Journal articles on the topic 'Radiance image simulator'
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Gouvello, Alix de, Laurent Soulier, and Antoine Dupret. "From the radiance reflected by a scene to a digital picture : a compact model based simulator for image sensor design." Electronic Imaging 2020, no. 7 (January 26, 2020): 329–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.7.iss-329.
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In order to explore the design space of a new, potentially unconventional, sensor or to optimize sensor characteristics for a given computer vision application, an image acquisition process simulator has been designed. Its aim is to be simple and modular, yet complete and accurate enough to match the physical phenomena involved. The approach has been described in this paper to highlight the different steps of the acquisition process and to explain the implementation choices and the hypotheses that were made. The simulator has been tested on images of point sources, on simulated test patterns and on real high definition pictures and has proven realistic.
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Zahidi, Usman A., Peter W. T. Yuen, Jonathan Piper, and Peter S. Godfree. "An End-to-End Hyperspectral Scene Simulator with Alternate Adjacency Effect Models and Its Comparison with CameoSim." Remote Sensing 12, no. 1 (December 24, 2019): 74. http://dx.doi.org/10.3390/rs12010074.
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In this research, we developed a new rendering-based end to end Hyperspectral scene simulator CHIMES (Cranfield Hyperspectral Image Modelling and Evaluation System), which generates nadir images of passively illuminated 3-D outdoor scenes in Visible, Near Infrared (NIR) and Short-Wave Infrared (SWIR) regions, ranging from 360 nm to 2520 nm. MODTRAN TM (MODerate resolution TRANsmission), is used to generate the sky-dome environment map which includes sun and sky radiance along with the polarisation effect of the sky due to Rayleigh scattering. Moreover, we perform path tracing and implement ray interaction with medium and volumetric backscattering at rendering time to model the adjacency effect. We propose two variants of adjacency models, the first one incorporates a single spectral albedo as the averaged background of the scene, this model is called the Background One-Spectra Adjacency Effect Model (BOAEM), which is a CameoSim like model created for performance comparison. The second model calculates background albedo from a pixel’s neighbourhood, whose size depends on the air volume between sensor and target, and differential air density up to sensor altitude. Average background reflectance of all neighbourhood pixel is computed at rendering time for estimating the total upwelled scattered radiance, by volumetric scattering. This model is termed the Texture-Spectra Incorporated Adjacency Effect Model (TIAEM). Moreover, for estimating the underlying atmospheric condition MODTRAN is run with varying aerosol optical thickness and its total ground reflected radiance (TGRR) is compared with TGRR of known in-scene material. The Goodness of fit is evaluated in each iteration, and MODTRAN’s output with the best fit is selected. We perform a tri-modal validation of simulators on a real hyperspectral scene by varying atmospheric condition, terrain surface models and proposed variants of adjacency models. We compared results of our model with Lockheed Martin’s well-established scene simulator CameoSim and acquired Ground Truth (GT) by Hyspex cameras. In clear-sky conditions, both models of CHIMES and CameoSim are in close agreement, however, in searched overcast conditions CHIMES BOAEM is shown to perform better than CameoSim in terms of ℓ 1 -norm error of the whole scene with respect to GT. TIAEM produces better radiance shape and covariance of background statistics with respect to Ground Truth (GT), which is key to good target detection performance. We also report that the results of CameoSim have a many-fold higher error for the same scene when the flat surface terrain is replaced with a Digital Elevation Model (DEM) based rugged one.
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Román, R., M. Antón, A. Cazorla, A. de Miguel, F. J. Olmo, J. Bilbao, and L. Alados-Arboledas. "Calibration of an all-sky camera for obtaining sky radiance at three wavelengths." Atmospheric Measurement Techniques Discussions 5, no. 1 (February 23, 2012): 1873–905. http://dx.doi.org/10.5194/amtd-5-1873-2012.
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Abstract. This paper proposes a method to obtain spectral sky radiances, at three wavelengths (464, 534 and 626 nm), from hemispherical sky images. Images are registered with an All-Sky Imager installed at the Andalusian Center for Environmental Research (CEAMA) in Granada (Spain). The methodology followed in this work for the absolute calibration in radiance of this instrument is based on the comparison of its output measurements with modelled sky radiances derived from the Libradtran/UVSPEC radiative transfer code under cloud-free conditions. Previously, in order to check the goodness of the simulated radiances, these are compared with experimental values recorded by a CIMEL sunphotometer. In general, modelled radiances are in agreement with experimental data, showing mean differences lower than 15% except for the pixels located next to the sun position that show larger errors. The comparison between the output signal of the All-Sky Imager and the modelled sky radiances provides a calibration matrix for each image. The variability of the matrix coefficients is analyzed, showing no significant changes along a period of 5 months. Therefore, a unique calibration matrix per channel is obtained for all selected images (a total of 705 images per channel). Camera radiances are compared with CIMEL radiances, finding mean absolute differences between 2% and 15% except for pixels near to the Sun and high zenith angles. We apply these calibration matrices to three images in order to study the sky radiance distributions for three different sky conditions: cloudless, overcast and partially cloudy. Horizon brightening under cloudless conditions has been observed together with the enhancement effect of individual clouds on sky radiance.
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Román, R., M. Antón, A. Cazorla, A. de Miguel, F. J. Olmo, J. Bilbao, and L. Alados-Arboledas. "Calibration of an all-sky camera for obtaining sky radiance at three wavelengths." Atmospheric Measurement Techniques 5, no. 8 (August 21, 2012): 2013–24. http://dx.doi.org/10.5194/amt-5-2013-2012.
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Abstract. This paper proposes a method to obtain spectral sky radiances, at three wavelengths (464, 534 and 626 nm), from hemispherical sky images. Images are registered with the All-Sky Imager installed at the Andalusian Center for Environmental Research (CEAMA) in Granada (Spain). The methodology followed in this work for the absolute calibration in radiance of this instrument is based on the comparison of its output measurements with modelled sky radiances derived from the LibRadtran/UVSPEC radiative transfer code under cloud-free conditions. Previously, in order to check the goodness of the simulated radiances, these are compared with experimental values recorded by a CIMEL sunphotometer. In general, modelled radiances are in agreement with experimental data, showing mean differences lower than 20% except for the pixels located next to the Sun position that show larger errors. The relationship between the output signal of the All-Sky Imager and the modelled sky radiances provides a calibration matrix for each image. The variability of the matrix coefficients is analyzed, showing no significant changes along a period of 5 months. Therefore, a unique calibration matrix per channel is obtained for all selected images (a total of 705 images per channel). Camera radiances are compared with CIMEL radiances, finding mean absolute differences between 2% and 15% except for pixels near to the Sun and high scattering angles. We apply these calibration matrices to three images in order to study the sky radiance distributions for three different sky conditions: cloudless, overcast and partially cloudy. Horizon brightening under cloudless conditions has been observed together with the enhancement effect of individual clouds on sky radiance.
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Ионова, Е. А., and Н. Ю. Давидюк. "Исследование фокусирующих свойств концентратора фотоэлектрического модуля в расширенном температурном диапазоне." Журнал технической физики 93, no. 1 (2023): 122. http://dx.doi.org/10.21883/jtf.2023.01.54071.160-22.
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Abstract: In the current work properties of a solar radiance concentrator with Fresnel lens made of Elastosil RT604 silicon made by Wacker have been investigated. The dependence of concentrator focal distance on temperature has been determined. Impact of variation of temperature-dependent concentrator focusing properties on the magnitude of short current of photovoltaic submodule has been determined by direct measurements using solar simulator. Using formalized model of modules based on the studied concentrator and solar cells with three and six p-n junctions dimensions of a solar image in a wavelength range corresponding to an absorption profile of individual p-n junctions has been calculated for the temperature range 10-60 C. It has been concluded that in the case of three p-n junctions the minimum size of solar image at focal plane was 4.7 mm with the distance between the concentrator and solar cell being equal to 106.25 mm, and in the case of six p-n junctions, the minimum size was 4.8 mm with the distance between concentrator and solar cell being equal to 106.5 mm.
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Antuña-Sánchez, Juan C., Roberto Román, Victoria E. Cachorro, Carlos Toledano, César López, Ramiro González, David Mateos, Abel Calle, and Ángel M. de Frutos. "Relative sky radiance from multi-exposure all-sky camera images." Atmospheric Measurement Techniques 14, no. 3 (March 22, 2021): 2201–17. http://dx.doi.org/10.5194/amt-14-2201-2021.
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Abstract. All-sky cameras are frequently used to detect cloud cover; however, this work explores the use of these instruments for the more complex purpose of extracting relative sky radiances. An all-sky camera (SONA202-NF model) with three colour filters narrower than usual for this kind of cameras is configured to capture raw images at seven exposure times. A detailed camera characterization of the black level, readout noise, hot pixels and linear response is carried out. A methodology is proposed to obtain a linear high dynamic range (HDR) image and its uncertainty, which represents the relative sky radiance (in arbitrary units) maps at three effective wavelengths. The relative sky radiances are extracted from these maps and normalized by dividing every radiance of one channel by the sum of all radiances at this channel. Then, the normalized radiances are compared with the sky radiance measured at different sky points by a sun and sky photometer belonging to the Aerosol Robotic Network (AERONET). The camera radiances correlate with photometer ones except for scattering angles below 10∘, which is probably due to some light reflections on the fisheye lens and camera dome. Camera and photometer wavelengths are not coincident; hence, camera radiances are also compared with sky radiances simulated by a radiative transfer model at the same camera effective wavelengths. This comparison reveals an uncertainty on the normalized camera radiances of about 3.3 %, 4.3 % and 5.3 % for 467, 536 and 605 nm, respectively, if specific quality criteria are applied.
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Clerbaux, N., S. Dewitte, C. Bertrand, D. Caprion, B. De Paepe, L. Gonzalez, A. Ipe, and J. E. Russell. "Unfiltering of the Geostationary Earth Radiation Budget (GERB) Data. Part II: Longwave Radiation." Journal of Atmospheric and Oceanic Technology 25, no. 7 (July 1, 2008): 1106–17. http://dx.doi.org/10.1175/2008jtecha1002.1.
