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A new method for determination of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping

机译:确定最可能的滑坡始发点并评估地形稳定制图中数字地形模型规模的新方法

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This paper introduces a new approach for determining the most likely initiation points for landslides from potential instability mapped using a terrain stability model. This approach identifies the location with critical stability index from a terrain stability model on each downslope path from ridge to valley. Any measure of terrain stability may be used with this approach, which here is illustrated using results from SINMAP, and from simply taking slope as an index of potential instability. The relative density of most likely landslide initiation points within and outside mapped landslide scars provides a way to evaluate the effectiveness of a terrain stability measure, even when mapped landslide scars include run out zones, rather than just initiation locations. This relative density was used to evaluate the utility of high resolution terrain data derived from airborne laser altimetry (LIDAR) for a small basin located in the Northeastern Region of Italy. Digital Terrain Models were derived from the LIDAR data for a range of grid cell sizes (from 2 to 50 m). We found appreciable differences between the density of most likely landslide initiation points within and outside mapped landslides with ratios as large as three or more with the highest ratios for a digital terrain model grid cell size of 10 m. This leads to two conclusions: (1) The relative density from a most likely landslide initiation point approach is useful for quantifying the effectiveness of a terrain stability map when mapped landslides do not or can not differentiate between initiation, runout, and depositional areas; and (2) in this study area, where landslides occurred in complexes that were sometimes more than 100 m wide, a digital terrain model scale of 10 m is optimal. Digital terrain model scales larger than 10 m result in loss of resolution that degrades the results, while for digital terrain model scales smaller than 10 m the physical processes responsible for triggering landslides are obscured by smaller scale terrain variability.
机译:本文介绍了一种新方法,可通过使用地形稳定性模型绘制的潜在不稳定性来确定滑坡最可能的起始点。该方法根据从山脊到山谷的每个下坡路径上的地形稳定性模型,使用临界稳定性指数来识别位置。这种方法可以使用任何地形稳定性度量,此处使用SINMAP的结果以及仅将坡度作为潜在不稳定性的指标进行说明。即使在映射的滑坡疤痕包括耗尽区域而不只是起始位置的情况下,映射的滑坡疤痕内部和外部最可能的滑坡起始点的相对密度提供了一种评估地形稳定措​​施有效性的方法。使用此相对密度来评估从机载激光测高仪(LIDAR)获得的高分辨率地形数据在意大利东北部地区的小盆地的实用性。数字地形模型是从LIDAR数据中得出的,其网格范围为2至50 m。我们发现,在10 m的数字地形模型网格单元中,映射的滑坡内外的最可能的滑坡起始点的密度之间存在明显的差异,其比率高达3或更大,且比率最高。这得出两个结论:(1)当测绘的滑坡不能或不能区分起裂区,径流和沉积区时,最有可能的滑坡始发点方法的相对密度可用于量化地形稳定性图的有效性; (2)在这个研究区域中,滑坡发生在有时超过100 m宽的复杂区域中,因此10 m的数字地形模型比例是最佳的。大于10 m的数字地形模型比例尺会导致分辨率降低,从而降低结果质量;而对于小于10 m的数字地形模型比例尺,负责触发滑坡的物理过程会因较小的比例尺地形变化而被遮盖。

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