This document summarizes a study that compares four atmospheric correction methods - 6S, FLAASH, Sen2Cor, and DOS - for processing Sentinel-2 satellite imagery. The methods were applied to a Sentinel-2 image of Heraklion, Greece. The physically-based 6S, FLAASH, and Sen2Cor methods generally performed better than the empirical DOS method, but require more input data and computation. The performance of the methods varied for different land cover types. 6S provided surface reflectance closest to reference data for grassland pixels. Overall, the study aims to evaluate different approaches to atmospheric correction of Sentinel-2 imagery.
A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use ...Muhammad Bilal
Advantages of SREM:
1. SREM is the simplest method compared to the existing surface reflectance (SR) estimation methods.
2. SREM performs SR inversion based on the 6S Radiative Transfer Model (RTM) equations.
3. SREM does not depend on RTM simulation and a comprehensive lookup table (LUT).
4. SREM does not use the following parameters:
a. aerosol optical depth (AOD),
b. aerosol model,
c. water vapor concentration,
d. ozone concertation, and
e. other gases.
5. SREM can provide SR retrievals over diverse land surfaces including urban, vegetated, and desert surfaces.
6. SREM SR values are comparable with the following satellite SR products:
a. Landsat SR product (LEDAPS & LaSRC) at 30 m resolution,
b. Sentinel-2A SR product at 10 m resolution,
c. MODIS (MOD09) SR product at 500 m resolution, and
d. Planet satellite at 3 m resolution.
7. SREM can be applied to other Multispectral as well as Hyperspectral satellite data.
SREM ENVI/IDL CODE:
SREM IDL codes for Multispectral and Hyperspectral satellite data are available on demand, please email me at muhammad.bilal@connect.polyu.hk with the subject “SREM_SatelliteName_Code” if anyone is interested, and please provide the following information:
a. Full name,
b. Position,
c. Affiliation,
d. Research application.
PDF Version: https://www.mdpi.com/2072-4292/11/11/1344/pdf
https://www.researchgate.net/project/Simplified-and-Robust-Surface-Reflectance-Estimation-Method-SREM
A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use ...Muhammad Bilal
Advantages of SREM:
1. SREM is the simplest method compared to the existing surface reflectance (SR) estimation methods.
2. SREM performs SR inversion based on the 6S Radiative Transfer Model (RTM) equations.
3. SREM does not depend on RTM simulation and a comprehensive lookup table (LUT).
4. SREM does not use the following parameters:
a. aerosol optical depth (AOD),
b. aerosol model,
c. water vapor concentration,
d. ozone concertation, and
e. other gases.
5. SREM can provide SR retrievals over diverse land surfaces including urban, vegetated, and desert surfaces.
6. SREM SR values are comparable with the following satellite SR products:
a. Landsat SR product (LEDAPS & LaSRC) at 30 m resolution,
b. Sentinel-2A SR product at 10 m resolution,
c. MODIS (MOD09) SR product at 500 m resolution, and
d. Planet satellite at 3 m resolution.
7. SREM can be applied to other Multispectral as well as Hyperspectral satellite data.
SREM ENVI/IDL CODE:
SREM IDL codes for Multispectral and Hyperspectral satellite data are available on demand, please email me at muhammad.bilal@connect.polyu.hk with the subject “SREM_SatelliteName_Code” if anyone is interested, and please provide the following information:
a. Full name,
b. Position,
c. Affiliation,
d. Research application.
PDF Version: https://www.mdpi.com/2072-4292/11/11/1344/pdf
https://www.researchgate.net/project/Simplified-and-Robust-Surface-Reflectance-Estimation-Method-SREM
This deals with the assessment of several parameterizations of longwave radiation. The parametes were calibrated using a calibration tool on Ameriflux data.
Performances evaluation of surface water areas extraction techniques using l...Abdelazim Negm
This presentation was presented at:
9th International Conference Interdisciplinarity in Engineering, INTER-ENG 2015, 8-9 October 2015, Tirgu-Mures, Romania
The complete paper will be published in Procedia Technology Journal soon.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Assessment of the Usefulness of Egnos Differential Corrections in Conducting ...IJERA Editor
The article presents the results of research in determining the position of the base station in a static mode using
EGNOS differential corrections. The experiment was conducted in the Dęblin airport area. The experiment
comprised determining the coordinates of three base stations (REF1, VirA i VirB). The analysis of the results
for the tools adopted pointed out to the fact that the accuracy of coordinate determination for each station was in
the range of less than 2 meters.
