Flood Prediction and Disaster Risk Analysis using GIS based Wireless Sensor Networks, A Review
Flood Prediction and Disaster Risk Analysis using GIS based Wireless Sensor Networks, A Review
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发表时间：
2013
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通讯作者：
Naveed Ahmad;M. Hussain;Naveed Riaz;Fazli Subhani;S. Haider;Khurram. S. Alamgir;Fahad Shinwari
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作者：
Naveed Ahmad;M. Hussain;Naveed Riaz;Fazli Subhani;S. Haider;Khurram. S. Alamgir;Fahad Shinwari
本文对利用地理信息系统(GIS)进行洪水分析和预报进行了全面的研究。来自世界各地的不同科学家和研究人员对专门针对人口的洪水风险评估进行了详细分析，并利用遥感和卫星图像在灾害危急情况发生之前或之后采取预防措施。在本研究中，我们利用无线传感器网络架构对基于地理信息系统的洪水预报技术进行了详细的分析。本文还提出了洪灾风险分析与预测模型，为灾区洪灾损失的评估提供了理论依据。事实证明，地理信息系统领域对我们进行地理调查和识别造成巨大潜在经济损失的海啸非常有帮助。在本次研究中，我们还利用Arc地理信息系统仿真工具进行了灾前、灾后洪水风险识别分析。我们的研究重点是各种专门为洪水灾害管理而设计的地理信息系统，并分析必要的输入参数，包括土壤水分、气压、风向、湿度和降雨量。这些参数将非常有助于我们模拟现实生活中的情景，特别是在发生洪水灾害的情况下。我们提出的模型也非常有助于我们预测即将到来的灾难，以及应急和救援当局在这种危急情况发生之前采取必要行动拯救数千人的生命。
This paper presents a comprehensive study of the flood analysis and prediction using Geographical Information system (GIS). Different scientists and researchers from all over the world had performed detailed analysis of flood risk assessment specifically for human population and to take precautionary measurements before or after the critical condition of disaster occurs using Remote sensing and satellite images. In this research study, we had performed detailed analysis of Flood Prediction techniques based on GIS using Ad hoc wireless Sensor Network Architecture. We had also proposed a Model for Flood Risk Analysis and prediction, which would be very helpful for us in calculating the impact of Flood damage in disaster hit regions. The GIS domain proves to be very helpful for us in geographical survey and to identify the tsunamis causing vast potential and economical damage. In this research study, we had also used Arc GIS simulation tool to identify pre and post disaster flood risk analysis. Our Research study focuses on various geographical information Systems specifically designed for Flood Disaster management and to analyze necessary input parameters including soil moisture, air pressure, direction of wind, humidity and rain fall. These parameters would be very helpful for us in modelling real life scenarios specifically in case of flood disasters. Our proposed model is also very helpful for us in predicting the upcoming disasters and to take necessary actions by emergency and rescue authorities to save the life of thousands of people before this critical condition occurs.