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Effectiveness of RGB Imagery from Diverse Sources for Real-Time Urban Flood Water Mapping

机译:RGB图像从各种资源中的RGB图像实时城市洪水水平

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Timeliness is a critical requirement for the provision of information during disasters such as floods in urban areas. Images from RGB remote sensors (such as those carried on satellites, aircraft, UAVs and on the International Space Station) are potentially cost-effective data sources for real-time applications. This paper describes work undertaken to evaluate two high resolution RGB image datasets for rapid response mapping and monitoring of urban visible flood water extent. Our overall goal is to develop a robust methodology for universally applicable extraction of the flooded area information. The methods and results are demonstrated as a case study of the characterization and delineation of visible flood extent and its changes that occurred during the June 2013 city of Calgary flood event. The input imagery included very high resolution aerial photography and imagery acquired with the International Space Station's (ISS) SERVIR Environmental Research and Visualization System (ISERV). The methodology development involved analysis and comparison of the spectral responses of urban land surface types, shadows and turbid flood water. Based on an understanding of these spectral properties, a universally applicable method was developed and assessed to extract visible flood water from RGB imagery.
机译:及时性是在城市地区洪水等灾害期间提供信息的关键要求。来自RGB远程传感器的图像(例如卫星,飞机,无人机和国际空间站上携带的图像)是用于实时应用的可能性有效的数据源。本文介绍了对评估两个高分辨率RGB图像数据集进行的工作,用于快速响应映射和城市可见洪水范围的监测。我们的总体目标是为普遍适用的洪水区域信息开发一种强大的方法。证明方法和结果是对可见洪水范围的表征和描绘的案例研究及其在2013年6月的卡尔加里洪水事件中发生的变化。输入图像包括使用国际空间站(ISS)Servir环境研究和可视化系统(Iserv)获得的非常高分辨率的航空摄影和图像。方法发展涉及城市陆地面积,阴影和浑水水的光谱响应的分析与比较。基于对这些光谱性质的理解,开发和评估了普遍适用的方法,以从RGB图像提取可见的洪水。

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