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Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

机译:UAV-SFM摄影测量和空中激光器在灾难性的洪水中的应用:日本中部Kinu河新成立的裂片展的重复地形测量

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Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10(-1) m - including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works -were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300-500m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.
机译:2015年9月形成的灾难性裂隙SPLAY的几制影响及其形成后修改是通过使用日本中部Kinu河的居住和耕种的洪泛区的重复的高清数字表面模型(DSM)来定量记录。 DSMS基于预洪水(分辨率:2米)和洪水后(分辨率:1米)分别于2007年1月和2015年9月和2015年9月的航空光检测和测距(LIDAR)数据( SFM)摄影测量数据(分辨率:3.84厘米)从2015年12月由无人机(UAV)拍摄的空中照片源于占用的航拍照片。消除了DSMS中的系统误差和SFM衍生的DSM的下行采样后,提升更改10(-1)M的顺序 - 包括不仅是地形,而且还包括植被的增长,洪水的消失,以及恢复和修理工程 - 检测到。 DSM的比较表明,洪水侵蚀的体积大于突破的人工堤内的面积内的面积内的沉积体积的两倍于,地形显着影响。结果表明,基于UAV-SFM和LIDAR数据组合的DSM可用于量化,快速和丰富的细节,洪水引起的洪泛平坦的地形变化。

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