scholarly journals Atmospheric correction algorithm for short-wave channels of the MSU-MR device of the Meteor-M no. 2 satellite

2019 ◽  
pp. 3-12
Author(s):  
M. O. Kuchma ◽  
V. D. Bloshchinskiy
Keyword(s):  
Reference Values ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Short Wave ◽  
Atmospheric Conditions ◽  
Correction Algorithm ◽  
Low Resolution ◽  
Scanning Device ◽  
Observation Geometry ◽  
Present Algorithm

The problem of atmospheric correction for short-wave channels of a multispectral low-resolution scanning device installed on the Meteor-M No. 2 satellite is considered. To solve the problem the existing atmospheric correction algorithms are investigated. The developed atmospheric correction algorithm is based on the use of special Look-up Tables generated by the authors. Look-up Tables contain information about reflectance of the satellite device channels for various atmospheric conditions and observation geometry. The results of atmospheric correction for the first channel of the device were verified. Verification showed a high correlation with the reference reflectance, which is the data from the EUMETSAT portal Surface Albedo Validation Sites. An additional, verification of the present algorithm was also performed with the first channel data of the AVHRR device MetOp-A satellite. The correlation of the reference values and the results of atmospheric correction of both satellite devices are comparable.

scholarly journals Atmospheric Correction of OLCI Imagery over Extremely Turbid Waters Based on the Red, NIR and 1016 nm Bands and a New Baseline Residual Technique

2019 ◽  
Vol 11 (3) ◽  
pp. 220 ◽  
Author(s):  
Juan Gossn ◽  
Kevin Ruddick ◽  
Ana Dogliotti
Keyword(s):  
Atmospheric Correction ◽  
Short Wave ◽  
Considerable Improvement ◽  
Atmospheric Conditions ◽  
Black Water ◽  
Baseline Subtraction ◽  
Spectral Bands ◽  
Turbid Waters ◽  
Swir Band ◽  
Infra Red

A common approach to the pixel-by-pixel atmospheric correction of satellite water colour imagery is to calculate aerosol and water reflectance at two spectral bands, typically in the near infra-red (NIR, 700–1000 nm) or the short-wave-infra-red (SWIR, 1000–3000 nm), and then extrapolate aerosol reflectance to shorter wavelengths. For clear waters, this can be achieved simply for NIR bands, where the water reflectance can be assumed negligible i.e., the “black water” assumption. For moderately turbid waters, either the NIR water reflectance, which is non-negligible, must be modelled or longer wavelength SWIR bands, with negligible water reflectance, must be used. For extremely turbid waters, modelling of non-zero NIR water reflectance becomes uncertain because the spectral slopes of water and aerosol reflectance in the NIR become similar, making it difficult to distinguish between them. In such waters the use of SWIR bands is definitely preferred and the use of the MODIS bands at 1240 nm and 2130 nm is clearly established although, on many sensors such as the Ocean and Land Colour Instrument (OLCI), such SWIR bands are not included. Instead, a new, cheaper SWIR band at 1016 nm is available on OLCI with potential for much better atmospheric correction over extremely turbid waters. That potential is tested here. In this work, we demonstrate that for spectrally-close band triplets (such as OLCI bands at 779–865–1016 nm), the Rayleigh-corrected reflectance of the triplet’s “middle” band after baseline subtraction (or baseline residual, BLR) is essentially independent of the atmospheric conditions. We use the three BLRs defined by three consecutive band triplets of the group of bands 620–709–779–865–1016 nm to calculate water reflectance and hence aerosol reflectance at these wavelengths. Comparison with standard atmospheric correction algorithms shows similar performance in moderately turbid and clear waters and a considerable improvement in extremely turbid waters.

scholarly journals Critical surface albedo and its implications to aerosol remote sensing

2011 ◽  
Vol 4 (6) ◽  
pp. 7725-7750 ◽  
Author(s):  
F. C. Seidel ◽  
C. Popp
Keyword(s):  
Remote Sensing ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Single Scattering ◽  
Critical Surface ◽  
Aerosol Absorption ◽  
Sensing Applications ◽  
Aerosol Remote Sensing ◽  
Absorbing Aerosols ◽  
Observation Geometry

