院报 ›› 2022, Vol. 39 ›› Issue (6): 138-144.DOI: 10.11988/ckyyb.20210469

• 信息技术应用 • 上一篇    下一篇

岩溶山区滑坡监测预警云平台设计与实现

陈磊, 李斌, 彭程, 毕晓伟, 杨成生   

  1. 长安大学 地质工程与测绘学院,西安 710054
  • 收稿日期:2021-05-14 修回日期:2021-07-29 出版日期:2022-06-01 发布日期:2022-06-30
  • 通讯作者: 李 斌(1962-),男,湖南邵阳人,副教授,博士,研究方向为GIS应用开发、空间数据库设计、三维建模等。E-mail:binliok@chd.edu.cn
  • 作者简介:陈 磊(1996-),男,安徽安庆人,硕士研究生,主要研究方向为地质灾害监测与WebGIS开发。E-mail: 572773121@qq.com
  • 基金资助:
    国家重点研发计划项目(211226190080)

Design and Implementation of Cloud Platform for Landslide Monitoring and Early Warning in Karst Mountainous Area

CHEN Lei, LI Bin, PENG Cheng, BI Xiao-wei, YANG Cheng-sheng   

  1. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
  • Received:2021-05-14 Revised:2021-07-29 Online:2022-06-01 Published:2022-06-30

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摘要： 针对西南岩溶山区滑坡监测数据量大、类型多、来源杂、集成与分析难等问题,基于Hadoop进行数据的存储与计算,并应用WebGIS等关键核心技术,设计并初步实现了适用于岩溶山区滑坡监测预警的云平台原型系统。首先,设计了多元监测数据集成管理的普适性云平台系统架构;其次,依托校园大数据平台、采用网络开发技术,搭建了应用型云平台;最后,基于原型平台实现并验证了岩溶山区滑坡监测预警云平台的基本功能模块。平台原型及其试验结果表明:岩溶滑坡监测预警云平台的构建设想与技术路线合理、可行,是探索岩溶山区滑坡信息化并进行岩溶滑坡地质灾害监测预警的有效手段和平台支撑。

关键词: 滑坡监测, 滑坡预警, Hadoop, 云平台, 岩溶山区

Abstract: The landslide monitoring data in the karst mountainous area in southwest China is featured with large amount, various type, and complex sources, hence is difficult to be integrated and analyzed. A cloud platform prototype system for landslide monitoring and early warning for karst mountainous area is designed and implemented using WebGIS based on Hadoop for data storage and calculation. First, the universal cloud platform architecture for the integrated management of multiple monitoring data is designed; in subsequence, an application-oriented cloud platform is built based on campus big data platform and network development technology; finally, the basic function modules for landslide monitoring and early warning are realized and verified based on the prototype platform. The prototype platform and its test results manifest that the construction idea and technical route of the cloud platform for karst landslide monitoring and early warning are reasonable and feasible, offering an effective approach and platform support for exploring landslide informatization and monitoring and early warning of karst landslide geological disasters.

Key words: landslide monitoring, landslide early-warning, Hadoop, cloud platform, karst mountainous area

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