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Abstract The method used to estimate the unfiltered longwave broadband radiance from the filtered radiances measured by the Geostationary Earth Radiation Budget (GERB) instrument is presented. This unfiltering method is used to generate the first released edition of the GERB-2 dataset. This method involves a set of regressions between the unfiltering factor (i.e., the ratio of the unfiltered and filtered broadband radiances) and the narrowband observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. The regressions are theoretically derived from a large database of simulated spectral radiance curves obtained by radiative transfer computations. The generation of this database is fully described. Different sources of error that may affect the GERB unfiltering have been identified and the associated error magnitudes are assessed on the database. For most of the earth–atmosphere conditions, the error introduced during the unfiltering processes is well under 0.5% (RMS error of about 0.1%). For more confidence, the unfiltered radiances of GERB-2 are validated by cross comparison with collocated and coangular Clouds and the Earth’s Radiant Energy System (CERES) observations. The agreement between the unfiltered radiances is within the science goals (1% accuracy for GERB and 0.5% for CERES) for the Flight Model 2 (FM2). For the CERES Flight Model 3 (FM3) instrument, an overall difference of 1.8% is observed. The intercomparisons indicate some scene-type dependency, which is due to the unfiltering for the cloudy scenes. This should be corrected for subsequent editions of the database.
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Clerbaux, N., S. Dewitte, C. Bertrand, D. Caprion, B. De Paepe, L. Gonzalez, A. Ipe, J. E. Russell, and H. Brindley. "Unfiltering of the Geostationary Earth Radiation Budget (GERB) Data. Part I: Shortwave Radiation." Journal of Atmospheric and Oceanic Technology 25, no. 7 (July 1, 2008): 1087–105. http://dx.doi.org/10.1175/2007jtecha1001.1.
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Abstract The method used to estimate the unfiltered shortwave broadband radiance from the filtered radiances measured by the Geostationary Earth Radiation Budget (GERB) instrument is presented. This unfiltering method is used to generate the first released edition of the GERB-2 dataset. The method involves a set of regressions between the unfiltering factor (i.e., the ratio of the unfiltered and filtered broadband radiances) and the narrowband observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. The regressions are theoretically derived from a large database of simulated spectral radiance curves obtained by radiative transfer computations. The generation of the database is fully described. Different sources of error that may affect the GERB unfiltering have been identified and the associated error magnitudes are assessed on this database. For most of the earth–atmosphere conditions, the error introduced during the unfiltering process is below 1%. In some conditions (e.g., low sun elevation above the horizon) the error can present a higher relative value, but the absolute error value remains well under the accuracy goal of 1% of the full instrument scale (2.4 W m−2 sr−1). To increase the confidence level, the edition 1 unfiltered radiances of GERB-2 are validated by cross comparison with collocated and coangular Clouds and the Earth’s Radiant Energy System (CERES) observations for different scene types. In addition to an overall offset between the two instruments, the intercomparisons indicate a scene-type dependency up to 4% in unfiltered radiance. Further studies are required to confirm the cause, but an insufficiently accurate characterization of the shortwave spectral response of the GERB instrument in the visible part of the spectrum is one area under further investigation.
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Dandini, Paolo, Céline Cornet, Renaud Binet, Laetitia Fenouil, Vadim Holodovsky, Yoav Y. Schechner, Didier Ricard, and Daniel Rosenfeld. "3D cloud envelope and cloud development velocity from simulated CLOUD (C3IEL) stereo images." Atmospheric Measurement Techniques 15, no. 20 (October 27, 2022): 6221–42. http://dx.doi.org/10.5194/amt-15-6221-2022.
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Abstract. A method to derive the 3D cloud envelope and the cloud development velocity from high spatial and temporal resolution satellite imagery is presented. The CLOUD instrument of the recently proposed C3IEL mission lends itself well to observing at high spatial and temporal resolutions the development of convective cells. Space-borne visible cameras simultaneously image, under multiple view angles, the same surface domain every 20 s over a time interval of 200 s. In this paper, we present a method for retrieving cloud development velocity from simulated multi-angular, high-resolution top of the atmosphere (TOA) radiance cloud fields. The latter are obtained via the image renderer Mitsuba for a cumulus case generated via the atmospheric research model SAM and via the radiative transfer model 3DMCPOL, coupled with the outputs of an orbit, attitude, and camera simulator for a deep convective cloud case generated via the atmospheric research model Meso-NH. Matching cloud features are found between simulations via block matching. Image coordinates of tie points are mapped to spatial coordinates via 3D stereo reconstruction of the external cloud envelope for each acquisition. The accuracy of the retrieval of cloud topography is quantified in terms of RMSE and bias that are, respectively, less than 25 and 5 m for the horizontal components and less than 40 and 25 m for the vertical components. The inter-acquisition 3D velocity is then derived for each pair of tie points separated by 20 s. An independent method based on minimising the RMSE for a continuous horizontal shift of the cloud top, issued from the atmospheric research model, allows for the obtainment of a ground estimate of the velocity from two consecutive acquisitions. The mean values of the distributions of the stereo and ground velocities exhibit small biases. The width of the distributions is significantly different, with higher a distribution width for the stereo-retrieved velocity. An alternative way to derive an average velocity over 200 s, which relies on tracking clusters of points via image feature matching over several acquisitions, was also implemented and tested. For each cluster of points, mean stereo and ground positions were derived every 20 s over 200 s. The mean stereo and ground velocities, obtained as the slope of the line of best fit to the mean positions, are in good agreement.
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Wang, Yuye, Guofeng Zhang, and Xiaoguang Hu. "Large-scale scene real-time infrared simulation based on texture blending." International Journal of Intelligent Computing and Cybernetics 9, no. 4 (November 14, 2016): 406–15. http://dx.doi.org/10.1108/ijicc-07-2016-0024.
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Purpose Infrared simulation plays an important role in small and affordable unmanned aerial vehicles. Its key and main goal is to get the infrared image of a specific target. Infrared physical model is established through a theoretical research, thus the temperature field is available. Then infrared image of a specific target can be simulated properly while taking atmosphere state and effect of infrared imaging system into account. For recent years, some research has been done in this field. Among them, the infrared simulation for large scale is still a key problem to be solved. In this passage, a method of classification based on texture blending is proposed and this method effectively solves the problem of classification of large number of images and increase the frame rate of large infrared scene rendering. The paper aims to discuss these issues. Design/methodology/approach Mosart Atmospheric Tool (MAT) is used first to calculate data of sun radiance, skyshine radiance, path radiance, temperatures of different material which is an offline process. Then, shader in OGRE does final calculation to get simulation result and keeps a high frame rate. Considering this, the authors convert data in MAT file into textures which can be easily handled by shader. In shader responding, radiance can be indexed by information of material, vertex normal, eye and sun. Adding the effect of infrared imaging system, the final radiance distribution is obtained. At last, the authors get infrared scene by converting radiance to grayscale. Findings In the fragment shader, fake infrared textures are used to look up temperature which can calculate radiance of itself and related radiance. Research limitations/implications The radiance is transferred into grayscale image while considering effect of infrared imaging system. Originality/value Simulation results show that a high frame rate can be reached while guaranteeing the fidelity.
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Chami, Malik, Morgane Larnicol, Audrey Minghelli, and Sebastien Migeon. "Influence of the Suspended Particulate Matter on the Satellite Radiance in the Sunglint Observation Geometry in Coastal Waters." Remote Sensing 12, no. 9 (May 2, 2020): 1445. http://dx.doi.org/10.3390/rs12091445.
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The analysis of satellite ocean color data that are acquired over coastal waters is highly relevant to gain understanding of the functioning of these complex ecosystems. In particular, the estimation of the suspended particulate matter (SPM) concentrations is of great interest for monitoring the coastal dynamics. However, a high number of pixels of satellite images could be affected by the surface-reflected solar radiation, so-called the sunglint. These pixels are either removed from the data processing, which results in a loss of information about the ocean optical properties, or they are subject to the application of glint correction techniques that may contribute to increase the uncertainties in the SPM retrieval. The objective of this study is to demonstrate the high potential of exploiting satellite observations acquired in the sunglint viewing geometry for determining the water leaving radiance for SPM dominated coastal waters. For that purpose, the contribution of the water leaving radiance Lw to the satellite signal LTOA is quantified for the sunglint observation geometry using forward radiative transfer modelling. Some input parameters of the model were defined using in-situ bio-optical measurements performed in various coastal waters to make the simulations consistent with real-world observations. The results showed that the sunglint radiance is not sufficiently strong to mask the influence of the oceanic radiance at the satellite level, which oceanic radiance remains significant (e.g., 40% at 560 nm for a SPM concentration value of 9 g m−3). The influence of the sunglint radiance is even weaker for highly turbid waters and/or for strong wind conditions. In addition, the maximum radiance simulated in the sunglint region for highly turbid waters remains lower than the saturation radiances specified for the current ocean color sensors. The retrieval of Lw and SPM should thus be feasible from radiances measured in the sunglint pattern by satellite sensors, thus increasing the number of exploitable pixels within a satellite image. The results obtained here could be used as a basis for the development of inverse ocean color algorithms that would interestingly use the radiance measured in sunglint observation geometry as it has been done for other topics than the field of ocean color research.
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Lyu, Zheng, Krithin Kripakaran, Max Furth, Eric Tang, Brian Wandell, and Joyce Farrell. "Validation of image systems simulation technology using a Cornell Box." Electronic Imaging 2021, no. 7 (January 18, 2021): 122–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.7.iss-122.
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We describe and experimentally validate an end-to-end simulation of a digital camera. The simulation models the spectral radiance of 3D-scenes, formation of the spectral irradiance by multi-element optics, and conversion of the irradiance to digital values by the image sensor. We quantify the accuracy of the simulation by comparing real and simulated images of a precisely constructed, three-dimensional high dynamic range test scene. Validated end-to-end software simulation of a digital camera can accelerate innovation by reducing many of the time-consuming and expensive steps in designing, building and evaluating image systems.
