urbanization level from 8.7% to nearly 30%. Urban growth predominantly extended toward coastal zones, bayfront areas, and major transportation corridors, accompanied by reductions in natural forests, mangroves, and water surfaces due to reclamation and spatial expansion. Analysis of urbanization speed and rate highlights contrasts between saturated urban cores and areas with remaining development capacity. Zones with high growth rates but low existing urban share represent potential growth clusters, while nearly saturated areas tend toward vertical development or outward expansion. These findings provide a scientific basis for land-use planning and sustainable urban development strategies in Ha Long City.

Trích dẫn
Hung Manh Nguyen ., Toan Duy Dao, Chieu Dinh Vu, Dung Ngoc Luong, Dong Thanh Khuc, Son Mai Le và Trong Gia Nguyen, 2026. Assessing coastal urbanization and land use efficiency from multi-temporal optical imagery using machine learning: case study in Ha Long City, Tạp chí Khoa học kỹ thuật Mỏ - Địa chất, số 67, kỳ 4, tr. 42-59.
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