ENGLISH

19卷/1期

19卷/1期

華藝線上圖書館

Pages:

1-11

論文名稱

DGPS與PPP於空載光達解算定位精度成果之研究

Title

A Comparison of Positioning Accuracy for Airborne LIDAR Data Solved by DGPS and PPP

作者

吳歷韋, 劉進金, 徐偉城, 鐘郁翔, 陳慧鵬

Author

Li-Wei WU, Jin-King LIU, Wei-Chen HSU, Yu-Hsiang CHUNG, Hui-Peng CHEN

中文摘要

空載光達點雲精度深受GPS定位精度影響。空載光達施測時,於台灣部份已是人煙罕至高山區域架設地面參考基站,這是一項挑戰不可能的任務。因此,本研究嘗試運用精密單點定位(PPP)定位解算,作為不易架設地面基站區域之替代方案可能性。PPP主要是以IGS公告衛星精密星曆及精密時鐘差修正資料,輔助以單點無差分方式進行定位,可達成後處理高精度的定位成果。本研究分別以差分定位(DGPS)與PPP兩種解算方式,在6條空載光達掃瞄航線中選出調查區塊進行比較。首先,比較兩種解算方式產出之航跡差異。再以DGPS及PPP各別解算航跡產出光達離散點雲LASer(LAS)成果,以對應時間戳記比較平差前、後點雲兩種解算方式差量。另外,以結合DGPS及PPP各別產出LAS平差成果與僅DGPS解算產出LAS平差成果比較,試瞭解在難以設置地面基站作業區域中PPP替代DGPS可能性。本研究結論DGPS及PPP兩種解算方式於不同大地基準情況下,PPP產出之航帶點雲能有效利用航帶平差作業方式,達成結合DGPS及PPP兩種解算點雲之成果。

Abstract

The positioning accuracy of airborne LiDAR point clouds is mainly originated from GPS positioning. In general, DGPS method is used in Taiwan for solving the position of GPS rover on the air-plane with a ground base station within 20 km. However, part of the high mountains in Taiwan is inaccessible, where suitable site for installing ground reference stations is almost impossible. It is important to know the potential of applying Precise Point Positioning(PPP). PPP by using IGS GPS satellite precise ephemeris and clock anywhere in the world can achieve real-time or post processing for high-precision positioning. In this study, a test is carried out by using both conventional DGPS and PPP methods for a block of 6 selected flight strips of LiDAR scans. Results of LAS data generated by both methods are compared by the TIMESTAMP of point clouds for both before and after strip adjustment. In addition, results of adjustment of strips combined from both DGPS and PPP are compared with those of all strips of DGPS and, thus, to understand the possibility of using PPP instead of DGPS for the area not accessible for installing continuous GPS stations. It is concluded that though there is a datum difference between DGPS and PPP, strips of point clouds generated by PPP can be effectively merged into strip adjustment combining both strips of point clouds by DGPS and PPP.

關鍵字

GPS時間戳記, 航帶平差, 資料合併, 地面參考站, 光達點雲

Keywords

GPS timestamp, strip adjustment, data merge, base station, LiDAR LAS

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

13-35

論文名稱

以物件為基礎之光達點雲分類

Title

Object-Based Classification for LiDAR Point Cloud

作者

林耿帆, 徐百輝

Author

Keng-Fan Lin, Pai-Hui Hsu

中文摘要

近年來,影像分類方法逐漸由像元式發展為物件式分類,其藉由像元間之空間關係建立影像物件,並納入影像物件之光譜、形狀、及紋理等物件特徵作為分類依據,進而提高影像分類之成效。本研究嘗試將二維物件式影像分類架構延伸至三維光達點雲分類,期望藉由物件分類之觀念提升光達資料自動分類目標物之能力。本研究首先將光達點雲資料自動分割為獨立的三維點雲物件,接續利用自行設計之物件特徵進行特徵萃取,最後以物件特徵自動化分類點雲。實驗中分別以空載及地面光達資料進行測試。在空載光達部份,研究中選用結構物、樹及車輛作為分類標的,於整體分類精度與Kappa值分別達到98.40 % 與0.9638 之分類成效;在地面光達部份,本研究選用建物、小型結構物、樹、樹幹與樹叢等類別作為分類目標,整體分類精度與Kappa值分別為84.28% 與0.7221。由實驗結果可知,以物件為基礎之光達點雲分類,能藉由描述點群具有的空間特性輔助點雲資料之判釋,不僅有效提升分類成果之完整性,在分類品質上亦能有不錯的表現。

