气候变化领域集成服务门户(CCPortal): Flood mapping under vegetation using single SAR acquisitions

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DOI	10.1016/j.rse.2019.111582
	Flood mapping under vegetation using single SAR acquisitions
	Grimaldi S.; Xu J.; Li Y.; Pauwels V.R.N.; Walker J.P.
发表日期	2020
ISSN	00344257
卷号	237
英文摘要	Synthetic Aperture Radar (SAR) enables 24-hour, all-weather flood monitoring. However, accurate detection of inundated areas can be hindered by the extremely complicated electromagnetic interaction phenomena between microwave pulses, and horizontal and vertical targets. This manuscript focuses on the problem of inundation mapping in areas with emerging vegetation, where spatial and seasonal heterogeneity makes the systematic distinction between dry and flooded backscatter response even more difficult. In this context, image interpretation algorithms have mostly used detailed field data and reference image(s) to implement electromagnetic models or change detection techniques. However, field data are rare, and despite the increasing availability of SAR acquisitions, adequate reference image(s) might not be readily available, especially for fine resolution acquisitions. To by-pass this problem, this study presents an algorithm for automatic flood mapping in areas with emerging vegetation when only single SAR acquisitions and common ancillary data are available. First, probability binning is used for statistical analysis of the backscatter response of wet and dry vegetation for different land cover types. This analysis is then complemented with information on land use, morphology and context within a fuzzy logic approach. The algorithm was applied to three fine resolution images (one ALOS-PALSAR and two COSMO-SkyMed) acquired during the January 2011 flood in the Condamine-Balonne catchment (Australia). Flood extent layers derived from optical images were used as validation data, demonstrating that the proposed algorithm had an overall accuracy higher than 80% for all case studies. Notwithstanding the difficulty to fully discriminate between dry and flooded vegetation backscatter heterogeneity using a single SAR image, this paper provides an automatic, data parsimonious algorithm for the detection of floods under vegetation. © 2019 Elsevier Inc.
英文关键词	Flooded vegetation; Fuzzy logic; Inundation extent; SAR
语种	英语
scopus关键词	Backscattering; Catchments; Computer circuits; Floods; Fuzzy logic; Geometrical optics; Land use; Mapping; Synthetic aperture radar; Vegetation; Electromagnetic interactions; Electromagnetic models; Fine-resolution images; Fuzzy logic approach; Image interpretation; Inundation extent; Inundation mappings; Overall accuracies; Radar imaging; accuracy assessment; algorithm; backscatter; catchment; flood; fuzzy mathematics; heterogeneity; land cover; mapping method; synthetic aperture radar; vegetation type; Australia
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179516
作者单位	Department of Civil Engineering, Monash University, Clayton, Victoria, Australia; WMAwater, Newtown, Victoria, Australia
推荐引用方式 GB/T 7714	Grimaldi S.,Xu J.,Li Y.,et al. Flood mapping under vegetation using single SAR acquisitions[J],2020,237.
APA	Grimaldi S.,Xu J.,Li Y.,Pauwels V.R.N.,&Walker J.P..(2020).Flood mapping under vegetation using single SAR acquisitions.Remote Sensing of Environment,237.
MLA	Grimaldi S.,et al."Flood mapping under vegetation using single SAR acquisitions".Remote Sensing of Environment 237(2020).