{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:34:04Z","timestamp":1772822044721,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,4,2]],"date-time":"2023-04-02T00:00:00Z","timestamp":1680393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Atkins Global","award":["20000021"],"award-info":[{"award-number":["20000021"]}]},{"name":"Atkins Global","award":["EP\/N010329\/1"],"award-info":[{"award-number":["EP\/N010329\/1"]}]},{"name":"Engineering and Physical Sciences Research Council (EPSRC)","award":["20000021"],"award-info":[{"award-number":["20000021"]}]},{"name":"Engineering and Physical Sciences Research Council (EPSRC)","award":["EP\/N010329\/1"],"award-info":[{"award-number":["EP\/N010329\/1"]}]},{"DOI":"10.13039\/501100000266","name":"Remote Sensing MDPI","doi-asserted-by":"publisher","award":["20000021"],"award-info":[{"award-number":["20000021"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Remote Sensing MDPI","doi-asserted-by":"publisher","award":["EP\/N010329\/1"],"award-info":[{"award-number":["EP\/N010329\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the increase in rainfall intensity, population, and urbanised areas, surface water flooding (SWF) is an increasing concern impacting properties, businesses, and human lives. Previous studies have shown that microtopography significantly influences flow paths, flow direction, and velocity, impacting flood extent and depth, particularly for the shallow flow associated with urban SWF. This study compares two survey strategies commonly used by flood practitioners, S1 (using Unmanned Aerial Systems-based RGB data) and S2 (using manned aircraft with LiDAR scanners), to develop guidelines on where to use each strategy to better characterise microtopography for a range of flood features. The difference between S1 and S2 in elevation and their accuracies were assessed using both traditional and robust statistical measures. The results showed that the difference in elevation between S1 and S2 varies between 11 cm and 37 cm on different land use and microtopographic flood features. Similarly, the accuracy of S1 ranges between 3 cm and 70 cm, and the accuracy of S2 ranges between 3.8 cm and 30.3 cm on different microtopographic flood features. Thus, this study suggests that the flood features of interest in any given flood study would be key to select the most suitable survey strategy. A decision framework was developed to inform data collection and integration of the two surveying strategies to better characterise microtopographic features. The findings from this study will help improve the microtopographic representation of flood features in flood models and, thus, increase the ability to identify high flood-risk prompt areas accurately. It would also help manage and maintain drainage assets, spatial planning of sustainable drainage systems, and property level flood resilience and insurance to better adapt to the effects of climate change. This study is another step towards standardising flood extent and impact surveying strategies.<\/jats:p>","DOI":"10.3390\/rs15071912","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T02:10:13Z","timestamp":1680487813000},"page":"1912","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Accuracy Assessment of Surveying Strategies for the Characterization of Microtopographic Features That Influence Surface Water Flooding"],"prefix":"10.3390","volume":"15","author":[{"given":"Rakhee","family":"Ramachandran","sequence":"first","affiliation":[{"name":"School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0939-235X","authenticated-orcid":false,"given":"Yadira","family":"Baj\u00f3n Fern\u00e1ndez","sequence":"additional","affiliation":[{"name":"School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ian","family":"Truckell","sequence":"additional","affiliation":[{"name":"School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos","family":"Constantino","sequence":"additional","affiliation":[{"name":"Atkins Limited, One St Aldates, St Aldate\u2019s, Oxford OX1 1DE, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Casselden","sequence":"additional","affiliation":[{"name":"Atkins Limited, The Hub, 500 Park Avenue, Aztec West, Almondsbury, Bristol BS32 4RZ, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul","family":"Leinster","sequence":"additional","affiliation":[{"name":"School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4169-3099","authenticated-orcid":false,"given":"M\u00f3nica","family":"Rivas Casado","sequence":"additional","affiliation":[{"name":"School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,2]]},"reference":[{"key":"ref_1","unstructured":"World Meteorological Organisation WMO (2021, May 16). 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