ENGLISH

23卷/3期

23卷/3期

華藝線上圖書館

Pages:

141-156

論文名稱

應用整合位移偵測演算法於臺灣西部河道變化之研究

Title

Geomorphological Change Detection Using an Integrated Method: A Case Study on the River Channel of Western Taiwan

作者

吳俊毅、史天元

Author

Jyun-Yi Wu, Tian-Yuan Shih

中文摘要

本研究利用整合位移偵測方法測試短時期劇烈變化之大安溪中游研究區,將測試成果以實測資料及前人研究比對,驗證本研究之偵測方法之可行性,探討河道變遷情形。研究成果顯示,大安溪河段地形隆起後,從2001至2010年間共可分成3個階段,分別為2001至2003年、2004至2006年及2007至2010年。河道一開始並無固定流路,行水路徑逐年變化,在氾濫平原區域擺盪,至侵蝕到護甲層流失造成岩床裸露後,確定河道位置,接著河道開始下切,其下切最大值為15 m。整合位移偵測方法考量河道水平擺盪情形加上DSM相減成果,確實可擷取出河道之真實三維變化,並詳細描述河道變遷歷程。

Abstract

We propose the integration method that combines the Particle Image Velocimetry (PIV) technique and DEM subtraction, which is described to detect the active kinematics of the river morphology in this thesis. While PIV can provide estimates for the channel change direction and magnitude; vertical analysis such as river incision rate derivation could be performed using the height difference between multi-temporal surface models. It is observed that the proposed scheme is capable of identifying three river evolution stages from the extracted movements in the Taan case. These stages are: years 2001 to 2003, 2004 to 2006, and 2007 to 2010, respectively. The channel begins to have no stable path, and have regular path from 2001 to 2010. The maximum value of incision between 2001 and 2010 is about 15 m. This study demonstrates that both PIV and DSM subtraction are effective in river geomorphological change identification. The integration of these two approaches could provide more information when observing the evolution of river morphology.

關鍵字

PIV、DEM相減、河道變遷、多時序分析

Keywords

PIV, DEM subtraction, channel changing, multi-temporal analysis

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10218661-201809-201809210003-201809210003-141-156

備註說明

N / A

Pages:

157-172

論文名稱

無人機多鏡頭多光譜相機系統之穩健自適應波段套合法

Title

Robust and Adaptive Band Co-registration for UAS Multi-lens Multispectral Camera System

作者

詹鈞評、饒見有

Author

Jyun-Ping Jhan, Jiann-Yeou Rau

中文摘要

多鏡頭多光譜相機系統搭載於無人飛行系統(Unmanned Aerial System, UAS)上,能獲取高空間解析度之多光譜影像進行植生調查應用。多鏡頭設計使各鏡頭能獲取特定之波長,但卻會因不同的透視中心、視角差異與透鏡畸變等差異,導致原影像存在因波段錯位所造成的鬼影現象。針對此問題,本研究開發一穩健自適應的波段對波段影像轉換法(Robust and Adaptive Band-to-Band Image Transform, RABBIT),透過相機率定與修正之透視投影轉換公式進行波段套合,且額外加入穩健自適應誤差修正以補償各種誤差類型。成果證明該方法適用於各式多鏡頭多光譜相機系統,並可達到0.2-0.4像元的波段套合精度。

Abstract

Multi-lens multispectral camera system can be mounted on an Unmanned Aerial System (UAS) for high resolution remote sensing data acquisition. The adopted multi-lens structure allows it to acquire multi-band images with each independent camera and specific filter. However, this lead to significant band misregistration effects as the perspective centers, viewing angles, and lens distortion effects differ to each other. In this study, a Robust and Adaptive Band-to-Band Image Transform (RABBIT) is proposed to solve the band misregistration issues of multi-lens multispectral camera. The RABBIT utilizes a modified projective transform for transferring the multi-sensor geometry into one sensor geometry, in which all the necessary coefficients are derived from camera system calibration. Considering the coefficients uncertainty during the calibration, a simulation procedure is conducted to understand the systematic effects, and a robust and adaptive correction is thus developed to correct the various systematic errors. Several datasets were collected from three state-of-the-art multi-lens multispectral camera system for the accuracy analysis and reliability evaluation. The experiments show that RABBIT can achieve 0.2-0.4 pixels band co-registration accuracy, better than the other proposed method, and is robust to different cameras, different camera calibration approaches, and different flight missions.

