- 期刊
- Ahead-of-Print
Estimation of Landslide-Induced Riverbed Roughness Variation by Using Lidar Data
並列摘要
With advancement in efficiency and accuracy on investigation techniques and equipment, the remote sensing technologies have been widely employed in river circumstance investigations. In the past, quantifying the morphology along a river channel has been proven difficult till the airborne laser altimetry technology, Light Detection and Ranging (LiDAR), has started providing high-resolution and high-accuracy topographical data. Data derived from airborne LiDAR has been adopted for analyses in recognition of riverbed morphology. The 〞roughness index〞 in this study is defined as the standard deviation of residual topography. The variable moving window was used in deriving the smoothed DEM. The standard deviation of residual topography was used as a measure of roughness where the residual topography is the difference between the original and smoothed DEM. Roughness data derived from pre-disaster riverbed by different reaches were compared with the post-disaster data. Results showed that the upper-reaches demonstrate higher roughness values than lower-reaches. Thus, the post-disaster riverbed surface relief was close to the derived smoothed relief. Such characteristics were also reflected in the major differences evaluated by slope measurement for riverbed morphological analysis; of which the location of the peak value also appeared to have changed after the disaster. It concluded that these remote sensing techniques have become vital in assisting the ordinary survey for regional investigation through its rapid and accurate construction of an integrated plane-wise fluvial circumstance of a river watershed area