scholarly journals An Exponential Algorithm for Bottom Reflectance Retrieval in Clear Optically Shallow Waters from Multispectral Imagery without Ground Data

2021 ◽  
Vol 13 (6) ◽  
pp. 1169
Author(s):  
Yunhan Ma ◽  
Huaguo Zhang ◽  
Xiaorun Li ◽  
Juan Wang ◽  
Wenting Cao ◽  
...  
Keyword(s):  
Large Scale ◽  
North Pacific Ocean ◽  
Oceanic Islands ◽  
Radiative Transfer Model ◽  
Shallow Waters ◽  
Benthic Habitat ◽  
Transfer Model ◽  
Landsat 8 ◽  
Exponential Relationship

Bottom reflectance is a significant parameter characterizing the bottom types for clear optically shallow waters, typically in oceanic islands and reefs. However, there is not an effective physics-based method for inverting the bottom reflectance using multispectral images. In this study, we propose a novel approach for quantitatively inverting the bottom reflectance at 550 nm without the dependence of in situ bottom reflectance data or any other priori knowledge. By linking different pixels in the same image and utilizing the strong linear relationship between their water depths and the spectral related parameters, the global situation of the radiative transfer model was constrained, and an exponential relationship between the log-transformed ratio of the blue–green band reflectance and the bottom reflectance was established. The proposed model was checked by comparing the Hydrolight input bottom reflectance with that inverted from Hydrolight simulated spectrum, resulting in correlating well. Our method has successfully performed using WorldView-2 and Landsat-8 in Midway Island in the North Pacific Ocean, with the cross- and indirectly checking and obtained reliable and robust results. In addition, we assessed the potential of the quantitative bottom reflectance in benthic classification and inversion ranges under different bottom reflectance. These results indicated that compared with those methods relying on in situ data or hyperspectral imagery, our algorithm is more likely to efficiently improve the parameterization of bottom reflectance, which can be very useful for benthic habitat mapping and transferred to large-scale regions in clean reef waters, as well as monitor time-series dynamics of oceanic bottom types to forecast coral reef bleaching.

scholarly journals DEVELOPMENT OF SCHEME FOR THE ATMOSPHERIC CORRECTION OF LANDSAT-8 OLI DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 671-674
Author(s):  
V. N. Pathak ◽  
M. R. Pandya ◽  
D. B. Shah ◽  
H. J. Trivedi
Keyword(s):  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Coefficient Of Determination ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Standard Data ◽  
Satellite Signal

<p><strong>Abstract.</strong> In the present study, a physics based method called Scheme for Atmospheric Correction of Landsat-8 (SACLS8) is developed for the Operational Land Imager (OLI) sensor of Landsat-8. The Second Simulation of the Satellite Signal in the Solar Spectrum Vector (6SV) radiative transfer model is used in the simulations to obtain the surface reflectance. The surface reflectance derived using the SACL8 scheme is validated with the <i>in-situ</i> measurements of surface reflectance carried out at the homogeneous desert site located in the Little Rann of Kutch, Gujarat, India. The results are also compared with Landsat-8 surface reflectance standard data product over the same site. The good agreement of results with high coefficient of determination (R<sup>2</sup><span class="thinspace"></span>><span class="thinspace"></span>0.94) and low root mean square error (of the order of 0.03) with <i>in-situ</i> measurement values as well as those obtained from the Landsat-8 surface reflectance data establishes a good performance of the SACLS8 scheme for the atmospheric correction of Landsat-8 dataset.</p>

scholarly journals Level 2 processing for the imaging Fourier transform spectrometer GLORIA: derivation and validation of temperature and trace gas volume mixing ratios from calibrated dynamics mode spectra

2015 ◽  
Vol 8 (6) ◽  
pp. 2473-2489 ◽  
Author(s):  
J. Ungermann ◽  
J. Blank ◽  
M. Dick ◽  
A. Ebersoldt ◽  
F. Friedl-Vallon ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Horizontal Resolution ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ionization Mass ◽  
Fourier Transform Spectrometer ◽  
Upper Troposphere ◽  
Mixing Ratios

