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Meteorological and Earth observation remote sensing data for mass movement preparedness

机译:气象和地球观测遥感数据,为大规模运动做好准备

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One of the major problems of the efficient synergetic use of remote sensing data for natural disaster mitigation is the fusion of various meteo- and geodata sets of significantly different spatial resolution. On the other hand, different morphological types of mass movements are based on alternate concepts i.e. of generation which, again has to be initially reflected in differing methodological approaches. The unifying idea and stronghold, however, of the presented approach is the precipitation parameters which trigger the debris flows. Albeit, frequently there are no relevant precipitation climatic data available. Despite significant drawbacks in the integration of Landsat and/or SPOT data sound hazard zonation maps can be generated. For a test area in the French Alps it has been shown that remote sensing data can be used to predict potential debris flow events. High temporal frequency remote sensing data from the Meteosat series of satellites allow the identification of cloud clusters most likely to result in intense rainfall which are, in turn, likely to initiate debris flow activity. Video evidence, field observations and an empirical debris flow model linked to an instantaneous rain gauge were used to ascertain the exact times of debris flow initiation. Due to the high spatial and temporal variability of rainfall in mountainous regions and the large areas vulnerable to debris flows compared to the coverages of these observations, there are, however, restrictions on the use of these data for large regions to provide early warning of debris flow events operationally. Additionally, the possible timeliness of warnings using such observations is restricted to the relatively short interval between the onset of the triggering phenomena and the hazard event. The remote sensing techniques developed in this study, allow warning of potential debris flow events to be derived before the triggering phenomenon occurs, by attempting to recognise the evolution if intense rain-bearing clouds. In this, role the meteorological remote sensing data are not used to retrieve rainfall amounts but, instead, to derive rain cloud properties that produce debris flow triggering conditions.
机译:有效协同使用遥感数据缓解自然灾害的主要问题之一是融合空间分辨率明显不同的各种气象和地理数据集。另一方面,质量运动的不同形态类型是基于替代概念,即产生的概念,这又必须首先以不同的方法论方法来体现。但是,该方法的统一思想和据点是触发泥石流的降水参数。尽管经常没有相关的降水气候数据。尽管在整合Landsat和/或SPOT数据方面存在重大缺陷,但仍可以生成声音危害分区图。对于法国阿尔卑斯山的一个测试区域,已显示出遥感数据可用于预测潜在的泥石流事件。来自Meteosat系列卫星的高时频遥感数据可以识别最有可能导致强降雨的云团,从而又可能引发泥石流活动。使用视频证据,现场观察和与瞬时雨量计相关的经验性泥石流模型来确定泥石流开始的确切时间。与这些观测的覆盖范围相比,由于山区和大范围易受泥石流影响的地区降雨的时空变化较大,因此,在大范围地区使用这些数据来提供碎屑预警具有一定的限制。在操作上流事件。另外,使用这种观察的警告的及时性被限制在触发现象的发生和危险事件之间的相对短的间隔。在这项研究中开发的遥感技术,通过尝试识别强烈的含雨云,可以在发生触发现象之前就警告可能发生的泥石流事件。在这种情况下,气象遥感数据的作用不是用来获取降雨量,而是用来导出产生泥石流触发条件的雨云特性。

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