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ASSESSMENT OF FLOODED AREAS PROJECTIONS AND FLOODS POTENTIAL IMPACTS APPLYING REMOTE SENSING IMAGERY AND DEMOGRAPHIC DATA

机译:应用遥感图像和人口统计数据的洪水区预测和洪水潜在影响的评估

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Assessing vulnerability and potential impacts associated with extreme discharges requires an accurate topographic description in order to estimate the extension of flooded areas. However, in most populated regions, topographic data obtained by in-situ measurements is not available. In this case, digital elevation models derived from remote sensing date are usually applied. Moreover, this digital elevation models have intrinsic errors that introduce bigger uncertainty in results than the associated to hydrological projections. On the other hand, estimations of flooded areas through remote sensing images provide accurate information, which could be used for the construction of river level-flooded area relationships regarding vulnerability assessment. In this work, this approach is applied for the city of Porto Velho in the Brazilian Amazonia to assess potential vulnerability to floods associated with climate change projections. The approach is validated using census data, provided by the Brazilian Institute of Geography and Statistics, and information about socio-economical injuries associated to historical floods, provided by the Brazilian Civil Defence. Hydrological projections under climate change are carried out using several downscaling of climate projections as inputs in a hydrological model. Results show more accurate estimation of flood impacts than the obtained using digital elevation models derivate from remote sensing data. This reduces uncertainties in the assessment of vulnerability to floods associated with climate change in the region.
机译:评估与极端放电相关的漏洞和潜在影响需要准确的地形描述,以估计淹没区域的延伸。然而,在大多数人填充的区域中,通过原位测量获得的地形数据不可用。在这种情况下,通常应用来自遥感日期的数字高程模型。此外,这种数字高度模型具有内在的误差,其在结果中引入更大的不确定性而不是与水文投影相关联。另一方面,通过遥感图像的淹没区域的估计提供了准确的信息,可用于建造关于漏洞评估的河流淹没的区域关系。在这项工作中,这种方法适用于巴西亚马西亚的波尔图维罗市,以评估与气候变化预测相关的洪水的潜在脆弱性。该方法使用巴西地理和统计研究所提供的人口普查数据,以及巴西民防提供的历史洪水相关的社会经济伤害的信息。气候变化下的水文预测是使用几种气候预测次数作为水文模型的输入进行的。结果显示比使用从遥感数据衍生的数字高度模型获得的洪水冲击更准确地估算。这减少了对与该地区气候变化相关的漏洞评估的不确定性。

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