Automating geological hazard identification, magnitude and timing in New Zealand through 3D landscape reconstruction of high resolution satellite imagery.

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Profile Display Name:

Niall Lehane

E-mail Address:

niall.lehane.15@ucl.ac.uk

Start Year

2015 (Cohort 2)

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PhD Project
PhD Title

Automating geological hazard identification, magnitude and timing in New Zealand through 3D landscape reconstruction of high resolution satellite imagery.

Research Theme

Natural and Biological Hazards

Primary Supervisor
Primary Institution

QMUL

Secondary Supervisor
Secondary Institution

QMUL

Abstract

Owing to its location at the boundary of the Australian and Pacific plates, New Zealand is geologically very active with natural hazard events continually driving landscape evolution. While continual monitoring of these hazards is undertaken, there is no approach to quantifying the volumetric geomorphic change observed in the landscape. Traditional methods, such as airborne LiDAR, terrestrial laser scanning and structure from motion, used to generate high resolution, sub 1m DEMs for the purpose of geomorphic change detection, have been limited by both the spatial extent and low frequency of the surveys. High resolution, Worldview 3 satellite imagery will be used as the basis to optimize and automate a workflow from processing imagery through to delivering a final data product – quantifying the magnitude and timing of natural hazard events in New Zealand. Panchromatic stereo imagery at 31cm GSD will be used to create multi-temporal DEMs at an unprecedented scale and frequency. The accuracy of the derived DEMs will be assessed across a range of criteria using control data collected during this research as well as surveys undertaken after significant hazard events including the February 2011 Christchurch earthquake.

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