Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/nhess-2017-101
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
11 Apr 2017
Review status
This discussion paper is under review for the journal Natural Hazards and Earth System Sciences (NHESS).
Estimating Grassland Curing with Remotely Sensed Data
Wasin Chaivaranont1, Jason P. Evans1, Yi Y. Liu1,2, and Jason J. Sharples3 1ARC Centre of Excellence for Climate Systems Science and Climate Change Research Centre, UNSW, Sydney, 2052, Australia
2School of Geography and Remote Sensing, Nanjing University of Information Science and Technology, Nanjing, 210044, China
3School of Physical, Environmental and Mathematical Sciences, UNSW, Canberra, ACT 2600
Abstract. Wildfire can become a catastrophic natural hazard, especially during dry summer seasons in Australia. Severity is influenced by various meteorological, geographical, and fuel characteristics. Modified Mark 4 McArthur's Grassland Fire 10 Danger Index (GFDI) is a commonly used approach to determine the fire danger level in grassland ecosystems. The degree of curing (DOC, i.e. proportion of dead material) of the grass is one key ingredient in determining the fire danger. It is difficult to collect accurate DOC information in the field, therefore, ground observed measurements are rather limited. In this study, we used satellite observed vegetation greenness (Normalised Difference Vegetation Index, NDVI) and vegetation water content (Vegetation Optical Depth, VOD) information to improve the accuracy of the DOC estimation. First, a statistically 15 significant relationship is established between selected ground observed DOC and satellite observed vegetation datasets (NDVI and VOD) with an r2 of 0.67. DOC levels estimated using satellite observations were then evaluated using field measurements with an r2 of 0.55. Results suggest that satellite based DOC estimation can reasonably reproduce ground based observations in space and time. Comparison with currently available satellite based DOC products shows that our model has a comparable and arguably more balanced performance.

Citation: Chaivaranont, W., Evans, J. P., Liu, Y. Y., and Sharples, J. J.: Estimating Grassland Curing with Remotely Sensed Data, Nat. Hazards Earth Syst. Sci. Discuss., doi:10.5194/nhess-2017-101, in review, 2017.
Wasin Chaivaranont et al.
Wasin Chaivaranont et al.
Wasin Chaivaranont et al.

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Short summary
This study explore the feasibility of using a combination of recent and traditional satellite products to estimate the grassland fire fuel availability across space and time over Australia. We found a significant relationship between both recent and traditional satellite products and observed grassland fuel availability and develop an estimation model. We hope our estimation model will provide a more balanced alternative to the currently available grass fuel availability estimation models.
This study explore the feasibility of using a combination of recent and traditional satellite...
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