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Govaerts, Yves, Frank Rüthrich, Viju John, and Ralf Quast. "Climate Data Records from Meteosat First Generation Part I: Simulation of Accurate Top-of-Atmosphere Spectral Radiance over Pseudo-Invariant Calibration Sites for the Retrieval of the In-Flight Visible Spectral Response." Remote Sensing 10, no. 12 (December 5, 2018): 1959. http://dx.doi.org/10.3390/rs10121959.
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Meteosat First-Generation satellites have acquired more than 30 years of observations that could potentially be used for the generation of a Climate Data Record. The availability of harmonized and accurate a Fundamental Climate Data Record is a prerequisite to such generation. Meteosat Visible and Infrared Imager radiometers suffer from inaccurate pre-launch spectral function characterization and spectral ageing constitutes a serious limitation to achieve such prerequisite. A new method was developed for the retrieval of the pre-launch instrument spectral function and its ageing. This recovery method relies on accurately simulated top-of-atmosphere spectral radiances matching observed digital count values. This paper describes how these spectral radiances are simulated over pseudo-invariant targets such as open ocean, deep convective clouds and bright desert surface. The radiative properties of these targets are described with a limited number of parameters of known uncertainty. Typically, a single top-of-atmosphere radiance spectrum can be simulated with an estimated uncertainty of about 5%. The independent evaluation of the simulated radiance accuracy is also addressed in this paper. It includes two aspects: the comparison with narrow-band well-calibrated radiometers and a spectral consistency analysis using SEVIRI/HRVIS band on board Meteosat Second Generation which was accurately characterized pre-launch. On average, the accuracy of these simulated spectral radiances is estimated to be about ±2%.
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Liu, Li, Xing Fa Gu, Tao Yu, Xiao Ying Li, Jia Guo Li, Hai Liang Gao, and Yuan Sun. "Static Target Identification Based on the Simulation of Thermal Infrared Image." Advanced Materials Research 505 (April 2012): 299–304. http://dx.doi.org/10.4028/www.scientific.net/amr.505.299.
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Based on the principle of the simulation of the infrared thermal image, the static aircraft in the background of cement surface, at 2:00, 11:00, 14:00, are simulated under the remote sensors with spatial resolution of 5m and 10m. The evaluation is based on the radiance of target and the background extracted from the simulation image. The results indicate that the method in this paper can reflect the difference of radiance between the static target and the background which is useful in the target identification.
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Okamoto, Kozo, and John C. Derber. "Assimilation of SSM/I Radiances in the NCEP Global Data Assimilation System." Monthly Weather Review 134, no. 9 (September 1, 2006): 2612–31. http://dx.doi.org/10.1175/mwr3205.1.
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Abstract A technique for the assimilation of Special Sensor Microwave Imager (SSM/I) data in the National Centers for Environmental Prediction (NCEP) global data assimilation and forecast system is described. Because the radiative transfer model used does not yet allow for cloud/rain effects, it is crucial to properly identify and exclude (or correct) cloud/rain-contaminated radiances using quality control (QC) and bias correction procedures. The assimilation technique is unique in that both procedures take into account the effect of the liquid cloud on the difference between observed and simulated brightness temperature for each SSM/I channel. The estimate of the total column cloud liquid water from observed radiances is used in a frequency-dependent cloud detection component of the QC and as a predictor in the bias correction algorithm. Also, a microwave emissivity Jacobian model with respect to wind speed is developed for oceanic radiances. It was found that the surface wind information in the radiance data can be extracted through the emissivity model Jacobian rather than producing and including a separate SSM/I wind speed retrieval. A two-month-long data assimilation experiment from July to August 2004 using NCEP’s Gridpoint Statistical Interpolation analysis system and the NCEP operational forecast model was performed. In general, the assimilation of SSM/I radiance has a significant positive impact on the analyses and forecasts. Moisture is added in the Northern Hemisphere and Tropics and is slightly reduced in the Southern Hemisphere. The moisture added appears to be slightly excessive in the Tropics verified against rawinsonde observations. Nevertheless, the assimilation of SSM/I radiance data reduces model spinup of precipitation and substantially improves the dynamic fields, especially in measures of the vector wind error at 200 hPa in the Tropics. In terms of hurricane tracks, SSM/I radiance assimilation produces more cases with smaller errors and reduces the average error. No disruption of the Hadley circulation is found from the introduction of the SSM/I radiance data.
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Ding, Shouguo, Ping Yang, Bryan A. Baum, Andrew Heidinger, and Thomas Greenwald. "Development of a GOES-R Advanced Baseline Imager Solar Channel Radiance Simulator for Ice Clouds." Journal of Applied Meteorology and Climatology 52, no. 4 (April 2013): 872–88. http://dx.doi.org/10.1175/jamc-d-12-0180.1.
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AbstractThis paper describes the development of an ice cloud radiance simulator for the anticipated Geostationary Operational Environmental Satellite R (GOES-R) Advanced Baseline Imager (ABI) solar channels. The simulator is based on the discrete ordinates radiative transfer (DISORT) model. A set of correlated k-distribution (CKD) models is developed for the ABI solar channels to account for atmospheric trace gas absorption. The CKD models are based on the ABI spectral response functions and also consider when multiple gases have overlapping absorption. The related errors of the transmittance profile are estimated on the basis of the exact line-by-line results, and it is found that errors in transmittance are less than 0.2% for all but one of the ABI solar channels. The exception is for the 1.378-μm channel, centered near a strong water vapor absorption band, for which the errors are less than 2%. For ice clouds, the band-averaged bulk-scattering properties for each ABI [and corresponding Moderate Resolution Imaging Spectroradiometer (MODIS)] solar channel are derived using an updated single-scattering property database of both smooth and severely roughened ice particles, which include droxtals, hexagonal plates, hexagonal hollow and solid columns, three-dimensional hollow and solid bullet rosettes, and several types of aggregates. The comparison shows close agreement between the radiance simulator and the benchmark model, the line-by-line radiative transfer model (LBLRTM)+DISORT model. The radiances of the ABI and corresponding MODIS measurements are compared. The results show that the radiance differences between the ABI and MODIS channels under ice cloud conditions are likely due to the different band-averaged imaginary indices of refraction.
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Ma, Zaizhong, Eric S. Maddy, Banglin Zhang, Tong Zhu, and Sid Ahmed Boukabara. "Impact Assessment of Himawari-8 AHI Data Assimilation in NCEP GDAS/GFS with GSI." Journal of Atmospheric and Oceanic Technology 34, no. 4 (April 2017): 797–815. http://dx.doi.org/10.1175/jtech-d-16-0136.1.
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AbstractAs the first of the next-generation geostationary meteorological satellites, Himawari-8 was successfully launched in October 2014 by the Japan Meteorological Agency (JMA) and placed over the western Pacific Ocean domain at 140.7°E. It carries the Advanced Himawari Imager (AHI), which provides full-disk images of Earth at 16 bands in the visible and infrared domains every 10 min. Efforts are currently ongoing at the National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite, Data, and Information Service (NESDIS)/Center for Satellite Applications and Research (STAR) to assimilate Himawari-8 AHI radiance measurements into the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation analysis system (GSI). All software development within the GSI to allow for assimilation of Himawari-8 AHI radiance has been completed.This study reports on the assessment of AHI preassimilation data quality by comparing observed clear-sky ocean-only radiances to those simulated using collocated ECMWF analysis, as well as describing procedures implemented for quality control. The impact of the AHI data assimilation on the resulting analyses and forecasts is then assessed using the NCEP Global Forecast System (GFS). A preliminary assessment of the assimilation of AHI data from infrared water vapor channels and atmospheric motion vectors (AMVs) on top of the current global observing system shows neutral to marginal positive impact on analysis and forecast skill relative to an assimilation without AHI data. The main positive impact occurs for short- to medium-range forecasts of global upper-tropospheric water vapor. The results demonstrate the feasibility of direct assimilation of AHI radiances and highlight how humidity information can be extracted within the assimilation system.
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Bu, Fan, Canyu Wang, Xiaoyuan Ren, Dou Sun, Zhan Wang, and Zhuang Wang. "3D Reconstruction Method of Space Target on Optical Images with Wide Baseline via Neural Radiance Field." Journal of Physics: Conference Series 2347, no. 1 (September 1, 2022): 012019. http://dx.doi.org/10.1088/1742-6596/2347/1/012019.
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Abstract 3D reconstruction of space targets using optical measurement data is an important topic in the field of space surveillance and spacecraft service in orbit. The core of current mainstream 3D reconstruction methods is to establish feature association between optical images. In space-based optical imaging scenes, the texture of target region is missing and the range of view is large, which causes great difficulties in feature extraction and matching of image sequences. Neural radiance field technology does not need to extract explicit features, and its implicit expression of 3D scenes has great potential for solving reconstruction problems in weak texture and broad baseline cases. Therefore, a novel 3D reconstruction method for a sequence of images based on neural radiance field is proposed. The proposed method breaks through the limitation of traditional 3D reconstruction methods which rely on rich texture and narrow baseline image sequences. Simulation experiments show that compared with the existing methods for space target images with weak texture and wide baseline, our method performs better in terms of accuracy and completeness.
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Qiu, Xianfei, Huijie Zhao, Guorui Jia, and Jiyuan Li. "Atmosphere and Terrain Coupling Simulation Framework for High-Resolution Visible-Thermal Spectral Imaging over Heterogeneous Land Surface." Remote Sensing 14, no. 9 (April 24, 2022): 2043. http://dx.doi.org/10.3390/rs14092043.
