ENGLISH

10卷/1期

10卷/1期

華藝線上圖書館

Pages:

1-14

論文名稱

空載雷射掃描資料於推估樹冠高度之應用

Title

Estimation of Forest Canopy Height Using Airborne Lidar Data

作者

詹進發

Author

Jihn-Fa Jan

中文摘要

森林生態系經營有賴於詳實之林分結構資訊,傳統地面調查需耗費大量人力、物力、經費與時間, 不易獲得迅速且正確之資訊。空載雷射掃描儀具有高密度測點與穿透樹冠間隙之特性,可迅速獲取林分之三度空間資料,適合用於林分結構相關資料之蒐集。本研究利用以Leica ALS40掃描陽明山地區所獲取之空載雷射掃描資料,產生林分數值表面模型,進而以林分數值表面模型與數值高程模型之差推估樹冠高度模型,並與11個地面樣區實測樹高比較,以評估其準確度。結果顯示以LIDAR資料估測樹冠高度普遍有低估之現象,若能提高數值表面模型與數值地形模型之精度,應可建立較準確之樹冠高度推估模式。

Abstract

Forest ecosystem management depends on detailed information about forest stand structure. Traditional ground investigation requires vast amount of manpower, resources, costs, and time, hence it is not easy to promptly obtain accurate information by using ground investigation. Airborne laser scanner (LIDAR) is capable of measuring objects at very high density and penetrating gaps among tree crowns, therefore it can rapidly obtain 3D data about forest stands, and can be used for acquiring related data about forest stand structures. This study utilized an airborne laser scanner data set, acquired using Leica ALS40 scanner, of the Yangminshan National Park area to derive digital surface model for the forest canopy. Furthermore, the forest canopy height model was estimated by computing the difference between the digital surface model and a digital elevation model. The canopy height model was compared to the tree heights measured in eleven ground sample plots in order to assess its accuracy. The results indicate that the forest canopy height is generally underestimated by using the LIDAR data. More accurate forest canopy height model can be achieved, if the accuracy of the digital surface model and digital elevation model can be improved.

關鍵字

空載雷射掃描、樹冠高度、數值表面模型、數值高程模型

Keywords

airborne lidar, canopy height, digital surface model, digital elevation model

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-1-14

Pages:

15-25

論文名稱

空載雷射掃瞄測高資料區域平差模式之建立與可行性之研究

Title

A Study on the Establishment of Block Adjustment Model and Feasible Investigation for Airborne Laser Altimeter Data

作者

尤瑞哲,蔡欣怡

Author

R. J. You,S. Y. Tsay

中文摘要

空載雷射掃瞄技術以GPS的定位和INS的姿態決定可直接推導得地面雷射點的高程。理論上,不需要其他輔助方法。目前所有的雷射掃瞄系統皆採用此種方法求得地面點的高程。本論文則輔以掃瞄帶重疊的幾何特性提出一個平差模式,研究由高程資料進行區域平差計算之可行性,藉以提高空載雷射掃瞄的精度。本文所提的方法適用於高程的一階導數連續之資料。研究結果顯示,在綠色植被地區,應用本法可以得到約20cm的高程精度。

Abstract

The airborne laser scanning technique with GPS positioning and INS orientation is useful for height determination of ground points. In principle, no other auxiliary data are needed, and the coordinates of topographic points can be derived directly from the computational results of GPS and INS data. All current developed airborne laser scanning systems apply the method for the height determination. In the paper, we present a block adjustment model for sufficiently utilizing the overlaps between the scanning strips and study the feasibility of the model in order to improve the accuracy of the height determination by airborne laser scanning technique. Our method is applicable for height data which have a continuous first order derivative. The results show that the accuracy at ±20 cm level is achievable.

關鍵字

空載雷射掃瞄、區域平差

Keywords

airborne laser scanning, block adjustment

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-15-25

Pages:

