Active/Passive Microwave Remote Sensing in Application to Vegetation & Soil and Snow & Soil
Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
Final Report Abstract
L-band microwave satellite missions such as the ESA’s Soil Moisture and Ocean Salinity (SMOS) and the NASA’s Soil Moisture Active Passive (SMAP) missions are promising microwave data sources to retrieve information on soil and vegetation properties at large scale with a high temporal and spatial resolution. However, accurate validations and advance in the development of radiative transfer (RT) models are needed to improve remote-sensing data products for the retrieval of soil and vegetation properties. The main objective of this research was to explore the microwave RT that determines active and passive microwave signals of areas covered by vegetation. A second objective was to integrate the RT models in different inversion schemes, resulting in a full retrieval of soil and vegetation properties. To this end, controlled experiments with ground-based active (radar) and passive (radiometer) microwave measurements accompanied by simultaneous in-situ soil and vegetation measurements were performed. In a first study, we analyzed the time, polarization, and angle dependency of the vegetation optical depth (τ), the relationship between the radiometer-derived τ and several vegetation properties measured in situ over a full vegetation cycle, and the impact of the quality of the τ parameter on the soil moisture retrieval. The results showed that over a wheat canopy, τ has a high temporal variability, which corresponded to changes of the vegetation states, mainly VWC and LAI. This study clearly showed the importance of using a time, polarization, and angle dependent τ parameter at the field scale for accurate soil moisture retrieval. Then, we developed and validated at the field scale a new approach to retrieve the gravimetric vegetation water content (mg) from the attenuation of L-band microwave measurements radiations through vegetation (τ-parameter). It is based on the inversion of a physical modeling framework describing the dependency of the attenuation of microwave radiation on vegetation height, vegetation volume fraction (δ), and mg. The δ-parameter is shown to have a high impact on the thermal emission at L-band, with small changes in δ resulting in relatively large changes in the retrieved mg. The results indicated a strong agreement between the in situ measured and retrieved mg. In the third study, we applied the combined full-waveform and roughness radar model proposed by Jonard et al. (2012) to the GPR data from the controlled and in situ experiments of André et al. (2015; 2016) in order to investigate the ability of the approach to properly reconstruct litter horizons, and to evaluate thereby the potentiality of the technique to provide quantitative characterization of litter for both surface roughness and horizon constitutive properties. The proposed modeling approach successfully reproduced radar data, showing agreement between measured and modeled signals at least equivalent and even often better than that obtained previously using the effective electrical conductivity frequency dependent model. Such improved performances for the present approach would arise from a better physical description of scattering through the roughness model than when considering frequency dependence of litter effective electrical conductivity. In the last study, we developed a new closed-form asymptotic EM model considering random rough layers based on the SKA model that we combined with planar multilayered media Green’s functions and a full-wave, closed-form radar-antenna model. This generalizes the model of Jonard et al. (2012), in which only scattering in reflection from the rough surface, i.e., the upper air/soil medium interface, was considered. The newly developed model applies to multilayered media with random rough layers, and it takes into account the scattering in transmission through the rough interfaces. It is also an easily implementable and computationally efficient model suitable for inversion using a 3-D analytical formulation. This new model was successfully validated through comparisons with a 3-D reference GPR simulation software, namely, gprMax, and the performance of the model for retrieving medium properties from GPR full-wave inversion was shown. These studies offer valuable insights into the microwave RT that determines active- and passive microwave signals of areas covered by vegetation. The fundamental knowledge gained during the project is essential to improve the performance and to advance the range of parameters that can be retrieved from active and passive microwave remote sensing of soils and vegetation. This should help to improve the global soil moisture and vegetation properties retrieval from satellite instruments such as SMOS and SMAP and from the upcoming L-band microwave satellite missions. Further research should investigate the joint analyses of active and passive microwave remote sensing data to characterize soils and vegetation. To overcome the individual limitations of the passive and active microwave sensing techniques and benefit from their different sensitivities (to vegetation, soil surface roughness, forest litter, etc), the combined use of these two technologies might be a promising solution for the retrieval of soil and vegetation properties.
Publications
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2018. Vegetation optical depth and soil moisture retrieved from L-band radiometry over the growth cycle of a winter wheat t. Remote Sensing, 10: 1637
Meyer T., Weihermüller L., Vereecken H., and Jonard F.
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Fully polarimetric L-band brightness temperature signatures of azimuthal permittivity patterns - measurements and model simulations, 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) - Proceedings, Valencia, Spain, July 22-27, 2018, pp. 6500-6503
Søbjærg S. S., Link M., Jagdhuber T., Montzka C., Jonard F., Dill S., Peichl M., and Meyer T.
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Ground-based passive microwave remote sensing of soil moisture and vegetation optical depth through a growing season, 15th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), Cambridge, MA, USA, March 27-30, 2018
Meyer T., Jonard F., and Weihermüller L.
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Passive microwave remote sensing of soil moisture and vegetation optical depth over the entire growing season of a winter wheat, Geophysical Research Abstracts, Vol. 20, EGU2018-12516, EGU General Assembly, Vienna, Austria, April 8-13, 2018
Meyer T., Jonard F., and Weihermüller L.
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Vegetation optical depth and soil moisture retrieval using L-band radiometry over the entire growing season of a winter wheat stand, 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) - Proceedings, Valencia, Spain, July 22-27, 2018, pp. 3093-3096
Meyer T., Jonard F., and Weihermüller L.
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2019. Accounting for surface roughness scattering in the characterization of forest litter with ground-penetrating radar. Remote Sensing, 11: 828
André F., Jonard F.1, Jonard M., Vereecken H., and Lambot S.
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2019. Modeling of multilayered media Green’s functions with rough interfaces. IEEE Transactions on Geoscience and Remote Sensing
Jonard F., André F., Pinel N., Warren C., Vereecken H., and Lambot S.
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Estimation of volume fraction and gravimetric moisture of winter wheat based on microwave attenuation: validation at the field scale, 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Yokohama, Japan, July 28 - August 02, 2019
Meyer T., Jagdhuber T., Piles M., Fink A., Vereecken H., and Jonard F.
