ENGLISH

22卷/4期

22卷/4期

華藝線上圖書館

Pages:

227‐241

論文名稱

Landsat 8 衛星影像支持向量機雲偵測演算法

Title

Cloud Detection Based on Support Vector Machine for Landsat 8 Imagery

作者

李冠毅、林昭宏

Author

Kuan-Yi Lee, Chao-Hung Lin

中文摘要

光學遙感探測衛星影像中普遍有雲覆蓋地表的問題,同時限制處理影像的方法。多數先前研究中,使用門檻值是最普遍的方法,然而,因地制宜的門檻值通常只適合該研究地區;地球環境不斷推移變化,如持續用同一門檻值,勢必有失效情況發生。根據支持向量機雲偵測演算法,可避免上述問題。故本研究利用統計模式建立分類基準,避免使用相對主觀的門檻值,依照雲和其他目標物對於不同波段之物理特性相互調整出合適光譜特徵;紋理特徵部分則使用Hotelling transform 再經過共現矩陣產生之紋理影像。經實驗後,結果顯示本研究提出之方法其整體準確度介於93%至97%。

Abstract

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images. In previous studies, thresholding is a common and rapid method in cloud detection. However, a selected threshold is usually suitable for local study areas, and it may be failed in other cases. Besides, there are many exceptions to control, and the environment is changed dynamically. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method. According to the physical characteristics of clouds and other objects, the spectral features are appropriately designed for classification. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix of the Hotelling transform is used in proposed method. Experiment results demonstrate the detection accuracy of the proposed method is about 93% to 97%.

關鍵字

雲偵測、分類、支持向量機

Keywords

Cloud Detection, Classification, Support Vector Machine

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/Index/10218661-201712-201712270005-201712270005-227-241/

備註說明

N / A

Pages:

243-262

論文名稱

應用衛星影像的水線辨識於外傘頂洲的灘線變遷

Title

Shoreline Evolution of the Waisanding Barrier Using Waterline Detection from Satellite Images

作者

張憲國、賴羿齊、陳蔚瑋

Author

Hsien-Kuo Chang, Yi-Chi Lai, Wei-Wei Chen

中文摘要

本文提出擷取衛星影像的水線,平移至灘線的方法,並探討外傘頂洲的灘線變遷。研究方法的影像處理技巧包括,IHS轉換法、NDWI、影像強化、形態學及Canny法。另外,修正NAO99b潮位數值模式的潮位資料融合法,來解決外傘頂洲無觀測潮汐資料的問題。 自1994至2015年的灘線及陸上面積的長期變化分析後發現,外傘頂洲的海側灘線在北端以-30.5m/yr,而南端以-119m/yr 的速度往內陸內縮;陸上面積被侵蝕速率近年有增加的趨勢,且長期的變化有夏季增加,但冬季減少的季節特性。若以2009~2015年的陸地面積被侵蝕速率,可預測外傘頂洲的陸地將於2060年完全低於平均潮位而淪為潛沒沙洲。

Abstract

This paper investigates the shoreline evolution of Waisanding barrier using waterline detection from satellite images. Required image processing includes (1) IHS conversion method (2) NDWI index (3) Image enhancement method (4) Morphology and (5) Canny edge detection for capturing the waterline. Due to no observation on tides at the Waisanding barrier data blending method associated with NAO99b tidal model is used to accurately compute the tidal levels. The horizontal distance to shift the waterline to the shoreline is determined by both obtained tidal level and beachface slope. The shoreline evolution and land-area variation above mean sea level of the Waisanding barrier from 1994 to 2015 are evaluated to show that the northern shoreline of the Waisanding barrier is receding by a rate of 30.5 m/yr and the southern part is by 119 m/yr. The results also indicate that the land area of the Waisanding barrier has a long-term decreasing trend with a faster rate in the recent period and a regular and seasonal variation of erosion in the winter and accretion in the summer. Depending on the decreasing rate of land area from 2009 to 2015 the Waisanding barrier will vanish in 2060 based on the rate.