Abstract. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an airborne infrared limb imager combining a two-dimensional infrared detector with a Fourier transform spectrometer. It was operated aboard the new German Gulfstream G550 High Altitude LOng Range (HALO) research aircraft during the Transport And Composition in the upper Troposphere/lowermost Stratosphere (TACTS) and Earth System Model Validation (ESMVAL) campaigns in summer 2012. This paper describes the retrieval of temperature and trace gas (H2O, O3, HNO3) volume mixing ratios from GLORIA dynamics mode spectra that are spectrally sampled every 0.625 cm−1. A total of 26 integrated spectral windows are employed in a joint fit to retrieve seven targets using consecutively a fast and an accurate tabulated radiative transfer model. Typical diagnostic quantities are provided including effects of uncertainties in the calibration and horizontal resolution along the line of sight. Simultaneous in situ observations by the Basic Halo Measurement and Sensor System (BAHAMAS), the Fast In-situ Stratospheric Hygrometer (FISH), an ozone detector named Fairo, and the Atmospheric chemical Ionization Mass Spectrometer (AIMS) allow a validation of retrieved values for three flights in the upper troposphere/lowermost stratosphere region spanning polar and sub-tropical latitudes. A high correlation is achieved between the remote sensing and the in situ trace gas data, and discrepancies can to a large extent be attributed to differences in the probed air masses caused by different sampling characteristics of the instruments. This 1-D processing of GLORIA dynamics mode spectra provides the basis for future tomographic inversions from circular and linear flight paths to better understand selected dynamical processes of the upper troposphere and lowermost stratosphere.

scholarly journals SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1532 ◽  
Author(s):  
Guido Masiello ◽  
Carmine Serio ◽  
Sara Venafra ◽  
Laurent Poutier ◽  
Frank-M. Göttsche
Keyword(s):  
Radiative Transfer ◽  
Real Time ◽  
Forward Model ◽  
Radiative Transfer Model ◽  
Computational Time ◽  
Transfer Model ◽  
Real Time Processing ◽  
In Situ Observations ◽  
Infrared Radiances

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

scholarly journals Large-scale validation of SCIAMACHY reflectance in the ultraviolet

2005 ◽  
Vol 5 (2) ◽  
pp. 1771-1796 ◽  
Author(s):  
G. van Soest ◽  
L. G. Tilstra ◽  
P. Stammes
Keyword(s):  
Radiative Transfer ◽  
Validation Study ◽  
Large Scale ◽  
Scale Validation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Time Level ◽  
Standard Calibration ◽  
Level 1 ◽  
Reflectance Data

Abstract. In this paper we present an extensive validation of calibrated SCIAMACHY nadir reflectance in the UV (240–400 nm) by comparison with spectra calculated with a fast radiative transfer model. We use operationally delivered near-real-time level 1 data, processed with 5 standard calibration tools. A total of 9 months of data has been analysed. This is the first reflectance validation study incorporating such a large amount of data. It is shown that this method is a valuable tool for spotting spatial and temporal anomalies. We conclude that SCIAMACHY reflectance data in this wavelength range are stable over the investigated period. In addition, we show an example of an 10 anomaly in the data due to an error in the processing chain that could be detected by our comparison. This validation method could be extremely useful too for validation of other satellite spectrometers, such as OMI and GOME-2.

scholarly journals An Approach to Minimize Atmospheric Correction Error and Improve Physics-Based Satellite-Derived Bathymetry in a Coastal Environment

2020 ◽  
Vol 12 (17) ◽  
pp. 2752
Author(s):  
Christopher O. Ilori ◽  
Anders Knudby
Keyword(s):  
Remote Sensing ◽  
Environmental Factors ◽  
Complete Solution ◽  
Atmospheric Correction ◽  
Florida Keys ◽  
Radiative Transfer Model ◽  
Inversion Method ◽  
Transfer Model ◽  
Landsat 8 ◽  
Depth Range

