1,721,102 research outputs found
Evolutions of Sentinel-2 Level-2A Cloud Masking Algorithm: Sen2Cor Prototyp First Results
Full text linkReliable cloud screening remains a critical issue for the analysis of optical imagery. In this work we present the recent evolutions of the Cloud Screening and Scene Classification module of Sen2Cor processor for the
Copernicus Sentinel-2 mission. In addition to a Level-2A surface reflectance product, Sen2Cor provides a Scene Classification (SCL) map divided into 11 classes. The information provided by this map is of great interest for automated processing chains. It can be used to mask out clouds, cloud shadow, water, snow/ice from the Sentinel-2 imagery, so that downstream processing can be performed on clear land pixels, suitable for time-series analysis and quantitative remote sensing.
The performance and limitations of the current algorithm are recalled. The updates aimed at improving the overall accuracy of the cloud screening are described (efficient topographic shadows computation, mitigation of false snow detection in clouds and mitigation of false clouds detection on bright targets). Preliminary results based on a Sen2Cor prototype are discussed
Validation Examples of ATCOR Haze Removal of Rapid-Eye Images
No full textAtmospheric correction of satellite images is necessary for many applications of remote sensing. Among them are applications for agriculture, forestry, land cover and land cover change, urban mapping, emergency and inland water. ATCOR is a widely used atmospheric correction tool which can process data of many optical satellite sensors, for instance Landsat, Sentinel-2, SPOT and RapidEye. ATCOR includes a terrain and adjacency correction of satellite images and several Special algorithms like haze detection, haze correction, cirrus correction, de-shadowing and empirical methods for BRDF correction. 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. Last year we presented validation results of aerosol retrieval by the widely used atmospheric correction tool ATCOR. We compared vertical column aerosol-optical
thickness (AOT) spectra derived from Rapid-Eye data with in-situ sun-photometer measurements on the ground. Mean uncertainty was ΔAOT550 ≈ 0.04. The presentation will update these results including reference measurements on the ground in year 2015. Haze removal gives the chance to add more observation points in time series analysis. We started to investigate the accuracy of ATCOR haze removal by comparing haze-removed Rapid-Eye Images with atmospherically corrected images from nearby cloudless data takes. First results are shown in the
proposed presentation
Sentinel-2 L2A Surface Reflectance Product compared with Reference Measurements on Ground
Full text linkSurface reflectance measurements on ground in parallel to Sentinel-2 overpasses provide an essential reference for validation of atmospheric correction algorithms.
Those measurements performed in vegetated area in Northern Germany are compared with surface reflectance retrieval of L2A-processsor Sen2Cor. All bands are within or slightly outside surface reflection specification |ΔSR| less than 0.05*SRref+0.005
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Simulation of MOS spectra by radiative transfer calculations using ground-truth data and atmospheric models
No full textA radiative transfer simulation technique (RTST) is described that is applied to simulate spectral signatures recorded by the ocean colour sensor MOS onbo-ard the IRS-P3 platform. The RTST is based on a successive order technique and considers ab-sorption and multiple scatte-ring of solar radiation by particu-late and molecu-lar species. Aerosol optical depths are retrieved from ground-based solar absorption measurements while the scattering phase functions are primarily determined from almucantar measurements and are then fitted by two- or three-term Henyey-Greenstein functions. Quasi-mono-chro-matic line-by-line calcu-lations are used to predict molecular trans-mission functions at 10 nm spectral resolutions in a layered atmo-sphe-re. The inherent pure sea water reflectance and reflection functions due to solar and sky glitter effects are considered in the simulations by use of ground-based measurement data as well as model assumptions. Synthetic VIS and NIR spectra that have been calcula-ted in the 400-1700 nm wavelength range for a varie-ty of atmo-sphe-ric mo-dels and surface condi-tions are compared with selected MOS measurements
Ground based measurements of aerosol properties using Microtops instruments
No full textAtmospheric aerosols originate from a wide variety of sources in both the marine and the continental environments. Aerosol properties vary significantly in space and time depending upon whether the air mass is anthropogenic or natural, marine or continental, rural or urban.
Aerosol particles influence the radiation field of the earth. Variations of aerosol properties in time and space are the dominating source of the variability of remote sensing signals in the optical spectral range. Consequently, the contribution of aerosols to the signals at top of the atmosphere must be accounted for remote sensing of the ocean and land surface, which is known as atmospheric correction. Validation of atmospheric correction procedures require ground based measurements of aerosol properties. Ground based measurements of aerosol properties give also a basis for validation of the aerosol models used by atmospheric correction algorithms. More, measurements of aerosol properties are useful for climate studies because aerosol particles have an impact on the radiation balance of the earth due to its influence on the radiation field.
Ground based measurements of aerosol properties have been performed in the coastal area of the southern Baltic Sea and near Berlin with a Microtops II Sunphotometer and a Microtops II ozone monitor. The data set at the Baltic Sea includes 7 observation periods at 4 different locations. The present paper reports some experience how to perform and analyze measurements with the Microtops instruments. Some advice is provided both for measurements at the land surface and onboard ships. Finally some results are presented.
Sunphotometer measurements over several years require a large effort to maintain accurate radiometric calibration of the instruments. Sensor calibration was found to be very stable. Sensor degradation per year is less than 0.1% with exception of the 1020 nm channel, where it is about 1% per year.
The dataset includes very clear and very turbid conditions. Situations with dominating large aerosol particles have been observed as well as situations with dominating small aerosol particles. Aerosol optical thickness at 550 nm varies from 0.04 to 0.7 and the Angstrœm exponent ranges from 0.25 to 1.8. Variations of the observed optical aerosol parameters in the coastal area show no clear relation to the related wind and humidity conditions, because the dataset is still too small for this kind of analysis.
Validation of atmospheric correction algorithms is demonstrated with a comparison of column aerosol optical thickness resulting from satellite data with aerosol optical thickness from ground based measurements at time of satellite overpass. The agreement is better than ±0.03 at 750 nm. Another example uses the aerosol properties found from ground based measurements as input to radiative transfer modeling of the signals received at satellite. The agreement between modeled and measured signals is fine within the expectable uncertainty
Estimation of optical thickness of volcanic ash clouds using satellite data
No full textRadiance 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 exampl
Aerosol optical thickness from Lake Süßer See (Germany) during the Inland Water Remote Sensing Validation Campaign 2017
No full textSpectral surface albedo derived from GOME-2/Metop measurements
No full textSpectral 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
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