Review of High Resolution Thermal Infrared Applications and Requirements: The Fuegosat Synthesis Study

Sobrino, José A.; Frate, Fabio Del; Drusch, Matthias; Jiménez-Muñoz, Juan C.; Manunta, Paolo

doi:10.1007/978-94-007-6639-6_10

Cited by 6 publications

(6 citation statements)

References 53 publications

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“…Considering the generally-accepted error at the level of 1-2 K [70,71], the three tested procedures (SC, RTE-ACPC, and MW) can be used for LST estimation from Landsat-5 TM thermal data. RMSDs obtained for SC and RTE-ACPC procedures are below 1 °C , with the best results for SC (RMSD = 0.5 °C).…”

Section: Discussionmentioning

confidence: 99%

Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling

et al. 2014

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Land Surface Temperature (LST) is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global change) and FLUXPEC (Monitoring changes in water and carbon fluxes from remote and proximal sensing in Mediterranean -dehesa‖ ecosystem) projects LST retrieved from Landsat data is required to integrate ground-based observations of energy, water, and carbon fluxes with multi-scale remotely-sensed data and assess water and carbon balance in ecologically fragile heterogeneous ecosystem of Mediterranean wooded grassland (dehesa). Thus, three methods based on the Radiative Transfer Equation were used to extract LST from a series of 2009-2011 Landsat-5 TM images to assess the applicability for temperature input . Differences between Landsat-retrieved LST and MODIS LST are in the range of 2 to 4 °C and can be explained mainly by differences in observation geometry, emissivity, and time mismatch between Landsat and MODIS overpasses. There is a seasonal bias in Landsat-MODIS LST differences due to greater variations in surface emissivity and thermal contrasts between landcover components.

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Section: Discussionmentioning

confidence: 99%

Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling

et al. 2014

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“…For monitoring purposes in the thermal infrared (IR) domain, dual-band instruments are often sufficient [1,2], provided they offer daily revisit time. This is achievable using constellations of small satellites, which sets the need for compact dual-band IR imagers.…”

Section: Introductionmentioning

confidence: 99%

Thickness optimization algorithm to improve multilayer diffractive optical elements performance

Laborde¹,

Loicq

HASTANIN³

et al. 2023

Appl. Opt.

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The diffractive zone thicknesses of conventional diffractive optical elements (DOEs) are generally obtained using the thin element approximation (TEA). However, the TEA yields inaccurate results in the case of thick multilayer DOEs (MLDOEs). The extended scalar theory (EST) is an alternative thickness optimization method that depends on the diffractive order and the optimization wavelength. We developed an algorithm to research suitable EST input parameters. It combines ray-tracing and Fourier optics to provide a performance estimate for each EST parameter pair. The resulting “best” MLDOE designs for three different material combinations are analyzed using rigorous finite-difference time-domain. Compared to the TEA, the proposed algorithm can provide performing zone thicknesses.

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“…Earth observation in the thermal infrared (IR) bandwidth addresses numerous issues, particularly in the security and surveillance domains. According to the reviews in [1,2], most IR applications require only two distinct bandwidths: agriculture, irrigation monitoring, forest fires detection, etc. In these cases, expensive multispectral spaceborne instruments can be replaced by smaller dual-band instruments.…”

Section: Introductionmentioning

confidence: 99%

Multilayer diffractive optical element material selection method based on transmission, total internal reflection, and thickness

Laborde¹,

Loicq²,

HASTANIN³

et al. 2022

Appl. Opt.

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The polychromatic integral diffraction efficiency (PIDE) metric is generally used to select the most suitable materials for multilayer diffractive optical elements (MLDOEs). However, this method is based on the thin element approximation, which yields inaccurate results in the case of thick diffractive elements such as MLDOEs. We propose a new material selection approach, to the best of our knowledge, based on three metrics: transmission, total internal reflection, and the optical component’s total thickness. This approach, called “geometric optics material selection method” (GO-MSM), is tested in mid-wave and long-wave infrared bands. Finite-difference time-domain is used to study the optical performance (Strehl ratio) of the “optimal” MLDOE combinations obtained with the PIDE metric and the GO-MSM. Only the proposed method can provide MLDOE designs that perform. This study also shows that an MLDOE gap filled with a low index material (air) strongly degrades the image quality.

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Review of High Resolution Thermal Infrared Applications and Requirements: The Fuegosat Synthesis Study

Cited by 6 publications

References 53 publications

Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling

Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling

Thickness optimization algorithm to improve multilayer diffractive optical elements performance

Multilayer diffractive optical element material selection method based on transmission, total internal reflection, and thickness

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