Physics-based radiative transfer model (RTM) inversion methods have been developed and implemented for satellite-derived bathymetry (SDB); however, precise atmospheric correction (AC) is required for robust bathymetry retrieval. In a previous study, we revealed that biases from AC may be related to imaging and environmental factors that are not considered sufficiently in all AC algorithms. Thus, the main aim of this study is to demonstrate how AC biases related to environmental factors can be minimized to improve SDB results. To achieve this, we first tested a physics-based inversion method to estimate bathymetry for a nearshore area in the Florida Keys, USA. Using a freely available water-based AC algorithm (ACOLITE), we used Landsat 8 (L8) images to derive per-pixel remote sensing reflectances, from which bathymetry was subsequently estimated. Then, we quantified known biases in the AC using a linear regression that estimated bias as a function of imaging and environmental factors and applied a correction to produce a new set of remote sensing reflectances. This correction improved bathymetry estimates for eight of the nine scenes we tested, with the resulting changes in bathymetry RMSE ranging from +0.09 m (worse) to −0.48 m (better) for a 1 to 25 m depth range, and from +0.07 m (worse) to −0.46 m (better) for an approximately 1 to 16 m depth range. In addition, we showed that an ensemble approach based on multiple images, with acquisitions ranging from optimal to sub-optimal conditions, can be used to estimate bathymetry with a result that is similar to what can be obtained from the best individual scene. This approach can reduce time spent on the pre-screening and filtering of scenes. The correction method implemented in this study is not a complete solution to the challenge of AC for satellite-derived bathymetry, but it can eliminate the effects of biases inherent to individual AC algorithms and thus improve bathymetry retrieval. It may also be beneficial for use with other AC algorithms and for the estimation of seafloor habitat and water quality products, although further validation in different nearshore waters is required.

scholarly journals Retrieval of total column and surface NO<sub>2</sub> from Pandora zenith-sky measurements

2019 ◽  
Author(s):  
Xiaoyi Zhao ◽  
Debora Griffin ◽  
Vitali Fioletov ◽  
Chris McLinden ◽  
Jonathan Davies ◽  
...  
Keyword(s):  
Transport Model ◽  
Surface Concentration ◽  
In Situ Measurements ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Chemical Transport Model ◽  
High Quality ◽  
Vertical Column

Abstract. Pandora spectrometers can retrieve nitrogen dioxide (NO2) vertical column densities (VCDs) via two viewing geometries: direct-sun and zenith-sky. The direct-sun NO2 VCD measurements have high quality (0.1 DU accuracy in clear-sky conditions) and do not rely on any radiative transfer model to calculate air mass factors (AMFs); however, they are not available when the sun is obscured by clouds. To perform NO2 measurements in cloudy conditions, a simple but robust NO2 retrieval algorithm is developed for Pandora zenith-sky measurements. This algorithm derives empirical zenith-sky NO2 AMFs from coincident high-quality direct-sun NO2 observations. Moreover, the retrieved Pandora zenith-sky NO2 VCD data are converted to surface NO2 concentrations with a scaling algorithm that uses chemical-transport-model predictions and satellite measurements as inputs. NO2 VCDs and surface concentrations are retrieved from Pandora zenith-sky measurements made in Toronto, Canada, from 2015 to 2017. The retrieved Pandora zenith-sky NO2 data (VCD and surface concentration) show good agreement with both satellite and in situ measurements. The diurnal and seasonal variations of derived Pandora zenith-sky surface NO2 data also agree well with in situ measurements (diurnal difference within ±2 ppbv). Overall, this work shows that the new Pandora zenith-sky NO2 products have the potential to be used in various applications such as future satellite validation in moderate cloudy scenes and air quality monitoring.

scholarly journals A Refined Four-Stream Radiative Transfer Model for Row-Planted Crops

2020 ◽  
Vol 12 (8) ◽  
pp. 1290 ◽  
Author(s):  
Xu Ma ◽  
Tiejun Wang ◽  
Lei Lu
Keyword(s):  
Radiative Transfer ◽  
Computer Simulations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Growth Stages ◽  
Canopy Reflectance ◽  
Transfer Equations ◽  
Radiative Transfer Equations ◽  
Different Growth Stages

In modeling the canopy reflectance of row-planted crops, neglecting horizontal radiative transfer may lead to an inaccurate representation of vegetation energy balance and further cause uncertainty in the simulation of canopy reflectance at larger viewing zenith angles. To reduce this systematic deviation, here we refined the four-stream radiative transfer equations by considering horizontal radiation through the lateral “walls”, considered the radiative transfer between rows, then proposed a modified four-stream (MFS) radiative transfer model using single and multiple scattering. We validated the MFS model using both computer simulations and in situ measurements, and found that the MFS model can be used to simulate crop canopy reflectance at different growth stages with an accuracy comparable to the computer simulations (RMSE < 0.002 in the red band, RMSE < 0.019 in NIR band). Moreover, the MFS model can be successfully used to simulate the reflectance of continuous (RMSE = 0.012) and row crop canopies (RMSE < 0.023), and therefore addressed the large viewing zenith angle problems in the previous row model based on four-stream radiative transfer equations. Our results demonstrate that horizontal radiation is an important factor that needs to be considered in modeling the canopy reflectance of row-planted crops. Hence, the refined four-stream radiative transfer model is applicable to the real world.