關鍵字

多鏡頭相機系統、無人飛行系統、多光譜影像、波段套合

Keywords

Multi-lens Camera System, UAS, Multispectral Image, Band Co-registration

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10218661-201809-201809210003-201809210003-157-172

備註說明

N / A

Pages:

173-189

論文名稱

利用偏移偵測法監測格陵蘭Russell冰河之位移

Title

Tracking Greenland Russell Glacier Movements Using Pixel-offset Method

作者

蔡亞倫、林士淵、Jung-Rack Kim

Author

Ya-Lun Tsai, Shih-Yuan Lin, Jung-Rack Kim

中文摘要

近年全球暖化現象日益嚴重,格陵蘭等極區融冰所造成之海平面上升將對全球人類帶來嚴重威脅。因冰層質量之改變與冰河移動速度高度相關,故可藉由監測格陵蘭冰層(Greenland Ice Sheet, GrIS)上冰河之移動推估全球暖化對其造成之影響。衛星影像因具有連續且快速獲得大範圍地表資訊之能力,故已廣泛應用於廣域冰河之監測;然各項技術受限於快速移動且地貌不穩定之冰河表面而有諸多限制,故本研究使用偏移偵測法(Pixel-offset, PO)以衛載光學及合成孔徑雷達(Synthetic Aperture Radar, SAR)影像獲得冰河表面之位移向量。經比較不同影像品質、處理參數等調整對於變動偵測成果之影響後,本研究發現目前免費衛載光學影像以Landsat-8的全色態波段有最佳成果,而SAR影像以經Log處理之HH偏極影像為最優。

Abstract

Global warming has been a worldwide issue and significantly increasing icecap melting rate over polar area. Consequently the sea level rises continuously and poses a fundamental threat to whole human beings. Since the mass loss of Greenland ice sheet (GrIS) is highly correlated to the velocity of glacier movement, this study aims to monitor the impact of global warming by tracking glacier terminus displacement over GrIS using spaceborne remote sensing techniques which are widely applied in cryosphere monitoring for its continuous and efficient data collection ability. However, as many techniques are limited by the rapid changing and instable landscape dynamics of glacier surface, the present study utilizes the pixel-offset (PO) method with optical and synthetic aperture radar (SAR) images to track glacier deformation. In addition, by comparing the combinations of different quality images, processing parameters and pre-processing methods, we found the pan channel of Landsat-8 images and the log-processed HH polarization SAR images show the most promising results.

關鍵字

偏移偵測法、格陵蘭冰層、合成孔徑雷達

Keywords

Pixel-offset, Greenland Ice Sheet, Synthetic Aperture Radar

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10218661-201809-201809210003-201809210003-173-189

備註說明

N / A

Pages:

191-204

論文名稱

應用土地利用迴歸模式推估北部空品區細懸浮微粒之時空分布

Title

Spatial-Temporal Variability of Fine Particulate Matter in Northern Air Quality Zone of Taiwan Using Land Use Regression

作者

曾于庭、吳治達、龍世俊

Author

Yu-Ting Zeng, Chih-Da Wu, Shih-Chun Candice Lung

中文摘要

細懸浮微粒(Fine Particulate Matter, PM2.5)對人體健康之衝擊與危害為近日倍受關注的議題。受限於空氣品質監測站數目上之分布、加上多元且複雜的區域污染排放源,如多元餐廳類型、工業區等,因此土地利用迴歸模式(Land Use Regression, LUR)在國際間越來越被廣泛運用,然而目前國內相關應用案例仍不多見。本研究針對細懸浮微粒以及土地利用迴歸模式之相關文獻進行系統性回顧後,利用環保署於北部空品區所設立之24個空氣品質監測站於2006-2011年六年間之所有歷史監測資料,分別建立逐年、逐月北部空品區PM2.5之土地利用迴歸模式;而在變數選取部分,納入前人研究鮮少考量的常態化差異植生指標(Normalized Difference Vegetation Index, NDVI)衛星影像來代表環境植生狀況,以及中式餐飲、寺廟等亞洲特有汙染源進行分析。結果顯示,中式餐飲、寺廟等亞洲特有汙染源都有包含在最後模式當中,所建立的月以及年模式之R2為0.75、0.85,經過多種模式驗證方法亦確認,本研究所建模式穩定且可信。最後利用建立之模式推估北部空品區污染濃度之時空分布發現,都會地區常年均為濃度較高處,隨著年份增加細懸浮微粒濃度有略微下降之趨勢。