Abstract

Recently, image classification methods have transferred from pixel-based to object-based. Under the consideration of specific spatial features of objects, such as spectral, shape, texture, or the subordinative relations among them, object-based image analysis (OBIA) could improve the efficiency of image classification. In order to raise the capability of automatic recognition of land features from LiDAR data, 2D object-based classification method is extended for 3D point cloud classification of LiDAR data in this study. First, point cloud is segmented to independent 3D objects by various methods. Second, object features designed by this study are calculated. At last, the point clouds are classified automatically according to the object features . This study applies airborne LiDAR and ground-based LiDAR to automatic land feature classification. On the part of airborne LiDAR, structures, trees and cars were chosen to be the targets of classification. The overall accuracy and kappa value ran up to 98.40 % and 0.9638 respectively. On the other hand, on the part of ground-based LiDAR,  buildings, small structures, trees, trunks and groves were chosen to be the targets. The overall accuracy and kappa value were 84.28 % and 0.7221 respectively. The results show that utilizing the object-based concept to classify LiDAR point cloud can give assistance to point cloud recognition by means of depicting the spatial characters of these objects. The classification results then, therefore, improve not only the completeness, but also the quality.

關鍵字

物件式分類、分割、特徵萃取、決策規則

Keywords

Object-Based Classification, Segmentation, Feature Extraction, Decision Rules

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

37-47

論文名稱

空載光達資料產製數值高程模型之品質評估探討

Title

Quality Assessment of DEM Generation from Airborne Laser Scanning Data

作者

王正楷, 曾義星, 劉囿維

Author

Cheng-Kai Wang, Yi-Hsing Tseng, Yu-Wei Liu

中文摘要

空載光達資料目前已成為生產大範圍數值高程模型(Digital Elevation Model, DEM)的主要來源之一。藉由點雲的過濾程序,點雲即可被分類為地面點和非地面點,而分類後的地面點即可用以生產DEM。欲評估DEM的成果,過去經常使用的方法為計算點雲分類後之分類精度;另一方法則利用一個已知的DEM或是已知的控制點當作檢核資料,再與所生產的DEM進行高程差異比較。在這二個方法中,當採用分類精度的指標時,其缺點在於無法顯示點雲分類的成果是否有過度濾除之現象(即代表地面重要特徵的點位被濾除了),或是地面點群中仍然存在極大的高程差異之非地面點,此分類精度的缺點雖然可以利用高程差異比較的方法來彌補,但高程差異法在實務的檢核應用上,往往僅適用於平坦地,不適於地勢陡峭之測區,此乃因地勢陡峭之區域,其地面點和非地面點之分類往往容易混淆,造成有較大的誤差存在,若以直接高程差異的方式來評估DEM,這些區域通常難以通過檢核之標準,實務上,我們希望判斷的標準能夠隨著地勢之起伏而有所調整,且此標準能夠適當且合理的評估DEM之品質。因此本研究以實際應用面的層面來考量,提出一個正規化高程差異指標,此指標可適用於不同坡度之地形,研究中並透過此指標來評估自行所產製的DEM,實驗結果顯示,正規化高程差異指標在實際的檢核上,能有效的運用在市區和郊區中,在考慮坡度的因素後,能夠快速提供DEM品值判斷上之依據。

Abstract

The airborne laser scanning point clouds have become one of the primary data sources for DEM generation. By applying filtering algorithms to point clouds, the points can be classified into non-ground points and ground points. The DEM is then produced from the ground points. To assess the quality of DEM generation, a traditional method is to compute the classification accuracy of filtering results. Another method is to check the elevation differences between the produced DEM and a reliable reference DEM or some control points. However, the classification accuracy cannot reveal the over-filtering situations or any distinct non-ground points still remaining in the filtered ground data set. Although those disadvantages can be complemented by using the elevation difference method, the elevation difference method still needs to further take the topography relief into considerations for the use in a practical application. Usually those higher elevation differences occur in slope surfaces because the points on a slope surface are not easier to be classified by most filters compared with the points in a planar surface. For this reason, this paper presents a normalized elevation difference method which takes account of the surface slopes. The basic idea is using the slope as the weights for elevation difference computing. In a slope surface, the elevation difference toleration will raise while decrease in a planar surface. The experiment results show that our proposed method can be considered as a new assessment indicator especially in a practical application.

關鍵字

空載光達、數值高程模型、品質評估

Keywords

Airborne LiDAR, Digital Elevation Model, Quality Assessment

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

49-62

論文名稱

使用漸增式區塊化策略從光達點雲萃取面特徵

Title

Extraction of Surface Features from LiDAR Point Clouds Using Incremental Segmentation Strategy

作者

王淼, 曾義星

Author

Miao Wang, Yi-Hsing Tseng

中文摘要

以空載或地面光達(Light Detection and Ranging, LiDAR)掃瞄得到的資料是不規則分佈於被掃瞄物體表面的點觀測量,特徵萃取是將光達資料轉換為空間資訊的關鍵程序,其中面特徵是光達資料中最主要的空間特徵。本文提出一個通用性的方法-漸增式區塊化策略-進行共面點雲區塊化,漸增式區塊化策略可依應用需求分為數個步驟,在每個步驟採用適當的演算法和運算條件。本研究提出的方法將面特徵萃取分為四個步驟:第一、使用八分樹結構化體元空間建立點雲間的相鄰關係;第二、使用相連成份標記(Connected Component Labeling)演算法將點雲區分為數個相鄰點群;第三、使用基於八分樹之分割-合併演算法從每個點群中萃取出平面特徵;最後,使用區域成長法將相鄰的平面特徵合併為曲面特徵。實際上,四個步驟分別將光達點雲區分為組織化的點群、相鄰點群、共平面點群及共曲面點群。利用本研究提出的方法可採漸增方式進行大量點雲資料集之擷取及分析,實驗證明此方法可有效率地處理空載和地面光達點雲資料,而且,本方法的最終以及中間成果均可分別應用於不同目的的物體模塑。