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Realistic modeling of high-resolution earth radiation signals in the visible-thermal spectral domain remains difficult, due to the complex radiation interdependence induced by the heterogeneous and rugged features of land surface. To find the trade-off between accuracy and efficiency for image simulation, this paper established a unified simulation framework for the entire visible-thermal spectral domain, based on the energy balance between solar-reflected and thermal radiation components over rugged surfaces. Considering the joint contributions of atmospheric and topographic adjacency effects, three spatial–spectral convolution kernels were uniformly designed to quantify the topographic irradiance, the trapping effect, and the atmospheric adjacency effect. Radiation signal simulation was implemented in three forms: land surface temperature (LST), bottom of atmosphere (BOA) radiance, and top of atmosphere (TOA) radiance. The accuracy was validated with onboard data from China’s Gaofen-5 visual and infrared multispectral sensor (VIMS) over rugged desert. The simulation results demonstrate that the root mean square of relative deviations between the simulated and onboard TOA radiance are related to terrain, as 3–17% and 6–38% for the summer and winter scene, respectively. The evaluation of radiance components indicates the utility of the simulation framework to quantify the uncertainty associated with atmosphere and terrain coupling effects, in the sensor design and operation stages.
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Han, Hyojin, Jun Li, Mitch Goldberg, Pei Wang, Jinlong Li, Zhenglong Li, B. J. Sohn, and Juan Li. "Microwave Sounder Cloud Detection Using a Collocated High-Resolution Imager and Its Impact on Radiance Assimilation in Tropical Cyclone Forecasts." Monthly Weather Review 144, no. 10 (October 2016): 3937–59. http://dx.doi.org/10.1175/mwr-d-15-0300.1.
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Accurate cloud detection is one of the most important factors in satellite data assimilation due to the uncertainties associated with cloud properties and their impacts on satellite-simulated radiances. To enhance the accuracy of cloud detection and improve radiance assimilation for tropical cyclone (TC) forecasts, measurements from the Advanced Microwave Sounding Unit-A (AMSU-A) on board the Aqua satellite and the Advanced Technology Microwave Sounder (ATMS) are collocated with high spatial resolution cloud products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua and the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi-National Polar-Orbiting Partnership (Suomi-NPP) satellite. The cloud-screened microwave radiance measurements are assimilated for Hurricane Sandy (2012) and Typhoon Haiyan (2013) forecasts using the Weather Research and Forecasting (WRF) Model and the three-dimensional variational (3DVAR)-based Gridpoint Statistical Interpolation (GSI) data assimilation system. Experiments are carried out to determine the optimal thresholds of cloud fraction (CF) for minimizing track and intensity forecast errors. The results indicate that the use of high spatial resolution cloud products can improve the accuracy of TC forecasts by better eliminating cloud-contaminated microwave sounder field-of-views (FOVs). In conclusion, the combination of advanced microwave sounders and collocated high spatial resolution imagers is able to improve the radiance assimilation and TC forecasts. The methodology used in this study can be applied to process data from other pairs of microwave sounders and imagers on board the same platform.
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Quast, Ralf, Ralf Giering, Yves Govaerts, Frank Rüthrich, and Rob Roebeling. "Climate Data Records from Meteosat First Generation Part II: Retrieval of the In-Flight Visible Spectral Response." Remote Sensing 11, no. 5 (February 26, 2019): 480. http://dx.doi.org/10.3390/rs11050480.
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How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question is the key to developing Climate Data Records from the Meteosat Visible and Infrared Imager on board the Meteosat First Generation (MFG) of geostationary satellites, which acquired Earth radiance images in the Visible (VIS) broad band from 1977 to 2017. This article presents a new metrologically sound method for retrieving the VIS spectral response from matchups of pseudo-invariant calibration site (PICS) pixels with datasets of simulated top-of-atmosphere spectral radiance used as reference. Calibration sites include bright desert, open ocean and deep convective cloud targets. The absolute instrument spectral response function is decomposed into generalised Bernstein basis polynomials and a degradation function that is based on plain physical considerations and able to represent typical chromatic ageing characteristics. Retrieval uncertainties are specified in terms of an error covariance matrix, which is projected from model parameter space into the spectral response function domain and range. The retrieval method considers target type-specific biases due to errors in, e.g., the selection of PICS target pixels and the spectral radiance simulation explicitly. It has been tested with artificial and well-comprehended observational data from the Spinning Enhanced Visible and Infrared Imager on-board Meteosat Second Generation and has retrieved meaningful results for all MFG satellites apart from Meteosat-1, which was not available for analysis.
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Guzzi, Donatella, Vanni Nardino, Cinzia Lastri, and Valentina Raimondi. "A Fast Iterative Procedure for Adjacency Effects Correction on Remote Sensed Data." Remote Sensing 13, no. 9 (May 5, 2021): 1799. http://dx.doi.org/10.3390/rs13091799.
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This paper describes a simple, iterative atmospheric correction procedure based on the MODTRAN®5 radiative transfer code. Such a procedure receives in input a spectrally resolved at-sensor radiance image, evaluates the different contributions to received radiation, and corrects the effect of adjacency from surrounding pixels permitting the retrieval of ground reflectance spectrum for each pixel of the image. The procedure output is a spectral ground reflectance image obtained without the need of any user-provided a priori hypothesis. The novelty of the proposed method relies on its iterative approach for evaluating the contribution of surrounding pixels: a first run of the atmospheric correction procedure is performed by assuming that the spectral reflectance of the surrounding pixels is equal to that of the pixel under investigation. Such information is used in the subsequent iteration steps to estimate the spectral radiance of the surrounding pixels, in order to make a more accurate evaluation of the reflectance image. The results are here presented and discussed for two different cases: synthetic images produced with the hyperspectral simulation tool PRIMUS and real images acquired by CHRIS–PROBA sensor. The retrieved reflectance error drops after a few iterations, providing a quantitative estimate for the number of iterations needed. Relative error after the procedure converges is in the order of few percent, and the causes of remaining uncertainty in retrieved spectra are discussed.
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Ehrlich, A., E. Bierwirth, M. Wendisch, A. Herber, and J. F. Gayet. "Airborne hyperspectral surface and cloud bi-directional reflectivity observations in the Arctic using a commercial, digital camera." Atmospheric Chemistry and Physics Discussions 11, no. 9 (September 1, 2011): 24591–629. http://dx.doi.org/10.5194/acpd-11-24591-2011.
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Abstract. Spectral radiance measurements by a digital single-lens reflex camera were used to derive the bi-directional reflectivity of clouds and different surfaces in the Arctic. The camera has been calibrated radiometrically and spectrally to provide accurate radiance measurements with high angular resolution. A comparison with spectral radiance measurements with the SMART-Albedometer showed an agreement within the uncertainties of both instruments. The bi-directional reflectivity in terms of the hemispherical directional reflectance factor HDRF was obtained for sea ice, ice free ocean and clouds. The sea ice, with an albedo of ρ = 0.96, showed an almost isotropic HDRF, while sun glint was observed for the ocean HDRF (ρ = 0.12). For the cloud observations with ρ = 0.62, the fog bow – a backscatter feature typically for scattering by liquid water droplets – was covered by the camera. For measurements above a heterogeneous stratocumulus clouds, the required number of images to obtain a mean HDRF which clearly exhibits the fog bow has been estimated with about 50 images (10 min flight time). A representation of the HDRF as function of the scattering angle only reduces the image number to about 10 (2 min flight time). The measured cloud and ocean HDRF have been compared to radiative transfer simulations. The ocean HDRF simulated with the observed surface wind speed of 9 m s−1 agreed best with the measurements. For the cloud HDRF, the best agreement was obtained by a broad and weak fog bow simulated with a cloud droplet effective radius of Reff = 4 μm. This value agrees with the particle sizes from in situ measurements and retrieved from the spectral radiance of the SMART-Albedometer.
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Sulub, Yusuf, and Gary W. Small. "Simulated Radiance Profiles for Automating the Interpretation of Airborne Passive Multi-Spectral Infrared Images." Applied Spectroscopy 62, no. 10 (October 2008): 1049–59. http://dx.doi.org/10.1366/000370208786049150.
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Methodology is developed for simulating the radiance profiles acquired from airborne passive multispectral infrared imaging measurements of ground sources of volatile organic compounds (VOCs). The simulation model allows the superposition of pure-component laboratory spectra of VOCs onto spectral backgrounds that simulate those acquired during field measurements conducted with a downward-looking infrared line scanner mounted on an aircraft flying at an altitude of 2000–3000 ft (approximately 600–900 m). Wavelength selectivity in the line scanner is accomplished through the use of a multichannel Hg:Cd:Te detector with up to 16 integrated optical filters. These filters allow the detection of absorption and emission signatures of VOCs superimposed on the upwelling infrared background radiance within the instrumental field of view (FOV). By combining simulated radiance profiles containing analyte signatures with field-collected background signatures, supervised pattern recognition methods can be employed to train automated classifiers for use in detecting the signatures of VOCs during field measurements. The targeted application for this methodology is the use of the imaging system to detect releases of VOCs during emergency response scenarios. In the work described here, the simulation model is combined with piecewise linear discriminant analysis to build automated classifiers for detecting ethanol and methanol. Field data collected during controlled releases of ethanol, as well as during a methanol release from an industrial facility, are used to evaluate the methodology.
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Ehrlich, A., E. Bierwirth, M. Wendisch, A. Herber, and J. F. Gayet. "Airborne hyperspectral observations of surface and cloud directional reflectivity using a commercial digital camera." Atmospheric Chemistry and Physics 12, no. 7 (April 11, 2012): 3493–510. http://dx.doi.org/10.5194/acp-12-3493-2012.