Abstract. We analyse the critical surface albedo (CSA) and its implications to aerosol remote sensing. CSA is defined as the surface albedo, where the reflectance at top-of-atmosphere (TOA) does not depend on aerosol optical depth (AOD). AOD retrievals are therefore inaccurate at the CSA. The CSA is obtained by derivatives of the TOA reflectance with respect to AOD using a radiative transfer code. We present the CSA and the effect of surface albedo uncertainties on AOD retrieval and atmospheric correction as a function of aerosol single-scattering albedo, illumination and observation geometry, wavelength and AOD. In general, increasing aerosol absorption and increasing scattering angles lead to lower CSA. We show that the CSA also depends on AOD, which was often neglected in previous studies. The following implications to aerosol remote sensing applications were found: (i) surface albedo uncertainties result in large AOD retrieval errors, particularly close to the CSA; (ii) AOD retrievals of non-absorbing aerosols require dark surfaces, while strong absorbing aerosols can be retrieved more accurately over bright surfaces; (iii) the CSA may help to estimate aerosol absorption; and (iv) the presented sensitivity of the reflectance at TOA to AOD provides error estimations to optimise AOD retrieval algorithms.

scholarly journals SURFACE ALBEDO OBTAINED WITH MODIS IMAGES IN CASES OF LOW AND HIGH AEROSOL LOADING IN THE ATMOSPHERE

2014 ◽  
Vol 32 (1) ◽  
pp. 5 ◽  
Author(s):  
Juarez Dantas de Souza ◽  
Juan Carlos Ceballos ◽  
Bernardo Barbosa Da Silva
Keyword(s):  
Surface Albedo ◽  
Atmospheric Correction ◽  
Amazon Region ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Conditions ◽  
Imaging Spectrometer ◽  
Aerosol Loading ◽  
Moderate Resolution ◽  
Resolution Imaging

ABSTRACT. The surface albedo is a parameter of vital importance for estimating the net radiation. This parameter is obtained by using data obtained from satelliteimages and by utilizing the appropriate method for atmospheric correction. The method used by NASA (National Aeronautics and Space Administration) to obtainsurface reflectance through MODIS (Moderate Resolution Imaging Spectrometer) sensor aboard the Terra and Aqua satellites (MOD09 and MYD09 products) hasproved inaccurate for the detection of burning areas in the Amazon region – for products in both collection 4 and collection 5. Other methods have been used toobtain the albedo. However, these are limited to atmospheric conditions with negligible aerosol influence. In the present work, we have established a relationshipbetween surface reflectance and the top of atmosphere, based on a radiative transfer model in an atmosphere of multiple layers. The method applied to productsLevel 1B (MOD02 and MYD02) in regions of low aerosol loading (Northeast Brazil) produces results similar to those effected by product MOD09. Furthermore, inregions of high aerosol loading (burnings in the Amazon region of Brazil), the method presents much higher performance than that rendered by the MOD09 andMYD09 products, improving, therefore, by more than 10% the accuracy of these results. The method is simple, efficient and easy to use.Keywords: reflectance, atmospheric correction, method of two streams, burning regions. RESUMO. O albedo da superfície é um parâmetro fundamental na estimativa do saldo de radiação. Ele pode ser obtido através de dados gerados por imagens desatélite, utilizando um método adequado de correção atmosférica. O método usado pela NASA (National Aeronautics and Space Administration), para obter refletânciasda superfície, através do sensor MODIS (Moderate Resolution Imaging Spectrometer) abordo dos satélites Terra e Aqua (produtos MOD09 e MYD09), apresentaproblemas em regiões de queimadas na Amazônia, tanto os produtos da coleção 4 como os da coleção 5. Outros métodos têm sido utilizados para a obtenção doalbedo. No entanto, eles são limitados à aplicação em atmosfera com pouca influência de aerossol. Neste trabalho, é estabelecida uma relação entre a refletânciada superfície e a do topo da atmosfera, com base em um modelo de transferência radiativa numa atmosfera de múltiplas camadas. O método aplicado aos produtos nível 1B (MOD02 e MYD02), em regiões de baixa carga de aerossol (Nordeste do Brasil), produz resultados semelhantes ao produto MOD09, e em regiões de altacarga de aerossol (região de queimadas na Amazônia brasileira), apresenta desempenho superior aos produtos MOD09 e MYD09, melhorando em mais de 10% aprecisão desses resultados. O método é simples, eficiente e de fácil utilização.Palavras-chave: refletância, correção atmosférica, método de dois fluxos, região de queimadas.