Comparison Of Onsite And Nws Meteorology Data Sets Based On Varying Nearby La...BREEZE Software
A comparison of meteorological parameters influencing AERMOD-predicted concentrations between a meteorological dataset using only NWS data and one incorporating onsite wind speed and direction data is presented in this paper.
Titan’s Topography and Shape at the Endof the Cassini MissionSérgio Sacani
With the conclusion of the Cassini mission, we present an updated topographic map of Titan,including all the available altimetry, SARtopo, and stereophotogrammetry topographic data sets availablefrom the mission. We use radial basis func tions to interpolate the sparse data set, which covers only ∼9%of Titan’s global area. The most notable updates to the topography include higher coverage of the polesof Titan, improved fits to the global shape, and a finer resolution of the global interpolation. We alsopresent a statistical analysis of the error in the derived products and perform a global minimization on aprofile-by-profile basis to account for observed biases in the input data set. We find a greater flattening ofTitan than measured, additional topographic rises in Titan’s southern hemisphere and better constrain thepossible locations of past and present liquids on Titan’s surface.
Chronological Calibration Methods for Landsat Satellite Images iosrjce
IOSR Journal of Applied Physics (IOSR-JAP) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Calculation of solar radiation by using regression methodsmehmet şahin
Abstract. In this study, solar radiation was estimated at 53 location over Turkey with
varying climatic conditions using the Linear, Ridge, Lasso, Smoother, Partial least, KNN
and Gaussian process regression methods. The data of 2002 and 2003 years were used to
obtain regression coefficients of relevant methods. The coefficients were obtained based on
the input parameters. Input parameters were month, altitude, latitude, longitude and landsurface
temperature (LST).The values for LST were obtained from the data of the National
Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer
(NOAA-AVHRR) satellite. Solar radiation was calculated using obtained coefficients in
regression methods for 2004 year. The results were compared statistically. The most
successful method was Gaussian process regression method. The most unsuccessful method
was lasso regression method. While means bias error (MBE) value of Gaussian process
regression method was 0,274 MJ/m2, root mean square error (RMSE) value of method was
calculated as 2,260 MJ/m2. The correlation coefficient of related method was calculated as
0,941. Statistical results are consistent with the literature. Used the Gaussian process
regression method is recommended for other studies.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
This deals with the assessment of several parameterizations of longwave radiation. The parametes were calibrated using a calibration tool on Ameriflux data.
Performances evaluation of surface water areas extraction techniques using l...Abdelazim Negm
This presentation was presented at:
9th International Conference Interdisciplinarity in Engineering, INTER-ENG 2015, 8-9 October 2015, Tirgu-Mures, Romania
The complete paper will be published in Procedia Technology Journal soon.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Assessment of the Usefulness of Egnos Differential Corrections in Conducting ...IJERA Editor
The article presents the results of research in determining the position of the base station in a static mode using
EGNOS differential corrections. The experiment was conducted in the Dęblin airport area. The experiment
comprised determining the coordinates of three base stations (REF1, VirA i VirB). The analysis of the results
for the tools adopted pointed out to the fact that the accuracy of coordinate determination for each station was in
the range of less than 2 meters.
Comparison Of Onsite And Nws Meteorology Data Sets Based On Varying Nearby La...BREEZE Software
A comparison of meteorological parameters influencing AERMOD-predicted concentrations between a meteorological dataset using only NWS data and one incorporating onsite wind speed and direction data is presented in this paper.
Titan’s Topography and Shape at the Endof the Cassini MissionSérgio Sacani
With the conclusion of the Cassini mission, we present an updated topographic map of Titan,including all the available altimetry, SARtopo, and stereophotogrammetry topographic data sets availablefrom the mission. We use radial basis func tions to interpolate the sparse data set, which covers only ∼9%of Titan’s global area. The most notable updates to the topography include higher coverage of the polesof Titan, improved fits to the global shape, and a finer resolution of the global interpolation. We alsopresent a statistical analysis of the error in the derived products and perform a global minimization on aprofile-by-profile basis to account for observed biases in the input data set. We find a greater flattening ofTitan than measured, additional topographic rises in Titan’s southern hemisphere and better constrain thepossible locations of past and present liquids on Titan’s surface.
