DOI: 10.1016/j.jag.2014.06.017
Scopus记录号: 2-s2.0-84920671345
论文题名: Accounting for image uncertainty in SAR-based flood mapping
作者: Giustarini L ; , Vernieuwe H ; , Verwaeren J ; , Chini M ; , Hostache R ; , Matgen P ; , Verhoest N ; E ; C ; , de Baets B
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 34, 期: 1 起始页码: 70
结束页码: 77
语种: 英语
英文关键词: Bootstrap
; Flood mapping
; Speckle
; Synthetic aperture radar
; Uncertainty
Scopus关键词: bootstrapping
; flood
; image analysis
; mapping
; remote sensing
; speckle
; synthetic aperture radar
; uncertainty analysis
英文摘要: Operational flood mitigation and flood modeling activities benefit from a rapid and automated flood mapping procedure. A valuable information source for such a flood mapping procedure can be remote sensing synthetic aperture radar (SAR) data. In order to be reliable, an objective characterization of the uncertainty associated with the flood maps is required. This work focuses on speckle uncertainty associated with the SAR data and introduces the use of anon-parametric bootstrap method to take into account this uncertainty on the resulting flood maps. From several synthetic images, constructed through bootstrapping the original image, flood maps are delineated. The accuracy of these flood maps is also evaluated w.r.t. an independent validation data set,obtaining, in the two test cases analyzed in this paper, F-values (i.e. values of the Jaccard coefficient) comprised between 0.50 and 0.65. This method is further compared to an image segmentation method for speckle analysis, with which similar results are obtained. The uncertainty analysis of the ensemble of bootstrapped synthetic images was found to be representative of image speckle, with the advantage that no segmentation and speckle estimations are required. Furthermore, this work assesses to what extent the bootstrap ensemble size can be reduced while remaining representative of the original ensemble, as operational applications would clearly benefit from such reduced ensemble sizes. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79504
Appears in Collections: 气候变化事实与影响
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作者单位: Centre de Recherche Public - Gabriel Lippmann, Belvaux, Luxembourg; KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure links 653, Gent, Belgium; Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, Gent, Belgium
Recommended Citation:
Giustarini L,, Vernieuwe H,, Verwaeren J,et al. Accounting for image uncertainty in SAR-based flood mapping[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,34(1)