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Smart Landslide Information System – HKJCDPRI Research Grant 2016 (Half Yearly Progress Update)

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Smart Landslide Information System – HKJCDPRI Research Grant 2016 (Half Yearly Progress Update)

A prototype mobile App for the Landslide Information System (LIS)

The HKJCDPRI Research Grant 2016 was awarded to The Hong Kong University of Science and Technology (HKUST). The research aims to develop a new smart Landslide Information System (LIS) that can improve the planning of access and evacuation routes for emergency responders during intense rainstorms. Furthermore, the LIS aims to provide easily accessible real-time landslide information to the public and to enhance landslide incident reporting in Hong Kong via smart technology.

 

The HKUST Research Team has characterised relationships between landslide failure mechanisms and rainfall. Landslide hazard mapping was adopted to verify correlations between rainfall and landslide occurrence. The hazard map will be incorporated into the LIS mobile App which is currently under development (see Figs. 1 and 2 below for snapshots of the mobile App). It is envisioned that the final product will display and disseminate real-time landslide information, provide emergency routing information to emergency responders and identify high-risk landslide areas with the application of the landslide susceptibility model.

 

Later in October, the HKUST Research Team will attend an international geotechnical conference in Canada (GEO Ottawa 2017) to share their research findings on the LIS mobile App.

 

This research demonstrates how innovative smart technology can be used as an early warning system and play a major role reducing risk associated with landslides. More findings and progress on this research will be shared in the coming half year.

 

For more information, please contact the HKJCDPRI at [email protected]

 

HKUST Research Team (left to right)
Back: Mr. George Goodwin (PhD Student); Prof Clarence Choi; Mr. Haiming Liu (PhD Student)
Front: Mr. Luis Hengdou Liu (PhD Student); Mr. Desmond Ka Ho Cheung (PhD Student); Mr. Chao Wang (PhD Student)

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