Chronological Calibration Methods for Landsat Satellite Images iosrjce
IOSR Journal of Applied Physics (IOSR-JAP) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Calculation of solar radiation by using regression methodsmehmet şahin
Abstract. In this study, solar radiation was estimated at 53 location over Turkey with
varying climatic conditions using the Linear, Ridge, Lasso, Smoother, Partial least, KNN
and Gaussian process regression methods. The data of 2002 and 2003 years were used to
obtain regression coefficients of relevant methods. The coefficients were obtained based on
the input parameters. Input parameters were month, altitude, latitude, longitude and landsurface
temperature (LST).The values for LST were obtained from the data of the National
Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer
(NOAA-AVHRR) satellite. Solar radiation was calculated using obtained coefficients in
regression methods for 2004 year. The results were compared statistically. The most
successful method was Gaussian process regression method. The most unsuccessful method
was lasso regression method. While means bias error (MBE) value of Gaussian process
regression method was 0,274 MJ/m2, root mean square error (RMSE) value of method was
calculated as 2,260 MJ/m2. The correlation coefficient of related method was calculated as
0,941. Statistical results are consistent with the literature. Used the Gaussian process
regression method is recommended for other studies.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
At present, with the development of wind power project in China, there are more and more projects located at the complex terrain and complex environment. At the same time, since the large planned area of project, the complex mountain area, and limited number of met mast, even without met mast, in order to the reliable development of the wind power project, it is important that how to do the wind resource assessment without actual measurement wind data and other conditions such as less reliable wind data, and the met mast was not considered representative. This paper will use the atmospheric model to do mesoscale simulation calculation of wind resources, and then combine with CFD technology to downscaling computation to get high resolution wind power assessment result. Finally, in order to confirm the validity of this application in the actual project, the comparison between calculation values and measurement values is carried out. The verification result through the actual data of different met mast shows that the wind resource assessment method which combines the CFD and mesoscale technologies is reliable. The main contribution of the article is to provide the reference model and approach for regional planning and large scale wind resource assessment when there isn’t enough adequate and effective wind data.
AUTOMATIC IDENTIFICATION OF CLOUD COVER REGIONS USING SURF ijcseit
Weather forecasting has become an indispensable application to predict the state of the atmosphere for a
future time based on cloud cover identification. But it generally needs the experience of a well-trained
meteorologist. In this paper, a novel method is proposed for automatic cloud cover estimation, typical to
Indian Territory Speeded Up Robust Feature Transform(SURF) is applied on the satellite images to obtain
the affine corrected images. The extracted cloud regions from the affine corrected images based on Otsu
threshold are superimposed on the artistic grids representing latitude and longitude over India. The
segmented cloud and grid composition drive a look up table mechanism to identify the cloud cover regions.
Owing to its simplicity, the proposed method processes the test images faster and provides accurate
segmentation for cloud cover regions.
Similar to Comparación de los métodos de corrección atmosférica basados en imágenes y físicas para las imágenes satelitales sentinel 2 (20)
2. Comparison of physically & image based atmospheric correction
methods for Sentinel-2 satellite imagery
Giannis Lantzanakis*
, Zina Mitraka, Nektarios Chrysoulakis
Foundation for Research and Technology Hellas, N.Plastira 100, 70013 Heraklion, Greece
ABSTRACT
Atmospheric correction is the process to retrieve the surface reflectance from remotely sensed imagery by removing the
atmospheric effects (Scattering and Absorption). The process determines the optical characteristics of the atmosphere
and then applies it in order to correct the atmospheric effects on satellite images. Two main categories of atmospheric
correction methods can be identified, the ones that rely on radiative transfer modeling and the image-based ones.
In this study, four methods are compared, three physically-based (6S, FLAASH, Sen2Cor) and one image-based (DOS)
for their effectiveness on atmospheric correction of Sentinel-2 high resolution optical imagery. A Sentinel-2 image,
acquired on a clear day over Heraklion, Greece was used. Ancillary information on the aerosol optical thickness from the
Moderate Resolution Imaging Spectroradiometer (MODIS) was used for the physically based methods.
In line with similar studies using Landsat images, the physically based methods perform better than the image-based
ones also for the Sentinel-2 imagery. Nevertheless, their high computational demand and the need for ancillary
atmospheric information makes them difficult to apply. Different atmospheric correction methods showed different
results for specific land cover types, suggesting that the selection of the suitable method is also application dependent.
Keywords: 6S, FLAASH, Sen2Cor, DOS, atmospheric correction, comparison
1. INTRODUCTION
The magnitude of the signal received from a satellite sensor is dependent on several factors, particularly: reflectance of
the target; nature and magnitude of the atmospheric interactions; slope and aspect of the ground target area relative to the
solar azimuth; and angle of view of the sensor and solar elevation angles. The role of atmospheric correction is to
decompose the above signal and to extract the component that originates from the target, in order to estimate the target
reflectance. The fundamental philosophy of atmospheric correction is to determine the optical characteristics of the
atmosphere and then to apply this in order to correct for the atmospheric effects of satellite imagery [1]. Accurate
calculations of surface spectral reflectance are useful for object recognition, segmentation and material classification.