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Abstract. Spectral radiance measurements by a digital single-lens reflex camera were used to derive the directional reflectivity of clouds and different surfaces in the Arctic. The camera has been calibrated radiometrically and spectrally to provide accurate radiance measurements with high angular resolution. A comparison with spectral radiance measurements with the Spectral Modular Airborne Radiation measurement sysTem (SMART-Albedometer) showed an agreement within the uncertainties of both instruments (6% for both). The directional reflectivity in terms of the hemispherical directional reflectance factor (HDRF) was obtained for sea ice, ice-free ocean and clouds. The sea ice, with an albedo of ρ = 0.96 (at 530 nm wavelength), showed an almost isotropic HDRF, while sun glint was observed for the ocean HDRF (ρ = 0.12). For the cloud observations with ρ = 0.62, the cloudbow – a backscatter feature typically for scattering by liquid water droplets – was covered by the camera. For measurements above heterogeneous stratocumulus clouds, the required number of images to obtain a mean HDRF that clearly exhibits the cloudbow has been estimated at about 50 images (10 min flight time). A representation of the HDRF as a function of the scattering angle only reduces the image number to about 10 (2 min flight time). The measured cloud and ocean HDRF have been compared to radiative transfer simulations. The ocean HDRF simulated with the observed surface wind speed of 9 m s−1 agreed best with the measurements. For the cloud HDRF, the best agreement was obtained by a broad and weak cloudbow simulated with a cloud droplet effective radius of Reff = 4 μm. This value agrees with the particle sizes derived from in situ measurements and retrieved from the spectral radiance of the SMART-Albedometer.
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Li, Jun, W. Paul Menzel, Wenjian Zhang, Fengying Sun, Timothy J. Schmit, James J. Gurka, and Elisabeth Weisz. "Synergistic Use of MODIS and AIRS in a Variational Retrieval of Cloud Parameters." Journal of Applied Meteorology 43, no. 11 (November 1, 2004): 1619–34. http://dx.doi.org/10.1175/jam2166.1.
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Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable global monitoring of the distribution of clouds. MODIS is able to provide a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size, and cloud optical thickness at high spatial resolution (1–5 km). The combined MODIS–AIRS system offers the opportunity for improved cloud products, better than from either system alone; this improvement is demonstrated in this paper with both simulated and real radiances. A one-dimensional variational (1DVAR) methodology is used to retrieve the CTP and ECA from AIRS longwave (650–790 cm−1 or 15.38–12.65 μm) cloudy radiance measurements (hereinafter referred to as MODIS–AIRS 1DVAR). The MODIS–AIRS 1DVAR cloud properties show significant improvement over the MODIS-alone cloud properties and slight improvement over AIRS-alone cloud properties in a simulation study, while MODIS–AIRS 1DVAR is much more computationally efficient than the AIRS-alone 1DVAR; comparisons with radiosonde observations show that CTPs improve by 10–40 hPa for MODIS–AIRS CTPs over those from MODIS alone. The 1DVAR approach is applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS and Geostationary Operational Environmental Satellite sounder cloud products. Data from ground-based instrumentation at the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in Oklahoma are used for validation; results show that MODIS–AIRS improves the MODIS CTP, especially in low-level clouds. The operational use of a high-spatial-resolution imager, along with information from a high-spectral-resolution sounder will be possible with instruments planned for the next-generation geostationary operational instruments.
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Ye, Xin, Huazhong Ren, Pengxin Wang, Zhongqiu Sun, and Jian Zhu. "Mid-Infrared Emissivity Retrieval from Nighttime Sentinel-3 SLSTR Images Combining Split-window Algorithms and the Radiance Transfer Method." International Journal of Environmental Research and Public Health 20, no. 1 (December 20, 2022): 37. http://dx.doi.org/10.3390/ijerph20010037.
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Land surface emissivity is a key parameter that affects energy exchange and represents the spectral characteristics of land cover. Large-scale mid-infrared (MIR) emissivity can be efficiently obtained using remote sensing technology, but current methods mainly rely on prior knowledge and multi-temporal or multi-angle remote sensing images, and additional errors may be introduced due to the uncertainty of external data such as atmospheric profiles and the inconsistency of multiple source data in spatial resolution, observation time, and other information. In this paper, a new practical method was proposed which can retrieve MIR emissivity with only a single image input by combining the radiance properties of TIR and MIR channels and the spatial information of remote sensing images based on the Sentinel-3 Sea and land surface temperature radiometer (SLSTR) data. Two split-window (SW) algorithms that use TIR channels only and MIR and TIR channels to retrieve land surface temperature (LST) were developed separately, and the initial values of MIR emissivity were obtained from the known LST and TIR emissivity. Under the assumption that the atmospheric conditions in the local area are constant, the radiance transfer equations for adjacent pixels are iterated to optimize the initial values to obtain stable estimation results. The experimental results based on the simulation dataset and real SLSTR images showed that the proposed method can achieve accurate MIR emissivity results. In future work, factors such as angular effects, solar radiance, and the influence of atmospheric water vapor will be further considered to improve performance.
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Patel, P., H. Bhatt, and A. K. Shukla. "Absolute Vicarious Calibration of recently launched Indian Meteorological Satellite: INSAT-3D imager." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 291–98. http://dx.doi.org/10.5194/isprsarchives-xl-8-291-2014.
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Looking towards the advancements and popularity of remote sensing and an ever increasing need for the development of a variety of new and complex satellite sensors, it has become even more essential to continually upgrade the ability to provide absolute calibration of sensors. This article describes a simple procedure to implement post-launch calibration for VIS and SWIR channels of INSAT-3D imager over land site (Little Rann of Kutch (ROK), Gujarat) on three different days to account for characterization errors or undetermined post-launch changes in spectral response of the sensor. The measurements of field reflectance of study site (of extent ~6 km x 6 km) in the wavelength range 325–2500 nm, along with atmospheric parameters (Aerosol Optical Depth, Total Columnar Ozone, Water Vapor) and sensor spectral response functions, were input to the 6S radiative transfer model to simulate radiance at top of the atmosphere (TOA) for VIS and SWIR bands. The uncertainty in vicarious calibration coefficients due to measured spatial variability of field reflectance along with due to aerosol types were also computed for the INSAT-3D imager. The effect of surface anisotropy on TOA radiance was studied using a MODIS Bidirectional Reflectance Distribution Function (BRDF) product covering the experimental site. The results show that there is no indication of change in calibration coefficients in INSAT- 3D imager, for VIS and SWIR band over Little ROK. Comparison made between the INSAT-3D imager measured radiance and 6S simulated radiance. Analysis shows that for clear sky days, the INSAT-3D imager overestimates TOA radiance in the VIS band by 5.1 % and in the SWIR band by 11.7 % with respect to 6S simulated radiance. For these bands, in the inverse mode, the 6S corrected surface reflectance was closer to field surface reflectance. It was found that site spatial variability was a critical factor in estimating change in sensor calibration coefficients and influencing uncertainty in TOA radiance for Little ROK.
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Qin, Luyao, Yaodeng Chen, Tianlei Yu, Gang Ma, Yang Guo, and Peng Zhang. "Dynamic Channel Selection of Microwave Temperature Sounding Channels under Cloudy Conditions." Remote Sensing 12, no. 3 (January 27, 2020): 403. http://dx.doi.org/10.3390/rs12030403.
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To make better use of microwave radiance observations for data assimilation, removal of radiances contaminated by hydrometeor particles is one of the most important steps. Generally, all observations below the middle troposphere are eliminated before the analysis when precipitation is present. However, the altitude of the cloud top varies; when the weighting function peak height of a channel is higher than the altitude of the cloud top, observations are not affected by the absorption or scattering of cloud particles. Thus, the radiative transfer calculation can be performed under a clear sky scenario. In this paper, a dynamic channel selection (DCS) method was developed to determine the radiance observations unaffected by clouds under cloudy conditions in assimilation. First, the sensitivity of cloud liquid water (CLW) profiles to radiance from the microwave temperature sounding frequencies was analyzed. It was found that the impact of CLW on transmittance can be neglected where the cloud top height is below the weighting function peak height. Second, three lookup tables were devised through analysis of the impact of cloud fraction and cloud top height on radiance, which is the basis of the DCS method. The unified cloud top height of the Microwave Temperature Sounder (MWTS)-2 fields of view (FOVs) can be calculated by remapping the cloud mask and cloud top height data from the Medium Resolution Spectral Imager-2 (MERSI-2). Observations from various channels may be removed or retained based on real-time dynamic unified cloud top height data. Twelve-hour and long-term time-series brightness temperature simulation experiments both showed that an increase in the amount of observations used for data assimilation of more than 300% can be achieved by application of DCS, but this had no effect on the amount of error. Through DCS, areas of strong precipitation can be accurately identified and removed, and more observations above cloud top height can be included in the data assimilation. The application of DCS to data assimilation will greatly improve the data utilization rate, and therefore allow for more accurate characterization of upper atmospheric circulation.
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Minamide, Masashi, Fuqing Zhang, and Eugene E. Clothiaux. "Nonlinear Forecast Error Growth of Rapidly Intensifying Hurricane Harvey (2017) Examined through Convection-Permitting Ensemble Assimilation of GOES-16 All-Sky Radiances." Journal of the Atmospheric Sciences 77, no. 12 (December 2020): 4277–96. http://dx.doi.org/10.1175/jas-d-19-0279.1.
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AbstractThe dynamics and predictability of the rapid intensification (RI) of Hurricane Harvey (2017) were examined using convection-permitting initialization, analysis, and prediction from a cycling ensemble Kalman filter (EnKF) that assimilated all-sky infrared radiances from the Advanced Baseline Imager on GOES-16. The EnKF analyses were able to evolve the various scales of the radiance fields associated with Harvey close to those observed, including those associated with scattered individual convective cells before the onset of rapid intensification (RI) and the organized vortex-scale convective system during and after RI. This was true for more than 3 days of a continuous assimilation cycling. Deterministic forecasts initialized from the EnKF analyses captured the rapidly deepening intensity of Harvey more than 24 h prior to its onset. To explore the predictability of Harvey’s intensity during RI, ensemble probabilistic forecasts and sensitivity analyses were conducted. It was found that significant ensemble spread growth was induced by initial perturbations individually in either the wind or moisture fields. The nonlinear interactions between wind and moisture perturbations further limited the predictability of the intensification process of Harvey by increasing the uncertainty in the simulated wind and moisture distributions and modifying the convective activity and its feedback on vortex flow. This study highlights both the importance of better initializing the dynamic and moisture state variables simultaneously and the potential contribution of satellite all-sky radiance assimilation on constraining them and their associated convective activity that impacts RI of tropical cyclones.