In Situ and In Transit Computing for Large Scale Geoscientific Simulation

2020 ◽  
Author(s):  
Sebastian Friedemann ◽  
Bruno Raffin ◽  
Basile Hector ◽  
Jean-Martial Cohard
Keyword(s):  
Data Assimilation ◽  
High Performance ◽  
Large Scale ◽  
Transfer Model ◽  
Simulation Data ◽  
Computing Platform ◽  
Continental Scale ◽  
Physically Based ◽  
In Transit

&lt;p&gt;In situ and in transit computing is an effective way to place postprocessing and preprocessing tasks for large scale simulations on the high performance computing platform. The resulting proximity between the execution of preprocessing, simulation and postprocessing permits to lower I/O by bypassing slow and energy inefficient persistent storages. This permits to scale workflows consisting of heterogeneous components such as simulation, data analysis and visualization, to modern massively parallel high performance platforms. Reordering the workflow components gives a manifold of new advanced data processing possibilities for research. Thus in situ and in transit computing are vital for advances in the domain of geoscientific simulation which relies on the increasing amount of sensor and simulation data available.&lt;/p&gt;&lt;p&gt;In this talk, different in situ and in transit workflows, especially those that are useful in the field of geoscientific simulation, are discussed. Furthermore our experiences augmenting ParFlow-CLM, a physically based, state-of-the-art, fully coupled water transfer model for the critical zone, with FlowVR, an in situ framework with a strict component paradigm, are presented.&lt;br&gt;This allows shadowed in situ file writing, in situ online steering and in situ visualization.&lt;/p&gt;&lt;p&gt;In situ frameworks further can be coupled to data assimilation tools.&lt;br&gt;In the on going EoCoE-II we propose to embed data assimilation codes into an in transit computing environment. This is expected to enable ensemble based data assimilation on continental scale hydrological simulations with multiple thousands of ensemble members.&lt;/p&gt;

scholarly journals Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

2017 ◽  
Vol 17 (22) ◽  
pp. 13559-13572 ◽  
Author(s):  
Daniel H. Cusworth ◽  
Loretta J. Mickley ◽  
Eric M. Leibensperger ◽  
Michael J. Iacono
Keyword(s):  
United States ◽  
Radiative Transfer ◽  
Southeastern United States ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58–1.0 Wm−2 a−1 over the 2000–2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3–5.0  ×  10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000–2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear-sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm−2 a−1 at Goodwin Creek, MS, and +0.93 Wm−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990–2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

scholarly journals An Assessment of SAPHIR Calibration Using Quality Tropical Soundings

2015 ◽  
Vol 32 (1) ◽  
pp. 61-78 ◽  
Author(s):  
G. Clain ◽  
H. Brogniez ◽  
V. H. Payne ◽  
V. O. John ◽  
M. Luo
Keyword(s):  
Radiative Transfer ◽  
Incidence Angle ◽  
Intraseasonal Variability ◽  
Sensor Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Water Vapor Absorption ◽  
Infrared Observation ◽  
Cross Track

AbstractThe Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) instrument on board the Megha-Tropiques (MT) platform is a cross-track, multichannel microwave humidity sounder with six channels near the 183.31-GHz water vapor absorption line, a maximum scan angle of 42.96° (resulting in a maximum incidence angle of 50.7°), a 1700-km-wide swath, and a footprint resolution of 10 km at nadir. SAPHIR L1A2 brightness temperature (BT) observations have been compared to BTs simulated by the radiative transfer model (RTM) Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV-10), using in situ measurements from radiosondes as input. Selected radiosonde humidity observations from the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year (CINDY)–Dynamics of the Madden–Julian Oscillation (DYNAMO) campaign (September 2011–March 2012) were spatiotemporally collocated with MT overpasses. Although several sonde systems were used during the campaign, all of the sites selected for this study used the Vaisala RS92-SGPD system and were chosen in order to avoid discrepancies in data quality and biases.To interpret the results of the comparison between the sensor data and the RTM simulations, uncertainties associated with the data processing must be propagated throughout the evaluation. The magnitude of the bias was found to be dependent on the observing channel, increasing from 0.18 K for the 183.31 ± 0.2-GHz channel to 2.3 K for the 183.31 ± 11-GHz channel. Uncertainties and errors that could impact the BT biases were investigated. These can be linked to the RTM input and design, the radiosonde observations, the chosen methodology of comparison, and the SAPHIR instrument itself.

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