Atmospheric Correction over water surfaces ,
Atmospheric Correction over land surfaces ,
Aerosols ,
Validation of L2A-products ,
Sunphotometer measurements ,
O2A-band
Publications (11)
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In the frame of the Copernicus program, ESA launched the Copernicus Sentinel- 2 optical imaging satellites, which are fully operational since June 2017. Sentinel-2C- and -2D satellites will be launched following Sentinel-2A and -2B units with identical sensors.
This paper reports on a sensitivity analysis of Sentinel-2 atmospheric correction / cloud masking vs Signal-to Noise Ratio (SNR) in specific spectral bands. Some Sentinel-2 L1C products are selected to study this effect. Noisy products are simulated adding noise to original L1C-data applying different Gaussian noise models. Finally, both original and noisy L1C-products are processed with Level-2A processor Sen2Cor and resulting L2A-products are compared. Results showed, that added noise to B10 is most critical due to performance reduction of cloud masking. Added noise to B01 is less critical because it does not lead to systematic changes of average surface reflectance. It results in increased scatter of surface reflectance. Added noise to B09 is found to be uncritical because the impact on water vapor retrieval is within uncertainty of validation method.
The Sentinel-2 mission is dedicated to land monitoring, emergency management and security. It serves for monitoring of land-cover change and biophysical variables related to agriculture and forestry. The mission is also used to monitor coastal and inland waters and is useful for risk and disaster mapping. The Sentinel-2 mission is fully operating since June 2017 with a constellation of two polar orbiting satellite units. Both Sentinel-2A and Sentinel-2B are equipped with an optical imaging sensor MSI (Multi-Spectral Instrument) which acquires optical data products with spatial resolution up to 10 m. Accurate atmospheric correction of satellite observations is a precondition for the development and delivery of high quality applications. Therefore the atmospheric correction processor Sen2Cor was developed with the objective of delivering land surface reflectance products. Sen2Cor is designed to process monotemporal single tile Level-1C products, providing Level-2A surface (Bottom-of-Atmosphere) reflectance product together with Aerosol Optical Thickness (AOT), Water Vapour (WV) estimation maps and a Scene Classification (SCL) map for further processing. The paper will give an overview of the Level-2A product content and up-to-date information about the data quality of the Level-2A products generated with Sen2Cor 2.8 in terms of Cloud Screening and Atmospheric Correction. In addition the paper gives an outlook on the next updates of Sen2Cor and their impact on Level-2A Data Quality.
In the frame of the Copernicus programme, ESA has developed and launched the Sentinel-2 optical imaging mission that delivers optical data products designed to feed downstream services mainly related to land monitoring, emergency management and security. The Sentinel-2 mission is the constellation of two polar orbiting satellites Sentinel-2A and Sentinel-2B, each one equipped with an optical imaging sensor MSI (Multi-Spectral Instrument). Sentinel-2A was launched on June 23rd, 2015 and Sentinel-2B followed on March 7th, 2017. With the beginning of the operational phase the constellation of both satellites enable image acquisition over the same area every 5 days or less. To use unique potential of the Sentinel-2 data for land applications and ensure the highest quality of scientific exploitation, accurate correction of satellite images for atmospheric effects is required. Therefore the atmospheric correction processor Sen2Cor was developed by Telespazio VEGA Deutschland GmbH on behalf of ESA. Sen2Cor is a Level-2A processor which main purpose is to correct single-date Sentinel-2 Level-1C Top-Of-Atmosphere (TOA) products from the effects of the atmosphere in order to deliver a Level-2A Bottom-Of-Atmosphere (BOA) reflectance product. Additional outputs are an Aerosol Optical Thickness (AOT) map, a Water Vapour (WV) map and a Scene Classification (SCL) map with Quality Indicators for cloud and snow probabilities. Telespazio France and DLR have teamed up in order to provide the calibration and validation of the Sen2Cor processor. Here we provide an overview over the Sentinel-2 data, processor and products. It presents some processing examples of Sen2Cor applied to Sentinel-2 data, provides up-to-date information about the Sen2Cor release status and recent validation results at the time of the SPIE Remote Sensing 2017.
Atmospheric correction of satellite images is necessary for many applications of remote sensing, i.e. computation of vegetation indices and biomass estimation. The largest uncertainty in atmospheric correction arises out of spatial and temporal variation of aerosol amount and type. Therefore validation of aerosol estimation is one important step in validation of atmospheric correction algorithms. Our ground-based measurements of aerosol-optical thickness spectra (AOT) were performed synchronously to overpasses of satellites Rapid-Eye and Landsat. Validation of aerosol retrieval by the widely used atmospheric correction tool ATCOR1,2 was then realized by comparison of AOT derived from satellite data with the ground-truths. Mean uncertainty is ΔAOT550 ≈ 0.04, corresponding approximately to uncertainty in surface albedo of Δρ ≈ 0.004. Generally, ATCOR-derived AOT values are mostly overestimated when compared to the ground-truth measurements. Very little differences are found between Rapid-Eye and Landsat sensors. Differences between using rural and maritime aerosols are negligible within the visible spectral range.
