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Flood mapping using VHR satellite imagery: a comparison between different classification approaches

机译:使用VHR卫星图像进行洪水制图:不同分类方法之间的比较

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摘要

Various regions in Europe have suffered from severe flooding over the last decades. Flood disasters often have a broad extent and a high frequency. They are considered the most devastating natural hazards because of the tremendous fatalities, injuries, property damages, economic and social disruption that they cause. In this context, Earth Observation techniques have become a key tool for flood risk and damage assessment. In particular, remote sensing facilitates flood surveying, providing valuable information, e.g. flood occurrence, intensity and progress of flood inundation, spurs and embankments affected/threatened. The present work aims to investigate the use of Very High Resolution satellite imagery for mapping flood-affected areas. The case study is the November 2013 flood event which occurred in Sardinia region (Italy), affecting a total of 2,700 people and killing 18 persons. The investigated zone extends for 28 km2 along the Posada river, from the Maccheronis dam to the mouth in the Tyrrhenian sea. A post-event SPOT6 image was processed by means of different classification methods, in order to produce the flood map of the analysed area. The unsupervised classification algorithm ISODATA was tested. A pixel-based supervised technique was applied using the Maximum Likelihood algorithm; moreover, the SPOT 6 image was processed by means of object-oriented approaches. The produced flood maps were compared among each other and with an independent data source, in order to evaluate the performance of each method, also in terms of time demand.
机译:在过去的几十年中,欧洲各个地区遭受了严重的洪灾。洪水灾害往往范围广泛且频发。由于它们造成的巨大死亡,伤害,财产损失,经济和社会破坏,它们被认为是最具破坏性的自然灾害。在这种情况下,对地观测技术已成为洪水风险和破坏评估的关键工具。尤其是,遥感技术可以促进洪水调查,提供有价值的信息,例如洪水的发生,洪水泛滥的强度和进度,受潮/威胁的马刺和堤防。本工作旨在调查使用超高分辨率卫星影像绘制受灾地区的地图。案例研究是2013年11月在撒丁岛地区(意大利)发生的洪水事件,共影响2700人,造成18人死亡。从Maccheronis大坝到第勒尼安海河入海口,被调查区域沿Posada河延伸28平方公里。通过使用不同的分类方法对事件后的SPOT6图像进行处理,以生成分析区域的洪水地图。测试了无监督分类算法ISODATA。使用最大似然算法应用了基于像素的监督技术;此外,通过面向对象的方法处理了SPOT 6图像。将生成的洪水地图彼此之间进行比较,并与一个独立的数据源进行比较,以评估每种方法的性能,以及时间需求。

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