ENGLISH

14卷/3期

14卷/3期

華藝線上圖書館

Pages:

171-184

論文名稱

光達點雲資料面特徵重建

Title

Reconstruction of Surface Features from LiDAR Data

作者

羅英哲、曾義星

Author

Ying-Zhe Luo, Yi-Hsing Tseng

中文摘要

光達具有快速獲取大量三維坐標點資訊的優點,可提供每秒數千點至數萬點的觀測數據,這些大量的點雲分佈幾何隱含豐富的物面資訊。然而這些物面特徵資訊並非直接的幾何描述,必須轉換為數學函式或向量描述資料,才能成為可直接利用的顯性資訊。本研究利用區域成長法的概念,搭配面擬合的計算,合併具有共面特性的點群,進而萃取出點雲中的面特徵。在區域成長的過程中,以鄰近擬合面的法向量夾角以及掃描點到擬合面的距離為合併的判斷依據,則經由區域成長運算所集結的同類元素形成連結的區域可視為一個面特徵,所發展的面重建方法可重建點雲中的平面、球面、圓柱面及多項式曲面等面特徵。針對幾種不同地物的地面光達點雲資料進行實驗,得到相當良好的面重建成果,應用於空載光達點雲上,亦能成功地萃取屋頂面。實驗中亦針對面重建過程中所需要設定的預定參數,包括點雲的切割網格尺寸、角度門檻值、距離門檻值及種子的成長位置進行探討,並以半自動化的方式由點雲資料來獲取預定參數設置的相關資訊,以提供設定之參考依據。

Abstract

Lidar (Laser Scanner) is capable of collecting a large number of 3D points, in which abundant surface features are implied in the distribution of point cloud data. However, these surface features should be extracted to from explicit information, i.e., it is necessary to transfer the point cloud data into mathematical expressions or vector data descriptions. The proposed algorithm of surface reconstruction is based on the schemes of surface growing and surface feature fitting. It merges the co-plan points and extracts surface features from point cloud data. There are two factors to conduct the growing process: the angle between two normal vectors of adjacent patches and the distance of the point from the growing surface. Every merged cell is considered as a small patch, then the connect areas by region growing regarded as a surface feature. The reconstructive surface features in the proposed method include planar, spherical,cylindrical, and polynomial surface features. The experimental data include ground-based Lidar and airborne Lidar. The overall results show the successful application examples of the proposed algorithm. In the experiment, the initial parameters such as grid sizes, threshold of angle, threshold of distance and the growing seed position are also discussed and extracted from point cloud data using a semi- automatic method. The results of reconstructive surface provide points cluster with the same surface characteristics and fitting parameter of the surface features. The extracted surface features will be useful for 3D modeling

關鍵字

光達、區域成長法、面擬合、面重建

Keywords

LiDAR, Region Growing, Surface Fitting, Surface Reconstruction

附件檔名

華芸線上圖書館

N / A

備註說明

200909-14-3-171-184

Pages:

185-199

論文名稱

光達點雲平面特徵自動化匹配於航帶平差之應用

Title

Automated Planar Feature Matching for Adjustment of Lidar Strips

作者

尤瑞哲、王偉立

Author

R.J. You, W. L. Wang

中文摘要

空載光達的系統性誤差會造成相鄰航帶點位高程偏差,通常應用航帶平差方法來減低系統性誤差的影響。使用這種方法時,必須在不同航帶找出對應區域或連結點的位置。一般以人工選取的方式決定對應區域或連結點的位置,而人工選取的方式費工又費時。本文提出一套自動化選取對應區域或連結點的方法:首先以張量投票法自動偵測光達平面特徵;其次計算同一航帶內所萃取出的平面之位相關係,並將具有相似位相關係的平面以二階段的類神經網路演算法進行匹配,同時提出以二分樹法來提高匹配的正確率;最後再將匹配後得到的共軛平面之重心坐標視為連結點進行航帶平差。本法的好處是連結點的選取工作可以自動化地執行。航帶平差的實驗結果顯示:本文所提出的自動化匹配對應平面區域的方法對於改善空載光達高程精度是相當可行的。