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Gkaintatzi-Masouti, M., J. van Duijnhoven, and M. P. J. Aarts. "Review of spectral lighting simulation tools for non-image- forming effects of light." Journal of Physics: Conference Series 2042, no. 1 (November 1, 2021): 012122. http://dx.doi.org/10.1088/1742-6596/2042/1/012122.
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Abstract Light via our eyes influences visual performance, visual comfort and visual experience, but also affects several health related, non-image-forming (NIF) responses. New metrics have been developed to quantify the NIF effects of light. In order to incorporate these in lighting design practice, simulation tools are required that are able to process information about the spectral distribution of light sources and materials. However, most of the tools currently used for daylight and electric light simulations simplify the spectrum into RGB (Red, Green, Blue) colour values. This paper presents an overview of the currently used programs for simulating the NIF effects of light in building design and discusses the possibility of using existing spectral rendering software as an alternative. A review of literature shows that mostly Radiance or Radiance-based programs have been used so far, but new user-friendly tools could employ existing spectral rendering tools. As the NIF effects of light gain greater importance in lighting design, new simulation workflows are needed. This paper aims to support the development of future workflows by presenting the current state-of-the-art.
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Mejia, Felipe A., Ben Kurtz, Keenan Murray, Laura M. Hinkelman, Manajit Sengupta, Yu Xie, and Jan Kleissl. "Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth." Atmospheric Measurement Techniques 9, no. 8 (August 30, 2016): 4151–65. http://dx.doi.org/10.5194/amt-9-4151-2016.
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Abstract. A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red–blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red–blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλτc, θ0, ϑs, ϑz, and RBRτc, θ0, ϑs, ϑz are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeasϑs, ϑz, in addition to RBRmeasϑs, ϑz, to obtain a unique solution for τc. The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003) method for overcast skies. τc values ranged from 0 to 80 with values over 80, being capped and registered as 80. A τc RMSE of 2.5 between the Min et al. (2003) method and the USI are observed. The MWR and USI have an RMSE of 2.2, which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms.
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Kirk, R. L., D. P. Mayer, C. M. Dundas, B. H. Wheeler, R. A. Beyer, and O. Alexandrov. "COMPARISON OF DIGITAL TERRAIN MODELS FROM TWO PHOTOCLINOMETRY METHODS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 1059–67. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-1059-2022.
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Abstract. We evaluate the horizontal resolution and vertical precision for digital topographic models (DTMs) of the Moon derived from image radiance information, a process known as photoclinometry (PC) or shape-from-shading (SfS). We use the implementations in two available planetary image processing software systems, single image PC in the U.S. Geological Survey Integrated Software for Imagers and Spectrometers (ISIS) system, and multi-image SfS in the Ames Stereo Pipeline (ASP), and test results obtained with and without use of a starting solution from stereo, with single and multiple images, and for varying illumination conditions. To obtain the higher quality reference DTMs against which the products can be evaluated, we derived DTMs by stereoanalysis of Lunar Reconnaissance Orbiter Narrow-Angle Camera (LROC NAC) images at their native pixel spacing of ∼0.5 m, then produced a 16-m/post stereo DTM from images downsampled to 4 m/pixel and refined it with images at 16 m/pixel. When used with a single image, both algorithms improved resolution (by a factor of 1.4 for PC and 2.4 for SfS compared to stereo). An albedo map produced in ISIS by ratioing the image to a simulation based on the stereo DTM was well correlated with one output by SfS. The albedo correction was crucial for PC with ∼60° incidence but not at ∼80°. DTMs produced by PC and SfS without a starting stereo DTM had larger errors but good detail, and could be useful for many applications. In SfS, it was necessary to increase smoothing to get a usable DTM when the weighting on an a priori DTM was reduced. Multi-image SfS including modeling of spatially varying albedo reduced vertical errors by factors of 1.5 or more compared to single-image SfS.
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Modenini, Dario, Alfredo Locarini, and Marco Zannoni. "Attitude Sensor from Ellipsoid Observations: A Numerical and Experimental Validation." Sensors 20, no. 2 (January 13, 2020): 433. http://dx.doi.org/10.3390/s20020433.
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The preliminary design and validation of a novel, high accuracy horizon-sensor for small satellites is presented, which is based on the theory of attitude determination from ellipsoid observations. The concept consists of a multi-head infrared sensor capturing images of the Earth limb. By fitting an ellipse to the imaged limb arcs, and exploiting some analytical results available from projective geometry, a closed form solution for computing the attitude matrix is provided. The algorithm is developed in a dimensionless framework, requiring the knowledge of the shape of the imaged target, but not of its size. As a result, the solution is less sensitive to the limb shift caused by the atmospheric own radiance. To evaluate the performance of the proposed method, a numerical simulator is developed, which generates images captured in low Earth orbit, including also the presence of the atmosphere. In addition, experimental validation is provided due to a dedicated testbed, making use of a miniature infrared camera. Results show that our sensor concept returns rms errors of few hundredths of a degree or less in determining the local nadir direction.
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Bae, Taewuk, Youngchoon Kim, and Sangho Ahn. "IR-Band Conversion of Target and Background Using Surface Temperature Estimation and Error Compensation for Military IR Sensor Simulation." Sensors 19, no. 11 (May 29, 2019): 2455. http://dx.doi.org/10.3390/s19112455.
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Military infrared (IR) imaging systems utilize one or more IR wavelength-bands, among short wavelength IR (SWIR), middle wavelength IR (MWIR), and long wavelength IR (LWIR) band. The IR image wavelength-band conversion which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image is needed for IR signature modeling and image synthesis in the IR systems. However, the IR wavelength-band conversion is very challenging because absorptivity and transmittance of objects and background (atmosphere) are different according to the IR wavelength band and because radiation and reflectance characteristics of the SWIR are very different from the LWIR and MWIR. Therefore, the IR wavelength-band conversion in this paper applies to only IR targets and monotonous backgrounds at a long distance for military purposes. This paper proposes an IR wavelength-band conversion method which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image by using the surface temperature estimation of an object and the error attenuation method for the estimated temperature. The surface temperature of the object is estimated by an approximated Planck’s radiation equation and the error of estimated temperature is corrected by using the slope information of exact radiance along with the approximated one. The corrected surface temperature is used for generating another IR wavelength-band image. The verification of the proposed method is demonstrated through the simulations using actual IR images obtained by thermal equipment.
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Bassani, Cristiana, and Sindy Sterckx. "Calibration of Satellite Low Radiance by AERONET-OC Products and 6SV Model." Remote Sensing 13, no. 4 (February 20, 2021): 781. http://dx.doi.org/10.3390/rs13040781.
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For water quality monitoring using satellite data, it is often required to optimize the low radiance signal through the application of radiometric gains. This work describes a procedure for the retrieval of radiometric gains to be applied to OLI/L8 and MSI/S2A data over coastal waters. The gains are defined by the ratio of the top of atmosphere (TOA) reflectance simulated using the Second Simulation of a Satellite Signal in the Solar Spectrum—vector (6SV) radiative transfer model, REF, and the TOA reflectance acquired by the sensor, MEAS, over AERONET-OC stations. The REF is simulated considering quasi-synchronous atmospheric and aquatic AERONET-OC products and the image acquisition geometry. Both for OLI/L8 and MSI/S2A the measured TOA reflectance was higher than the modeled signal in almost all bands resulting in radiometric gains less than 1. The use of retrieved gains showed an improvement of reflectance remote sensing, Rrs, when with ACOLITE atmospheric correction software. When the gains are applied an accuracy improvement of the Rrs in the 400–700 nm domain was observed except for the first blue band of both sensors. Furthermore, the developed procedure is quick, user-friendly, and easily transferable to other optical sensors.
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Mejia, F. A., B. Kurtz, K. Murray, L. M. Hinkelman, M. Sengupta, Y. Xie, and J. Kleissl. "Coupling sky images with three-dimensional radiative transfer models: a new method to estimate cloud optical depth." Atmospheric Measurement Techniques Discussions 8, no. 10 (October 30, 2015): 11285–321. http://dx.doi.org/10.5194/amtd-8-11285-2015.
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Abstract. A method for retrieving cloud optical depth (τc) using a ground-based sky imager (USI) is presented. The Radiance Red-Blue Ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a 3-D Radiative Transfer Model (3DRTM). From these images the basic parameters affecting the radiance and RBR of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλ(τc, θ0, ϑs, ϑz) and the red-blue ratio, RBR(τc, θ0, ϑs, ϑz) are retrieved from the 3DRTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeas(ϑs, ϑz), in addition to RBRmeas(ϑs, ϑz) to obtain a unique solution for τc. The RRBR method is applied to images taken by a USI at the Oklahoma Atmospheric Radiation Measurement program (ARM) site over the course of 220 days and validated against measurements from a microwave radiometer (MWR); output from the Min method for overcast skies, and τc retrieved by Beer's law from direct normal irradiance (DNI) measurements. A τc RMSE of 5.6 between the Min method and the USI are observed. The MWR and USI have an RMSE of 2.3 which is well within the uncertainty of the MWR. An RMSE of 0.95 between the USI and DNI retrieved τc is observed. The procedure developed here provides a foundation to test and develop other cloud detection algorithms.
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Hayatbini, Negin, Kuo-lin Hsu, Soroosh Sorooshian, Yunji Zhang, and Fuqing Zhang. "Effective Cloud Detection and Segmentation Using a Gradient-Based Algorithm for Satellite Imagery: Application to Improve PERSIANN-CCS." Journal of Hydrometeorology 20, no. 5 (May 1, 2019): 901–13. http://dx.doi.org/10.1175/jhm-d-18-0197.1.
