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DETECTING FLOODED LOCATION USING SAR DATA AND ASSESSMENT OF POST-FLOODED CONDITION

机译:使用SAR数据检测洪灾地点并评估洪灾后的状况

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The aim of this study is to detect flooded location using SAR data and assessment of post-flooded conditions using a Geographic Information System (GIS) and SAR (Synthetic Aperture Radar) data images.The temporal characteristics of radar response form flooded were analyzed throughout the 2002summer flooded season.Flooded locations were identified by change detection technique of RADARSAT SAR data images. Multiple scenes of Radarsat SAR images were acquired before, during, and after the flood inundation. From the interpretation of colour composite imagery of the multi-temporal SAR data, as well as from the temporal profiles of radar backscatter, seven types of Landcover were separable according to flooded and post-flooded recovery conditions. Landover map of 2000.07 was classed 7 categories by water, urban, bare ground, marsh, grassland, forest and farming.As results, farming area showed 14.52km~2, forest flooded area showed 3.50km~2, %, grassland flooded area showed 1.06km~2, ground flooded area was accounted for 0.09km~2and urban flooded area showed 0.04km~2.The actual flooded damage to the standing farming crop depends on the duration of the flood and on subsequent recovery status. We found that image data acquired during and after flooded is necessary to assess accurately flood damage to farming area.From now on, this study will contribute to reduce the hazardous of natural disasters and to raise the pliability in the process of managing damage of natural disasters.
机译:本研究的目的是使用SAR数据检测淹没的位置,并使用地理信息系统(GIS)和SAR(合成孔径雷达)数据图像进行淹水条件的评估。 淹没了雷达响应形式的时间特征在洪水洪水洪水洪水中进行了分析。 通过RADARSAT SAR数据图像的变化检测技术来确定泛滥的位置。在洪水淹没之前,期间和之后获得了多个Radarsat SAR图像的雷达拉斯SAR图像。根据多时间SAR数据的彩色复合图像的解释,以及从雷达反向散射的时间轮廓,七种类型的Landcover根据洪水和淹水后的恢复条件可分离。 2000.07的含水层地图被水,城市,裸地,沼泽,草原,森林和农业所归类于7类。 结果,农业区显示为14.52公里〜2,森林洪水面积显示3.50km〜2,%,草原洪水区显示1.06km〜2,地面淹水区占0.09km〜2 和城市洪水区显示0.04km〜2。 对常设农业作物的实际洪水损坏取决于洪水的持续时间和随后的恢复地位。我们发现在洪水期间和之后获得的图像数据是评估对农业区域准确洪水损坏的必要条件。 从现在开始,这项研究将有助于减少自然灾害的危害,并在管理自然灾害损害过程中提高宽度。

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