scholarly journals Temperature and Emissivity Smoothing Separation with Nonlinear Relation of Brightness Temperature and Emissivity for Thermal Infrared Sensors

2019 ◽  
Vol 11 (24) ◽  
pp. 2959
Author(s):  
Xinyuan Miao ◽  
Ye Zhang ◽  
Junping Zhang ◽  
Xinyu Zhou
Keyword(s):  
Brightness Temperature ◽  
Nonlinear Model ◽  
Thermal Emission ◽  
Synthetic Data ◽  
Nonlinear Relationship ◽  
Atmospheric Conditions ◽  
Infrared Sensors ◽  
Nonlinear Constraint ◽  
Spectral Contrast ◽  
Contrast Materials

Aiming at low spectral contrast materials, the Optimized Smoothing for Temperature Emissivity Separation (OSTES) method was developed to improve the Temperature and Emissivity Separation (TES) algorithm based on the linear relationship between brightness temperature and emissivity features, but there was little smoothing improvement for higher spectral contrast materials. In this paper, a new nonlinear-relationship based algorithm is presented, focusing on improving the performance of the OSTES method for materials with middle or high spectral contrast. This novel approach is a two-step procedure. Firstly, by introducing atmospheric impact factor, the nonlinear relationship is mathematically proved using first-order Taylor series approximation. Moreover, it is proven that nonlinear model has stronger universality than linear model. Secondly, a new method named Temperature and Emissivity Separation with Nonlinear Constraint (TESNC) is proposed based on the nonlinear model for smoothing temperature and emissivity retrieval. The key procedure of TESNC is the lowest emissivity smoothing estimation based on nonlinear model and retrieved by minimizing the reconstruction error of the Planck radiance. TESNC was tested on a series of synthetic data with different kinds of natural materials representing several multispectral and hyperspectral infrared sensors. It is shown that, especially for materials with higher spectral contrast, the proposed method is less sensitive to changes in atmospheric conditions and sample temperatures. Furthermore, the standard Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) products in different kind of atmospheric conditions were used for verifying the improvement. TESNC is more accurate and stable with the decrease of emissivity and changes of atmospheric conditions compared with TES, Adjusted Normalized Emissivity Method (ANEM), and OSTES methods.

scholarly journals Systematic errors in dust mass determinations: insights from laboratory opacity measurements

2020 ◽  
Vol 499 (4) ◽  
pp. 4666-4686
Author(s):  
Lapo Fanciullo ◽  
Francisca Kemper ◽  
Peter Scicluna ◽  
Thavisha E Dharmawardena ◽  
Sundar Srinivasan
Keyword(s):  
Interstellar Dust ◽  
Thermal Emission ◽  
High Redshift ◽  
Synthetic Data ◽  
Far Infrared ◽  
Systematic Errors ◽  
Experimental Measurements ◽  
Dust Mass ◽  
Dusty Galaxies ◽  
Different Temperatures

ABSTRACT The thermal emission of dust is one of the most important tracers of the interstellar medium: multiwavelength photometry in the far-infrared (FIR) and submillimetre (submm) can be fitted with a model, providing estimates of the dust mass. The fit results depend on the assumed value for FIR/submm opacity, which in most models – due to the scarcity, until recently, of experimental measurements – is extrapolated from shorter wavelengths. Lab measurements of dust analogues, however, show that FIR opacities are usually higher than the values used in models and depend on temperature, which suggests that dust mass estimates may be biased. To test the extent of this bias, we create multiwavelength synthetic photometry for dusty galaxies at different temperatures and redshifts, using experimental results for FIR/submm dust opacity and then we fit the synthetic data using standard dust models. We find that the dust masses recovered by typical models are overestimated by a factor of 2–20, depending on how the experimental opacities are treated. If the experimental dust samples are accurate analogues of interstellar dust, therefore, current dust masses are overestimated by up to a factor of 20. The implications for our understanding of dust, both Galactic and at high redshift, are discussed.

scholarly journals Highly Automated Dipole EStimation (HADES)