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Abstract The effective identification of clouds and monitoring of their evolution are important toward more accurate quantitative precipitation estimation and forecast. In this study, a new gradient-based cloud-image segmentation algorithm is developed using image processing techniques. This method integrates morphological image gradient magnitudes to separate cloud systems and patches boundaries. A varying scale kernel is implemented to reduce the sensitivity of image segmentation to noise and to capture objects with various finenesses of the edges in remote sensing images. The proposed method is flexible and extendable from single to multispectral imagery. Case studies were carried out to validate the algorithm by applying the proposed segmentation algorithm to synthetic radiances for channels of the Geostationary Operational Environmental Satellite (GOES-16) simulated by a high-resolution weather prediction model. The proposed method compares favorably with the existing cloud-patch-based segmentation technique implemented in the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall retrieval algorithm. Evaluation of event-based images indicates that the proposed algorithm has potentials comparing to the conventional segmentation technique used in PERSIANN-CCS to improve rain detection and estimation skills with an accuracy rate of up to 98% in identifying cloud regions.
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Schüller, Lothar, Ralf Bennartz, Jürgen Fischer, and Jean-Louis Brenguier. "An Algorithm for the Retrieval of Droplet Number Concentration and Geometrical Thickness of Stratiform Marine Boundary Layer Clouds Applied to MODIS Radiometric Observations." Journal of Applied Meteorology 44, no. 1 (January 1, 2005): 28–38. http://dx.doi.org/10.1175/jam-2185.1.
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Abstract Algorithms are now currently used for the retrieval of cloud optical thickness and droplet effective radius from multispectral radiance measurements. This paper extends their application to the retrieval of cloud droplet number concentration, cloud geometrical thickness, and liquid water path in shallow convective clouds, using an algorithm that was previously tested with airborne measurements of cloud radiances and validated against in situ measurements of the same clouds. The retrieval is based on a stratified cloud model of liquid water content and droplet spectrum. Radiance measurements in visible and near-infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is operated from the NASA platforms Terra and Aqua, are analyzed. Because of uncertainties in the simulation of the continental surface reflectance, the algorithm is presently limited to the monitoring of the microphysical structure of boundary layer clouds over the ocean. Two MODIS scenes of extended cloud fields over the North Atlantic Ocean trade wind region are processed. A transport and dispersion model (the Hybrid Single-Particle Lagrangian Integrated Trajectory Model, HYSPLIT4) is also used to characterize the origin of the air masses and hence their aerosol regimes. One cloud field formed in an air mass that was advected from southern Europe and North Africa. It shows high values of the droplet concentration when compared with the second cloud system, which developed in a more pristine environment. The more pristine case also exhibits a higher geometrical thickness and, thus, liquid water path, which counterbalances the expected cloud albedo increase of the polluted case. Estimates of cloud liquid water path are then compared with retrievals from the Special Sensor Microwave Imager (SSM/I). SSM/I-derived liquid water paths are in good agreement with the MODIS-derived values.
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Geer, Alan J., Peter Bauer, and Christopher W. O’Dell. "A Revised Cloud Overlap Scheme for Fast Microwave Radiative Transfer in Rain and Cloud." Journal of Applied Meteorology and Climatology 48, no. 11 (November 1, 2009): 2257–70. http://dx.doi.org/10.1175/2009jamc2170.1.
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Abstract The assimilation of cloud- and precipitation-affected observations into weather forecasting systems requires very fast calculations of radiative transfer in the presence of multiple scattering. At the European Centre for Medium-Range Weather Forecasts (ECMWF), performance limitations mean that only a single cloudy calculation (including any precipitation) can be made, and the simulated radiance is a weighted combination of cloudy- and clear-sky radiances. Originally, the weight given to the cloudy part was the maximum cloud fraction in the atmospheric profile. However, this weighting was excessive, and because of nonlinear radiative transfer (the “beamfilling effect”) there were biases in areas of cloud and precipitation. A new approach instead uses the profile average cloud fraction, and decreases RMS errors by 40% in areas of rain or heavy clouds when “truth” comes from multiple independent column simulations. There is improvement all the way from low (e.g., 19 GHz) to high (e.g., 183 GHz) microwave frequencies. There is also improvement when truth comes from microwave imager observations. One minor problem is that biases increase slightly in mid- and upper-tropospheric sounding channels in light-cloud situations, which shows that future improvements will require the cloud fraction to vary according to the optical properties at different frequencies.
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Murino, Loredana, Umberto Amato, Maria Francesca Carfora, Anestis Antoniadis, Bormin Huang, W. Paul Menzel, and Carmine Serio. "Cloud Detection of MODIS Multispectral Images." Journal of Atmospheric and Oceanic Technology 31, no. 2 (February 1, 2014): 347–65. http://dx.doi.org/10.1175/jtech-d-13-00088.1.
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Abstract Methods coming from statistics and pattern recognition to estimate the cloud mask from radiance measured by visible and infrared sensors on board satellites are gaining greater consideration for their ability to properly exploit the increasing number of channels available with current and next-generation sensors. Endowed with physical arguments, they give rise to robust methods for accurately estimating the cloud mask. Application of such classification methods to Moderate Resolution Imaging Spectroradiometer (MODIS) data is discussed in this paper. Three different types of MODIS datasets are considered: synthetic (radiance is simulated by proper radiative transfer models); annotated (real MODIS data labeled by a meteorologist as clear or cloudy); and real MODIS data, whose truth is obtained from the official MODIS cloud mask product. A full assessment of the MODIS spectral bands is performed, aimed at understanding the role of the spectral bands in detecting clouds and at achieving top performance with very few properly chosen spectral channels. Local methods that use spatial correlation of images to improve classification, reducing the pseudonuisance of nonlocal methods, have also been tested on real data.
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Gentile, Sabrina, Francesco Di Paola, Domenico Cimini, Donatello Gallucci, Edoardo Geraldi, Salvatore Larosa, Saverio T. Nilo, et al. "3D-VAR Data Assimilation of SEVIRI Radiances for the Prediction of Solar Irradiance in Italy Using WRF Solar Mesoscale Model—Preliminary Results." Remote Sensing 12, no. 6 (March 12, 2020): 920. http://dx.doi.org/10.3390/rs12060920.
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Solar power generation is highly fluctuating due to its dependence on atmospheric conditions. The integration of this variable resource into the energy supply system requires reliable predictions of the expected power production as a basis for management and operation strategies. This is one of the goals of the Solar Cloud project, funded by the Italian Ministry of Economic Development (MISE)—to provide detailed forecasts of solar irradiance variables to operators and organizations operating in the solar energy industry. The Institute of Methodologies for Environmental Analysis of the National Research Council (IMAA-CNR), participating to the project, implemented an operational chain that provides forecasts of all the solar irradiance variables at high temporal and horizontal resolution using the numerical weather prediction Advanced Research Weather Research and Forecasting (WRF-ARW) Solar version 3.8.1 released by the National Center for Atmospheric Research (NCAR) in August 2016. With the aim of improving the forecast of solar irradiance, the three-dimensional (3D-Var) data assimilation was tested to assimilate radiances from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) geostationary satellite into WRF Solar. To quantify the impact, the model output is compared against observational data. Hourly Global Horizontal Irradiance (GHI) is compared with ground-based observations from Regional Agency for the Protection of the Environment (ARPA) and with MSG Shortwave Solar Irradiance estimations, while WRF Solar cloud coverage is compared with Cloud Mask by MSG. A preliminary test has been performed in clear sky conditions to assess the capability of the model to reproduce the diurnal cycle of the solar irradiance. The statistical scores for clear sky conditions show a positive performance of the model with values comparable to the instrument uncertainty and a correlation of 0.995. For cloudy sky, the solar irradiance and the cloud cover are better simulated when the SEVIRI radiances are assimilated, especially in the short range of the simulation. For the cloud cover, the Mean Bias Error one hour after the assimilation time is reduced from 41.62 to 20.29 W/m2 when the assimilation is activated. Although only two case studies are considered here, the results indicate that the assimilation of SEVIRI radiance improves the performance of WRF Solar especially in the first 3 hour forecast.
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Gosal, Jaskaran Singh, Sarbesh Tiwari, Tarunesh Sharma, Mohit Agrawal, Mayank Garg, Sayani Mahal, Suryanarayanan Bhaskar, Raghavendra Kumar Sharma, Vikas Janu, and Deepak Kumar Jha. "Simulation of surgery for supratentorial gliomas in virtual reality using a 3D volume rendering technique: a poor man's neuronavigation." Neurosurgical Focus 51, no. 2 (August 2021): E23. http://dx.doi.org/10.3171/2021.5.focus21236.
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OBJECTIVE Different techniques of performing image-guided neurosurgery exist, namely, neuronavigation systems, intraoperative ultrasound, and intraoperative MRI, each with its limitations. Except for ultrasound, other methods are expensive. Three-dimensional virtual reconstruction and surgical simulation using 3D volume rendering (VR) is an economical and excellent technique for preoperative surgical planning and image-guided neurosurgery. In this article, the authors discuss several nuances of the 3D VR technique that have not yet been described. METHODS The authors included 6 patients with supratentorial gliomas who underwent surgery between January 2019 and March 2021. Preoperative clinical data, including patient demographics, preoperative planning details (done using the VR technique), and intraoperative details, including relevant photos and videos, were collected. RadiAnt software was used for generating virtual 3D images using the VR technique on a computer running Microsoft Windows. RESULTS The 3D VR technique assists in glioma surgery with a preoperative simulation of the skin incision and craniotomy, virtual cortical surface marking and navigation for deep-seated gliomas, preoperative visualization of morbid cortical surface and venous anatomy in surfacing gliomas, identifying the intervenous surgical corridor in both surfacing and deep-seated gliomas, and pre- and postoperative virtual 3D images highlighting the exact spatial geometric residual tumor location and extent of resection for low-grade gliomas (LGGs). CONCLUSIONS Image-guided neurosurgery with the 3D VR technique using RadiAnt software is an economical, easy-to-learn, and user-friendly method of simulating glioma surgery, especially in resource-constrained countries where expensive neuronavigation systems are not readily available. Apart from cortical sulci/gyri anatomy, FLAIR sequences are ideal for the 3D visualization of nonenhancing diffuse LGGs using the VR technique. In addition to cortical vessels (especially veins), contrast MRI sequences are perfect for the 3D visualization of contrast-enhancing high-grade gliomas.