Abstract

ABSTRACT Systematic errors of airborne Lidar data cause elevation offset of point clouds. Strip adjustment is one of the ways to reduce systematic errors. Using strip adjustment, the locations of conjugate blocks or tie points have to be detected first and they usually be manually selected and decided with laborious and time-consuming efforts. The purpose of this study is to develop a method for automatically selecting conjugate blocks or tie points. In this article, the tensor voting method is adopted for the extraction of planar features from Lidar data and an artificial neural network method is applied to match the planes with similar topologic properties. The Bintree method is used for increasing the success rate of classification based on the artificial neural network algorithm. The gravity centers of matched conjugate planes are regarded as tie points for strip adjustments in this study. The advantage of the current algorithm is that the choice of tie points can be executed automatically. The results of experiments of strip adjustments show the feasibility of our algorithm to improve the height accuracy of airborne Lidar data.

關鍵字

張量投票、類神經網路、航帶平差、空載光達

Keywords

Tensor Voting, Artificial Neural Network, Strip Adjustment, Airborne Lidar

附件檔名

華芸線上圖書館

N / A

備註說明

200909-14-3-185-199

Pages:

201-210

論文名稱

使用空載光達資料萃取森林區立木樹冠

Title

Forest Canopy Extraction Using Airborne LIDAR Data

作者

羅詔元、陳良健

Author

Chao-Yuan Lo, Liang-Chien Chen

中文摘要

立木樹冠植生情況為森林管理重要的參考指標,包含單株立木數量、立木位置、立木高度、材積與樹冠涵蓋範圍等,為獲取上述資訊,除藉由現地量測、航照立體對與雷達回波等資料獲得外,亦可由空載光達三維離散點雲萃取立木樹冠範圍與立木位置。由於森林區的特性,現地量測耗時費力,而航照影像與雷達回波資料於樹冠密集處不易辨識邊界位置。隨著空載雷射掃描儀性能的提升,於三維物空間萃取樹冠資訊具可行性,但現今光達資料多以網格式處理,萃取成果與網格大小與內插方式直接相關,且內插會造成高程資訊的損失。因此,本研究擬使用三維離散點偵測高程不連續處萃取樹冠邊界,進而獲得立木位置。由研究成果顯示,分析高程不連續處可有效獲取立木位置、立木高度與樹冠邊界。

Abstract

The Biomass condition is important index in forest fields. The used information contain number of stems, stand position, tree height, timber volume, canopy cover, etc. In literature reviews, several studies extracted canopies using field surveying, aerial imagery, radar data, LIDAR data and so on. However, those manners are labor intensive and hard to identify crown edges in concentrated forest. Following the development of airborne laser scanning systems, this study proposes a scheme to detect forest canopies using high density point clouds. This study analyzes canopy profiles using empirical mode decomposition method to find the vertical discontinuities, i.e. crown edges. Finally, those adjacent detected boundaries are merged to describe complete canopy boundaries. The experimental results indicate that the proposed scheme has the capability to extract stand position, tree height, and crown edges.

關鍵字

森林、萃取、航照立體對、空載光達、雷達

Keywords

Forestry, Extraction, Aerial imagery, Laser scanning, Radar

附件檔名

華芸線上圖書館

N / A

備註說明

200909-14-3-201-210

Pages:

