Spatiotemporal characterisation of Fire Severity Over a 23 Year Period in South-East Queensland using data collected with Landsat sensors: A preliminary study

Brett M Parker; Tom Lewis; Sanjeev K Srivastava

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Spatiotemporal characterisation of Fire Severity Over a 23 Year Period in South-East Queensland using data collected with Landsat sensors: A preliminary study

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Spatiotemporal characterisation of Fire Severity Over a 23 Year Period in South-East Queensland using data collected with Landsat sensors: A preliminary study

Brett M Parker, Tom Lewis and Sanjeev K Srivastava

Proceedings of the QCON14 Conference, pp.1-19

QCON14 Conference: Repositioning for a Sustainable Future (Cairns, Australia, 07-Oct-2014–10-Oct-2014)

Surveying and Spatial Science Institute (Queensland)

2016

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Abstract

Geomatic Engineering

multi-decadal fire severity patterns

Landsat

GeoCBI

dNBR

heath

woodland

Land management agencies are increasingly using multispectral satellite imagery to monitor post-fire ground conditions to guide effective conservation and asset protection management strategies. Estimates derived from such data can span over multiple decades and can be analysed to identify spatiotemporal burnt area patterns. Interestingly, fire severity is rarely derived from multi-decadal remote sensing datasets. Accordingly, in this study we explored the utility of imagery captured with Landsat sensors (5 TM, 7 ETM+ and 8 OLI) to characterise fire severity of burnt areas over a 23 year period in a national park with a woodland and heath ecosystem. The multi-temporal differenced normalised burn ratio (dNBR) was used to estimate fire severity for individual burnt areas, which were then aggregated to identify spatiotemporal patterns. Accuracy assessment was achieved using ground truth data collected with the Geometrically Structured Composite Burn Index (GeoCBI), which incorporates the fraction of cover (FCOV) of vegetation over the total plot. Our results indicated that Landsat imagery was ideal for significantly estimating fire severity (accuracy = 72 %, kappa = 0.63, P = < 0.001) in sclerophyll woodland and heath ecosystems. Further, we had interesting insight into the patterns of increased fire severity within specific vegetation types and across the study site.

Details

Title: Spatiotemporal characterisation of Fire Severity Over a 23 Year Period in South-East Queensland using data collected with Landsat sensors: A preliminary study
Authors: Brett M Parker (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Tom Lewis (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Sanjeev K Srivastava (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Publication details: Proceedings of the QCON14 Conference, pp.1-19
Conference details: QCON14 Conference: Repositioning for a Sustainable Future (Cairns, Australia, 07-Oct-2014–10-Oct-2014)
Publisher: Surveying and Spatial Science Institute (Queensland)
Date published: 2016
Organisation Unit: School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Forest Research Institute; Sustainability Research Cluster
Language: English
Record Identifier: 99451178902621
Output Type: Conference paper

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