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
C. Campi ◽  
A. Pascarella ◽  
A. Sorrentino ◽  
M. Piana
Keyword(s):  
Inverse Problem ◽  
User Interface ◽  
Graphical User Interface ◽  
Particle Filtering ◽  
Synthetic Data ◽  
Nonlinear Relationship ◽  
Data Set ◽  
Automatic Estimation ◽  
Dipole Estimation ◽  
Dipolar Model

Automatic estimation of current dipoles from biomagnetic data is still a problematic task. This is due not only to the ill-posedness of the inverse problem but also to two intrinsic difficulties introduced by the dipolar model: the unknown number of sources and the nonlinear relationship between the source locations and the data. Recently, we have developed a new Bayesian approach, particle filtering, based on dynamical tracking of the dipole constellation. Contrary to many dipole-based methods, particle filtering does not assume stationarity of the source configuration: the number of dipoles and their positions are estimated and updated dynamically during the course of the MEG sequence. We have now developed a Matlab-based graphical user interface, which allows nonexpert users to do automatic dipole estimation from MEG data with particle filtering. In the present paper, we describe the main features of the software and show the analysis of both a synthetic data set and an experimental dataset.

Simulating Marine Litter observations from space to support Operations Research

2021 ◽  
Author(s):  
Stephen Emsley ◽  
Manuel Arias ◽  
Théodora Papadopoulou ◽  
François-Régis Martin-Lauzer
Keyword(s):  
Spatial Resolution ◽  
Operations Research ◽  
Open Space ◽  
Wind Waves ◽  
Synthetic Data ◽  
Atmospheric Conditions ◽  
Marine Litter ◽  
Model Components ◽  
River Mouths ◽  
Sentinel 2

<p>An breadboard for end-to-end (E2E) Marine Litter Optical Performance Simulations (ML-OPSI) is being designed in the frame of the ESA Open Space Innovation Platform (OSIP) Campaign to support Earth Observation (EO) scientists with the design of computational experiments for Operations Research. The ML-OPSI breadboard will estimate Marine Litter signal at Top-Of-Atmosphere (TOA) from a set of Bottom-Of-Atmosphere (BOA) scenarios representing the various case studies by the community (e.g., windrows, frontal areas, river mouths, sub-tropical gyres), coming from synthetic data (computer-simulated) or from real observations. It is a modular, pluggable and extensible framework, promoting re-use and be adapted for different missions, sensors and scenarios.</p><p>The breadboard consists of (a) the OPSI components for the simulation i.e. the process of using a model to study the characteristics of the system by manipulating variables and by studying the properties of the model allowing an evaluation to optimise performance and make predictions about the real system; and (b) the Marine Litter model components for the detection of marine litter. It shall consider the changes caused in the water reflectance and properties due to marine litter, exploiting gathered information of plastic polymers, different viewing geometries, and atmospheric conditions as naturally occurring. The modules of the breadboard include a Scenario Builder Module (SB) with maximum spatial resolution and best modelling as possible of the relevant physical properties, which for spectral sensors could include high spatial resolution and high spectral density/resolution BOA radiance simulations in the optical to SWIR bands; a Radiative Transfer Module (RTM) transforming water-leaving to TOA reflectance for varying atmospheric conditions and observational geometries; a Scene Generator Module (SGM) which could use Sentinel-2, Landsat, or PRISMA data as reference or any other instrument as pertinent; a Performance Assessment Module (PAM) for ML detection that takes into account the variability of the atmosphere, the sunlight & skylight at BOA, the sea-surface roughness with trains of wind waves & swells, sea-spray (whitecaps), air bubbles in the mixed layer, marine litter dynamics as well as instrumental noise to assess marine litter detection feasibility.</p><p>Marine Litter scenarios of reference shall be built based on in-situ campaigns, to reflect the true littering conditions at each case, both in spatial distribution and composition. The breadboard shall be validated over artificial targets at sea in field campaigns as relevant. This might include spectral measurements from ASD, on-field radiometers, and cameras on UAVs, concomitant with Copernicus Sentinel-2 acquisitions. Combined, they can be used to estimate atmospheric contribution and assess performance of the testes processing chain.</p><p>This activity collaborates on the ““Remote Sensing of Marine Litter and Debris” IOCCG taskforce.</p>

scholarly journals Retrieval of upper tropospheric water vapor and upper tropospheric humidity from AMSU radiances

