Physical Retrieval of Land Surface Emissivity Spectra from Hyper-Spectral Infrared Observations and Validation with In Situ Measurements

Masiello, Guido; Serio, Carmine; Venafra, Sara; Liuzzi, Giuliano; Poutier, Laurent; Göttsche, Frank-M.

doi:10.3390/rs10060976

Cited by 37 publications

(29 citation statements)

References 55 publications

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“…In 7, surface emissivity is either estimated from the corresponding value for the 10.8 µm MSG/SEVIRI channel, combining vegetation and bare ground emissivities of the land cover attributed to the pixel containing the station, or set to a constant value, e.g. at the Gobabeb desert site [83,84].…”

Section: In Situ Lstmentioning

confidence: 99%

An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

et al. 2019

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A new all-weather land surface temperature (LST) product derived at the Satellite Application Facility on Land Surface Analysis (LSA-SAF) is presented. It is the first all-weather LST product based on visible and infrared observations combining clear-sky LST retrieved from the Spinning Enhanced Visible and Infrared Imager on Meteosat Second Generation (MSG/SEVIRI) infrared (IR) measurements with LST estimated with a land surface energy balance (EB) model to fill gaps caused by clouds. The EB model solves the surface energy balance mostly using products derived at LSA-SAF. The new product is compared with in situ observations made at 3 dedicated validation stations, and with a microwave (MW)-based LST product derived from Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) measurements. The validation against in-situ LST indicates an accuracy of the new product between -0.8 K and 1.1 K and a precision between 1.0 K and 1.4 K, generally showing a better performance than the MW product. The EB model shows some limitations concerning the representation of the LST diurnal cycle. Comparisons with MW LST generally show higher LST of the new product over desert areas, and lower LST over tropical regions. Several other imagers provide suitable measurements for implementing the proposed methodology, which offers the potential to obtain a global, nearly gap-free LST product.

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Section: In Situ Lstmentioning

confidence: 99%

An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

et al. 2019

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“…In (11), surface emissivity is either estimated from the corresponding value for the 10.8 µm MSG/SEVIRI pixel, combining vegetation and bare ground emissivities of the land cover attributed to the pixel containing the station, or set to a constant value, i.e. at the Gobabeb desert site [85,86]. Surface temperature is then derived with the inverse Planck function, at the central wavelength of the radiometer response function ( ):…”

Section: In Situ Lstmentioning

confidence: 99%

An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

Martins¹,

Trigo²,

Ghilain³

et al. 2019

Preprint

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An all-weather land surface temperature (LST) product derived at the Satellite Application Facility on Land Surface Analysis (LSA-SAF) is presented. The product is based on clear-sky LST retrieved from MSG/SEVIRI infrared (IR) measurements, complemented by LST estimated with a land surface energy balance (EB) model to fill gaps caused by clouds. The EB model solves the surface energy balance mostly using products derived at LSA-SAF. The new product is compared with in situ observations made at 3 dedicated validation stations, and with a Microwave (MW) based LST product derived from AMSR-E measurements. The validation against in-situ LST indicates an accuracy of the new product between -0.8 K and 1.1 K and a precision between 1.0 K and 1.4 K, generally showing a better performance than the MW product. The EB model shows some limitations concerning the representation of the LST diurnal cycle. Comparisons with MW LST generally show higher LST of the new product over desert areas, and lower LST over tropical regions. Several other imagers provide suitable measurements for implementing the proposed methodology, which offers the potential to obtain a global, nearly gap-free LST product.

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“…only a minimum amount of dry grass was present. The various measurements performed during the field experiment are described in some detail in [30] and a detailed description of measurement site could be found in [16]. The in-situ emissivity spectra were obtained from measurements with a Fourier Transform Infrared (FTIR) spectrometer by ONERA, the French Aerospace Lab.…”

Section: In Situ Datamentioning

confidence: 99%

“…The retrieval of surface emissivity and temperature from space has been predominantly focus on statistical approaches and we refer the interested reader to [8,9] for reviews. Apart from SEVIRI, physically based ε, T s retrieval algorithms have been considered by various authors for applications to imagers and hyper-spectral infrared sounders (among many other we quote [10][11][12][13][14][15][16]).…”

Section: Introductionmentioning

confidence: 99%

“…The new forward model has been embedded within our KF scheme [1,2], and a retrieval exercise has been performed to show its effectiveness in retrieving emissivities. The retrieval exercise presented here has been performed over highly homogeneous and flat gravel plains around the permanent land surface temperature (LST) validation station Gobabeb in the Namib desert [16,21,22] operated by Karlsruhe Institute of Technology (KIT) within the framework of EUMETSAT's Satellite Application Facility on Land Surface Analysis (LSA SAF).…”

Section: Introductionmentioning

confidence: 99%

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SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Masiello

Serio

Venafra

et al. 2019

Preprint

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Timely processing of observations from hyper-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances for the physical retrieval of surface temperature and emissivity. The new radiative transfer model improves computational time by a factor of ≈ 7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the simultaneous retrieval of surface temperature and emissivity in three infrared channels (8.7, 10.8, 12 μm). The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e. average differences are generally well below 0.01.

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Physical Retrieval of Land Surface Emissivity Spectra from Hyper-Spectral Infrared Observations and Validation with In Situ Measurements

Cited by 37 publications

References 55 publications

An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

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