隨著越來越極端的氣候下,都市洪水事件發生的頻率與嚴重性 已在全球性的範圍下愈加嚴重,然而綜觀目前研究而言,對於都市 內的小區域所進行即時減災決策所需要的實境影像資訊較為不足。 本研究提出以河川與水資源監視影像為基礎的洪水影像自動化監視 與水位漲落分析,加值傳統的被動式水情監視攝影機使其具有智慧 化視覺感測與分析能力。
結合本研究所提出之視覺感測方法,傳統的水情監視鏡頭可具 有感測與分析現地洪水事件的能力,解決現有水情監測仍需仰賴人 力進行全天畫面監看的現況。再者,視覺感測網路與傳統感測網路 相比,傳統感測網路多數只能提供感測器所量測到之一維物理參 數,視覺感測網路則可以提供監測現場的動態影像資訊,補足水利 防災單位在進行減災行動的決策時缺乏的實地視覺資訊。
本文以視覺感測方法,提供自動化分析遠端水情監視之畫面, 並測定洪水事件之形成,並使用近期洪水事件進行實驗驗證,證實 能夠進行電腦自主式的畫面監看與測定洪水事件發生工作,藉由提 供洪水事件之預警偵測與水位變動數據,將能使水利防災管理單位 能快速正確地理解當地水情狀況,進而明確地發起相應的減災措 施,未來更可應用在智慧化都市之洪水監控。

With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value- added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring.
Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods.
This paper focuses on the determination of flood formation based on image- processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.

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