ENGLISH

20卷/3期

20卷/3期

華藝線上圖書館

Pages:

151-169

論文名稱

張量分析應用於結合空載光達資料與地形圖重建建物模型的品質預估之研究

Title

Tensor Analysis for Quality Prediction of Building Model Reconstruction by Integration of Airborne LiDAR Data and Topographic Information

作者

林柏丞, 尤瑞哲

Author

Bo-Cheng Lin, Rey-Jer You

中文摘要

本研究應用張量分析於光達點雲的特徵萃取,並針對資料融合空載光達資料與地形圖產製的建物模型進行品質預估。特徵萃取是從空載光達資料中萃取屋頂面區塊與屋脊線段,屋頂面區塊的萃取是利用張量投票法(Tensor Voting Method, TVM)推論每一個空載光達點隱含的幾何特徵資訊,並利用主特徵為種子點的區域成長法將具有平面特徵的點雲群聚在一起。屋脊線段則是利用已萃取的屋頂面區塊推論而得。此外,本文提出三個正規化的特徵強度指標以減少點雲數量對特徵辨識的影響。針對TVM萃取平面區塊的成果,除了第一類型與第二類型錯誤之外,還新增碎形錯誤與識別能力兩項新指標來評估。在資料融合空載光達資料與地形圖產製建物模型的過程,本研究引入穩健權函式的最小二乘法來匹配空載光達資料的建物屋頂面邊緣點與建物屋頂的二維向量圖的輪廓線,使兩組資料轉換至相同的坐標系統。基於融合資料的不一致會造成建物模型錯誤重建,本研究提出利用空載光達資料中建物屋頂面邊緣點與地形圖中建物輪廓線的殘差張量分析進行品質預估,目的是偵測在現有資料品質之下可能被重建錯誤的模型。實驗結果顯示,本研究所提的品質預估指標不僅提高自動化模型重建的可靠性,且減少人工檢核成果的時間。

Abstract

This study first presents a novel method based on the tensor voting framework for extracting building features from airborne LiDAR data. For the extraction of roof patches, geometric features of LiDAR points are represented by a tensor field. A region-growing method with principal features is developed from the properties of eigenvalues and eigenvectors of the tensor field. The extraction of ridge lines is then inferred from the segmented roof patches. On top of that, three new indicators of the strength of features are proposed to reduce the effect of the number of points on feature identification. Furthermore, Type I errors, Type II errors, fragmentation and discernment are used as quality indicators to represent the effectiveness of the proposed method. Next, we present an algorithm to integrate the LiDAR data and topographic maps for 3D building model reconstruction and develop a quality prediction indicator by the residual tensor analysis. To reduce influence of errors while integrating, a robust least squares method is applied to register boundary points extracted from LiDAR data and building outlines obtained from topographic maps. After registration, a quality indicator based on the tensor analysis of residuals is derived in order to evaluate the correctness of the automatic building model reconstruction. Finally, an actual dataset demonstrates the automatic model reconstruction quality of the predictions. The results show that our method can achieve reliable results and save both time and expense on model reconstruction.

關鍵字

空載光達、地形圖、張量分析、資料融合

Keywords

airborne LiDAR, topographic map, tensor analysis, data fusion

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

171-181

論文名稱

多光譜影像與空載光達於山崩植生復育監測之研究

Title

Landslides Vegetation Restoration Monitoring by Using Airborne LiDAR and Multispectral Imagery

作者

楊孟學, 吳銘志, 劉進金

Author

Mon-Shieh Yang, Ming-Chee Wu, Jin-King Liu

中文摘要

邊坡穩定往往與地形、地質及植生息息相關,這些條件也常被用來作為評估邊坡穩定的因子。然而對於大範圍邊坡穩定之調查,往往因面積過大而使得調查較為困難。隨著遙測技術的發展,近年來常藉由遙測影像輔助山區災害的調查。本研究結合多光譜遙測影像以及空載光達產製之地表粗糙度影像建立一適於山崩植生復育調查之三維植生覆蓋指標,該指標同時具有二維的植生健康度訊息以及三維的生長維度訊息,期藉此指標能更有效的評估植生的健康度與復育生長情形。其研究結果也顯示,整合多光譜影像所提供的二維資訊與光達三維資訊之三維植生指標,該指標除了整體趨勢與常用的植生指標趨勢一致外,對於植生之垂直維度的生長特徵也更加詳細。以分類精度比較,NDVI輔助SPOT影像之分類成果精度為72.61%、CHM輔助SPOT影像之分類成果精度為77.04%、三維植生覆蓋指標輔助SPOT影像之分類成果精度達89.75%。此外,利用三維植生指標輔助影像自動化判識之精度也有所提升,顯示三維植生指標可作為山崩植生復育重要的評估指標。

