Show simple item record

dc.creatorGebremichael, Esayas
dc.creatorMolthan, Andrew L.
dc.creatorBell, Jordan R.
dc.creatorSchultz, Lori A.
dc.creatorHain, Christopher
dc.date.accessioned2021-01-14T22:08:10Z
dc.date.available2021-01-14T22:08:10Z
dc.date.issued2020-11-01
dc.identifier.urihttps://doi.org/10.3390/rs12213588
dc.identifier.urihttps://repository.tcu.edu/handle/116099117/43060
dc.identifier.urihttps://www.mdpi.com/2072-4292/12/21/3588
dc.description.abstractThe Greater Houston metropolitan area has experienced recurring flooding events in the past two decades related to tropical cyclones and heavy inland rainfall. With the projected recurrence of severe weather events, an approach that outlines the susceptibility of different localities within the study area to potential floods based on analyses of the impacts from earlier events would be beneficial. We applied a novel C-band Sentinel-1 Synthetic Aperture Radar (SAR)-based flood detection method to map floodwater distribution following three recent severe weather events with the goal of identifying areas that are prone to future flood hazards. Attempts were made to calibrate and validate the C-band-based results and analyses to compensate for possible sources of error. These included qualitative and quantitative assessments on L-band aerial SAR data, as well as aerial imagery acquired after one of the events. The findings included the following: (1) most urban centers of Harris county, with few exceptions, are not believed to be prone to flooding hazards in contrast to the densely populated areas on the outskirts of Harris county; (2) nearly 44% of the mapped flood-prone areas lie within a 1 km distance of major drainage networks; (3) areas experiencing high subsidence rates have persistently experienced flooding, possibly exacerbated by morphological changes to the land surface induced by subsidence.
dc.language.isoen_USen_US
dc.publisherMultidisciplinary Digital Publishing Institute
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceRemote Sensing
dc.subjectSentinel-1
dc.subjectcoherence change detection
dc.subjectUAVSAR
dc.subjectflood hazard risk assessment
dc.titleFlood Hazard and Risk Assessment of Extreme Weather Events Using Synthetic Aperture Radar and Auxiliary Data: A Case Study
dc.typeArticle
dc.rights.holder2020 Gebremichael et al
dc.rights.licenseCC BY 4.0
local.collegeCollege of Science and Engineering
local.departmentGeological Sciences
local.personsGebremichael (GEOL)


Files in this item

Thumbnail
This item appears in the following Collection(s)

Show simple item record

https://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/