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A platform for research: civil engineering, architecture and urbanism
Dip-slope mapping of sedimentary terrain using polygon auto-tracing and airborne LiDAR topographic data
AbstractDip-slope mapping is a fundamental task for landslide investigation and mitigation. However, most dip-slope mapping methods involve visual interpretations and manual processes that are inevitably subjective and time consuming. The advent of high-resolution digital elevation models (DEM) and increases in computing power have provided opportunities to improve the dip-slope mapping process. This study proposes a polygon auto-tracing method for generating dip-slope maps based on airborne Light Detection and Ranging (LiDAR) data and a customized spatial analysis toolset developed in Python. This method requires the input of strata boundaries produced for sedimentary terrain based on 2m resolution LiDAR DEMs. The method begins by deriving the raster layer of the dip direction of the bedding, and it then executes a series of raster calculations among the three raster layers slope, aspect, and dip direction to extract the dip-slope raster cells. Using the clustering pattern of the dip-slope raster cells, we implement the Point-Density analysis tool to determine the dip-slope areas. The ArcGIS ModelBuilder platform is used to lay out an automated workflow for the proposed polygon auto-tracing method using the customized toolset. For demonstration purposes, we successfully mapped 298 dip slopes in the study area, which frequently experiences dip-slope landslides and is located in the sedimentary terrain of northern Taiwan. The dip-slope mapping results were compared and validated against two government-funded visually interpreted dip-slope maps. Our dip-slope mapping results were also used in a daylight analysis along major freeways to identify potential locations of daylighted dip slopes.
HighlightsA polygon auto-tracing method was proposed for dip-slope mapping using LiDAR data.An ArcGIS spatial analysis toolset was developed using Python for dip-slope mapping.New mapping results show efficiency and reliability using the proposed method.The daylighted slopes along the freeways in the study area were successfully identified.
Dip-slope mapping of sedimentary terrain using polygon auto-tracing and airborne LiDAR topographic data
AbstractDip-slope mapping is a fundamental task for landslide investigation and mitigation. However, most dip-slope mapping methods involve visual interpretations and manual processes that are inevitably subjective and time consuming. The advent of high-resolution digital elevation models (DEM) and increases in computing power have provided opportunities to improve the dip-slope mapping process. This study proposes a polygon auto-tracing method for generating dip-slope maps based on airborne Light Detection and Ranging (LiDAR) data and a customized spatial analysis toolset developed in Python. This method requires the input of strata boundaries produced for sedimentary terrain based on 2m resolution LiDAR DEMs. The method begins by deriving the raster layer of the dip direction of the bedding, and it then executes a series of raster calculations among the three raster layers slope, aspect, and dip direction to extract the dip-slope raster cells. Using the clustering pattern of the dip-slope raster cells, we implement the Point-Density analysis tool to determine the dip-slope areas. The ArcGIS ModelBuilder platform is used to lay out an automated workflow for the proposed polygon auto-tracing method using the customized toolset. For demonstration purposes, we successfully mapped 298 dip slopes in the study area, which frequently experiences dip-slope landslides and is located in the sedimentary terrain of northern Taiwan. The dip-slope mapping results were compared and validated against two government-funded visually interpreted dip-slope maps. Our dip-slope mapping results were also used in a daylight analysis along major freeways to identify potential locations of daylighted dip slopes.
HighlightsA polygon auto-tracing method was proposed for dip-slope mapping using LiDAR data.An ArcGIS spatial analysis toolset was developed using Python for dip-slope mapping.New mapping results show efficiency and reliability using the proposed method.The daylighted slopes along the freeways in the study area were successfully identified.
Dip-slope mapping of sedimentary terrain using polygon auto-tracing and airborne LiDAR topographic data
Yeh, Chih-Hsiang (author) / Lin, Ming-Lang (author) / Chan, Yu-Chang (author) / Chang, Kuo-Jen (author) / Hsieh, Yu-Chung (author)
Engineering Geology ; 222 ; 236-249
2017-04-04
14 pages
Article (Journal)
Electronic Resource
English
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