Abstract

Slope-safety factors associated with topography, geology, and vegetation, which can be considered as indices of the parameters of safety factors, is often quantified to assess their contributions to landslides. However, for large areas, variations in the parameters included for analyzing the safety factors are too large to quantify accurately. With advances in the efficiency and accuracy of investigative techniques, remote sensing technologies have become widely employed in assessing landslide hazards. In this paper, the effectiveness of using airborne laser altimeter retrieved data to evaluate landslide vegetation restoration is analyzed. For this purpose, satellite multi-spectrum image were integrated with airborne laser altimeter surface-roughness data to develop a method to characterize vegetation restoration on landslide areas. The analysis was performed in both 2D and 3D scales, the results of the integrated method suggest that airborne laser altimeter data can be used effectively for evaluating landslide vegetation restoration than using the NDVI, besides, the 3D vegetation index also shows the same characteristics and can describe the features of the vegetation effectively than using spectrum information only; the amplitude of the 3D vegetation index represents the vegetation condition both in the vertical and the horizontal dimension. The classification accuracy is improved from 72.61% for using traditional multispectral classification to 89.75% when using 3D vegetation index integrated with SPOT images. The results of the integrated method suggest that integrated method can be used effectively for evaluating landslide vegetation restoration.

關鍵字

光達、地質災害、地表粗糙度

Keywords

airborne LiDAR, geological hazard, surface roughness

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

183-199

論文名稱

光達數值地形於野外地質調查之應用:以獻肚山崩塌區及谷關-德基區域為例

Title

Application of LiDAR DEM for Field Geological Investigation: Take Xian-Du Landslide Area and Guguan – Deji Area for Example

作者

徐乙君, 張中白

Author

Yi-Chun Hsu, Chung-Pai Chang

中文摘要

以空載光達測距掃描技術獲取之高精度數值地形資料,有助於線形構造判釋,可做為野外調查之基礎,本研究以獻肚山崩塌區及中橫公路的谷關-德基地區為例。藉由高解析度數值地形判斷獻肚山崩塌區域有一系列的東北東-西南西向構造,在谷關-德基區域可觀察到近南北向及東北-西南向之構造,但無法判別其屬於何種構造,惟有經過野外勘查才能確定,野外調查尚可確認構造的活動特性、延續性及與其他構造之相互關係。高解析度數值地形判釋線形構造,可用於野外工作規劃,惟應用於區域構造解釋時必須謹慎,與實地查核作交互比對,避免過度解釋。

Abstract

Using the airbone LiDAR high-resolution DEM data to identify lineament structure provides an opportunity to generate more comprehensive structural maps. In this study, we use Mt. Xian-Du Landslide area (Hsiaolin Village) in Kaohsiung city and Guguan – Deji area in Central Cross-Island Highway as example to demonstrate how we applied the LiDAR DEM for field investigation. With the use of high-resolution DEM we identified a series of east-northeast to west-southwest trending structures in Mt. Xian-Du Landslide area. During field investigation we recognized characteristics of these structures, they are generally the strike-slip faults, and track its continuity, as well as other structural relationships. In the high- resolution DEM using of Guguan – Deji area, we observed the north-south and northeast – southwest trending structures. However, the structures in this area are complex in nature, and we cannot recognize the nature of structures directly by DEM. Using the high-resolution DEM can enhance the utility of remote sensing for structural mapping since these data sets enable the extraction of detailed information about both local and regional geological structures. However, field checking is always necessary before the structure.

關鍵字

光達數值地形、線形構造、野外調查

Keywords

LiDAR DEM, lineament structure, field investigation

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

201-215

論文名稱

空載光達DoD與兩期雷射點分佈關係之探討

Title

A Study on the Relationship between DoD and Distribution of LiDAR Point Clouds

作者

鐘郁翔, 徐偉城, 劉進金, 謝正倫, 謝明霖, 陳俞旭

Author

Yu-Shiang Chung, Wei-Cheng Hsu, Jin-King Liu, Chjeng-Lun Shieh, Ming-Lin Shieh, Yu-Shiu Chen

中文摘要

空載光達可有效的紀錄地貌特色,產生高精度之數值地形(DEM),故以DoD法(DEM of Difference)進行地形變化分析,DoD乃利用兩期高精度DEM相減後所得,是含高程差值之三維模型。此方法已經是研究地貌演變、集水區土砂產生、以及崩塌地量體等一個重要的分析方法。唯DoD之不確定性並非全區一致, LiDAR DEM品質主要決定於DEM產製過程相關條件,因此LiDAR DEM成果的誤差在每一個地點是不一樣。本研究之目的即在於探討光達點雲分佈不一致產生的DoD品質問題。 本研究以曾文水庫試驗區,利用LiDAR(光達)於2012年1月與2012年10月所產製之兩時期DEM進行地形變化的土方不確定分析。結果顯示直接使用DoD推估地形變化土方計算,全區DoD之不確定性等級最大的部分佔總面積59.49%,不確定性等級最大的範圍內地面點數量是極少的。因此,直接使用DoD推估地形變化土方,其結果將包含極大的誤差值。為確保LiDAR DEM在應用分析上的正確性,須對多時期LiDAR地面點進行DoD之分析評估。

