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Are High Severity Fires Increasing in Southern Australia?


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Wildfires worldwide are becoming more frequent but are they also becoming more severe? Here we used remotely sensed burn-severity data from wildfires in Victoria, southeastern Australia to address that question. We selected 162 wildfires of more than 1000 ha that occurred over the past 30 years across a wide range of forest types. Spectral indices derived from Landsat pre-and post-fire imagery were used to map fire severity. Our results show a significant increase in the absolute and proportional area burnt by high-severity fire over the last three decades. This study demonstrates that wildfires in the temperate forests of southern Australia are becoming more severe. Such change in fire regimes may have critical consequences for the sustainability and resilience of the studied forests. B. N. Tran, M. A. Tanase, L. T. Bennett and C. Aponte, "Are High Severity Fires Increasing in Southern Australia?," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 4630-4633, doi: 10.1109/IGARSS39084.2020.9324121.
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Bang Nguyen Tran 1,2, Mihai A. Tanase 3,4, Lauren T. Bennett 1, Cristina Aponte 1,4
1 School of Ecosystem and Forest Sciences, University of Melbourne, Australia
2 Faculty of Environment, Vietnam National University of Agriculture, Vietnam
3 Department of Geology, Geography and Environment, University of Alcala, Spain
4 National Institute for Research and DeveORSPHQWLQ)RUHVWU\³0DULQ'UDFHD´Romania
Wildfires worldwide are becoming more frequent but are
they also becoming more severe? Here we used remotely
sensed burn-severity data from wildfires in Victoria,
southeastern Australia to address that question. We selected
162 wildfires of more than 1000 ha that occurred over the
past 30 years across a wide range of forest types. Spectral
indices derived from Landsat pre- and post- fire imagery
were used to map fire severity. Our results show a
significant increase in the absolute and proportional area
burnt by high-severity fire over the last three decades. This
study demonstrates that wildfires in the temperate forests of
southern Australia are becoming more severe. Such change
in fire regimes may have critical consequences for the
sustainability and resilience of the studied forests.
Index Terms² Burn severity, eucalypt, Landsat,
spectral index, temperate forest
Wildfires are among the most important disturbances
worldwide with significant impacts on the carbon cycle,
biodiversity and human wellbeing [1, 2]. It has been shown
that forest wildfires are becoming more frequent and, in
some cases, also more extensive [3, 4], a change that has
been linked to climate change [4, 5]. Whether wildfires are
also becoming more severe is still unclear.
Fire severity is an important attribute of a fire regime. High-
severity forest fires can lead to carbon losses, elevated tree
mortalities, greater vulnerability to subsequent fires and
conversion of forest to less productive states [6-10].
Analyzing the retrospective temporal trend of high-severity
fire is therefore essential to better understand shifts in fire
regimes and how novel regimes might affect forest
2.1. Study area & fire history
This study focused on wildfires that occurred in the state of
Victoria, southeastern Australia over the past 30 years.
Using the fire history records provided by the Department of
Environment, Land, Water & Planning (DELWP) of
Victoria, we selected wildfires with a minimum area of 1000
ha that burnt between 1987 and 2017, totaling 162 wildfires
(Fig. 1). These fires occurred across seven bioregions of
varying soil and climate characteristics and affected a range
of temperate eucalypt forests differing in species
composition, structure, and regeneration strategy.
0 50 10025
Figure 1. Map of the State of Victoria, southeastern
Australia. (i) Victoria highlighted (grey) in the map of
Australia; (ii) Locations of study areas within the state of
Victoria in south-eastern Australia. Dots represent the center
of each of the 162 wildfires analysed in this study. Colours
relate to different bioregions.
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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium | 978-1-7281-6374-1/20/$31.00 ©2020 IEEE | DOI: 10.1109/IGARSS39084.2020.9324121
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2.2 Fire severity mapping and data analyses
Fire severity mapping was conducted using Landsat TM,
ETM+ and Landsat 8 images acquired within two months
before and after the fires to minimize differences in forest
phenology and general atmospheric conditions at the time of
acquisition. The images were selected and obtained through
the US Geological Survey (USGS) EarthExplorer as higher-
level surface reflectance products for each fire. The images
were masked for clouds and shadows using the Fmask
Four spectral indices (NBR, NDVI, NDWI, and MSAVI)
and their temporal differences (i.e. delta versions, which
calculate the change between pre-fire and post-fire spectral
index values) were computed for each of the 162 wildfires.
These indices are commonly used to assess fire severity [11,
12] and were identified in our previous study [13] as optimal
spectral indices for fire-severity mapping for the studied
forest types.
Figure 2. Fire severity map as a result of random forest
model for Kinglake area in 2009.
Fire severity was mapped using a random forest model
previously developed by the authors [14] for the same area.