27-46

論文名稱

整合光達點雲與空照影像重建三維建物模型

Title

Integration of LIDAR Point Clouds and Aerial Imagery for Building Reconstruction

作者

賴彥中,陳良健, 饒見有

Author

Yen-Chung Lai,Liang-Chien Chen, Jiann-Yeou Rau

中文摘要

本研究從資訊融合角度出發,結合光達資料及數位化彩色空照影像進行三維建物模型之重建。研究重點分成兩個部分,第一部份是房屋區塊偵測,第二部份是房屋模型重建。房屋區塊偵測部分,依原始光達資料之高度資訊,判別出地上物區域。利用空照影像之色彩分析,將地上物區域之樹木部分去除。殘餘之區塊設定一面積門檻,將面積過小之區塊濾除。之後進行區塊形狀以及表面分析,去除不合理之區塊,房屋區塊即建立完成。房屋模型重建部分,首先進行光達資料前處理,預估出概略屋緣位置,同時萃取出位於屋頂平面之光達點。將預估之概略屋緣位置投影至空照影像上,設定工作區域,在此區域內進行精確之直線偵測。所得之直線線段組合成房屋之候選屋頂面,搭配前處理中萃取出之光達點進行屋頂面之判別與高度計算後,投影回物空間獲得三維之屋頂面,最終結合SMS 方法建立房屋模型。研究中使用新竹科學園區之光達資料及大比例尺數位空照影像進行測試,並使用一千分之一數值地形圖以及人工量測航測立體對產生之房屋模型做為檢核。

Abstract

From the viewpoint of data fusion, we integrate LIDAR point clouds and digital aerial image to perform 3D building modeling in this study. The proposed scheme comprises two major parts: (1) building block detection and (2) building model reconstruction. In the first step, height differences from LIDAR point clouds are analyzed to detect the above ground areas. Color analysis is then performed for the exclusion of tree areas. Remaining regions are restricted by area threshold. After the refinement by shape and texture analysis, building blocks are established. In the second step, we analyze the height information of LIDAR point clouds to estimate the approximate roof-edges and extract the LIDAR points located on the rooftop. Based on the approximate roof-edges, accurate 2D edges are calculated in aerial image and then transformed into candidate roof-planes. Combined with the extracted LIDAR points, the correct roof-planes are selected and projected back to object space as 3D roof-planes. At last, a patented method SMS (Split-Merge-Shape) is employed to generate building models using the 3D roof-planes. LIDAR point clouds and large scale aerial image in Hsin-Chu Science-based Industrial Park were used in the test. A 1/1000 scale topographic map and reconstructed building models measured manually from stereo pairs were used to evaluate the results.

關鍵字

光達點雲、空照影像、資料融合、房屋偵測,房屋重建,房屋模型

Keywords

LIDAR point clouds, aerial image, building detection, building reconstruction, building model

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-27-46

Pages:

47-58

論文名稱

利用光達資料於DEM 生產及房屋偵測之研究

Title

DEM Generation and Automatic Building Detection Using LIDAR Data

作者

邵怡誠,陳良健

Author

Yi-Chen Shao,Liang-Chien Chen

中文摘要

本文研究利用光達資料進行二種自動化的作業,一是生產數值高程模型,二是偵測房屋區。第一部份主要是利用二種數學形態學的方法,平坦操作及圓頂轉換,在高程空間中自動重建地形以區隔出地物點,藉由保留的地面點來產生數值地表模型。第二部份則延用第一部份的地物點的群聚區塊,切取高度超過3公尺且面積較大的地物區,經斜率差計算後,使用10種統計量來偵測房屋位置。在數值高程模型產製部份,以新竹科學園區及大坑地區為測試區,本文成果與人工過濾成果進行精度評估,得平均值分別為-0.16m和0.07m、均方根誤差分別為0.45m和0.59m。至於房屋偵測部份,在新竹科學園區的測試區之成功率為87.7%。

Abstract

There are two main parts in our research. The first is to segment objects and to produce digital terrain model by using two mathematical morphology methods, i.e. flattening operation and H-Dome transformation, and control posts. The second is to detect buildings by slice the objects’ height, filtering out small areas and computing their statistics of differential slope on region-based method. There are two test areas, one is around Hsin-Chu Science Based Industry Park, and the other is around Ta-Keng area. The results of accuracy for digital terrain model production are -0.16m and 0.04m for mean, 0.45m and 1.12m for RMSE, respectively. And the successful rate for building detection is 87.7%

關鍵字

光達、數值高程模型、分類、房屋偵測

Keywords

LIDAR, DEM, Classification, Building Detection

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-47-58

Pages:

