一種有效率之邊坡滑動災害預測模式與感知監控系統之研究與設計

An Efficient Forecasting Model and Awareness Monitoring System for Slope Failure：Research and Design

吳哲一(Che-I Wu)

指導教授 ： 龔旭陽 ； 蔡光榮

國立屏東科技大學/工學院/坡地防災及水資源工程研究所/博士(2009年)

https://doi.org/10.6346/NPUST.2009.00022

摘要

台灣地區於颱風季節時期，經常會發生邊坡滑動災害與豪雨產生導致嚴重之土砂災害，那些災害產生嚴重的自然破壞及人民的財產與生命損失。本論文選擇台灣經常會出現土砂災害中之邊坡滑動災害為主要討論的研究議題，期望對民眾及防救災單位之預防與警示災害有所幫助。本研究提出先前邊坡滑動災害研究及分析做為參考依據，再整合新型的資訊科技提出預測支援模式與感知監控系統兩大系統協助解決災害發生前與災害當時之問題，因此在眾多的環境致災因子中評估、分析與篩選出七個(地形坡度、土壤種類、24小時內連續降雨量、植生覆蓋率、土壤滑動位移、土壤含水量與溫度)造成試驗區內邊坡滑動之致災因子，再依據這些因子蒐集變化值匯入設計之預測支援模式評估與分析災害等級及發生可能性。為了讓預測支援模式能夠「有效率」發揮預警成效，更能「即時性」做到災害預防及警示作用，故於研究中設計相輔的監控與傳輸工具，利用現地即時監控與傳輸的功能，完成有效率的預警與通報的效果。為了整合預測、預警、監控與即時通報之功能與效果，所以在這篇論文主要是提出及設計一套有效率之邊坡滑動災害預測模式與感知監控系統(An Efficient Forecasting Model and Awareness Monitoring System for Slope Failure, FAMS)警示民眾邊坡災害之發生。為了發揮災害預測、監控與及時通報的功能，FAM系統規劃與設計災害預測支援模式，預測支援模式包括了分析網路程序法(ANP)、倒傳遞類神經網路分析法(BPN)及多變量不安定指數分析法(MSA)之三種風險評估分析法比較出最適合的模式，這些分析法均採用相同因子及蒐集數據值評估與比較出何種模式在此區域最為適合，並與現地調查及監控狀況做比對預測模式之準確性。FAM系統採用三層架構，包含跨異質網路之使用者(Heterogeneous Network Users, HNUs)、多媒體應用伺服器端(Multimedia Application Server, MAS)及災情資料管理與預測支援系統端(Disaster Information Management and Prediction Supporting System, DIMPS2)，這系統架構間資料流通可以使用有線網路、無線網路及行動式通訊做溝通。
FAM系統也為一套利用無線感測網路蒐集環境變化因子，整合後分析邊坡災害因素、規劃預測模式及建置監控與通報之多媒體系統。FAM系統亦採用多媒體傳輸技術及品質服務保證機制得到現地災害狀況，將災害位置區及現地災害即時圖片及影像資料，讓使用者透過跨異質網路配合手持設備傳送或接受多媒體災害資訊及即時通報資料。FAM系統於管理功能面亦設計預測支援模式及災害資料管理介面，系統中整合式服務系統包含六個智慧型代理人處理接收環境資料，災情資料管理與預測支援模式系統(DIMPS2)包括災害資料管理系統、預測支援模式及即時通報系統，其主要功能是接收到環境災害因子資料值，推測邊坡滑動災害發生的機率。最後FAM系統亦結合網際網路地理資訊系統(Web-GIS)了解該區域地理環境資訊，快速顯示及連結災區多媒體資訊，讓整個系統整合性評估結果比傳統人工觀察預測得到更準確的災害預測效果。FAM系統有了預測支援模式與感知監控系統之技術整合服務，再輔以建置之災情即時的通報系統，本論文將可達到防救災資訊功能效果之全面性。

