the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Implementation of a Geological Disaster Monitoring and Early Warning System Based on Multi-source Spatial Data: A Case Study of Deqin County, Yunnan Province
Abstract. New technologies, such as three-dimensional laser scanning, interferometric synthetic aperture radar (InSAR), global navigation satellite systems (GNSSs), unmanned aerial vehicles (UAVs), and the Internet of Things, will provide greater volumes of data for surveying and monitoring as well as for the development of early warning systems (EWS). This research proposes solutions for the design and implementation of a geological hazard monitoring and early warning system (GHMEWS) for landslides and debris-flow hazards based on data multi-sourced from the aforementioned technologies. We describe the complex and changeable characteristics of the GHMEWS and analyze the architecture of the system, the composition of the multi-source database, the development mode and service logic, and the methods and key technologies of the system development. To illustrate the implementation process of the GHMEWS, we selected Deqin County as the case study area due to its unique terrain and diverse types of typical landslides and debris flows. First, we discuss the system's functional requirements and the monitoring and forecasting models of the system. Second, we examine the logic relations of the overall disaster process, including pre-disaster, disaster rescue, and post-disaster reconstruction, and develop a support tool for disaster prevention, disaster reduction, and geological disaster management. Third, we describe the methods for multi-source monitoring data integration and the generation and simulation of the mechanism model of geological disasters. Finally, we construct the GHMEWS for application to the dynamic and real-time management, monitoring, and forecasting of the entire hazard process in Deqin County.
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RC1: 'Implementation of a Geological Disaster Monitoring and Early Warning System Based on Multi-source Spatial Data: A Case Study of Deqin County, Yunnan Province', Anonymous Referee #1, 23 Aug 2017
- AC1: 'Response to the Interactive Comments', Junsan Zhao, 02 Jan 2018
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RC2: 'Reviewer comments', Anonymous Referee #2, 12 Oct 2017
- AC2: 'Response to the Interactive Comments', Junsan Zhao, 02 Jan 2018
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RC1: 'Implementation of a Geological Disaster Monitoring and Early Warning System Based on Multi-source Spatial Data: A Case Study of Deqin County, Yunnan Province', Anonymous Referee #1, 23 Aug 2017
- AC1: 'Response to the Interactive Comments', Junsan Zhao, 02 Jan 2018
-
RC2: 'Reviewer comments', Anonymous Referee #2, 12 Oct 2017
- AC2: 'Response to the Interactive Comments', Junsan Zhao, 02 Jan 2018
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4 citations as recorded by crossref.
- Analysis of radar technology identification model for potential geologic hazard based on convolutional neural network and Harris Hawks optimization algorithm F. He et al. 10.1007/s00500-021-06206-1
- Research on the Application of GIS Technology Combined with RBFNN‐GA Algorithm in the Delineation of Geological Hazard Prone Areas T. Lei et al. 10.1155/2021/2677453
- Design of English Teaching Corpus Resource-Sharing System Based on XML Technology L. Bing & N. Jan 10.1155/2022/7962668
- The Selection of Rain Gauges and Rainfall Parameters in Estimating Intensity-Duration Thresholds for Landslide Occurrence: Case Study from Wayanad (India) M. Abraham et al. 10.3390/w12041000