Remote sensing for urban Green Spaces: Technology for sustainable development and quality of life in the capital
Dr Nguyen Kim Anh at the Workshop on 3D Modelling of Urban Green Spaces from UAV Images
Amid rapid urbanisation in major cities such as Ha Noi, golf courses have increasingly emerged as a new form of urban green space – serving recreational needs while also playing a role in regulating the local microclimate. However, the rapid expansion of golf courses raises challenges in terms of land use, water resources, chemical maintenance, and their impact on the surrounding environment.
The project presents an innovative approach, applying multi-temporal remote sensing data combined with Geographic Information Systems (GIS) to track land-use change caused by golf course construction and to assess its impact on surface temperature – a critical indicator of urban microclimate change.
Using Sentinel-2 and Landsat satellite imagery, the research team built a thematic database on Ha Noi’s urban golf courses and tested two methods for detecting and monitoring them: (1) analysis of the Normalised Difference Vegetation Index (NDVI), and (2) object-based recognition relying on morphological features such as turf, sand bunkers, and fairways. Results showed that under tropical climatic conditions, NDVI was limited due to the spectral similarity among different vegetation types. In contrast, feature-based recognition combined with spectral mixing techniques proved more effective in accurately classifying and delineating golf courses.
The study not only contributes to monitoring land conversion dynamics for golf course development but also provides scientific evidence of their impact on local temperatures – vital information for urban planning and climate change adaptation. This is a prime example of connecting science and technology with modern urban life, aiming towards sustainable development and improving community quality of life.
Satellite imagery: Sand bunkers are easily recognisable (left), while the geometric shapes of golf courses are clearly detected (right). (Source: Nguyen et al. 2025)
Spectral signals: Sand (blue), Grass (green), and Mixed (red). (Source: Nguyen et al. 2025)
Dr Nguyen Kim Anh stated that this was an encouraging outcome of the research project. It also demonstrated the seriousness, creativity, and high-tech research capacity of scientists at Vietnam Academy of Science and Technology. He further shared that another notable achievement of the project is an international article entitled “Leveraging Remote Sensing and Machine Learning for Sustainable Management of Hanoi's Urban Golf Courses”, soon to be published in Progress in Earth and Planetary Science (PEPS) – a prestigious international journal in Earth sciences.
Translated by Tuyet Nhung
Link to Vietnamese version