Radiance measurements within the O2A-absorption band contain information about height distribution of scattering
particles. This is widely used for estimation of cloud-top height from satellite data. Within cloud free scenes over the
ocean, there is still enough information contained for separation of aerosol loading within the maritime boundary layer
and enhanced aerosol loading in the upper troposphere or stratosphere. If stratospheric aerosol content is low, then thin
cirrus clouds can be observed. Alternatively, a volcanic ash cloud within the stratosphere or upper troposphere can be
investigated after volcanic eruptions. This is demonstrated within this paper by one application example.
Spectral surface albedo is an important input for GOME-2 trace gas retrievals. An algorithm was developed for
estimation of spectral surface albedo from top-of-atmosphere (TOA)-radiances measured by the Global Ozone
Monitoring Experiment GOME-2 flying on-board MetOp-A. The climatologically version of this algorithm estimates
Minimum Lambert-Equivalent Reflectivity (MLER) for a fixed time window and can use data of many years in contrast
to the Near-real time version.
Accuracy of surface albedo estimated by MLER-computation increases with the amount of available data. Unfortunately,
most of the large GOME pixels are partly covered by clouds, which enhance the LER-data. A plot of LER-values over
cloud fraction is used within this presentation to account for this influence of clouds. This "cloud fraction plot" can be
applied over all surface types. Surface albedo obtained using the "cloud fraction plot" is compared with reference surface
albedo spectra and with the FRESCO climatology. There is a general good agreement; however there are also large
differences for some pixels.
Satellite remote sensing of atmospheric properties is important for investigation of atmospheric pollution and also for remote sensing of the underlying surface, where an atmospheric correction is needed. For the proof of new methodological concepts the multispectral imaging spectrometer MOS was developed in the DLR Institute of Space Sensor Technology and launched on the Indian satellite IRS- P3. It has 13 bands in the VIS/NIR region with 10nm bandwidth. MOS successfully provides data for more than 2 years over European and Northern African coasts. The paper will introduce a standard atmospheric correction scheme for MOS data over water regions using measurements in the near IR form 685 nm to 1000 nm. This method is based on a 2- channel correction, estimating the aerosol optical depth and the Angstrom coefficient for the spectral behavior of the optical thickness. After extrapolation of the visible region the atmospheric correction is applied. Examples will be shown from the Baltic and North Sea regions. The obtained result will be compared and discussed with available in situ measurements taken simultaneously with MOS overflights. Lastly, this algorithm is applied to an observation of forest fire smoke over Malaysia.
The database application system is developed to improve the selection of aerosol parameters for
radiation transport calculations. The user has to choose location and time for his simulation
calculations. The system presents proposals for the height dependence of optical properties of aerosols
as graphics. Depending on the user requirements ofthe simulation calculations the user may manipulate
the data content (e. g. variation of the mixing ratio, number of aerosol components, humidity, height
distribution, wavelength range). As one option the output of the database system can be immediately
used for MODTRAN calculations.
Radiance measurements in the O2A-band are sensitive to changes of optical depth of stratospheric and of tropospheric aerosols. There results a chance to use these measurements for separate estimation of optical depth of stratospheric and of tropospheric aerosols. First inversion results using simulated data are used to evaluate accuracy of stratospheric optical depth estimation. Possible applications are discussed.
A database application system was developed to provide aerosol parameters for radiative transfer calculations. The system is based on the aerosol model of d'Almeida (1991) and is directed in its first step to maritime applications. The user can choose location and time for his radiative transfer calculations. The system offers proposals as tables and curves for optical aerosol parameters and aerosol height distributions. Depending on the user requirements the data (e.g. mixing ratio, height distribution) can be modified.
The information content of radiance measurements in the O2A- and O2B-bands over the oceans for aerosol monitoring from space is discussed. A simple model of radiation transfer in the system atmosphere/ocean shall be used for estimation of optical thicknesses of different aerosol layers and ocean reflection. There are 3 nonredundant spectrometer channels in the O2A-band around 762 nm and 2 nonredundant channels in the O2B-band around 687 nm. High measurement accuracy of about 1% is more important for the measurements than a halfwidth (Delta) (lambda) FWHM of spectrometer channels smaller than 1 nm. A sensitivity analysis shows that the optical thickness of stratospheric aerosols can be estimated from measurements in the O2A- and O2B-bands. From these results the chance to use combined measurements in both bands for distinction between volcanic and background- stratospheric aerosols exists. There also is a chance to use measurements in the O2A-band for estimation of the optical thickness of aerosols in the free troposphere. The estimation of the optical thickness of aerosols within the maritime boundary layer can be expected from measurements in the O2A-band, if ocean reflection is known. To estimate optical thicknesses of different aerosol layers is not only useful for aerosol studies, but also for better atmospheric correction of satellite images of the ocean surface.
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