關鍵字

邊坡滑動災害 ； 致災因子 ； 預測支援模式 ； 感知監控系統 ； 無線感測網路 ； 即時通報系統

並列摘要

Taiwan generally has large-scale slope failure and torrential rainfall to cause sediment disaster during the typhoon season. Those disasters often result in the serious nature destruction and create the heavy losses of people's lives and properties. The kind of sediment disaster is numerous, and this mainly discussing topic of thesis choose often appear slope failure for sediment disaster to study in Taiwan. It expects to make discussion with the topic this thesis that can help people and prevention and rescuing units to prevent and alarm creating disaster. It was usually the gold period to prevent and rescue disaster with taking place before and creating at that time. It had taken place relevant disasters that all the materials were afterwards to collect and study, and judge causing disaster factors in the past, the time has already had no enough to save a critical situation. Therefore, this research study and analyze the past slope failure as basis of consulting, and combining new information technology to propose two major system themes, which are prediction supporting model and awareness monitoring system, to assist and solve problems of disaster. At first the mainly causing disaster factors of slope failure must be discussed and selected, so survey and examine the trial zone environment in thesis research. Numerous environment causing disaster factors will be chosen, assessed, analyzed, then select seven causing factors which include gradient, soil characteristics, 24-hour accumulated rainfall, vegetation index, soil displacement, soil hydrous and temperature, to cause slope failure. Then according to values of selecting disaster factors into designed prediction supporting model, the model system will assess and analyze the taking place disaster grade and possibility. In order to reach and develop early alarming effect, the prediction supporting model can make sure disaster preventing and alarming functions really, and the study also plans complemented monitoring and transmitting tools. The system will utilize these monitoring and transmitting functions to complete effect of prewarning and informing immediately. In order to combine functions and effects predicting, prewarning, monitoring, and real-time informing, so this paper proposes and designs “An Efficient Forecasting Model and Awareness Monitoring System for Slope Failure” (FAMS), which successfully alerts people the occurrence of slope failure. This thesis also mainly proposes and designs a real-time disaster information system, which is important for people to develop FAMS to assist the prevention disaster works, to obtain, inform, and display the disaster situation. In order to achieve forecasting and monitoring disaster functions, FAM is also implemented using the proposed disaster prediction supporting model, which prediction efficiency model includes Analytic Network Process (ANP), Back-Propagation Neural Network Analysis (BPN), and Multivariate Statistical Analysis (MSA), to compare the adaptable model. The FAMS adopts three tiers that are composed of Heterogeneous Network Users (HNUs), Multimedia Application Server (MAS), and Disaster Information Management and Prediction Supporting System server (DIMPS2) based on the wireless/mobile and Internet communications. The FAMS integrates technology and management parts to analyze the factors of slope failure, scheme forecasting model, and establish monitoring and informing multimedia system.
As wireless sensor networks (WSN) and mobile communication technologies advance rapidly, state-of-the-art technologies are adopted to build a model to reliably predict and monitor disasters, as well as accumulate environmental variation-related information. The FAM also combines multimedia transmission technology and quality of service (QoS) mechanism to reveal the real disaster situations, for example, the accurate position and the real-time image/video of accident events. Heterogeneous Network Users (HNUs) use the handheld devices to transmit and receive multimedia information about slope failure via the wireless/mobile and internet communications. Another Slope Monitoring and Sensing (SMS) system includes the Slope Monitoring Engine (SME), network camera, and sensors to sense and collect environment information. I also scheme and design some forecasting supporting model and disaster information management interface. Integrated Service Server (ISS) is composed of six intelligent agents to process the received environment information. Disaster Information Management and Prediction Supporting System server (DIMPS2) which includes Disaster Information Management System (DIMS) and Forecasting and Informing System (FIS) are responsible to determine the probability of slope failure occurrence based on the information from sensors and agents. The FAM adopts Web-GIS to visualize the environmental information in order that evaluation results of the system indicate that the proposed forecasting model achieves more accurate disaster determination than the conventional method. FAMS has integration services of prediction supporting model, awareness monitoring system, and establishing real-time disaster informing system, this thesis can reach the comprehension effects of prevention and rescuing information function.

並列關鍵字

Slope Failure ； Causing Disaster Factors ； Prevention Supporting Model ； Awareness Monitoring System ； Wireless Sensor Network ； Real-Time Informing System

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