scholarly journals Aerosol models from the AERONET data base. Application to surface reflectance validation

2021 ◽  
Author(s):  
Jean-Claude Roger ◽  
Eric Vermote ◽  
Sergii Skakun ◽  
Emilie Murphy ◽  
Oleg Dubovik ◽  
...  
Keyword(s):  
Critical Role ◽  
Spectral Band ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Surface Reflectance ◽  
Aerosol Model ◽  
Microphysical Properties ◽  
The Impact ◽  
Source Of Error ◽  
Base Application

Abstract. Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. As part of the validation of atmospheric correction of remote sensing data affected by the atmosphere, it is critical to utilize appropriate aerosol models as aerosols are a main source of error. In this paper, we propose and demonstrate a framework for building and identifying an aerosol model. For this purpose, we define the aerosol model by recalculating the aerosol microphysical properties (Cvf, Cvc, %Cvf, %Cvc, rvf, rvc, σr, σc, nr440, nr650, nr850, nr1020, ni440, ni650, ni850, ni1020, %Sph) based on the optical thickness at 440 nm τ440 and the Ångström coefficient α440–870 obtained from numerous AERosol RObotic NETwork (AERONET) sites. Using aerosol microphysical properties provided by the AERONET dataset, we were able to evaluate our own retrieved microphysical properties. The associated uncertainties are up to 23 %, except for the challenging, imaginary part of the refractive index ni (about 38 %). Uncertainties of the retrieved aerosol microphysical properties were incorporated in the framework for validating surface reflectance derived from space-borne Earth observation sensors. Results indicate that the impact of aerosol microphysical properties varies 3.5 × 10−5 to 10−3 in reflectance units. Finally, the uncertainties of the microphysical properties yielded an overall uncertainty of approximately of 1 to 3 % of the retrieved surface reflectance in the MODIS red spectral band (620–670 nm), which corresponds to the specification used for atmospheric correction.

scholarly journals The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

2015 ◽  
Vol 8 (3) ◽  
pp. 1593-1604 ◽  
Author(s):  
C. Bassani ◽  
C. Manzo ◽  
F. Braga ◽  
M. Bresciani ◽  
C. Giardino ◽  
...  
Keyword(s):  
Accuracy Assessment ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Hyperspectral Data ◽  
High Spectral Resolution ◽  
Quality Analysis ◽  
Microphysical Properties ◽  
Quantitative Remote Sensing ◽  
The Impact ◽  
Aerosol Types

Abstract. Hyperspectral imaging provides quantitative remote sensing of ocean colour by the high spectral resolution of the water features. The HICO™ (Hyperspectral Imager for the Coastal Ocean) is suitable for coastal studies and monitoring. The accurate retrieval of hyperspectral water-leaving reflectance from HICO™ data is still a challenge. The aim of this work is to retrieve the water-leaving reflectance from HICO™ data with a physically based algorithm, using the local microphysical properties of the aerosol in order to overcome the limitations of the standard aerosol types commonly used in atmospheric correction processing. The water-leaving reflectance was obtained using the HICO@CRI (HICO ATmospherically Corrected Reflectance Imagery) atmospheric correction algorithm by adapting the vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) radiative transfer code. The HICO@CRI algorithm was applied on to six HICO™ images acquired in the northern Mediterranean basin, using the microphysical properties measured by the Acqua Alta Oceanographic Tower (AAOT) AERONET site. The HICO@CRI results obtained with AERONET products were validated with in situ measurements showing an accuracy expressed by r2 = 0.98. Additional runs of HICO@CRI on the six images were performed using maritime, continental and urban standard aerosol types to perform the accuracy assessment when standard aerosol types implemented in 6SV are used. The results highlight that the microphysical properties of the aerosol improve the accuracy of the atmospheric correction compared to standard aerosol types. The normalized root mean square (NRMSE) and the similar spectral value (SSV) of the water-leaving reflectance show reduced accuracy in atmospheric correction results when there is an increase in aerosol loading. This is mainly when the standard aerosol type used is characterized with different optical properties compared to the local aerosol. The results suggest that if a water quality analysis is needed the microphysical properties of the aerosol need to be taken into consideration in the atmospheric correction of hyperspectral data over coastal environments, because aerosols influence the accuracy of the retrieved water-leaving reflectance.

