作者：朱武1, 张勤*1, 朱建军2, 黄观文1, 王彦平3, 朱鸿鹄4, 胡伟5, 胡俊2
1.长安大学地质工程与测绘学院,陕西 西安 710054;
2.中南大学地球科学与信息物理学院,湖南 长沙 410083;
3.北方工业大学信息学院,北京 100144;
4.南京大学地球科学与工程学院,江苏 南京 210023;
5.成都理工大学环境与土木工程学院,四川 成都 610059
摘要 特大滑坡灾害具有体量大、隐蔽性强、突发性强、破坏性强的明显特点,一旦发生将带来严重的人民生命财产损失。实施特大滑坡监测预警对防灾减灾至关重要。与不断创新发展的国际先进技术相比,中国在特大滑坡监测预警领域存在监测装备精度低、成本高等问题,难以实现实时动态跟踪和精准监测预警。基于此,为提升我国特大滑坡灾害防灾减灾水平,在“十三五”国家重点研发计划“特大滑坡实时监测预警与技术装备研发”专项的支持下,项目组突破了滑坡动态跟踪、实时监测、精准预警等关键核心技术,研发了低成本、大视场、智能化、高精度的滑坡实时监测装备,构建了多传感集成的滑坡实时监测预警系统,成功预警多起滑坡事件,实现人员零伤亡和财产零损失,显著提升了中国滑坡灾害防灾减灾水平。
关键词 ： 特大滑坡, 动态跟踪, 实时监测, 精准预警
参考文献
| [1] ZHANG J M, ZHU W, CHENG Y Q, et al.Landslide detection in the Linzhi-ya’an section along the Sichuan-Tibet railway based on InSAR and hot spot analysis methods[J]. Remote Sensing, 2021, 13(18): 3566. [2] 张勤, 黄观文, 杨成生. 地质灾害监测预警中的精密空间对地观测技术[J]. 测绘学报, 2017, 46(10): 1300-1307. (ZHANG Qin, HUANG Guan-wen, YANG Cheng-sheng.Precision space observation technique for geological hazard monitoring and early warning[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1300-1307. (in Chinese)) [3] WANG Y P, HONG W, ZHANG Y, et al.Ground-based differential interferometry SAR: a review[J]. IEEE Geoscience and Remote Sensing Magazine, 2020, 8(1): 43-70. [4] 王家琛, 朱鸿鹄, 王静, 等. 基于主动加热光纤法的毛细阻滞入渗模型试验研究[J]. 岩土工程学报, 2021, 43(1): 147-155. (WANG Jia-chen, ZHU Hong-hu, WANG Jing, et al.Laboratory model tests on capillary barrier infiltration using actively heated fiber optic method[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(1): 147-155. (in Chinese)) [5] GUAN L Y, HU J, PAN H B, et al.Fusion of public DEMs based on sparse representation and adaptive regularization variation model[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 169: 125-134. [6] LUO X J, WANG C C, LONG Y, et al. Analysis of the decadal kinematic characteristics of the daguangbao landslide using multiplatform time series InSAR observations after the Wenchuan earthquake[J]. Journal of Geophysical Research: Solid Earth, 2020, 125(12): e2019JB019325. [7] JI P F, LV X L, DOU F J, et al.Fusion of GPS and InSAR data to derive robust 3D deformation maps based on MRF L1-regularization[J]. Remote Sensing Letters, 2020, 11(2): 204-213. [8] ZENG W,XIAO J Q, LIN F Q,ZHU X.Design of Portable Mountain Flood Warning System Based on LoRa[J]. Canadian Journal of Electrical and Computer Engineering, 2012, 2: 141-147. [9] DU Y, HUANG G W, ZHANG Q, et al.A new asynchronous RTK method to mitigate base station observation outages[J]. Sensors, 2019, 19(15): 3376. [10] WANG Y P, SONG Y, LIN Y, et al.Interferometric DEM-assisted high precision imaging method for ArcSAR[J]. Sensors (Basel, Switzerland), 2019, 19(13): 2921. [11] WU W Q, HU J, LIU J H, et al.Derivation of high-quality three-dimensional surface deformation velocities through multi-source point cloud fusion: application to Kīlauea volcano[J]. International Journal of Applied Earth Observation and Geoinformation, 2021, 95: 102270. [12] PEI H F, ZHANG S Q.Molecular dynamics study on the zeta potential and shear plane of montmorillonite in NaCl solutions[J]. Applied Clay Science, 2021, 212: 106212. [13] PEI H F, ZHANG F, ZHANG S Q.Development of a novel Hall element inclinometer for slope displacement monitoring[J]. Measurement, 2021, 181: 109636. [14] ZHANG L, CHENG G, WU J H, et al.Study on slope failure evolution under surcharge loading and toe cutting with BOTDA technology[J]. Optical Fiber Technology, 2021, 66: 102644. |
引用本文:
朱武, 张勤, 朱建军, 黄观文, 王彦平, 朱鸿鹄, 胡伟, 胡俊. 特大滑坡实时监测预警与技术装备研发[J]. 岩土工程学报, 2022, 44(7): 1341-1350. ZHU Wu, ZHANG Qin, ZHU Jian-jun, HUANG Guan-wen, WANG Yan-ping, ZHU Hong-hu, HU Wei, HU Jun. Real-time monitoring and early warning technology for huge landslides. Chinese J. Geot. Eng., 2022, 44(7): 1341-1350.
Real-time monitoring and early warning technology for huge landslides
ZHU Wu1, ZHANG Qin1, ZHU Jian-jun2, HUANG Guan-wen1, WANG Yan-ping3, ZHU Hong-hu4, HU Wei5, HU Jun2
1. College of Geology Engineering and Geomatics, Chang’an University, Xi’an 710054, China;
2. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;
3. School of Information Science and Technology, North China University of Technology, Beijing 100144, China;
4. School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China;
5. College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu 610059, China
Abstract：The huge landslide will bring severe losses of people’s lives and properties due to its characteristics of large volume, strong concealment, strong abruptness and strong destructiveness. The real-time monitoring and early warning of the huge landslide is critical for disaster prevention and mitigation. Comparisons with the international technologies suggest that the current monitoring equipments for landslides are difficult to realize the tracing and real-time monitoring. In order to improve the level of disaster prevention and mitigation, the National Key Research and Development program “Real-time monitoring and early warning technology for huge landslides” was approved during the 13th Five-Year Plan period. The monitoring equipments for landslides with low-cost, large field of view, intelligence, high-precision have been produced through the researches on the dynamic tracking, real-time monitoring and early warning of landslides. A real-time monitoring and early warning system with multi-sensors is constructed. This system has successfully warned several landslide events, which leads to the zero casualties and zero-property losses. The program improves the level of disaster prevention and mitigation of landslides.
Key words： huge landslide dynamic trackng real-time monitoring early warning