Briefly, the model used a training dataset of 2238 reference
plots encompassing 13 forest types across Victoria. Plot fire
severity was assessed in situ or was visually interpreted on
very high resolution orthophotos as Unburnt: less than 1%
of eucalypt and non-eucalypt crowns scorched; Low
severity: light scorch of 1 - 35% of eucalypt and non-
eucalypt crowns; Moderate severity: 30 - 65% of eucalypt
and non-eucalypt crowns scorched; or High severity: 70 -
100% of eucalypt and non-eucalypt crowns burnt [15].
Accuracy of high severity mapping on an independent
validating dataset across all 13 forest types was very high,
with 0.06 and 0.18 commission and omission error
respectively [14].
Changes in the area burnt by high-severity fire (total and
proportional) over time were examined using linear models
with individual fires as the sampling unit and fire size as a
covariate. Data were transformed when needed to meet
assumptions of normality. All statistical tests were
conducted in the statistical programming language R [16].
Fire history records of the past three decades in Victoria
show a significant increase in the number of wildfires larger
than 1000 ha but no significant increase in their size (Fig.
3). In contrast to the trend in the overall fire size, our
analysis of the high-severity fire mapping indicates that
within those fires greater than 1000 ha both the area burnt
by high-severity fire and the proportion that high-severity
area represents have increased significantly (p<0.05 and
p<0.1 respectively) from 1987 to 2017 (Fig. 4).
Figure 3. Temporal trends over the past three decades in the
number of wildfires greater than 1000 ha (upper panel) and
the fire size of such fires (lower panel).
The increase in high-severity fires in south-eastern Australia
is of great concern. The impacts of high severity fires in
temperate Eucalyptus forest include soil erosion, reduction
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in carbon sequestration and carbon carrying capacity,
destruction of habitat, and loss of social and aesthetical
values [17-20]. The magnitude of such impacts depends on
the forest species composition, their regeneration strategy,
the occurrence of repeated fires at short intervals, and the
environmental conditions during post-fire regeneration [21-
23]. At landscape scales, nevertheless, the impact will
ultimately depend on the area burnt by high-severity fires.
Figure 4. Temporal trends in the area burnt by high severity
fire presented as total area (upper panel) and percentage of
burnt area (lower panel). Dots represent each of the 162
wildfires examined in this study.
Changes in the area of high-severity fire like those described
here have been predicted to occur as a result of climate
change for decades [24-26]. If that trend is to continue, as
expected under current climate change projections, it is
likely to result in large-scale changes in key structural
attributes of even the most fire-tolerant forests.
Our results are of critical importance for forest managers
and policy makers to acknowledge and act on the described
changes in the fire regimes to ensure that Victorian
temperate forests continue to provide us with ecosystem
services essential for our wellbeing.
The authors would like to acknowledge the financial support
of the Melbourne Research Scholarship program, the
Vietnam International Education Cooperation Department
(VIED) scholarship, and the Integrated Forest Ecosystem
Research program, supported by the Victorian Department
of Environment, Land, Water and Planning. We also
acknowledge the support of many staff and students from
the School of Ecosystem and Forest Sciences at the
University of Melbourne.
[1] L. Giglio, J.T. Randerson and G.R. van der Werf:
"Analysis of daily, monthly, and annual burned area using
(GFED4)". Journal of Geophysical Research:
Biogeosciences 2013, 118(1):317-328.
[2] C.A. Harper, W.M. Ford, M.A. Lashley, C.E. Moorman
and M.C. Stambaugh: "Fire effects on wildlife in the Central
Hardwoods and Appalachian regions, USA". Fire Ecology
2016, 12(2):127-159.
[3] S.L. Stephens, J.K. Agee, P.Z. Fule, M. North, W.
Romme, T. Swetnam and M.G. Turner: "Managing forests
and fire in changing climates". Science 2013, 342(6154):41-
[4] M.D. Flannigan, M.A. Krawchuk, W.J. de Groot, B.M.
Wotton and L.M. Gowman: "Implications of changing
climate for global wildland fire". International journal of
wildland fire 2009, 18(5):483-507.
[5] C. Aponte, W.J. de Groot and B.M. Wotton: "Forest
fires and climate change: causes, consequences and
management options". International Journal of Wildland
Fire 2016, 25(8):i-ii.
[6] L.T. Bennett, M.J. Bruce, J. Machunter, M. Kohout, S.J.
Krishnaraj and C. Aponte: "Assessing fire impacts on the
carbon stabilit\ RI ILUHဨWROHUDQW IRUHVWV Ecological
Applications 2017, 27(8):2497-2513.
[7] J.M. Earles, M.P. North and M.D. Hurteau: "Wildfire
and drought dynamics destabilize carbon stores of
ILUHဨVXSSUHVVHG IRUHVWV Ecological applications 2014,
[8] M.D. Hurteau and M.L. Brooks: "Short-and long-term
effects of fire on carbon in US dry temperate forest
systems". BioScience 2011, 61(2):139-146.
