Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/15945
標題: 坡地監測預警系統之決策支援架構-以梨山地層滑動區為例
Decision Support Scheme for Prewarning System of Slope Monitoring - A Case Study in Lishan Lanslide Area
作者: 陳毅輝
Chen, I-Hui
關鍵字: Slope monitoring,Decision support system,Fuzzy theory,Web 3D GIS,Service Oriented Architecture
坡地監測、決策支援系統、模糊理論、Web 3D GIS、服務導向架構
出版社: 土木工程學系所
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摘要: 本研究架構坡地監測預警系統具有三個主要功能,第一為建立更準確且即時的監測儀器設備,提供有效率且符合現地的監測方法;第二是設計有預警能力之決策支援模型,提供使用者或決策者更明確、即時的研判結果;第三為建構服務導向的整合系統,快速展示即時監測資料與模式分析結果,結合地理資訊系統,提供現地地形、地物與影像變化等空間資訊,透過網際網路服務的整合,達到具有防災流程管理的決策支援系統。 本研究結合決策分析模型建置網路式地理資訊的坡地監測決策支援架構,以梨山地層滑動區為建構整合系統之研究區域,本系統架構之理論與成果可分為三大項目說明: 一、本研究建立地層滑動區監測儀器之管理基準值,包括應用(Time Domain Reflectometry(TDR)監測地層變位以及Global Positioning System(GPS)監測地表位移,加上雨量計與地下水位計構成坡地監測系統之基礎,成為重要決策依據之監測儀器,為整合全區之管理基準研判,運用模糊理論考慮不確定性,建立各監測站的模糊集分佈,並以模糊層級分析法來建立管理基準值的評估模式,訂定各分區與自動監測站之間的權重,本研究共有雨量、地下水位、TDR、GPS四個監測儀器之模糊模型架構,分別包含安全、注意、警戒、極度危險四個歸屬函數,經由訂定模糊規則,然後解模糊求得全區監測管理基準值之權重分數,得到地滑危險程度之研判決策。 二、運用地理資訊系統之空間決策能力與資料套疊整合能力,建立完整之水文地質資料庫,綜合探討各分區的穩定狀態,並運用Web 3D GIS軟體建構水文地質3D資料展示、航空照片正攝影像和DTM的前後期比對,整合成為地理資料倉儲系統,並與空間資料庫引擎相互連結,作為網路查詢與展示之基本圖資。 三、以服務導向架構(SOA)整合坡地監測預警決策系統,服務導向架構是以Web Services為考量,結合Web 3D GIS軟體與Open source軟體,提供包括監測預警服務、監測數據服務、影像資訊服務、地理資訊服務與防災通報服務等流程管理,同時套用模糊理論決策模式計算全區之危險程度,以地理資訊結合網路伺服器控管功能,依啟動服務之順序提供使用者或決策者即時監測與預警燈號之資訊,架構完整之坡地監測網路服務決策支援系統。 研判梨山地層滑動區整體區域之危險程度是以模糊層級分析法之三層式的權重疊加計算,最底層為各監測站管理基準值的模糊集,包括地下水位之基準值是建立在轉換為邊坡穩定之安全係數,小於1.10在注意階段,小於1.05在警戒階段,小於1.0在極度危險階段;累積1小時雨量大於20mm為注意、累積24小時雨量大於100mm為注意、大於150mm為警戒、累積48小時雨量大於200mm為警戒;TDR之剪力變位大於10mm為注意,拉伸變位大於40mm為注意、大於100mm為警戒;GPS之累加2小時變位量大於10mm為注意、大於20mm為警戒,Tr值小於5小時為極度危險狀態。模糊層級分析法之第一層與第二層分別訂定梨山地滑區之分區與各監測站的權重分佈,地滑分區之權重分析結果為西區0.24、中區0.5、東南區0.10、東北區0.16,依監測站之權重評比後,B5測站最重要為0.41,其次為A1、C2、B4、C1、B9、B11、B13測站,分別為0.24、0.10、0.09、0.06、0.05、0.04、0.01。將梨山歷年颱風之雨量、地下水位、TDR、GPS的監測紀錄經由模糊理論架構計算出權數總評分,並分界危險等級之權重分析結果,全區之總評分大於72為注意階段、大於95為警戒階段、大於113為極度危險階段。 梨山地滑區監測預警決策支援架構分析全區之危險程度,經由歷年颱風事件之檢驗,研判結果符合現地情況,並對梨山地滑區緊急避難之決策標準訂定流程,納入本研究之服務導向架構的流程管理系統中,可以了解梨山在颱風暴雨或地震情況下梨山地滑全區與各監測站之狀態,以網頁分頁功能,查詢梨山地滑區之危險程度時,啟動監測預警服務,依據決策分析流程啟動監測數據服務、影像資訊服務、地理資訊服務與防災通報服務,使用者針對決策流程可以分為以下四個階段,第一由雨量觀察,若雨量達注意的基準值時,進行第二階段之地下水位觀察,若有監測站地下水位到達警戒時,由管理者或決策者隨時注意現場狀況,並進入第三階段地表位移量的觀察,觀察累積位移量是否持續2小時以上或Tr值小於5小時,然後進入第四階段,不論是權重總評分或單一監測站進入極度危險燈號,系統自動啟動緊急避難路線圖與防災通報服務,系統持續監控所有監測數據,並依據預警系統之決策支援,達到第一時間的防災與通報。
This study researches the three major functions of the monitoring and prewarning system in landslide areas. The first function of this study is to establish more accurate and real-time monitoring devices in order to provide an effective monitoring method suitable to the conditions of the site. The second function is to design a decision support model with prewarning ability in order to provide users and decision-makers with real-time analytical results. The third function is to establish an integrated service orientation system that can quickly indicate monitoring data and model analytical results in real-time. It can provide spatial information relative to the terrain, and image change of the site through the geographical information system in order to establish a decision support system and a disaster prevention process based on Internet service integration. This study combines the analytical model to build a landside monitoring decision support system of the web geographical information. The lanslide area of Lishan is a case study for the research. The theory and achievements of this system structure can be described in three parts: 1. This study establishes the management criterion value for the monitoring device of a stratum slipping area. This includes utilizing Time Domain Reflectometry (TDR) to monitor the stratum deflection and Global Positioning System (GPS) to monitor ground displacement. The monitored rain and groundwater level are the basis for the landslide monitoring system, and are vital monitoring devices for decision making. In order to integrate the management criterion analysis in the whole area, this study uses fuzzy theory to consider uncertainty and to establish the fuzzy set distribution for its various monitoring stations. It also utilizes the Fuzzy Analytic Hierarchical Process to establish the evaluation model for the management criterion value, which is crucial in designing the percentage of various zones and automatic monitoring stations. This study has four fuzzy model structures used in monitoring devices: rainfall, groundwater level, TDR, and GPS. In turn, these structures have four membership functions that are used to indicate safety, attention, warning, and severe danger. The analytical decision of the degree of landslide danger can be obtained through the fuzzy rules by determining the percentage of management criterion values. 