關鍵字

外傘頂洲、灘線變遷、影像處理、水線辨識

Keywords

Waisanding barrier, Shoreline evolution, Image processing, Waterline detection

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/Index/10218661-201712-201712270005-201712270005-243-262/

備註說明

N / A

Pages:

263-274

論文名稱

利用MODIS 資料推估PM2.5 濃度之研究-以2013 年石化工安意外為例

Title

Estimating PM2.5 Concentration with MODIS for 2013 Petrochemical Industrial Accident

作者

陳慧欣、史天元、江博煌

Author

Hui-Hsin Chen, Peter Tian-Yuan Shih, Po-Huang Chiang

中文摘要

行政院環保署(2015)定義,空氣中存在許多污染物,其中漂浮在空氣中類似灰塵的粒狀物稱為懸浮微粒(Particulate Matter, PM),PM粒徑小於或等於2.5μm的粒子,就稱為PM2.5,通稱細懸浮微粒。PM2.5濃度是一項評估空氣品質的重要指標,截至2014 年底,環保署建置76個PM2.5地面空氣品質測站。地面空氣品質監測站提供區域性的連續高精度觀測資料,而衛星遙測技術則可提供全球性的觀測資料,儘管如此,其資料會受限於氣候條件而影響。 在眾多衛星影像感測器中,MODIS所提供的一個標準科學產品MOD04,記錄氣膠光學厚度(Aerosol Optical Depth, AOD)資料。透過AOD 資料及PM2.5測站的觀測值,將兩者進行迴歸分析後,即可推估PM2.5濃度。本研究使用環保署本島的73個地面測站資料,以2013年2月14日台塑集團第6套油裂解廠工安意外事件的PM2.5濃度變化為例。透過工安意外事件當日全臺AOD 與PM2.5濃度的迴歸分析,結果顯示其R2值為0.50。除此之外,並發現六輕周圍5 個測站之PM2.5濃度於工安意外事件當日皆高達54μm/m3,已超過環保署公布空氣品質標準PM2.5之24小時值標準值35μm/m3。本研究藉由導入AOD資料,可提供一種PM2.5濃度推估方法,但仍需更進一步的模式及資料改善以降低其不確定性。

Abstract

There are many pollutants in the air. Particulate Matter (PM) is similar to floating dust. For those with size less than or equal to 2.5μm, they are called PM2.5 (Taiwan EPA, 2015). The concentration of PM2.5 is an important indicator of air condition. By 2014, there are 73 PM2.5 monitoring stations established by the Environmental Protection Administration (EPA) in Taiwan. While the ground stations provide continuous and high precision in-situ observations, satellite borne remote sensing technique could provide a vast area coverage but with limited time epoch information. Among a number of satellite image sensors, MODIS provides a standard scientific product, MOD04, for AOD (Aerosol Optical Depth, AOD) measurement. With MOD04, PM2.5 concentration could be estimated with correlation and regression to in-situ measurements. This study utilized the 73 EPA ground stations for an incidence occurred on Feb. 14, 2013 in the 6th naphtha cracker of Formosa Plastic Group. The result shows that the correlation index R2 between AOD and PM2.5 is 0.50 among Taiwan. According to the 5 ground in situ PM2.5 data nearby the 6th naphtha cracker, they are all up to 54μm/m3 and have exceeded the EPA standard of 35μm/m3 the air quality standard per 24 hours. While the AOD measurements derived from satellite images offer a way for estimating PM2.5 concentrations, further improvement in the modeling and data processing is required for reducing the uncertainty.

關鍵字

PM2.5、MODIS、氣膠光學厚度、空氣汙染

Keywords

AOD, air pollution, MODIS, PM2.5

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/Index/10218661-201712-201712270005-201712270005-263-274/

備註說明

N / A

Pages:

275-290

論文名稱

象鼻鋼管縮尺模型之水下物件追蹤及四維動畫重建

Title

Underwater Object Tracking and 4D Animation Reconstruction of Elephant Trunk Steel Pipe Scale Model