Two main categories of atmospheric correction methods can be identified, the ones that rely on radiative transfer
modeling and the image-based methods. The later rely only on the information of the image in question and they are
mainly using statistical analysis of the satellite TOA(top-of-atmosphere) observations. On the other hand, the
atmospheric correction methods that rely on radiative transfer modeling, require independent data for atmospheric
optical characteristics at the time of image acquisition. These methods employ radiative transfer models.
The European satellite, Sentinel-2A was put into orbit by the European Space Agency (ESA) on 23 June 2015. Sentinel-
2 is ESA’s high resolution mission, providing frequent high resolution information with two satellites, the second
planned for launched in mid-2016 [2]. Sentinel-2 carries a Multispectral Instrument (MSI) [3], recording in 13 spectral
channels, covering a wide range of wavelengths from the 440 up to 2200 nm. The spectral channels 2, 3, 4 and 8
corresponding to blue, green, red and near infrared, have a resolution of 10 m. The spectral channels 5, 6, 7, 8a, 11 and
12 have a resolution of 20 m, while 1, 9 and 10 of 60 m.
In this study, four atmospheric correction methods are compared, three physically-based (6S,FLAASH,Sen2Cor) and one
image-based (DOS) for simulating the interaction between land and atmosphere and retrieve surface reflectance for
Sentinel-2 imagery.
6S (Second Simulation of Satellite Signal in the Solar Spectrum) [4] is an advanced NASA's radiative transfer
code for a wide range of atmospheric, spectral, and geometric conditions..
3. FLAASH (Fast Line-of-sight Atmospheric Analysis of Hypercubes) [5] is an atmospheric correction module in
the ENVI software that corrects wavelengths in the visible through near-infrared and shortwave infrared regions
Sen2cor (Sentinel-2 Level-2A Atmospheric Correction Processor) [6] is an ESA's Prototype Processor for
processing Sentinel-2 Top of Atmosphere reflectance (Level 1C) data into Bottom of Atmospheric corrected
(Level 2A) data. It additionally performs a Scene Classification of the corresponding input.
DOS (Dark Object Subtraction) [7] is a simple empirical atmospheric correction method for satellite imagery
available in ENVI.
The above mentioned atmospheric correction methods are applied for a case study, using Sentinel-2 data. The data used
and the methodology applied to atmospherically correct the Sentinel-2 data are presented in Section 2. Comparisons
among the different methods were held, to identify the differences among them and the results are presented and
discussed in Section 3. Conclusion follow in Section 4.
2. DATA AND METHODOLOGY
2.1 Data
In this study, a Sentinel-2 level 1C product [8] image was used, acquired on a clear day over Heraklion, Greece
(09.01.2016, 9:30 GMT). The scene covers an extent of 13 x 11 km2
over the broader area of Heraklion, Greece (Fig. 1),
and includes a wide range of surface cover i.e. buildings, roads, industrial areas, parks, an airport, and agricultural
surfaces, mainly olive trees and vineyards.
Figure 1. True-colour composition (4-3-2) of the Sentinel-2 simulated image of the study area, the broader area of
Heraklion, Greece (09.01.2016).
Information on the Sentinel-2 MSI spectral response function was available from ESA (Sentinel-2 MSI Technical
Guides). Ancillary information on the aerosol optical thickness (AOT) at 550 nm from the MODIS, MOD02_L2 [9] was
used for the physically based methods. A Digital Surface Model (DSM) of 0.8 m was available from the National
Cadastre of Greece.
4. 2.2 Methodology
Four different atmospheric correction methods were applied for the Sentinel-2 scene, i.e. the 6S, the FLAASH, the
Sen2Cor and the DOS methods. The necessary input for all methods was prepared, then the different models were run
independent and the individual surface reflectance products were then compared. The overall approach followed in this
study is presented in Fig. 2.
For applying the atmospheric corrections methods, it was necessary to have information on the TOA radiance measured
by the Sentinel-2 MSI, the aerosol optical thickness (or visibility) at the time of Sentinel-2 acquisition and information
on the surface elevation. Thus pre-processing of the available data was necessary.
Figure 2. Methodology flowchart
The Sentinel-2 level-1C product was converted from DN to TOA reflectance by dividing with a scale factor of 10000.
