Title

以高光譜影像和光達建置高速公路邊坡隆起和下陷監控

Translated Titles

The Study of Monitoring Highway Heaving/Settlement on Slope-hills through LiDAR Image Data

Authors

萬絢(Shiuan Wan);張士勳(Shih-Hsun Chang);王依蘋(Yi-Pin Wang);劉啟清(Chi-Ching Liu)

Key Words

光達影像 ; 高光譜影像 ; 邊坡潛變 ; 邊坡監控 ; Hyper-spectral ; LIDAR ; Creep and Creep monitoring

PublicationName

中華水土保持學報

Volume or Term/Year and Month of Publication

47卷4期(2016 / 12 / 01)

Page #

185 - 190

Content Language

繁體中文

Chinese Abstract

本研究在使用光達和高光譜兩種影像材料,分析高速公路的高程變化,分別利用這兩種材料建置一個評估系統,建立一套可行的評估方法。高速公路的邊坡一年約有十公分到二十公分的隆起、沉陷變化,但目前光達平面精度約為五十公分,裸地的高程精度約為二十公分,高光譜影像的精度約為二十公分,如何有效監控邊坡之變動潛勢是重要的課題。本研究提出改善上述的缺點的方法,擬以區域成長法(Regional-based Object Classification)中區塊物件的概念,將連續圖素 (pixel) 轉製成ROI (Region of Interest)物件,此次研究主要實證區以國道三號邊坡擋土牆因土壓而引起高程變化現象,擬以不同時期高光譜與光達材料,確認位置精確後,先以高光譜紋理概念降低植生干擾資訊,後透過光達之高程資料計算不同時期地表變化造成之高程變化量。本研究案鎖定不同時期的航拍高光譜影像(用於建立ROC模型)和光達(用於建立地表垂直位移),並以平均差量法和基礎校正法兩種不同的計算方法,求得地表的隆起或下陷,分別分析DEM 移動量。研究結果顯示基礎校正法為較佳的預測模型並且可以提供一簡單回歸公式,可用於初期邊坡高程變化量的估算。結果顯示,平均差量法計算獲得坡地整區移動量約24 mm,而基礎校正法計算之移動量為19 mm,顯示這兩種不同估算方法的結果接近。

English Abstract

Hyper-spectral and LIDAR images provide a series of image data for geoscience applications. However, few applications of this image material have been proposed to establish a land creep prediction system. The spatial resolution of a LIDAR image is approximately 50 cm, while the typical creep displacement is about 20 cm. It is thus a difficult task to predict the land creep displacement by the use of LIDAR images. Nonetheless, the present study addresses the above issues by using Regional-based growing Object Classification (ROC). The ROC technique is a computational object model that is transformed into a ROI module by the connecting neighboring pixels of similar intensity. The creep displacement is predicted by analyzing the DEM model, which is generated by LIDAR images. The study region is the retaining wall and the slide of a hillslope along Formosa Freeway. The creep displacement is so small that a series of hyperspectral and LIDAR images taken at the same geological location but at different time periods are used for investigation. The hyperspectral data is used to generate the ROC model, and LIDAR data is used to create the DEM model for measuring heaving/settlement. This study proposed two different approaches to investigate the results: the average of difference and baseline correction methods. The average of displacement obtained by the average of difference method is 24 mm, and that obtained by the baseline-correction method is 19 mm. The result indicates the baseline-correction method is a better prediction model, and its regression formula can be used to estimate the amount of heaving/settlement in the early stage of analysis.

Topic Category 生物農學 > 農業
生物農學 > 森林
生物農學 > 畜牧
生物農學 > 漁業
生物農學 > 生物環境與多樣性
工程學 > 土木與建築工程
工程學 > 市政與環境工程