Abstract

Airborne LiDAR is an effective tool for recording details of landscape and producing high-resolution digital elevation models (DEM). Therefore, DoD (DEM of Difference) method a straight-forward method for conducting volumetric change of two different time with multitemporal DEMs. And, DoD becomes a basic tool for the analyses of landscape change, erosion and sedimentation, volume of landslides, and others. Nevertheless, the accuracy or quality of a DoD cannot remain the same for every grid pixels. For effective application, the main challenge is to understand and suppress the uncertainties caused by this quality problem. The purpose of this study is to explore the uncertainties caused by un-even distribution of point clouds and thus to propose a method using ground points to assess the uncertainties of DoD. The study area is located in Tseng-Wen Watershed of southern Taiwan. Two Airborne LiDAR surveys were conducted in January and October of 2012, respectively. The results show that 59.49% of the area of a DoD is under high uncertainties within which the number of ground points of a grid cell is low. High uncertainties and high risk can take place if volumetric measures are taken from these areas. An alternative approach for suppress the uncertainties is to apply a stencil of polygons generated from manual edited bare lands. Consequently, only 5.55% of the area of a DoD is under high uncertainties. It is concluded that using ground points of multi-temporal LiDAR survey, uncertainty can be effectively assessed to assure the quality of LiDAR DEMs and applications.

關鍵字

遙測、空載光達、高精度航測、侵蝕與淤積、防災

Keywords

remote sensing, airborne LiDAR, high resolution photogrammetry, natural disaster, sedimentation

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

217-229

論文名稱

「技術短文」衛星影像雲遮蔽區域之移除與填補演算法

Title

A Cloud Removing Algorithm for Multi-temporal Satellite Images

作者

蔡博閎, 林昭宏

Author

Po-Hung Tsai, Chao-Hung Lin

中文摘要

衛星影像在地球表面觀測相關領域上一直是重要的資料之一,近年來也廣泛的應用於自然科學、環境探測、軍事監控、土地利用與規畫等領域上,然而,衛星影像各波段會受到雲層干擾,使得影像無法完整的呈現地表資訊,因此雲遮蔽是目前衛星影像在使用與分析上的一大問題。本文提出一個衛星影像雲層遮蔽區域移除與填補演算法,對於一張有雲遮蔽的衛星影像,藉由前後相鄰時間的影像資訊進行套合與填補,產生一無雲遮蔽的衛星影像。首先使用監督式分類方法尋找雲遮蔽區,接著以本研究所提出的無縫鑲嵌技術,以不同時期衛星影像資訊對遮蔽區域進行資訊填補,在多時期衛星影像選取方面,藉由影像品質評估方法,選取適合的候選影像以進行資料填補。本文提出解帕森方程式(Poisson equation)的自動化無縫遮蔽區域填補演算法,依影像品質評估填補區域的相似度,以提供後續資料使用上的一項參考指標。本研究的實驗影像為Landsat 7 ETM+衛星影像,實驗過程中,對於各種不同類型的地區進行測試,根據實驗結果顯示,本方法可應用在不同特性之區域,並可成功處理大量的雲層遮蔽之衛星影像。

Abstract

Satellite images have a widespread use in many fields such as natural science, environment detection, military monitoring, land use and land planning. However, the cloud cover is a problem in the usage of images acquired by optical sensors. The ground information in the regions covered by cloud will miss. Thus, cloud detection and removing is a fundamental research issue with many applications in the field of geodesic and remote sensing. In this study, a cloud removal approach based on information cloning is introduced. The approach removes cloud-contaminated portions of a satellite image, and then reconstructs the information of missing data utilizing temporal correlation of multi-temporal images. The basic idea is to clone information from cloud-free patches to their corresponding cloud-contaminated patches under the assumption that land covers change insignificantly over a short period of time. The patch-based information reconstruction is mathematically formulated as a Poisson equation and solved using a global optimization process. Thus, the proposed approach can potentially yield better results in terms of radiometric accuracy and consistency compared with related approaches. Some experimental analyses on sequences of images acquired by the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor are conducted. The experimental results show that the proposed approach can process large clouds in a heterogeneous landscape, which is difficult for cloud removal approaches. In addition, quantitative and qualitative analyses on simulated data with different cloud contamination conditions are conducted using quality index and visual inspection, respectively, to evaluate the performance of the proposed approach.

關鍵字

雲遮蔽區域移除、影像無縫鑲嵌、帕森方程式

Keywords

cloud removing, seamless replacement, Poisson equation

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

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