{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T11:17:02Z","timestamp":1774351022881,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,6,22]],"date-time":"2021-06-22T00:00:00Z","timestamp":1624320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["80NM0018F0590"],"award-info":[{"award-number":["80NM0018F0590"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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 (B\u1ea1c Li\u00eau, C\u00e0 Mau, S\u00f3c Tr\u0103ng, T\u00e2n An, and Phan Thi\u1ebft) 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 H\u00f2n S\u01a1n and H\u00f2n 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 Ki\u00ean Giang, individual wind towers in the off-shore wind farm in B\u1ea1c Li\u00eau, and oilrigs in the V\u0169ng T\u00e0u 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\u2013urban landscapes and on sea surfaces with different environmental conditions.<\/jats:p>","DOI":"10.3390\/rs13132439","type":"journal-article","created":{"date-parts":[[2021,6,22]],"date-time":"2021-06-22T22:10:59Z","timestamp":1624399859000},"page":"2439","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Building Structure Mapping on Level Terrains and Sea Surfaces in Vietnam"],"prefix":"10.3390","volume":"13","author":[{"given":"Khanh","family":"Ngo","sequence":"first","affiliation":[{"name":"School of Environmental and Geographical Sciences, University of Nottingham Malaysia, Semenyih 43500, Selangor, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4592-2979","authenticated-orcid":false,"given":"Son","family":"Nghiem","sequence":"additional","affiliation":[{"name":"NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2050-9480","authenticated-orcid":false,"given":"Alex","family":"Lechner","sequence":"additional","affiliation":[{"name":"Lincoln Centre for Water and Planetary Health, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6656-8016","authenticated-orcid":false,"given":"Tuong","family":"Vu","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Science, Curtin University, Miri 98009, Sarawak, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1111\/j.1467-9671.2009.01171.x","article-title":"GIS Approach to Estimation of Building Population for Micro-Spatial Analysis","volume":"13","author":"Lwin","year":"2009","journal-title":"Trans. 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