scholarly journals iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2

2021 ◽  
Vol 13 (4) ◽  
pp. 654
Author(s):  
Erwin Wolters ◽  
Carolien Toté ◽  
Sindy Sterckx ◽  
Stefan Adriaensen ◽  
Claire Henocq ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Vegetation Indices ◽  
Atmospheric Correction ◽  
Negative Bias ◽  
Surface Reflectance ◽  
Temporal Consistency ◽  
Correction Algorithm ◽  
Land Surfaces ◽  
Relative Differences ◽  
Level 2

To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR’s statistical and temporal consistency is high. iCOR AOT retrievals overestimate relative to AERONET, but less than SYN L2. iCOR and SYN L2 TOC reflectances exhibit a negative bias of ~−0.01 and −0.02, respectively, in the Blue bands compared to the simulations. This diminishes for RED and NIR, except for a +0.02 bias for SYN L2 in the NIR. The intercomparison with RadCalNet shows relative differences < ±6%, except for bands Oa02 (Blue) and Oa21 (NIR), which is likely related to the reported OLCI “excess of brightness”. The intercomparison between iCOR and SYN L2 showed R2 = 0.80–0.93 and R2 = 0.92–0.96 for TOC reflectance and VIs, respectively. iCOR’s higher temporal smoothness compared to SYN L2 does not propagate into a significantly higher smoothness for TOC reflectance and VIs. Altogether, we conclude that iCOR is well suitable to retrieve statistically and temporally consistent AOT, TOC reflectance, and VIs over land surfaces from Sentinel-3/OLCI observations.

scholarly journals Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

2021 ◽  
Vol 13 (10) ◽  
pp. 1927
Author(s):  
Fuqin Li ◽  
David Jupp ◽  
Thomas Schroeder ◽  
Stephen Sagar ◽  
Joshua Sixsmith ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Correction Method ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Correction Algorithm ◽  
Simple Method ◽  
North East ◽  
The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

scholarly journals The Determination of Snow Albedo from Satellite Measurements Using Fast Atmospheric Correction Technique

2020 ◽  
Vol 12 (2) ◽  
pp. 234 ◽  
Author(s):  
Alexander Kokhanovsky ◽  
Jason E. Box ◽  
Baptiste Vandecrux ◽  
Kenneth D. Mankoff ◽  
Maxim Lamare ◽  
...  
Keyword(s):  
Atmospheric Correction ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Correction Algorithm ◽  
Satellite Measurements ◽  
Snow Albedo ◽  
Single View ◽  
French Alps ◽  
Correction Technique

We present a simplified atmospheric correction algorithm for snow/ice albedo retrievals using single view satellite measurements. The validation of the technique is performed using Ocean and Land Colour Instrument (OLCI) on board Copernicus Sentinel-3 satellite and ground spectral or broadband albedo measurements from locations on the Greenland ice sheet and in the French Alps. Through comparison with independent ground observations, the technique is shown to perform accurately in a range of conditions from a 2100 m elevation mid-latitude location in the French Alps to a network of 15 locations across a 2390 m elevation range in seven regions across the Greenland ice sheet. Retrieved broadband albedo is accurate within 5% over a wide (0.5) broadband albedo range of the (N = 4155) Greenland observations and with no apparent bias.

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