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Robles-Kelly, Antonio, and Edwin R. Hancock. "Estimating the surface radiance function from single images." Graphical Models 67, no. 6 (November 2005): 518–48. http://dx.doi.org/10.1016/j.gmod.2004.12.003.
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Yao, Bin, Chao Liu, Yan Yin, Zhiquan Liu, Chunxiang Shi, Hironobu Iwabuchi, and Fuzhong Weng. "Evaluation of cloud properties from reanalyses over East Asia with a radiance-based approach." Atmospheric Measurement Techniques 13, no. 3 (March 4, 2020): 1033–49. http://dx.doi.org/10.5194/amt-13-1033-2020.
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Abstract. Extensive observational and numerical investigations have been performed to better characterize cloud properties. However, due to the large variations in cloud spatiotemporal distributions and physical properties, quantitative depictions of clouds in different atmospheric reanalysis datasets are still highly uncertain. A radiance-based evaluation approach is introduced and performed to evaluate the quality of cloud properties from reanalysis datasets. The China Meteorological Administration reanalysis (CRA); the ECMWF fifth-generation reanalysis (ERA5); and the Modern-Era Retrospective analysis for Applications, Version 2 (MERRA-2), i.e., those reanalyses providing sufficient cloud information, are considered. To avoid the influence of assumptions and uncertainties on satellite retrieval algorithms, forward radiative transfer simulations are used as a bridge to translate the reanalyses to corresponding radiances that are expected to be observed by satellites. The simulated reflectances and brightness temperatures (BTs) are directly compared with observations from the Advanced Himawari Imager onboard the Himawari-8 satellite in the East Asia region. We find that the simulated reflectances and BTs based on CRA and ERA5 are close to each other. CRA represents the total and midlayer cloud cover better than the other two datasets, and ERA5 depicts deep-convection structures more closely than CRA does. Comparisons of the simulated and observed BT differences suggest that water clouds are generally overestimated in ERA5 and MERRA-2, and MERRA-2 also overestimates the ice clouds over cyclone centers. Overall, clouds from CRA, ERA5, and MERRA-2 show their own advantages in different aspects. The ERA5 reanalysis has the best capability to represent the cloudy atmospheres over East Asia, and the CRA representations are close to those in ERA5.
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Asriana, Nova, and Dewi Rachmaniatus Syariyah. "PENGGUNAAN SIMULASI DESKTOP RADIANCE PADA KONFIGURASI BENTUK BUKAAN." Jurnal Arsitektur ARCADE 5, no. 2 (August 2, 2021): 171. http://dx.doi.org/10.31848/arcade.v5i2.629.
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Abstract: The usage of daylight in a room or building during the day is a wide strategy for illuminating the room naturally without artificial lighting services so that it can reduce the energy consumption of building. In addition, the use of daylight aims to enhance the quality of spatial visualization, vision health, environmental comfort, and increase the performance of user productivity in the room. This research will discourse about the amount of light get into room to identify how much the daylight can be useful and captured by human sight’s perception through a radiance simulation camera which will be translated into realistic images. This simulation is experimental-based that include two phases, namely the configuration of alternative openings and draws light according to the perception of user’s vision, then the set of radiance simulation based on scripting to generate the realistic images. Based on this simulation, the amount of daylight is influenced by source, quantity, position, area of openings and the building orientation or building. The amount of light intensity also affects the visual comfort of users who have activities in the room. The result of this simulation is to identify the room that generates daylight area and non-daylight area to decrease the artificial lighting.Abstrak: Pemanfaatan pencahayaan alami (daylight) pada sebuah ruangan dan bangunan di siang hari merupakan salah satu strategi desain untuk menerangi ruangan secara alami tanpa bantuan cahaya buatan sehingga dapat mengurangi konsumsi energi pada bangunan. Selain itu juga, permanfaatan pencahayaan alami (daylight) bertujuan untuk meningkatkan kualitas visual dalam ruangan, kesehatan indera penglihatan, kenyamanan lingkungan dan meningkatkan produktivitas kinerja pengguna bangunan. Pada penelitian ini akan membahas mengenai besaran cahaya yang masuk ke dalam suatu ruangan untuk melihat seberapa besar pencahayaan alami yang masuk dan ditangkap dalam suatu persepsi indera penglihatan manusia melalui kamera simulasi radiance yang diwujudkan ke dalam foto realistik. Simulasi ini dilakukan dengan metode berbasis eksperimen mandiri (experimental-based) yang terdiri dua tahap, yaitu tahapan konfigurasi bentuk bukaan dan draw light berdasarkan persepsi indera penglihatan peneliti, kemudian dilanjutkan dengan simulasi radiance berbasis scripting untuk menghasilkan foto realistik. Berdasarkan hasil simulasi ini, besarnya cahaya alami yang masuk ke dalam ruangan dipengaruhi oleh beberapa faktor, yaitu sumber bukaan, jumlah bukaan, posisi bukaan, besaran bukaan, dan orientasi ruangan atau bangunan. Besarnya intensitas cahaya yang masuk juga akan mempengaruhi kenyamanan visual bagi pengguna yang beraktivitas dalam ruangan tersebut. Hasil dari penelitian ini untuk melihat konfigurasi mana yang menghasilkan sebagian area daylight dan area non-daylight yang cukup merata untuk menghindari bantuan cahaya buatan.
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Zhao, Huijie, Bolun Cui, and Guorui Jia. "A Flight Direction Design Method for Airborne Spectral Imaging Considering the Anisotropy Reflectance of the Target in Rugged Terrain." Sensors 19, no. 12 (June 17, 2019): 2715. http://dx.doi.org/10.3390/s19122715.
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An excellent mission plan is the prerequisite for the acquisition of high quality airborne hyperspectral images which are useful for environmental research, mining etc. In order to minimize the radiance non-uniformity caused by the anisotropic reflectance of targets, the flight direction is mostly designed on the solar azimuth or 180° from it for whiskbroom and pushbroom imagers. However, the radiance to the observer is determined not only by the reflectance of the target, but also by the terrain, the illumination direction and the observation direction. So, the flight direction which is defined to minimize radiance non-uniformity might change with the terrain. In order to find the best flight direction for rugged terrain, we firstly analyze the causes of the effect of terrain on radiation non-uniformity based on the radiative transfer process. Then, the flight direction design method is proposed for composite sloping terrain. Tested by digital and physical simulation experiments, the radiance non-uniformity is minimized when the aircraft flies in the designated direction. Finally, a workflow for flight direction planning and optimizing is summarized, considering the flight mission planning techniques and the workflow of remote sensing missions.
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Zhou, Qu, Liqiao Tian, Jian Li, Qingjun Song, and Wenkai Li. "Radiometric Cross-Calibration of Tiangong-2 MWI Visible/NIR Channels over Aquatic Environments using MODIS." Remote Sensing 10, no. 11 (November 14, 2018): 1803. http://dx.doi.org/10.3390/rs10111803.
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The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.
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Nardino, Vanni, Gabriele Amato, Donatella Guzzi, Cinzia Lastri, and Valentina Raimondi. "Experimental Tests on TIR Multispectral Images for Temperature-Emissivity Separation by Using the MaxEnTES Algorithm." Proceedings 27, no. 1 (September 18, 2019): 10. http://dx.doi.org/10.3390/proceedings2019027010.
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Satellite images in the TIR are relevant for several Earth Observation applications. The retrieval of temperature and emissivity from the emitted radiance, however, requires the use of suitable algorithms, such as the MaxEnTES that uses the concept of maximum entropy to solve the Temperature-Emissivity Separation problem. Here we discuss the performance of MaxEnTES when applied to TIR images with a limited number of channels, specifically simulated HyspIRI multispectral images and real multispectral images by ASTER. The results were respectively compared with the original temperatures used for the simulations and with the temperatures obtained by using the ASTER TES algorithm.
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Greenwald, Thomas J., R. Bradley Pierce, Todd Schaack, Jason Otkin, Marek Rogal, Kaba Bah, Allen Lenzen, Jim Nelson, Jun Li, and Hung-Lung Huang. "Real-Time Simulation of the GOES-R ABI for User Readiness and Product Evaluation." Bulletin of the American Meteorological Society 97, no. 2 (February 1, 2016): 245–61. http://dx.doi.org/10.1175/bams-d-14-00007.1.
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Abstract In support of the Geostationary Operational Environmental Satellite R series (GOES-R) program, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin–Madison is generating high quality simulated Advanced Baseline Imager (ABI) radiances and derived products in real time over the continental United States. These data are mainly used for testing data-handling systems, evaluating ABI-derived products, and providing training material for forecasters participating in GOES-R Proving Ground test bed activities. The modeling system used to generate these datasets consists of advanced regional and global numerical weather prediction models in addition to state-of-the-art radiative transfer models, retrieval algorithms, and land surface datasets. The system and its generated products are evaluated for the 2014 Pacific Northwest wildfires; the 2013 Moore, Oklahoma, tornado; and Hurricane Sandy. Simulated aerosol optical depth over the Front Range of Colorado during the Pacific Northwest wildfires was validated using high-density Aerosol Robotic Network (AERONET) measurements. The aerosol, cloud, and meteorological modeling system used to generate ABI radiances was found to capture the transport of smoke from the Pacific wildfires into the Front Range of Colorado and true-color imagery created from these simulated radiances provided visualization of the smoke plumes. Evaluation of selected simulated ABI-derived products for the Moore tornado and Hurricane Sandy cases was done using real-time GOES sounder/imager products produced at CIMSS. Results show that simulated ABI moisture and atmospheric stability products, cloud products, and red–green–blue (RGB) airmass composite imagery are well suited as proxy ABI data for user preparedness.