Preprints
https://doi.org/10.5194/bg-2022-85
https://doi.org/10.5194/bg-2022-85
 
13 Apr 2022
13 Apr 2022
Status: a revised version of this preprint is currently under review for the journal BG.

Assessing the sensitivity of multi-frequency passive microwave vegetation optical depth to vegetation properties

Luisa Schmidt1, Matthias Forkel1, Ruxandra-Maria Zotta2, Samuel Scherrer2, Wouter A. Dorigo2, Alexander Kuhn-Régnier3,4, Robin van der Schalie5, and Marta Yebra6,7 Luisa Schmidt et al.
  • 1Technische Universität Dresden, Institute of Photogrammetry and Remote Sensing, 01069 Dresden, Germany
  • 2Technische Universität Wien, Department of Geodesy and Geoinformation, Vienna, Austria
  • 3Leverhulme Centre for Wildfires, Environment, and Society, London, SW7 2AZ, UK
  • 4Department of Physics, Imperial College London, London, SW7 2AZ, UK
  • 5Planet, Wilhelminastraat 43A, 2011 VK Haarlem, The Netherlands
  • 6Fenner School of Environment & Society, Australian National University, ACT 2601, Australia
  • 7School of Engineering, Australian National University, ACT 2601, Australia

Abstract. Vegetation attenuates the microwave emission from the land surface. The strength of this attenuation is quantified in models in terms of the parameter Vegetation Optical Depth (VOD), and is influenced by the vegetation mass, structure, water content, and observation wavelength. Earth observation satellites operating in the microwave frequencies are used for global VOD retrievals, enabling the monitoring of vegetation status at large scales. VOD has been used to determine above-ground biomass, monitor phenology or estimate vegetation water status. VOD can be also used for constraining land surface models or modelling wildfires at large scale. Several VOD products exist differing by frequency/wavelength, sensor, and retrieval algorithm. Numerous studies present correlations or empirical functions between different VOD datasets and vegetation variables such as normalised difference vegetation index, leaf area index, gross primary production, biomass, vegetation height or vegetation water content. However, an assessment of the joint impact of land cover, vegetation biomass, leaf area, and moisture status on the VOD signal is challenging and has not yet been done.

This study aims to interpret the VOD signal as a multi-variate function of several descriptive vegetation variables. The results will help to select certain VOD wavelengths for specific applications and can guide the development of appropriate observation operators to integrate VOD with large-scale land surface models. Here we use VOD from the Land Parameter Retrieval Model (LPRM) of Ku-, X- and C-bands of the harmonised VODCA dataset and level 3 L-band derived from SMOS and SMAP sensors. Within a multivariable regression random forest model for simulating these VOD signals, leaf area index, live-fuel moisture content, above-ground biomass, and land cover are able to explain up to 0.95 of the variance (coefficient of determination). Thereby, the variance in L-band VOD is reproduced spatially and for Ku-, X- and C-band VOD spatially as well as temporally. Analyses of accumulated local effects demonstrate that Ku-, X- and C-band VOD is mostly sensitive to leaf area index and L-band VOD to above-ground biomass. However, for all VODs the global relationships with vegetation properties are non-monotonic and complex and differ with land cover type. This indicates that the use of simple global regressions to estimate single vegetation properties (e.g. above-ground biomass) from VOD is over-simplistic.

Luisa Schmidt et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-85', Martin Baur, 20 Apr 2022
    • RC3: 'Reply on RC1', Anonymous Referee #1, 05 May 2022
      • AC1: 'Reply on RC3', Luisa Schmidt, 24 Jun 2022
    • AC2: 'Reply on RC1', Luisa Schmidt, 24 Jun 2022
  • RC2: 'Comment on bg-2022-85', Andrew Feldman, 03 May 2022
    • AC3: 'Reply on RC2', Luisa Schmidt, 24 Jun 2022

Luisa Schmidt et al.

Luisa Schmidt et al.

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Short summary
Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the parameter Vegetation Optical Depth (VOD), and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help to understand the effects of ecosystem properties on VOD.
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