首页> 外文OA文献 >APPLICATIONS OF SENTINEL-1 SYNTHETIC APERTURE RADAR IMAGERY FOR FLOODS DAMAGE ASSESSMENT: A CASE STUDY OF NAKHON SI THAMMARAT, THAILAND
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APPLICATIONS OF SENTINEL-1 SYNTHETIC APERTURE RADAR IMAGERY FOR FLOODS DAMAGE ASSESSMENT: A CASE STUDY OF NAKHON SI THAMMARAT, THAILAND

机译:Sentinel-1合成孔径雷达图像在洪水损伤评估中的应用 - 以泰国Nakhon Si Thammarat为例

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摘要

Flooding is one of the major disasters occurring in various parts of the world. Estimation of economic loss due to flood often becomes necessary for flood damage mitigation. This present practice to carry out post flood survey to estimate damage, which is a laborious and time-consuming task. This paper presents a framework of rapid estimation of flood damage using SAR earth observation satellite data.In Nakhon Si Thammarat, a southern province in Thailand, flooding is a recurrent event affecting the entire province, especially the urban area. Every year, it causes lives and damages to infrastructure, agricultural production and severely affects local economic development. In order to monitor and estimate flood damages in near-real time, numerous techniques can be used, from a simply digitizing on maps, to using detailed surveys or remote sensing techniques. However, when using the last-mentioned technique, the results are conditioned by the time of data acquisition (day or night) as well as by weather conditions. Although, these impediments can be surpassed by using RADAR satellite imagery. The aim of this study is to delineate the land surface of Chian Yai, Pak Phanang and Hua Sai districts of that was affected by floods in December 2018 and January 2019. For this case study, Sentinel-1 C-Band SAR data provided by ESA (European Space Agency) were used. The data sets were taken before and after the flood took place, all within 1 days and were processed using Sentinel Toolbox. Cropland mapping has been carried out to assess the agricultural loss in study area using Sentinel-1 SAR data. The thematic accuracy has been assessed for cropland classification for test site shows encouraging overall accuracy as 82.63 % and kappa coefficients (κ) as 0.78.
机译:洪水是世界各地发生的主要灾害之一。洪水损害减缓的洪水估计估计经济损失通常是必要的。本实践实践开展洪水调查估算损害,这是一种费力且耗时的任务。本文采用SAR地球观测卫星数据迅速估算洪水损伤的框架。在泰国的南部南部,洪水中,洪水是一种经常发生的事件,影响整个省,特别是市区。每年,它会导致基础设施,农业生产和严重影响当地经济发展的生命和损害。为了在近实时监测和估计洪水损坏,可以从地图上简单地数字化使用许多技术,以使用详细的调查或遥感技术。然而,在使用上述技术时,结果是通过数据采集(日或夜间)以及天气条件的时间调节。虽然,通过使用雷达卫星图像可以超越这些障碍。本研究的目的是描绘Chian yai,Pak Phanang和华塞地区的土地面积于2018年12月和2019年1月的洪水影响。在本案研究中,ESA提供的Sentinel-1 C-BAND SAR数据(欧洲空间机构)被使用。在洪水发生之前以及在1天内进行的数据集进行了拍摄,并使用Sentinel工具箱进行处理。已经进行了农田映射,以评估使用Sentinel-1 SAR数据的研究区域的农业损失。针对测试场所的农作物分类评估了主题准确度,显示令人鼓舞的总体准确性为82.63%,Kappa系数(κ)为0.78。

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