作者

詹鈞評、饒見有、周志明

Author

Jyun-Ping Jhan, Jiann-Yeou Rau, Chih-Ming Chou

中文摘要

本文結合物件追蹤與水下攝影測量技術,用以觀察曾文水庫防淤隧道工程之象鼻鋼管(Elephant Trunk Steel Pipe, ETSP)縮尺模型於水下安置模擬作業的六自由度(6 Degree-of-Freedom, 6DOF)動態變化,並整合 三維模型重建四維動畫。因水下攝影系統安裝困難,本研究採三維導向的物件追蹤,應用後方交會求解 相機位置與姿態。在相對運動概念下,象鼻鋼管的六自由度動態變化可經多相機系統的座標轉換或單相 機的相對方位轉換求得。從成果比較來看,單相機與多相機解算成果具備高一致性,能提供六自由度動 態數據協助實務工程作業上的分析,與多相機系統相比,單相機作法更具備低成本與高效率之優點。

Abstract

In this study, the underwater photogrammetry and object tracking techniques are adopted for monitoring the 6 Degree-of-Freedom (6DOF) dynamic change of an Elephant Trunk Steel Pipe (ETSP) scale model during its underwater installation simulation, and then reconstruct its 4D animation by integrating its 3D model and 6DOF parameters. Considering the difficulty of camera installation in the underwater environment, the 3D model based object tracking technic is adopted to compute the positions and attitudes of camera instead of tracking feature points on objects. Under the concept of relative motion, the 6DOF parameters of ETSP can be obtained through multi-camera coordinate transformation or single camera relative orientation transformation if their orientation parameters are calculated by space resection. Results and analysis show that both multi-camera and single camera approaches can derive the 6DOF parameters of ETSP, in which single camera approach shows higher convenience that has benefits of low cost and high efficiency.

關鍵字

物件追蹤、六自由度、水下攝影測量

Keywords

Object tracking, 6DOF, Underwater photogrammetry

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/Index/10218661-201712-201712270005-201712270005-275-290/

備註說明

N / A

Pages:

291-301

論文名稱

無人飛行載具編隊飛行模擬平台開發與測試

Title

Development and Testing of a Formation Flight Simulator for Unmanned Aerial Vehicles

作者

賴盈誌、丁繹仁、王婷

Author

Ying-Chih Lai, Yi-Ren Ding, Ting Wang

中文摘要

本研究的目的是開發無人飛行載具(Unmanned Aerial Vehicle, UAV)之編隊飛行模擬平台,目標是開發出多智能體硬體迴路模擬系統。主要的研究內容包含編隊飛行導航與控制、編隊飛行演算法開發、硬體迴路系統設計以及模擬與驗證等項目,目標是做到使用模擬平台來進行固定翼載具與旋翼機的編隊飛行控制與編隊演算法開發。本研究成功使用所開發的編隊模擬平台來驗證編隊控制器與編隊演算法。模擬的結果顯示,所開發的模擬平台可用於兩種不同構型的載具,包含固定翼載具與旋翼機上,同時驗證軟體迴路與硬體迴路模擬皆可以達到UAV編隊控制器與編隊演算法的驗證。

Abstract

The goal of this study is to develop a formation flight simulation platform for Unmanned Aerial Vehicles (UAVs). By using the developed platform, the formation flight control for multi-agent system can be designed and simulated. The multi-agent system comprises of more than one physically independent agent while having a common goal. The main tasks in this study contain formation flight navigation and control and navigation, formation scheme and algorithm development, Hardware-In-the-Loop (HIL) system setup, and flight simulation and verification. The adopted UAVs include fixed-wing and rotorcraft types. The quad-rotor UAV was selected to be the target aircraft for rotorcraft. This study successfully performed the formation flight controller and algorithm on the developed HIL platform. The results show that both the fixed-wing UAV and rotorcraft can be simulated on this platform.

關鍵字

無人飛行載具、固定翼載具、旋翼機、硬體迴路模擬

Keywords

Unmanned Aerial Vehicle (UAV), Fixed-wing Aircraft, Rotorcraft, Hardware-In-the-Loop (HIL)

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/Index/10218661-201712-201712270005-201712270005-291-301/

備註說明

N / A

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