Details:

Journal Title:
JAWRA Journal of the American Water Resources Association
Personal Author:
Munasinghe, Dinuke ; Cohen, Sagy ; Huang, Yu‐Fen ; Tsang, Yin‐Phan ; Zhang, Jiaqi ; ... More +
Munasinghe, Dinuke ; Cohen, Sagy ; Huang, Yu‐Fen ; Tsang, Yin‐Phan ; Zhang, Jiaqi ; Fang, Zheng Less -
NOAA Program & Office:
NOAA General Documents
Description:
The objective of this study was to determine the accuracy of five different digital image processing techniques to map flood inundation extent with Landsat 8–Operational Land Imager satellite imagery. The May 2016 flooding event in the Hempstead region of the Brazos River, Texas is used as a case study for this first comprehensive comparison of classification techniques of its kind. Five flood water classification techniques (i.e., supervised classification, unsupervised classification, delta‐cue change detection, Normalized Difference Water Index [NDWI], modified NDWI [MNDWI]) were implemented to characterize flooded regions. To identify flood water obscured by cloud cover, a digital elevation model (DEM)–based approach was employed. Classified floods were compared using an Advanced Fitness Index to a “reference flood map” created based on manual digitization, as well as other data sources, using the same satellite image. Supervised classification yielded the highest accuracy of 86.4%, while unsupervised, MNDWI, and NDWI closely followed at 79.6%, 77.3%, and 77.1%, respectively. Delta‐cue change detection yielded the lowest accuracy with 70.1%. Thus, supervised classification is recommended for flood water classification and inundation map generation under these settings. The DEM‐based approach used to identify cloud‐obscured flood water pixels was found reliable and easy to apply. It is therefore recommended for regions with relatively flat topography.
Keywords:
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Earth-Surface Processes Ecology Water Science And Technology
Source:
JAWRA Journal of the American Water Resources Association, 54(4), 834-846
DOI:
https://doi.org/10.1111/1752-1688.12626
ISSN:
1093-474X;1752-1688;
Format:
PDF
Publisher:
Wiley
Document Type:
Journal Article
Rights Information:
Accepted Manuscript
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:af568518c09b3279eba76c64996490f4e9cf339e26dafc7c791e83660c66bcc3
Download URL:
https://repository.library.noaa.gov/view/noaa/57043/noaa_57043_DS1.pdf
File Type:

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