211-223

論文名稱

「技術短文」空載光達飛航雲因風險機率計算研究: 以馬公機場為例

Title

The Cloud Caused Risk Probability of Airborne Lidar Operation, Magong Airport

作者

史天元、廖杞昌、王慧蓉、陳杰宗、陳佳勳

Author

Tian-Yuan Shih, Chi-Chang Liao, Hui-Jung Wang, Jie-Chung Chen, Jia-Hsun Chen

中文摘要

雲幕高,或稱雲冪高,為雲量超過天空一半之最低雲底高度,為航空氣象中之一項參數。本研究探討由歷史性雲量、雲高等觀測資料,萃取雲幕高,以多年觀測紀錄,由長時期統計值分析航空測量飛航雲因風險機率,以為空載光達評估雲因飛航風險之應用。本研究所稱雲因飛航風險,乃以天氣是否適合航空測量蒐集數據為標的。本文先描述雲屬、雲量、雲高等觀測資料之內涵,以及雲幕高之定義與產出方式,並以澎湖馬公機場十年數據作為探討之實例。本研究顯示飛航雲因風險機率確實難於預估,但是長時期統計值亦確實可提供一分析基礎。

Abstract

Cloud Ceiling is a parameter describing the cloud used in meteorology. This parameter is related to the amount of the cloud and the cloud height at a specific location. From the cloud observations, the cloud ceiling can be derived. This study investigates the probability of cloud caused risk to aerial mapping, based on the historic record of the cloud observations. Because the cloud status could vary drastically from day to day, month to month, and year to year, it is very difficult, if not impossible, to predicate the cloud conditions. This study utilizes more than 10 years cloud observation for the statistical analysis. The observation from Magong airport located in Penghu is analyzed as a sample. It is demonstrated that the monthly statistics does provide information to the cloud caused risk assessment. However, the cloud ceilings are still difficult to predict, as observed from the yearly changes of monthly probability.

關鍵字

雲幕高、航空測量

Keywords

Cloud Ceiling, Aerial Survey

附件檔名

華芸線上圖書館

N / A

備註說明

200909-14-3-211-223

Pages:

225-236

論文名稱

有理函式秩虧處理

Title

Alternative Treatment Of Rank Deficiency When Solving Rational Function Model

作者

趙鍵哲、彭念豪、 黃泊森

Author

Jen-Jer Jaw, Nei-Hao Perng, Po-Sen Huang

中文摘要

應用衛星影像進行物空間定位及測圖任務須依賴可靠之物像對應關係,其中,有理函數模式(Rational Function Model, RFM)具有不需引入感測器物理模式並能在某些條件具足下呈現近乎等同於嚴密感測器模式的物像幾何對應品質,並深具使用上的透明性及便利性,遂成為一通用的物像對應數學工具。然而,實務作業中,引用控制點方式進行高階有理函式物像對應之參數解算受制於過度參數化影響,為一秩虧(Rank Deficiency)方程,現行作業常以加入微小常數方式使求解系統穩定,然作業上仍有諸多不便之處。本研究探討以消除相依參數之概念處理上述問題,經由初步之測試成果驗證,本文引用之方法為能夠選用獨立參數組且能達提升工作效能之益。

Abstract

Among models sufficiently employed for positioning and mapping tasks by using satellite imagery, rational function model (RFM) performs almost as equally well as rigorous sensor model when fulfilling some restrictions, and has gained increasing popularity due to its transparency and convenience on application side. One disadvantage of RFM is the issue of rank deficiency when estimating high-order RFM coefficients by exclusively using ground control points with insufficient geometry as referring to RFM. Although the approach of regularizing normal matrix by adding a small multiplication of the identity matrix has been commonly used to stabilize the system and obtain the solution, non-smoothing processing still gets bothered and suggests that more efficient methods are welcome and expected. To this end, the authors proposed a method in which correlated parameters are to be eliminated. The preliminary result shows that effectiveness of the proposed method towards the solution is highly performed. Apart from that, identifying the correlations among the parameters highlights the very unique contribution as compared to other alternatives.

關鍵字

秩虧、特徵值、特徵根

Keywords

Rank Deficiency, Eigenvalue, Eigenvector

附件檔名

華芸線上圖書館

N / A

備註說明

200909-14-3-225-236

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