應用光達地形進行沉積岩層繪製及順向坡自動化圈繪之研究

Sedimentary Strata Mapping and Dip Slope Auto-tracing with LiDAR DEM Using Self-developed Geoprocessing Toolsets

葉致翔(Chih-Hsiang Yeh)

指導教授 ： 林銘郎

共同指導教授 ： 詹瑜璋(Yu-Chang Chan)

國立臺灣大學/工學院/土木工程學研究所/博士(2016年)

https://doi.org/10.6342/NTU201701816

摘要

傳統的地質製圖方式以野外調查工作為主, 由於經常受到植被及困難地形的阻礙，使得傳統的製圖程序十分的費時且費工，所製作的地質圖資除了例尺較小外，重要的環境地質資訊如順向坡範圍等亦顯得過於簡化。近二十年來由於遙測影像的發展，對於地表地形地質與防災領域的研究中已獲得相當大的進展，而其中利用光達(LiDAR)技術所測製而成的數值高程模型(DEM)提供了高解析度真實的地表地形資訊，使得以往被植被覆蓋的細微地表地形地質的特徵有機會能夠在影像中顯露並得以人工判釋。這樣精細的光達資料雖已廣泛的使用在相關的研究領域，但對於輔助地質圖資製作的工作上仍有相當程度潛在應用尚未開發。本研究利用2公尺解析度光達高程數值模型(LiDAR DEM)，以三維顯像技術製作兩種不同型式的光達立體影像，並進一步應用於判釋沉積岩層區的細微地表特徵，特別是二維影像較難顯示的地層邊界線型。我們的研究目的是驗證三維光達影像用於地層線型繪製與大比例尺製圖的可行性，以及發展順向坡自動化判釋的方法進而改善目前以人工圈繪方式為主的限制。本研究選定基隆河北岸46平方公里的沉積岩層區做為展示區域，本區鄰近台北、基隆兩大人口稠密都市，歷年來因受到人為開發影響已發生多起大型順向坡破壞的災害。本研究流程大致可分兩個階段，第一階段我們使用三維光達影像繪製了19條主要的地層邊界線，並利用地層線型所圍成的三角面計算出39處地層位態，再進一步製作大比例尺1:2,500的地層邊界分布圖。第二階段我們接續上一階段地層線型的成果製作各地層趨勢面並得出曲面方程式，在GIS平台計算出精細的地表地層位態GIS圖層後，建立順向坡自動化圈繪程序繪製順向坡分布圖，並可進一步挑選國道兩側高風險的順向坡進行地層見光線(Daylight)的分析。為有效率的處理光達資料在地質上的問題，本研究使用Python程式語言自主發展GIS工具套件，以提升光達資料處理的效率並實現順向坡製圖自動化。在研究驗證方面，我們進行了適當的野外調查工作以檢視光達資料所推衍出位態資料，亦將本研究順向坡分佈的成果與現有的順向坡分佈圖進行比對。其驗證結果顯示，本研究所提出的研究方法可大大改善傳統沉積岩地層及順向坡圈繪的製圖程序，並提供了更經濟更有效率的流程方法提升地質製圖的研究精度與品質。

關鍵字

光達 ； 光達立體影像 ； 沉積岩層繪製 ； 順向坡自動化圈繪 ； 地層見光線分析 ； 基隆河北岸

並列摘要

Traditional geological mapping may be hindered by rough terrain and dense vegetation resulting in obscuration of geological details. Consequently, stratum units and mainly topographic features such as dip slopes are often mapped at coarse scales and simplifications. The advent of airborne Light Detection and Ranging (LiDAR) offers a very precise digital elevation model (DEM). However, its full potential in complementing traditional geological mapping remains to be explored using 3D rendering techniques. This study uses two types of 3D images which differ in imaging principles to further explore the finer details of sedimentary terrain. Our purposes are to demonstrate detailed strata mapping with LiDAR 3D images, and to develop an auto-tracing method with LiDAR data for improving existing dip-slope mapping using an example from an about 46 km2 sedimentary area of the north bank of Keelung River, northern Taiwan. This area located between two densely populated cities has been developed for transport infrastructures and large-scale communities, which has resulted in many dip-slope landslides. The research process of this study can be divided two phases. In the first phase, we use LiDAR 3D images to derive 19 LiDAR-based strata boundaries and 39 measurements of LiDAR-derived strike and dip that are located in areas where terrain is difficult to access for generating a 1:2,500-scale strata map. In the second phase, we follow the above result of LiDAR-based strata boundaries to derive a high-precise GIS raster of geological attitudes for building an auto-tracing process in dip-slope mapping, and further identifying the daylighted dip slopes along the freeway. By using self-developed geoprocessing toolsets programmed by Python, we enhance efficiency of LiDAR data processing and practice an automatic processing in dip-slope mapping. For demonstration, we conducted fieldworks to validate the correctness of LiDAR-derived strike and dip, and compared and validated our dip-slope mapping results against two government-funded visually interpreted dip-slope maps. The proposed practices and approaches in sedimentary strata mapping and dip slope auto-tracing should greatly improve the quality, the accuracy and the efficiency in the generation of maps in the future.

並列關鍵字

LiDAR DEM ； 3D visualization ； Strata mapping ； Dip slope auto-tracing ； Daylight analysis ； North bank of Keelung River

參考文獻

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