Back to Search Start Over

Panzhihua airport landslide (Oct. 3rd 2009) and an emergency monitoring and warning system based on the internet of things.

Authors :
Wang, Hong-hui
Tuo, Xian-guo
Zhang, Gui-yu
Peng, Feng-ling
Source :
Journal of Mountain Science; Oct2013, Vol. 10 Issue 5, p873-884, 12p
Publication Year :
2013

Abstract

Panzhihua city (26°05′-27°21′N, 101°08′-102°15′E), located in a mountainous area, is one of the large cities in Sichuan province, China. A landslide occurred in the filling body of the eastern part of the Panzhihua airport on October 3, 2009 (hereafter called the 10.3 landslide). We conducted field survey on the landslide and adopted emergency monitoring and warning models based on the Internet of Things (IoT) to estimate the losses from the disaster and to prevent a secondary disaster from occurring. The results showed that four major features of the airport site had contributed to the landslide, i.e, high altitude, huge amount of filling rocks, deep backfilling and great difficulty of backfilling. The deformation process of the landslide had six stages and the unstable geological structure of high fillings and an earthquake were the main causes of the landslide. We adopted relative displacement sensing technology and Global System for Mobile Communications (GSM) technology to achieve remote, real-time and unattended monitoring of ground cracks in the landslide. The monitoring system, including five extensometers with measuring ranges of 200, 450 and 700 mm, was continuously working for 17 months and released 7 warning signals with an average warning time of about 26 hours. At 10 am on 6 December 2009, the system issued a warning and on-site workers were evacuated and equipment protected immediately. At 2:20 pm on 7 December, a medium-scale collapse occurred at the No. 5 monitoring site, which justified the alarm and proved the reliability and efficiency of the monitoring system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16726316
Volume :
10
Issue :
5
Database :
Complementary Index
Journal :
Journal of Mountain Science
Publication Type :
Academic Journal
Accession number :
90470790
Full Text :
https://doi.org/10.1007/s11629-013-2368-3