2005 ◽  
Vol 5 (8) ◽  
pp. 2019-2028 ◽  
Author(s):  
A. Houshangpour ◽  
V. O. John ◽  
S. A. Buehler
Keyword(s):  
Water Vapor ◽  
Synthetic Data ◽  
Weighted Average ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
Data Set ◽  
Microwave Sounding Unit ◽  
Upper Tropospheric Humidity ◽  
Microwave Sounding ◽  
Average Relative Humidity

Abstract. A regression method was developed to retrieve upper tropospheric water vapor (UTWV in kg/m2) and upper tropospheric humidity (UTH in % RH) from radiances measured by the Advanced Microwave Sounding Unit (AMSU). In contrast to other UTH retrieval methods, UTH is defined as the average relative humidity between 500 and 200hPa, not as a Jacobian weighted average, which has the advantage that the UTH altitude does not depend on the atmospheric conditions. The method uses AMSU channels 6-10, 18, and 19, and should achieve an accuracy of 0.48 kg/m2 for UTWV and 6.3% RH for UTH, according to a test against an independent synthetic data set. This performance was confirmed for northern mid-latitudes by a comparison against radiosonde data from station Lindenberg in Germany, which yielded errors of 0.23 kg/m2 for UTWV and 6.1% RH for UTH.

Evaluation of Surface Temperature and Emissivity Derived from ASTER Data: A Case Study Using Ground-Based Measurements at a Volcanic Site

2010 ◽  
Vol 27 (10) ◽  
pp. 1677-1688 ◽  
Author(s):  
África Barreto ◽  
Manuel Arbelo ◽  
Pedro A. Hernández-Leal ◽  
Laia Núñez-Casillas ◽  
María Mira ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Thermal Emission ◽  
Surface Composition ◽  
Atmospheric Correction ◽  
Naval Research ◽  
Measurement Scales ◽  
Aster Data ◽  
Spectral Contrast

Abstract The land surface temperature (LST) and emissivity (LSE) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were evaluated in a low spectral contrast volcanic site at an altitude of 2000 m on the island of Tenerife, Spain. The test site is almost flat, thermally homogeneous, and without vegetation cover or variation in its surface composition. ASTER data correspond to six scenes, under both day- and nighttime conditions during 2008. This case study analyzes the impacts of the sources of inaccuracies using the temperature–emissivity separation (TES) algorithm. Uncertainties associated with inaccurate atmospheric correction were minimized by means of local soundings and the climate advantages of the area. Concurrent ground-based radiometric measurements were performed for LST, and laboratory and field measurements for LSE, to obtain reference values. The TES evaluation showed a good level of agreement in the emissivity derived for ASTER bands 13 and 14 [root-mean-square difference (RMSD) lower than 0.002] and discrepancies in ASTER bands 10 and 11 that were within the expected performance of the algorithm (±0.015). However, out-of-threshold errors were retrieved in band 12, producing an artificial increase in spectral contrast. The underestimated TES LSE spectra point to the presence of a roughness effect at measurement scales that may increase the laboratory band emissivity values. TES LST comparison with ground data showed an RMSD value of 0.5 K. ASTER standard products AST08 (LST) and AST05 (LSE) atmospherically corrected by means of Naval Research Laboratory (NRL) data were also tested, showing a similar level of performance for the TES implemented with local soundings, but failed in high-humidity atmospheric conditions.

scholarly journals Detection of secondary eclipses of WASP-10b and Qatar-1b in the Ks band and the correlation between Ks-band temperature and stellar activity.

