12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > Determining the rheology of active lava flows f...
View graph of relations

Download

« Back

Determining the rheology of active lava flows from photogrammetric image sequence processing

Research output: Contribution to conferencePoster

Published

Publication date2010
Original languageEnglish

Abstract

We describe a photogrammetric approach used to determine the rheological properties of active lava flows based on stereo image sequences. Bulk rheological properties can be estimated from measurements of flow slope, velocity and dimensions and so, at flow-fronts, they can be calculated from
sequential digital elevation models (DEMs) acquired as the flow advances over new ground. For useful flow parameters to be extracted, DEMs may need to be obtained at approximately minute intervals, over durations of up to multiple hours. To deliver such data, we use oblique stereo pair sequences captured by
digital SLR cameras and a semi-automated DEM-generation pipeline. Although similar data could be acquired with a terrestrial laser scanner, with deployments in remote and hazardous regions the photogrammetric approach offers significant logistical advantages in terms of reduced equipment cost, bulk,
weight and power requirements.
We describe the application of the technique to an active lava flow on Mount Etna, Sicily, in 2006. Image sequences were acquired from two tripod-mounted cameras over a period of ~3 hours, as the flow-front advanced ~15 m. Photogrammetric control was provided by 11 targets placed in the scene, with their coordinates determined by dGPS. The cameras were synchronised by a shutter release cable and triggered by an external timer (intervalometer). Image pairs were obtained every minute with DEMs extraction carried out on every fourth epoch; 57 DEMs, with a 0.25-m resolution, were generated.
We describe the challenges associated with data collection in this remote environment and the techniques required to automate the photogrammetric analysis and sequence-DEM generation.