博碩士論文 107322089 完整後設資料紀錄

DC 欄位 語言
DC.contributor土木工程學系zh_TW
DC.creator洪一展zh_TW
DC.creatorYi-Chan Hungen_US
dc.date.accessioned2020-7-14T07:39:07Z
dc.date.available2020-7-14T07:39:07Z
dc.date.issued2020
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=107322089
dc.contributor.department土木工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract深入瞭解地表地形與水體的相關資訊是模擬淹水情境、灌溉分析等其他應用的關鍵。多光譜影像與透水光達為常見的水下建模工具,該兩種屬於光學測深方式,此外亦有聲學測深裝置如單音束、多音束測深儀,利用聲學回波的性質探測水深甚至分類水底地貌。然而,光學測深僅適用於水質潔淨、淺水的實驗場域,聲學測深則是在船載與設備上的調度有相當大的成本。近年來,隨著消費級無人機的成本降低,使其廣泛地運用在地理資訊領域中。無人機的高機動性、懸停精準性提供另一種移動操作平台。 為了探討行動測深系統於淺水水域量測水深與體積的可行性,本研究選擇桃園地區的埤塘群做為研究水域,結合無人機、微型聲納並針對80口埤塘進行外業。每口埤塘需要三至四位工作人員,其耗時約一小時至一小時半。懸掛微型聲納、手機的無人機在各實驗點位停留一分鐘以獲取足夠的深度估計,並操作另一台無人機進行航拍,期間佈設控制點以在後續建模時提供地面定位座標,最後量測埤塘的平均坡度與水門高供內業使用。內業中使用反距離權重法與邊緣坡度、水門高建置埤塘水下模型,並利用航照、控制點建置地上模型,其水深、最大蓄水體積可以由水下模型得出,結合上述模型即可得到整合模型。本研究與桃園水務局資料庫相比較,其面積與體積的相關係數分別是0.99和0.84。最後利用簡易淹水模式模擬桃園市八德區之淹水情況,設計三種情境討論埤塘系統對於淹水事件可貢獻之效益,並說明埤塘系統與外業更新體積之效益。zh_TW
dc.description.abstractA thorough understanding of surface terrain and the information of inland waterbodies is crucial for flood prevention, irrigation management, and other hydrological applications. Nowadays, multispectral satellite images and LiDAR are widely used to establish underwater model with optical methods. Another possibility is to use single/multi-beam echo sounders to survey in acoustic approaches. However, optical methods are only appropriate for shallow and clean water, while acoustic methods would require considerable cost in dispatching vessels and equipment. The reduced cost of commercial unmanned aerial vehicle (UAV) in recent years has facilitated its wide applications in geoinformatics fields. Owing to its high mobility, UAV provides another kind of mobile platform for the surveying equipment. In order to update water depth and water volume of 80 ponds in Taoyuan city, this study deploys a mobile bathymetric mapping module for the fieldwork, where each pond requires 3 to 4 operators for 1 to 1.5 hours. An UAV hanging a cellphone and a micro-sonar is designed to measure water depth over water surface. Another UAV is dispatched for aerial photography to build surface terrain around the ponds with a few control points. Finally, the slope and dyke height around the pond are measured for generating the pond DEM. Pond bottom elevation is modeled by the Inverse Distance Weighting of point measurements, and combined with slope and dyke height. The surface model is constructed using the stereo pairs of aerial images and control points. Finally, an integrated model obtained by combining both models is used to derive water storage. The correlation coefficients of water area and storage between our approach and data from the Department of Water Resources, Taoyuan (TYWR) achieve 0.99 and 0.84, respectively. Next, the Simplified Inundation Model (SPM) is used to simulate the flood extent in Bade District, Taoyuan, assuming the ponds are emptied in advance for stormwater detention purposes. Three scenarios were designed to discuss the efficiency of detention rate. Finally, the benefits of pond system and the importance of volume update are described.en_US
DC.subject移動測繪zh_TW
DC.subject無人機zh_TW
DC.subject聲納zh_TW
DC.subject簡易淹水模式zh_TW
DC.subjectMobile Mappingen_US
DC.subjectUnmanned Aerial Vehicleen_US
DC.subjectSonaren_US
DC.subjectSimplified Inundation Modelen_US
DC.title利用行動測深系統產製淺水區深度模型zh_TW
dc.language.isozh-TWzh-TW
DC.titleUsing Mobile Bathymetry System to Produce Bathymetry Model in Shallow Water Areaen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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