2016 ◽  
Vol 12 (S328) ◽  
pp. 363-370
Author(s):  
Patricia Cruz ◽  
David Barrado ◽  
Jorge Lillo-Box ◽  
Marcos Diaz ◽  
Mercedes López-Morales ◽  
...  
Keyword(s):  
Light Curve ◽  
Brightness Temperature ◽  
Thermal Emission ◽  
Activity Index ◽  
Principal Component ◽  
Brightness Temperatures ◽  
A Value ◽  
Orbital Configuration ◽  
Systematic Effects ◽  
Calar Alto

AbstractThe Calar Alto Secondary Eclipse study was a program dedicated to observe secondary eclipses in the near-IR of two known close-orbiting exoplanets around K-dwarfs: WASP-10b and Qatar-1b. Such observations reveal hints on the orbital configuration of the system and on the thermal emission of the exoplanet, which allows the study of the brightness temperature of its atmosphere. The observations were performed at the Calar Alto Observatory (Spain). We used the OMEGA2000 instrument (Ks band) at the 3.5m telescope. The data was acquired with the telescope strongly defocused. The differential light curve was corrected from systematic effects using the Principal Component Analysis (PCA) technique. The final light curve was fitted using an occultation model to find the eclipse depth and a possible phase shift by performing a MCMC analysis. The observations have revealed a secondary eclipse of WASP-10b with depth of 0.137%, and a depth of 0.196% for Qatar-1b. The observed phase offset from expected mid-eclipse was of −0.0028 for WASP-10b, and of −0.0079 for Qatar-1b. These measured offsets led to a value for |ecosω| of 0.0044 for the WASP-10b system, leading to a derived eccentricity which was too small to be of any significance. For Qatar-1b, we have derived a |ecosω| of 0.0123, however, this last result needs to be confirmed with more data. The estimated Ks-band brightness temperatures are of 1647 K and 1885 K for WASP-10b and Qatar-1b, respectively. We also found an empirical correlation between the (R′HK) activity index of planet hosts and the Ks-band brightness temperature of exoplanets, considering a small number of systems.

scholarly journals Non-thermal electrons and stellar radio emission

1989 ◽  
Vol 104 (2) ◽  
pp. 37-40
Author(s):  
S. M. White ◽  
M. R. Kundu
Keyword(s):  
Radio Emission ◽  
Brightness Temperature ◽  
Solar Radio ◽  
Thermal Emission ◽  
The Sun ◽  
Apparent Brightness ◽  
Flare Stars ◽  
Apparent Brightness Temperature

AbstractRadio emission from dMe flare stars has both a flaring and a quiescent component. When we compare stellar radio emission with the Sun, however, we find that the apparent brightness temperature of the quiescent component often exceeds the temperature of non-thermal solar radio flares, and so it is likely that stellar quiescent emission also comes from non-thermal electrons. The duration of stellar quiescent emission is much longer than solar non-thermal emission. Obvious questions to ask are, what is the source of the non-thermal electrons, where do they reside, and how can non-thermal emission last so long? Here we briefly review the observations of quiescent emission, argue that the emitting regions are small, show that such small regions can still account for the observed fluxes, and discuss the source of electrons.

scholarly journals Global 15-Meter Mosaic Derived from Simulated True-Color ASTER Imagery

2019 ◽  
Vol 11 (4) ◽  
pp. 441 ◽  
Author(s):  
Louis Gonzalez ◽  
Valérie Vallet ◽  
Hirokazu Yamamoto
Keyword(s):  
Thermal Emission ◽  
Atmospheric Conditions ◽  
Image Libraries ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Fine Structures ◽  
Level 1 ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
True Color ◽  
Blue Reflectance

This work proposes a new methodology to build an Earth-wide mosaic using high-spatial resolution ( 15 m ) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in pseudo-true color. As ASTER originally misses a blue visible band, we have designed a cloud of artificial neural networks to estimate the ASTER blue reflectance from Level-1 data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same satellite Terra platform. Next, the granules are radiometrically harmonized with a novel color-balancing method and seamlessly blended into a mosaic. We demonstrate that the proposed algorithms are robust enough to process several thousands of scenes acquired under very different temporal, spatial, and atmospheric conditions. Furthermore, the created mosaic fully preserves the ASTER fine structures across the various building steps. The proposed methodology and protocol are modular so that they can easily be adapted to similar sensors with enormous image libraries.