2. This study utilizes the spatial analytic ability of geographical information systems and data telescopic integration to establish a complete hydro-geological database for the comprehensive analysis of stable state in the whole area. Web 3D GIS software is used to construct the hydro-geological three-dimensional (3D) information display. Aerial photography and DTM comparison is used to integrate the information into a geographical database system that links with the engine of the spatial database used as the basic image data for web searches and display. 3. This study integrates the landslide monitoring and pre-warning system with SOA. SOA takes Web Services into consideration and combines with Web 3D GIS software and Open Source software to provide process management that covers monitoring and prewarning services, monitoring data services, image information services, geographical information services, and disaster prevention services. It also adopts the fuzzy theory model to calculate the degree of danger for the whole region, combining geographical information with network information control function to provide real-time monitoring and prewarning information to users and decision-makers in order to build a complete service and decision support system for the landslide monitoring network. The analysis of the degree of danger for the stratum slipping zones of the whole region of Lishan is based on the supposed three-layer percentage calculation of fuzzy level analysis. The bottom layer is the fuzzy set of the criteria for various monitoring stations, including groundwater criterion based on the transference of landslide stability safety coefficient. This factor of coefficient is divide into 1.10, 1.05 and 1.0 with attention, warning and danger criteria, respectively. Furthermore, the attention value of the accumulated rainfall in per hour is 20 mm and when the accumulated rainfall in 24 hours, the attention value is 100 mm and the warning value is 150 mm and when the accumulated rainfall in 48 hours, the warning value is 200 mm; in the state of attention when the TDR shearing deformation is larger than 10 mm and the extension deformation is larger than 40 mm, and in the state of warning is larger than 100 mm; in the state of attention when the GPS accumulation in 2 hours is larger than 10 mm, and in the state of warning when GPS accumulation is larger than 20 mm; and in the state of danger when the Tr value is smaller than 5 hours. The first and second layers of fuzzy layer processes determine the boundaries of landslide areas in Lishan and the percentage distribution of various monitoring stations, respectively. Having evaluated the percentage of the monitoring station, Station B5 appears to have been the most important, with a result of 0.41. In order, the other stations are A1, C2, B4, C1, B9, B11, and B13 stations, with 0.24, 0.10, 0.09, 0.06, 0.05, 0.04, and 0.01, respectively. Calculating the total score of monitoring record of the typhoon rainfall, groundwater level, TDR, and GPS in Lishan through the fuzzy theory can determine the analytical results of degrees of risk. In this whole region, safety is in the state of attention when the total score is larger than 72; in a state of alert when total score is larger than 95; and in a state of severe danger when total score is larger than 113. The results are then used to design procedures for the emergency decision standards in the landslide area of Lishan. Using the online function, these decision standards likewise provide real-time and decision information to users and, through the sequence of service activation, initiate the monitoring prewarning services according to the decision analytical results. These processes involve monitoring data service, image information service, geographical information service, and disaster prevention service. The monitoring data service provides data of various monitoring stations and danger indicators of various degrees. These decision processes can be classified into four stages. The first stage is the observation of the rainfall; when the rainfall has reached the criterion of attention value, the second stage is the observation of the ground water. When the groundwater has reached the state of warning, the manager or decision maker should pay attention to the conditions on the site and proceed to the third stage. The third stage observes if the accumulated ground displacement has continued for two hours or above, or if the Tr value is smaller than 5 hours. If so, the manager or decision maker should proceed to the fourth stage. The system will automatically activate the emergency evacuation routes chart and disaster announcement services. The system provides real-time monitoring data, and prewarning decision support in order to announce and potentially prevent the disaster at the earliest time.
URI: http://hdl.handle.net/11455/15945
其他識別: U0005-1002201010264500
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1002201010264500
Appears in Collections:土木工程學系所

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