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Volume 18, issue 6
Nat. Hazards Earth Syst. Sci., 18, 1535–1554, 2018
https://doi.org/10.5194/nhess-18-1535-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nat. Hazards Earth Syst. Sci., 18, 1535–1554, 2018
https://doi.org/10.5194/nhess-18-1535-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 04 Jun 2018

Research article | 04 Jun 2018

Estimating grassland curing with remotely sensed data

Wasin Chaivaranont et al.
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Allan, G., Johnson, A., Cridland, S., and Fitzgerald, N.: Application of NDVI for predicting fuel curing at landscape scales in northern Australia: can remotely sensed data help schedule fire management operations?, Int. J. Wildland Fire, 12, 299–308, 2003.
Andela, N. and van der Werf, G. R.: Recent trends in African fires driven by cropland expansion and El Nino to La Nina transition, Nat. Clim. Change, 4, 791–795, https://doi.org/10.1038/nclimate2313, 2014.
Andela, N., Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., and McVicar, T. R.: Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data, Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, 2013.
Anderson, S. A. J., Anderson, W. R., Hollis, J. J., and Botha, E. J.: A simple method for field-based grassland curing assessment, Int. J. Wildland Fire, 20, 804–814, https://doi.org/10.1071/WF10069, 2011.
Berrisford, P., Dee, D. P., Poli, P., Brugge, R., Fielding, M., Fuentes, M., Kållberg, P. W., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim archive Version 2.0, ECMWF, https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-interim, 2011.
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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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