59-70

論文名稱

光達資料八分樹結構化於平面特徵萃取

Title

LIDAR Data Octree Structurizing for Plane Extraction

作者

王淼,湯凱佩,曾義星

Author

Miao Wang, Kai-Pei Tang,Yi-Hsing Tseng

中文摘要

光達可快速獲取被掃瞄物表面高精度及高密度的三維點雲資料。由於資料量非常龐大,其中包含豐富的空間資訊,為了有效率地處理光達資料,必須先將點雲組織成有利於後續處理的結構,並且保留其原有的資料精度。本文提出以八分樹結構組織光達點雲資料的方法,可將點雲資料組織成三維網格的型式,使用三維指標方式快速搜尋點雲資料,並從光達資料中萃取出隱含的三維平面資訊。本文提出的方法可以適用於空載及地面光達資料,對於具有多重反射或由多掃瞄站合併的點雲資料亦可適用。

Abstract

Lidar point cloud is a collection of a large amount of accurate 3D point data densely distributed on the scanned object surface. It implicitly contains abundant spatial information. To explore valuable spatial information from Lidar data becomes an active research topic. However, the processing of the huge amount of point data needs unusually large CPU time and storage volume. A well organized data structure is needed for the analysis or extraction of spatial features from point cloud in an efficient way. This paper proposes a novel method using an octree structure to organize point cloud in a 3D regular grid. The nodes of octree structure represent the cells of the 3D grids, which can be accessed easily and quickly based on a designed 3D array index. Two 3D plane extraction methods, named split & merge and 3D region growing, are proposed. These two methods fully explore the designed octree structure of point cloud. The plane extraction methods are practicable to both airborne and ground-based Lidar data. Test data include an airborne Lidar data set containing points of multiple echoes and a combined point cloud data set from several scan stations of ground-based Lidar were processed. The test results show meaningful feature extraction from lidar data. This study provides a stepping stone for the extraction of spatial information from lidar data.

關鍵字

光達、八分樹、三維網格、平面萃取

Keywords

Lidar、Laser Scanning, Octree、3D Grid、Plane extraction

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-59-70

Pages:

71-87

論文名稱

適應性點雲過濾演算法於空載光達資料

Title

An Adaptive Point Cloud Filtering Algorithm for DEM Generation from Airborne LIDAR Data

作者

周富晨,曾義星

Author

Fu-Chen Chou,Yi-Hsing Tseng

中文摘要

目前空載光達最主要的應用為生產DEM,而空載光達所得之點雲資料包含了地表點及地物點,應用於生產DEM 則須先將非地面點濾除。本研究以形態學理論為基礎,提出適應性點雲過濾演算法,目的在於過濾點雲中的非地面點,生產DEM。本演算法利用三維網格結構化點雲資料,計算地表大範圍之趨勢面及局部坡度,主要以適應性坡度的概念過濾點雲。經由實際資料測試,本演算法對多數地形狀況能有效濾除非地面點,獲得良好的過濾結果,唯在地形斷線處以及地形突然隆起或是下陷處,可能會將地面點過度濾除。而針對少部分過濾有誤的地方仍須以人工進行檢核編修,以確保DEM 之成果品質。

Abstract

DEM generation is the primary application of airborne LIDAR. The point cloud provided by airborne LIDAR not only represents the terrain surface, but also contains buildings, egetation, or other ground objects. The major process of generating DEM from airborne LIDAR is to filter out non-ground points from the point cloud data. The purpose of this study is to propose an adaptive filtering algorithm for DEM generation using airborne LIDAR data. The filtering algorithm is based on the principle of morphological filtering theory. To make the algorithm adaptive, a 3-D grid structure is used to organize point cloud data, so that the trend surface and local slope of the ground can be estimated. The feasibility of the proposed algorithm is tested by using some test data with different characteristics of topography. The algorithm is proved to be effective and practicable in most test cases, but in some cases some ground points in the rough terrain may be over-filtered. To assure the quality of DEM product, manual check and editing is still necessary against improper filtering results.

關鍵字

數值高程模型、空載光達、點雲、過濾演算法

Keywords

DEM, LIDAR, Point Cloud, Filtering

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-71-87

Pages:

89-102

論文名稱

以光達資料之控制直線求解單張像片外方位參數之模式探討與可行性評估

Title

LIDAR-based Control Lines for Single Photo Orientation

作者

趙鍵哲,彭念豪

Author

Jen-Jer Jaw,Nei-Hao Perng

中文摘要

空載光達(Airborne LIDAR)及地面光達(Ground-based LIDAR)系統能迅速地收集空間三維資料,提供豐富的物空間幾何訊息;而像片資料則具有較豐富的輻射資訊,便於影像判讀,但其空間三維幾何必須藉助方位求解及交會定點才能確定。因此結合光達資料與攝影測量方法應用之一即為如何藉助從光達資料中萃取的物空間特徵(如點、線、面特徵)作為像片求解外方位參數之控制資料。本研究利用三維的光達資料,從中萃取物空間直線特徵(本文稱為控制直線)作為控制資料,利用直線特徵在物、像空間與投影中心之幾何關聯求解像片外方位參數,並在數學模式中引入控制直線之誤差估計量,藉以合理化平差程序獲致較佳的外方位參數解算成果。本研究中實例之分析除了說明光達控制直線用於求解單張像片外方位參數之實用性,並闡述平差計算後之誤差特性。