Following, TOA reflectance was converted to TOA radiance by RADTOA = REFTOA·d(t)·ES·cos( S)· -1
[10], where
RADTOA is the TOA radiance, REFTOA is the TOA reflectance, t is the Julian day, d(t) is a correction to take the sun-
Earth distance variation into account, ES is the equivalent extra-terrestrial solar spectrum and depends on the spectral
response of the Sentinel-2 MSI bands and S: is the zenith angle (ESA, 2016). This was done for bands 2, 3, 4, 5, 6,
7,8a,11,12. Bands 1, 9, 10 were excluded since they are atmospheric bands designed for aerosol, water vapor, cirrus
clouds.
For the FLAASH method, the AOT ( A550) was converted to visibility (VIS) by VIS = 3.9449/( A550 – 0.08498) [11]. To
adjust the physically-based methods to the sensor in question, information on the MSI spectral response was necessary.
The MSI spectral response function was used in the 6S model, while for FLAASH, the mean wavelength of each band
was used.
By applying the different atmospheric correction methods, three surface reflectance products were estimated. TOA
reflectance information was used for the DOS method; TOA radiance, DEM and AOT was used for 6S; radiance and
visibility was used for FLAASH, as shown in Fig. 2. All input data used in this study were resampled to 10 m resolution.
The surface reflectance products created using the different methods, were then compared to evaluate the performance of
the methods. The differences between all the image products were estimated to assess the spatial differences among
methods and common statistics were computed. The results were also evaluated against higher resolution surface cover
information.
6. e) f) m
Figure 3. shows the spectral surface reflectance for specific land cover types a)water, b)grass, c)trees, d)bare soil,
e)urban, f)bright man made materials, calculated using the four different atmospheric correction methods. With grey line
is the TOA reflectance, which is the Sentinel-2 level-1C product. With red line is the surface reflectance calculate by 6S,
with green by FLAASH, with orange by Sen2Cor and with blue by DOS.
For pixels which contains a lot of trees and for bare soil pixels, all the models compute similar
surface reflectance. For water and grass pixels, 6S, FLAASH and DOS compute similar surface
reflectance, and Sen2Cor completely different. For urban and bright man made materials(High
Albedo), all the models compute different surface reflectance.
In figure 3 for a grass pixel was used also data from JPL(Jet Propulsion Laboratory) library [12] to
compare the products of all the atmospheric correction methods that were used in this study. This
took place only for grass pixel, because this is the only one homogeneous pixel, and the surface
reflectance computed by the four different atmospheric correction methods must be close to this JP
library spectral signatures. Surface reflectance computed by 6S fits better with JP library.
4. CONCLUSION
This study compared four atmospheric correction methods for the recently launched Sentinel-2 MSI.
The methods were parametrized and applied for a Sentinel-2 scene over the case study of Heraklion,
Greece. All methods perform similarly for bare soil pixels, and pixels with more trees, and different
for water, grass, urban and bright man made materials. The Sentinel-2 is in rump-up phase, thus,
when the operational products become available, the study will be repeated to evaluate absolute
values of surface reflectance after atmospheric correction.
7. ACKNOWLEDGMENTS
Work carried out in the framework of the Hellenic Republic-Siemens Agreement partially funded by the Programmatic
Agreement Between Research Centers-GSRT 2015-2017.
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Solar Spectrum, 6S: An Overview,” IEEE Transactions on Geoscience and Remote Sensing, 35 (3), 675–686 (1997)
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[6] Main-Knorn M., Pflug b., Debaecker V., and Louis J "Calibration and validation plan for the l2a processor and
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[7] Chavez, PS. "An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of
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[8] Baillarin SJ, Meygre A., Dechoz C., Petrucci B., Lacherade S., Tremas T., Isola C., Martimort P., and Spoto F.,
"Sentinel-2 level 1 products and image processing performance" International Archives of the Photogrammetry,
Remote Sensing and Spatial Information Sciences (2012)
[9] Remer, L.A., Mattoo, S., Levy, R.C., and Munchak, L. A. "MODIS 3 km aerosol product: algorithm and global
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[10] ESA, "Level-1C Algorithm," <https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-
1c/algorithm> (2016)
[11] Retalis A., Hadjimitsis D. G., Michaelides S., Tymvios F., Chrysoulakis N., C. R. I. Clayton , and Themistocleous
K. "Comparison of aerosol optical thickness with in situ visibility data over Cyprus,"
Natural Hazards and Earth System Sciences, 10, 421-428 (2010)
[12] NASA, "Aster Spectral Library," <Retrieved from http://speclib.jpl.nasa.gov/search-1> (2016)
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