Assessment of Urban Land Cover structure Change in Hanoi City from 2005 to 2025 Using Multi-Temporal Remote Sensing Data

Authors

1 Trường Đại học Mỏ - Địa chất, Hà Nội

DOI:

https://doi.org/10.67484/GeoGIS.83.1205.2026

Keywords:

urban land cover structure; multi-temporal remote sensing; urbanization; spatial analysis; Hanoi City.
Received 2026-06-23
Published 2026-10-30

Abstract

Urban land cover change is one of the key indicators reflecting spatial development processes and the degree of urbanization in large cities. During the period from 2005 to 2025, Hanoi experienced rapid urban expansion, resulting in significant changes in the structure of surface land cover. This paper presents an assessment of urban land cover transformation in Hanoi through the integration of multi-temporal remote sensing data and spatial analysis techniques. Satellite imagery acquired for the study years of 2005, 2015, and 2025 was collected and processed to generate urban land cover maps consisting of four major classes: built-up land, bare land, vegetation cover, and water bodies. Based on land cover classification results and time-series change analysis, the study quantified the extent of transitions among land cover types and evaluated the spatial patterns of urban development.The results indicate that the proportion of built-up land increased continuously throughout the study period and expanded predominantly from central urban districts toward suburban areas, whereas the areas of bare land, water bodies, and part of the vegetation cover showed a declining trend. The land cover transformation process exhibited characteristics of increasing construction density combined with outward urban expansion along infrastructure development corridors and newly developed urban zones. The findings demonstrate the effectiveness of using multi-temporal remote sensing data for monitoring urban land cover dynamics and provide a scientific basis for land management, spatial planning, and sustainable urban development strategies in Hanoi.

Downloads

Download data is not yet available.

References

1. Tran, D. T., Xu, D., & Liu, B. (2019). Assessment of Urban Land Cover Change Based on Landsat Satellite Data: A Case Study from Hanoi, Vietnam. IOP Conference Series: Earth and Environmental Science, 384, 012150. DOI 10.1088/1755-1315/384/1/012150 DOI: https://doi.org/10.1088/1755-1315/384/1/012150

2. Hoang Anh Huy. (2017). Assessment of Fractional Vegetation Cover Changes in Some Urban and Sub-urban Areas of Hanoi Using Multi-spectral and Multi-temporal LANDSAT Images. VNU Journal of Science: Earth and Environmental Sciences, 33(2). https://doi.org/10.25073/2588-1094/vnuees.4097 DOI: https://doi.org/10.25073/2588-1094/vnuees.4097

3. Nguyen, T. T. (2020). Landsat Time-series Images-based Urban Heat Island Analysis: The Effects of Changes in Vegetation and Built-up Land on Land Surface Temperature in Summer in the Hanoi Metropolitan Area, Vietnam. Environment and Natural Resources Journal, 18(2). DOI: 10.32526/ennrj.18.2.2020.17 DOI: https://doi.org/10.32526/ennrj.18.2.2020.17

4. Sharma, A., Liu, X., & Yang, X. (2017). Land Cover Classification from Multi-temporal, Multi-spectral Remotely Sensed Imagery using Patch-Based Recurrent Neural Networks. https://doi.org/10.1016/j.neunet.2018.05.019. DOI: https://doi.org/10.1016/j.neunet.2018.05.019

5. Lê Thị Thu Hà (2020), Ứng dụng công nghệ viễn thám và GIS đánh giá sự biến động lớp phủ thực vật thành phố Cẩm Phả giai đoạn 2000-2020 do tác động của hoạt động khai thác khoáng sản, Tạp chí Khoa học công nghệ mỏ, tr 63-70.

6. Quynh, H. T., et al. (2025). Assessment of Vegetation Cover Dynamics and Its Relationship with Urbanization in Hanoi from 2000 to 2023 Using Multi-temporal Remote Sensing Data. VNU Journal of Science: Earth and Environmental Sciences. https://doi.org/10.25073/2588-1094/vnuees.5319 DOI: https://doi.org/10.25073/2588-1094/vnuees.5319

7. Le, T. M. P., Vu, L. A., & Nguyen, H. Q. (2021). Research on Urban Land Use Change in Ha Noi, Viet Nam Using Remote Sensing and GIS for Planning Oriented Work. International Journal of Sustainable Construction Engineering and Technology. https://doi.org/10.30880/ijscet.2021.12.03.00

8. Myint, S. W., Gober, P., Brazel, A., Grossman-Clarke, S., & Weng, Q. (2011). Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sensing of Environment, 115(5), 1145–1161. https://doi.org/10.1016/j.rse.2010.12.017. DOI: https://doi.org/10.1016/j.rse.2010.12.017

9. Whiteside, T. G., Boggs, G. S., & Maier, S. W. (2011). Comparing object-based and pixel-based classifications for mapping savannas. International Journal of Applied Earth Observation and Geoinformation, 13(6), 884–893. https://doi.org/10.1016/j.jag.2011.06.008. DOI: https://doi.org/10.1016/j.jag.2011.06.008

10. Blaschke, T. (2010). Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1), 2–16. https://doi.org/10.1016/j.isprsjprs.2009.06.004 DOI: https://doi.org/10.1016/j.isprsjprs.2009.06.004

Published

2026-10-30

How to Cite

[1]
“Assessment of Urban Land Cover structure Change in Hanoi City from 2005 to 2025 Using Multi-Temporal Remote Sensing Data”, GeoGIS, vol. 12, no. 05, pp. 12–23, Oct. 2026, doi: 10.67484/GeoGIS.83.1205.2026.

Most read articles by the same author(s)

Similar Articles

1-10 of 76

You may also start an advanced similarity search for this article.