Abstract

Airborne and ground-based LIDAR systems are able to quickly support the tasks of three dimensional spatial data acquisition and provide users with abundant geo-spatial information. Optical images, on the other hand, recorded with adequate radiometric detail offer advantages for better interpretation of the scene, three dimensional coordinates of object points can only be determined after orientation and intersection steps, however. Thus, one of the apparent gains in fusing LIDAR data sets with photogrammetry is to solve the photo orientation by using control information resulting from extracting features from LIDAR data sets. This study aims at employing control lines extracted from LIDAR data sets solving for single photo orientation. The functional model describing the geometric relationships among perspective center, line observations in image space, and that in object space, the random model characterizing the control line measuring errors both in image space and object space are established and tested in this work. The experimental results suggest the application potential of fusing LIDAR data sets with images for the task of single photo orientation.

關鍵字

控制直線、單張像片外方位參數求解

Keywords

Control Lines, Single Photo Orientation

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-89-102

Pages:

103-128

論文名稱

「科技短文」農委會空載光達台灣地區測試

Title

The COA Test Flights of Airborne LIDAR System in Taiwan

作者

史天元,彭淼祥,吳水吉,吳麗娟

Author

Tian-Yuan Shih,Miao-Hsiang Peng,Shoei-Jyi Wu,Liza Wu

中文摘要

空載光達整合雷射、GPS、與慣性導航系統,可提供高密度、高精度之高程資訊。為探討此一技術之作業特性,農委會委託交通大學執行本次測試。本文概述測試作業的步驟流程、並以九份二山測區為例,評估空載雷射掃描作業之成果精度。本次測試採用兩組不同的商業化系統重複作業,第一組為Optech ALTM 2033,作業期間在2002年3月20日至4月3日,掃描測區包括九份二山與台中大坑測區。第二組為LH ALS 40,作業期間在2002年4月10日至4月16日,掃描測區包括九份二山、台中大坑、草嶺潭、新竹及陽明山測區。以地面測量檢核點為基準進行九份二山測區精度驗證,發現不同的地類覆蓋有不同之成果。其中LH ALS 40數據呈現系統性誤差。在平坦裸露路面,ALTM 2033數值高程成果均方根誤差為9.2公分,ALS 40於扣除平均誤差後數值高程成果均方根誤差為14.0公分。在坡度22度的階梯茶園區,均方根誤差小於40公分。本研究並就雷射測高精度與地形坡度、測點密度、地形特徵變化有高度相關性進行分析。

Abstract

Airborne lidar system integrates the laser ranging, GPS, and inertial navigation systems. This integration provides an instrument capable for high density and high accuracy terrain relief measurement. A pilot study was conducted by the National Chiao-Tung Universtity, with support from the Council of Agriculture. This paper reports the process of this pilot study.The data acquisition includes two commercially available systems, Optech ALTM 2033 and Leica ALS 40. The flight period for the Optech ALTM 2033 is between March 20 and April 3, 2002. Test areas include the Ta-Keng of Taichung, and Jeou-Fen-Ell-San. The flight for Leica ALS 40 is conducted from April 10 to 16, 2002. Test areas include Ta-Keng, Jeou-Fen-Ell-San, Hsin-Chu, Tsao-Ling-Tarn, and Yang-Ming-San. The agreement of lidar measurements and field data gathered with RTK-GPS and total stations differs with land surface cover type. Comparing with the field data in the Jeou-Feng-Ell-San area, the root mean square error of Optech ALTM 2033 is 9.9 cm for the paved road surfaces. There are systematic errors presented in the Leica data set. After removing the average error, the root mean square error is 11.6 cm. In the area of 30% slope and covered with tea plants, the root mean square errors of both systems are less than 38 cm.

關鍵字

數值表面模型、數值高程模型

Keywords

Digital Surface Model, DSM、Digital Elevation Model, DEM

附件檔名

華芸線上圖書館

N / A

備註說明

200503-10-1-103-128

更多活動學刊