Authorized licensed use limited to: University of Melbourne. Downloaded on February 22,2021 at 06:57:17 UTC from IEEE Xplore. Restrictions apply.
[9] M.D. Hurteau, S. Liang, K.L. Martin, M.P. North, G.W.
Koch and B.A. Hungate: "Restoring forest structure and
southwestern ponderosa pine forests". Ecological
applications 2016, 26(2):382-391.
[10] L.T. Bennett, M.J. Bruce, J. MacHunter, M. Kohout,
M.A. Tanase and C. Aponte: "Mortality and recruitment of
fire-tolerant eucalypts as influenced by wildfire severity and
recent prescribed fire". Forest Ecology and Management
2016, 380:107-117.
[11] J.W. Van Wagtendonk, R.R. Root and C.H. Key:
"Comparison of AVIRIS and Landsat ETM+ detection
capabilities for burn severity". Remote Sensing of
Environment 2004, 92(3):397-408.
[12] S. Veraverbeke, W.W. Verstraeten, S. Lhermitte and
R. Goossens: "Evaluating Landsat Thematic Mapper
spectral indices for estimating burn severity of the 2007
Peloponnese wildfires in Greece". International journal of
wildland fire 2010, 19(5):558-569.
[13] B. Tran, M. Tanase, L. Bennett and C. Aponte:
"Evaluation of spectral indices for assessing fire severity in
Australian temperate forests". Remote Sensing 2018,
[14] N. Tran, M. Tanase, L. Bennett and C. Aponte: "Fire-
severity classification across temperate Australian forests:
random forests versus spectral index thresholding". Remote
Sensing for Agriculture, Ecosystems, and Hydrology XXI
2019, 11149:111490U.
[15] DELWP: Fire History Records of Fires Primarily on
Public Land. In. Melbourne, Victoria, Australia: Department
of Environment Land Water and Planning; 2017.
[16] R.C. Team: "R: A language and environment for
statistical computing". 2013.
[17] B.T. Bormann, P.S. Homann, R.L. Darbyshire and
B.A. Morrissette: "Intense forest wildfire sharply reduces
mineral soil C and N: the first direct evidence". Canadian
Journal of Forest Research 2008, 38(11):2771-2783.
[18] D.M. Bowman, B.P. Murphy, M.M. Boer, R.A.
Bradstock, G.J. Cary, M.A. Cochrane, R.J. Fensham, M.A.
Krawchuk, O.F. Price and R.J. Williams: "Forest fire
management, climate change, and the risk of catastrophic
carbon losses". Frontiers in Ecology and the Environment
2013, 11(2):66-67.
[19] W.H. Cai and J. Yang: "High-severity fire reduces
early successional boreal larch forest aboveground
productivity by shifting stand density in north-eastern
China". International journal of wildland fire 2016,
[20] X. Hu, J. Zhu, C. Wang, T. Zheng, Q. Wu, H. Yao and
J. Fang: "Impacts of fire severity and post-fire reforestation
on carbon pools in boreal larch forests in Northeast China".
Journal of Plant Ecology 2015, 9(1):1-9.
[21] .- $QGHUVRQဨ7HL[HLUD $' 0LOOHU -( 0RKDQ
T.W. Hudiburg, B.D. Duval and E.H. DeLucia: "Altered
dynamics of forest recovery under a changing climate".
Global change biology 2013, 19(7):2001-2021.
[22] T.A. Fairman, C.R. Nitschke and L.T. Bennett: "Too
much, too soon? A review of the effects of increasing
wildfire frequency on tree mortality and regeneration in
temperate eucalypt forests". International journal of
wildland fire 2016, 25(8):831-848.
[23] L.D. Prior, G.J. Williamson and D.M. Bowman:
"Impact of high-severity fire in a Tasmanian dry eucalypt
forest". Australian Journal of Botany 2016, 64(3):193-205.
[24] M.D. Flannigan and C.E.V. Wagner: "Climate change
and wildfire in Canada". Canadian Journal of Forest
Research 1991, 21(1):66-72.
[25] M.S. Torn and J.S. Fried: "Predicting the impacts of
global warming on wildland fire". Climatic change 1992,
[26] T. Beer, A. Gill and P. Moore: Australian bushfire
planning for climatH FKDQJH¶(G *, 3HDUPDQ SS ±
427. In.: CSIRO: East Melbourne; 1988.
Authorized licensed use limited to: University of Melbourne. Downloaded on February 22,2021 at 06:57:17 UTC from IEEE Xplore. Restrictions apply.
... Over the last decades, an increasing trend in larger and more severe wildfires has been generally observed over many fire-prone regions, namely in the Mediterranean basin [1][2][3], California [4][5][6], and Australia [7,8]. More frequent hot and dry summer conditions, combined with climate change and high fuel accumulation over time and space, have already been shown to promote large and intense fire seasons across these regions [9][10][11]. ...
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