Abstract

Fine Particulate Matter (PM2.5) is one of the pollutants which affects human health and has been attracting attention in recent years. Due to the uneven distribution and limited number of monitoring sites, observations from the monitoring stations are not capable of depicting the variability of PM2.5 over intra-urban areas in Taiwan. Land Use Regression (LUR) is one of the solution to deal with this challenge and has been widely applied in western cities recently. However, there are limited cases related to LUR in Taiwan. In this work, 6-year observations of 24 air quality monitoring stations located in the Northern Air Quality Zone of Taiwan operated by Environmental Protection Agency were collected. Compared with previous studies, several culture-specific emission sources such as temples, and Chinese restaurants, and a long-term satellite-based vegetation index were further considered to develop the LUR model at monthly and yearly resolutions for estimating the spatial-temporal variability of PM2.5. The R2 of the resultant models are 0.75 and 0.85 for monthly and yearly resolutions, respectively. Moreover, temples, and Chinese restaurants were both selected as important predictors in the developed models. The results of external data verification confirmed the robustness of the model performance. Finally, spatial-temporal variability of fine particle estimated using the developed models show a slightly decreasing during the study period over high polluted areas clustered in the urban cores of Taipei and Taoyuan cities.

關鍵字

細懸浮微粒、地理資訊系統、土地利用迴歸模式、亞洲特有污染源

Keywords

Fine Particulate Matter, Geographic Information System, Land Use Regression, Culture-specific Emission Source

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10218661-201809-201809210003-201809210003-191-204

備註說明

N / A

Pages:

205-221

論文名稱

利用多軸無人機影像萃取橋梁劣化區三維空間資訊

Title

Three-dimensional Information Extraction of Bridge Deteriorating Area through Multi-rotary UAV Imagery

作者

蕭凱文、饒見有、王瑞麟

Author

Kai-Wen Hsiao, Jiann-Yeou Rau, Jui-Lin Wang

中文摘要

橋梁為民生重要的交通基礎建設,橋梁表面的裂縫與剝落是橋梁安全的重要指標。傳統橋樑檢測方法主要是目視檢測,某些過程會相當危險、耗時且判斷較主觀。本研究中,利用物件導向影像分析對無人機影像進行自動化裂縫檢測,大部分的案例生產者精度(Producer Accuracy)與使用者精度(User Accuracy)分別達到90%及80%以上。偵測出裂縫位於相片上的位置後,將原始相片轉成核影像,再透過影像匹配得到裂縫的共軛點,即可透過前方交會得到裂縫的三維空間資訊。剝落區部份,可以人工於影像上圈選剝落區粗略位置,再利用立體對影像密集匹配產生三維點雲,並將其與擬合的平面相減得到所有點雲與平面之高度差,轉換及製作成數值表面模型(Digital Surface Model),藉由高度差偵測剝落區位置,再計算出剝落區的體積。未來研究可繼續透過前後兩期橋梁裂縫三維空間資訊,進行變異偵測與分析,以達橋梁檢測的目的。

Abstract

Bridge is an important infrastructure construction for human living. Its surface’s crack and concrete delamination are important indicators that can reflect its safety status. In conventional, the bridge inspection was mainly conduct visually. Some of the process are dangerous and time-consuming to the inspector. Meanwhile, the judgement is subjective. In this research, we utilize object-based image analysis for automatic crack detection from UAV acquired images. Most case studies present more than 90% producer accuracy and more than 80% user accuracy. Later, based on the detected crack position on the image, we convert the original image into epipor one. Then, utilize image matching to detect conjugate point and perform space forward intersection to obtain the three-dimensional information of crack. For the concrete delamination, the approximate location of concrete delamination is manual selected. Then, we conduct dense image matching to obtain 3D point cloud and convert to a digital surface model (DSM) by subtract a fitted plane. By means of the elevation difference, we can detect the delamination area and calculate its volume. In the future works, the change detection and analysis of crack’s three-dimensional information between two different times can assist the safety inspection of bridges.

關鍵字

裂縫偵測、物件導向分析(OBIA)、無人機影像

Keywords

Crack detection, OBIA, UAV Imagery

附件檔名

華芸線上圖書館

http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=10218661-201809-201809210003-201809210003-205-221

備註說明

N / A

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