scholarly journals O uso de Imagens do Sensor Aster no Mapeamento de Unidades Vulcano- Sedimentares do Platô da Ramada, Vila Nova do Sul, RS

2006 ◽  
Vol 33 (1) ◽  
pp. 23
Author(s):  
JUSSARA ALVES PINHEIRO SOMMER ◽  
EVANDRO FERNANDES DE LIMA ◽  
DEJANIRA LUDERITZ SALDANHA ◽  
CARLOS AUGUSTO SOMMER ◽  
RONALDO PIEROSAN
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Thermal Emission ◽  
Volcanic Rocks ◽  
Sedimentary Rocks ◽  
Principal Component ◽  
Alkaline Magmatism ◽  
Common Information ◽  
Spectral Contrast

The remote sensing products which are generated by orbitals sensors of middle spatial and spectral resolution and the development of new technique of digital image processing has been a auxiliary tool in the basic geological surveys. In this work was utilized images obtained from the ASTER sensor (Advanced Spaceborne Thermal Emission and Reflection Radiometer) to identify the lithologies in the Ramada Plateau area, situated closed to Vila Nova do Sul town, in the southernmost Brazil, giving emphasis to the volcanic sequence of the plateau and the encase sedimentary rocks unit. The volcanic unit represent a important part of the Neoproterozoic alkaline magmatism in the Sul-rio-grandense Shield and is interpreted as one of the volcanic cycles of the post-collisional period of Brasiliano Cycle in the southern Brazil. The selective principal component analysis technique was used in the digital image processing, because it provided the best results enhancing the existent spectral differences of the studied lithologies. In this processing were utilized only two spectral bands to reduce the data dimensionality, permitting a better interpretation of them. The first generated image (PC1) concentrate the common information of the two bands (albedo and topographic shading), while PC2 image present the differential information of the scene, representing the spectral contrast of the two original bands. From this technique was generated a color composite image from the PC’s2 images of the pair of bands 4-5 (R), 3-4 (G) and 8-9 (B). This image has shown the spectral differences between volcanic rocks of the Ramada Plateau and the sedimentary rocks of the Maricá Group and its individualization in two sub-units, mainly considering the concentration of rhyolitic dykes and sills in the north of the area. In this study was identify too in the southwestern portion of the Ramada Plateau, a dioritic intrusive body.

scholarly journals Retrieval of upper tropospheric water Retrieval of upper tropospheric water Retrieval of upper tropospheric water

2005 ◽  
Vol 5 (2) ◽  
pp. 1551-1584
Author(s):  
A. Houshangpour ◽  
V. O. John ◽  
S. A. Buehler
Keyword(s):  
Synthetic Data ◽  
Weighted Average ◽  
Regression Method ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
Data Set ◽  
Microwave Sounding Unit ◽  
Upper Tropospheric Humidity ◽  
Microwave Sounding ◽  
Average Relative Humidity

Abstract. A regression method was developed to retrieve upper tropospheric water vapor (UTWV in kg/m2) and upper tropospheric humidity (UTH in %RH) from radiances measured by the Advanced Microwave Sounding Unit (AMSU). In contrast to other UTH retrieval methods, UTH is defined as the average relative humidity between 500 and 200 hPa, not as a Jacobian weighted average, which has the advantage that the UTH altitude does not depend on the atmospheric conditions. The method uses AMSU channels 6–10, 18, and 19, and should achieve an accuracy of 0.48 kg/m2 for UTWV and 6.3%RH for UTH, according to a test against an independent synthetic data set. This performance was confirmed for northern mid-latitudes by a comparison against radiosonde data from station Lindenberg in Germany, which yielded errors of 0.23 kg/m2 for UTWV and 6.1%RH for UTH.

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