...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy)
【24h】

Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy)

机译：利用最大熵方法和ASTER数据评估Giampilieri流域的泥石流和泥石流敏感性（意大利西西里岛东北）

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating 50 replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fit. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence-only methods and remote sensing derived predictors. Copyright (c) 2016 John Wiley & Sons, Ltd.
机译：这项研究旨在评估最大熵方法在评估滑坡敏感性，利用地形和多光谱遥感预测因子方面的性能。我们选择了位于西西里岛（意大利南部）东北部的Giampilieri溪流的集水区作为测试点。 2009年10月1日，暴雨在该地区引发数百种泥石流/雪崩现象，造成广泛的经济损失和生命损失。在该区域内，基于仅存在的统计方法被应用于获得能够区分泥石流和泥石流未来激活点的磁化率模型，这是泥石流或雪崩型传播失败机制的主要来源。本实验中使用的一组预测变量包括主要和次要地形属性，这些属性是通过处理高分辨率数字高程模型，CORINE土地覆盖数据以及通过处理多光谱ASTER图像获得的一组植被和矿物指数得出的。所有选定的数据源的日期都在灾难发生之前。采用空间随机分区技术进行验证，为两种考虑的运动类型分别生成50个重复，以评估模型的准确性，精度和可靠性。泥石流和泥石流敏感性模型具有很高的性能，第一种类型最适合。对于每个映射像素，均值附近的概率估计值的评估显示出一种反比关系，其中最鲁棒的模型对应于碎片流。关于建模阶段中每个预测变量的作用，泥石流似乎主要受地形属性控制，而碎屑滑坡可以通过遥感导出的索引更好地解释，尤其是以前在山坡上发生的野火。两种模型的总体优异性能为仅存在方法和遥感派生的预测器的应用提供了广阔的前景。版权所有（c）2016 John Wiley＆Sons，Ltd.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号