Flooded with Error: Handling Uncertainty in SRTM for the Assessment of Sea Level Rise in the Mississippi River Delta.
Digital elevation data are essential to estimate coastal vulnerability to flooding due to sea-level rise. Shuttle Radar Topography Mission (SRTM) 1 arc-second global is considered the best free global digital elevation data set available. Inundation estimates from SRTM, however, are subject to uncer...
| Publicado en: | Professional Geographer Vol. 73; no. 3; pp. 404 - 413 |
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| Autores principales: | , |
| Formato: | Artículo |
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Taylor & Francis Ltd
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=151481064&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 151481064 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00330124 PGG jtl: Professional Geographer issn: 00330124 maglogo: Y pubinfo: dt: 2021 vid: 73 iid: 3 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 151481064 10.1080/00330124.2021.1898992 ppf: 404 ppct: 9 formats: tig: atl: Flooded with Error: Handling Uncertainty in SRTM for the Assessment of Sea Level Rise in the Mississippi River Delta. aug: au: Kadhim, Ameen A. Shortridge, Ashton M. affil: University of Karbala and Michigan State University Michigan State University su: Uncertainty Sea level Marshes Altitudes Statistical errors sug: subj: Uncertainty Sea level Marshes Altitudes Statistical errors keyword: error propagation modeling inundation model (bathtub) Mississippi River Delta region sea-level rise error propagation modeling inundation model (bathtub) Mississippi River Delta region sea-level rise ab: Digital elevation data are essential to estimate coastal vulnerability to flooding due to sea-level rise. Shuttle Radar Topography Mission (SRTM) 1 arc-second global is considered the best free global digital elevation data set available. Inundation estimates from SRTM, however, are subject to uncertainty due to inaccuracies in the elevation data. Small systematic errors in low, flat areas can generate large errors in inundation models, and SRTM is subject to positive bias in the presence of vegetation canopy, such as along channels and within marshes. In this study, we conducted an error assessment and developed a statistical error model for SRTM to improve the quality of elevation data in the Mississippi River Delta (MRD) region. Vegetation cover, SRTM elevation, and slope were found to be closely associated with SRTM error for a random sample of 10,000 small sites across the MRD region, with an ordinary least squares regression model using these variables explaining over 80 percent of the variation in error. Residuals from this model were spatially autocorrelated, and a variogram model was readily fit to them. We conclude by speculating on the utility of application of this model, developed for the MRD region, to similar near-coastal riverine regions around the world. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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