Building Structure Mapping on Level Terrains and Sea Surfaces in Vietnam Article Swipe
Khanh Duc Ngo
,
S. V. Nghiem
,
Alex M. Lechner
,
Tuong Thuy Vu
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/rs13132439
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/rs13132439
Mapping building structures is crucial for environmental change and impact assessment, and is especially important to accurately estimate fossil fuel CO2 emissions from human settlements. In this regard, the objective of this study is to develop novel and robust methods using time-series data acquired from Sentinel-1 synthetic aperture radar (SAR) to identify and map persistent building structures from coastal plains to high plateaus, as well as on the sea surface. From annual composites of SAR data in the two-dimensional VV-VH polarization space, we determined the VV-VH domain for detecting building structures, whose persistence was defined based on the number of times that a pixel was identified as a building in time-series data. Moreover, the algorithm accounted for misclassified buildings due to water-tree interactions in radar signatures and due to topography effects in complex mountainous landforms. The methods were tested in five cities (Bạc Liêu, Cà Mau, Sóc Trăng, Tân An, and Phan Thiết) in Vietnam located in different socio-environmental regions with a range of urban configurations. Using in-situ data and field observations, we validated the methods and found that the results were accurate, with an average false negative rate of 10.9% and average false positive rate of 6.4% for building detection. The algorithm could also detect small houses in rural settlements and in small islands such as in Hòn Sơn and Hòn Tre. Over sea surfaces, the algorithm effectively identified lines of power poles connecting islands to the mainland, guard shacks in marine blood clam farms in Kiên Giang, individual wind towers in the off-shore wind farm in Bạc Liêu, and oilrigs in the Vũng Tàu oil fields. The new approach was developed to be robust against variations in SAR incidence and azimuth angles. The results demonstrated the potential use of satellite dual-polarization SAR to identify persistent building structures annually across rural–urban landscapes and on sea surfaces with different environmental conditions.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs13132439
- https://www.mdpi.com/2072-4292/13/13/2439/pdf
- OA Status
- gold
- Cited By
- 7
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3175684261
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3175684261Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/rs13132439Digital Object Identifier
- Title
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Building Structure Mapping on Level Terrains and Sea Surfaces in VietnamWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-06-22Full publication date if available
- Authors
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Khanh Duc Ngo, S. V. Nghiem, Alex M. Lechner, Tuong Thuy VuList of authors in order
- Landing page
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https://doi.org/10.3390/rs13132439Publisher landing page
- PDF URL
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https://www.mdpi.com/2072-4292/13/13/2439/pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2072-4292/13/13/2439/pdfDirect OA link when available
- Concepts
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Landform, Terrain, Remote sensing, Synthetic aperture radar, Human settlement, Series (stratigraphy), Geology, Physical geography, Environmental science, Geography, Cartography, Geomorphology, Archaeology, PaleontologyTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2025: 2, 2024: 3, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
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29Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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