EGU2020-10860
https://doi.org/10.5194/egusphere-egu2020-10860
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Characterising vegetation fuel moisture conditions from microwave satellite observations for fire danger prediction at continental to global scales

Matthias Forkel1, Niels Andela2, Wouter A. Dorigo3, Markus Drüke4, Sandy P. Harrison5, Leander Moesinger3, Luisa Schmidt1, and Marta Yebra6
Matthias Forkel et al.
  • 1Technische Universität Dresden, Institute for Photogrammetry and Remote Sensing, Dresden , Germany (matthias.forkel@tu-dresden.de)
  • 2NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, USA
  • 3Technische Universität Wien, Department of Geodesy and Geoinformation, Vienna, Austria
  • 4Potsdam Institute for Climate Impact Research, Earth System Analysis, Potsdam, Germany
  • 5The University of Reading, Department of Geography and Environmental Science, United Kingdom
  • 6Australian National University, Fenner School of Environment and Society, Canberra ACT, Australia

Spatial patterns and temporal changes in live fuel moisture content (LFMC) have been intensively estimated from satellite observations in the optical domain of the electromagnetic spectrum. Such estimates are valuable to predict regional to local variations in fire danger (Yebra et al., 2018). However, optical satellite measurements saturate fast in dense canopies and are generally hampered during cloud cover. Microwave satellite observations can penetrate clouds and the canopy (dependent on the wavelength) and hence have been intensively used to derive surface soil moisture (SSM) or vegetation optical depth (VOD), which is a proxy for vegetation water content (Moesinger et al., 2019). However, the relationship of microwave VOD to LFMC and the predictive capabilities of VOD for fire dynamics have not yet been investigated at large scales. Here we aim to assess how VOD reflects changes in LFMC and the sensitivity of VOD to different properties of fire dynamics such as fire occurrence, size, burned area, and fire radiative power.

We compared VOD in different microwave bands (Ku-, X-, and C-band) from the VODCA dataset (Moesinger et al., 2019) with LFMC from MODIS retrievals (Yebra et al., 2018). Our results demonstrate that VOD and LFMC are moderately to highly correlated but the strength and shape of the relationship depends on land cover type. In a preliminary analysis, we then predicted the probability of fire occurrence (Andela et al., 2019) and fire radiative power (Kaiser et al., 2012) from VOD, SSM, and climate data using the random forest machine learning approach. The initial results show that VOD is a skilful predictor for continental-scale fire dynamics. Furthermore, our results suggest that the combination of LFMC from optical satellites with microwave SSM and VOD might allow to comprehensively estimate ecosystem fuel moisture conditions. Hence microwave satellite observations will be valuable for the development of integrated fire danger prediction systems.

 

References

Andela, N., Morton, D.C., Giglio, L., Paugam, R., Chen, Y., Hantson, S., Werf, G.R. van der, Randerson, J.T., 2019. The Global Fire Atlas of individual fire size, duration, speed and direction. Earth Syst. Sci. Data 11, 529–552. https://doi.org/10.5194/essd-11-529-2019

Kaiser, J.W., Heil, A., Andreae, M.O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M.G., Suttie, M., van der Werf, G.R., 2012. Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power. Biogeosciences 9, 527–554. https://doi.org/10.5194/bg-9-527-2012

Moesinger, L., Dorigo, W., Jeu, R. de, Schalie, R. van der, Scanlon, T., Teubner, I., Forkel, M., 2019. The Global Long-term Microwave Vegetation Optical Depth Climate Archive VODCA. Earth Syst. Sci. Data Discuss. 1–26. https://doi.org/10.5194/essd-2019-42

Yebra, M., Quan, X., Riaño, D., Rozas Larraondo, P., van Dijk, A.I.J.M., Cary, G.J., 2018. A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing. Remote Sens. Environ. 212, 260–272. https://doi.org/10.1016/j.rse.2018.04.053

How to cite: Forkel, M., Andela, N., Dorigo, W. A., Drüke, M., Harrison, S. P., Moesinger, L., Schmidt, L., and Yebra, M.: Characterising vegetation fuel moisture conditions from microwave satellite observations for fire danger prediction at continental to global scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10860, https://doi.org/10.5194/egusphere-egu2020-10860, 2020

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