Abstract

LiDAR (Light Detection and Ranging) point clouds are measurements of irregularly distributed points on scanned object surfaces acquired with airborne or terrestrial LiDAR systems. Feature extraction is the key to transform LiDAR data into spatial information. Surface features are dominant in most LiDAR data corresponding to scanned object surfaces. This paper proposes a general method to segment co-surface points. An incremental segmentation strategy is developed for the implementation, which comprises several algorithms and employs various criteria to gradually segment LiDAR point clouds into several levels. There are four operation steps. First, the proximity of point clouds is established as spatial indices defined in an octree-structured voxel space. Second, a connected-component labeling algorithm for voxels is applied for segmenting neighboring points. Third, coplanar points then can be segmented with the octree-based split-and-merge algorithm as plane features. Finally, combining neighboring plane features forms surface features. With respect to each step, processed LiDAR point clouds are segmented into organized points, neighboring point groups, coplanar point groups, and co-surface point groups. The proposed method enables an incremental retrieval and analysis of a large LiDAR dataset. Experiment results demonstrate the effectiveness of the segmentation algorithm in handling both airborne and terrestrial LiDAR data. The end results as well as the intermediate results of the segmentation may be useful for object modeling of different purposes using LiDAR data.

關鍵字

光達點雲、區塊化、八分樹、體元空間、空間特徵、漸增式

Keywords

LiDAR Point Cloud, Segmentation, Octree, Voxel Space, Spatial Feature, Incremental

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

63-73

論文名稱

比較各種空載光達儀器與飛航參數對於森林穿透率影響

Title

LiDAR Penetration Comparisons at Different Instruments and Flight Parameters in Forest

作者

李崇誠, 邱珮榕, 王驥魁

Author

Chung-Cheng Lee, Pei-Jung Chiu, Chi-Kuei Wang

中文摘要

空載光達的雷射可穿越樹冠層的遮蔽到達地表面,對於面積較大之森林區域,可在短時間獲得大量點雲的反射強度值(Intensity)以及三維坐標。點雲資料包含地面點以及地物點,可用於森林地區製作DEM (Digital Elevation Model)。而雷射的穿透率會受到地表覆蓋物、航高以及雷射入射角的影響。本研究樣區分別為南仁山生態保護區以及那瑪夏區達卡努瓦里,兩樣區皆有大量森林覆蓋。三種空載光達(Optech Pegasus HD400、Leica ALS60、Riegl LMS-Q680i)收集資料於同一樣區的低、中及高航高的資料分別計算地面穿透率,由實驗結果可以得出Optech HD400與Riegl LMS-Q680i於低航高2000 m及1250 m的穿透率與中航高及高航高相比,穿透率大於0.2的次數較多;Leica ALS60在不同航高的穿透率則無顯著差異。同一地區不同空載光達的穿透率為Optech HD400於南仁山的穿透率最佳;Leica ALS60於達卡努瓦里穿透率最低。由研究成果,穿透率的成果與光達的參數設定及其飛航資料有關。

Abstract

Airborne LiDAR can obtain abundant 3D coordinates and intensity of point clouds which include ground points and object points in short time by penetrating the canopies to the ground in forest areas which can be used in making DEM (Digital Elevation Model). The coverage on the topography, flying height and laser incident angle have an effect on the laser penetration of the LiDAR. Three different types of airborne LiDAR (Optech HD400, Leica ALS60 & Riegl LMS-Q680i) separately collect data in low, medium and high flying altitude in the same area to calculate the ground penetration where plenteous tree species cover two study areas: Najenshan ecological reserve area and Dakanuwa village, Namaxia district, Kaohsiung City. To sum up from the research, the number of penetration rate greater than 0.2 in low flying altitude, 2000 m for Optech HD400 and 1250 m for Riegl LMS-Q680i respectively, are much more than medium and high flying height in contrast that Leica ALS60 has no significant discrepancy. Besides the effect of flying altitude, the setting of LiDAR’s parameters result the better penetration for Optech HD400 in Najenshan ecological reserve area and worse to Leica ALS60 in Dakanuwa village.

關鍵字

空載光達、光達雷射穿透率、森林穿透率

Keywords

airborne LiDAR, laser penetration of LiDAR, penetration in forest

附件檔名

華芸線上圖書館

N / A

備註說明

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