scholarly journals Impact of Various Atmospheric Corrections on Sentinel-2 Land Cover Classification Accuracy Using Machine Learning Classifiers

2020 ◽  
Vol 9 (4) ◽  
pp. 277 ◽  
Author(s):  
Luka Rumora ◽  
Mario Miler ◽  
Damir Medak
Keyword(s):  
Machine Learning ◽  
Land Cover ◽  
Classification Accuracy ◽  
Atmospheric Correction ◽  
Land Cover Classification ◽  
Support Vector ◽  
Atmospheric Effects ◽  
Surface Reflectance ◽  
The Impact ◽  
Sentinel 2

Atmospheric correction is one of the key parts of remote sensing preprocessing because it can influence and change the final classification result. This research examines the impact of five different atmospheric correction processing on land cover classification accuracy using Sentinel-2 satellite imagery. Those are surface reflectance (SREF), standardized surface reflectance (STDSREF), Sentinel-2 atmospheric correction (S2AC), image correction for atmospheric effects (iCOR), dark object subtraction (DOS) and top of the atmosphere (TOA) reflectance without any atmospheric correction. Sentinel-2 images corrected with stated atmospheric corrections were classified using four different machine learning classification techniques namely extreme gradient boosting (XGB), random forests (RF), support vector machine (SVM) and catboost (CB). For classification, five different classes were used: bare land, low vegetation, high vegetation, water and built-up area. SVM classification provided the best overall result for twelve dates, for all atmospheric corrections. It was the best method for both cases: when using Sentinel-2 bands and radiometric indices and when using just spectral bands. The best atmospheric correction for classification with SVM using radiometric indices is S2AC with the median value of 96.54% and the best correction without radiometric indices is STDSREF with the median value of 96.83%.

Research on Atmospheric Correction and Surface Reflectance Inversion of UAV (Unmanned Aerial Vehicle) Remote Sensing Data

2013 ◽  
Vol 427-429 ◽  
pp. 1485-1488 ◽  
Author(s):  
Zhi Le Jia ◽  
Xiao Ping Lu ◽  
Feng Jie Zheng ◽  
Wen Qan Zang ◽  
Qing Chen Liu
Keyword(s):  
Remote Sensing ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Bare Soil ◽  
Surface Reflectance ◽  
Remote Sensing Images ◽  
Quantitative Remote Sensing ◽  
Aerial Vehicle ◽  
Soil Area ◽  
Water Vegetation

Through atmospheric correction of UAV remote sensing images, inversion to obtain surface reflectance, typical objects with measured experimental area water, vegetation and bare soil area reflectance comparative analysis, the experimental results prove the feasibility of using UVA to carry out the quantitative remote sensing research, and its advantages.

scholarly journals EVALUATION OF THE AEROSOL TYPE EFFECT ON THE SURFACE REFLECTANCE RETRIEVAL USING CHRIS/PROBA IMAGES OVER LAND

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1311-1316 ◽  
Author(s):  
C. Tirelli ◽  
C. Manzo ◽  
G. Curci ◽  
C. Bassani
Keyword(s):  
Land Surface ◽  
Transport Model ◽  
Atmospheric Correction ◽  
Hyperspectral Data ◽  
Radiative Transfer Model ◽  
Urban Site ◽  
Transfer Model ◽  
Surface Reflectance ◽  
Aerosol Model ◽  
Aerosol Type

Surface reflectance has a central role in the analysis of land surface for a broad variety of agricultural, geological and urban studies. An accurate atmospheric correction, obtained by an appropriate selection of aerosol type and loading, is the first requirement for a reliable surface reflectance estimation. The aerosol type is defined by its micro-physical properties, while the aerosol loading is described by optical thickness at 550 nm. The aim of this work is to evaluate the radiative impact of the aerosol model on the surface reflectance obtained from CHRIS (Compact High Resolution Imaging Spectrometer) hyperspectral data over land by using the specifically developed algorithm CHRIS@CRI (CHRIS Atmospherically Corrected Reflectance Imagery) based on the 6SV radiative transfer model. Five different aerosol models have been used: one provided by the AERONET inversion products (used as reference), three standard aerosol models in 6SV, and one obtained from the output of the GEOS-Chem global chemistry-transport model (CTM). As test case the urban site of Bruxelles and the suburban area of Rome Tor Vergata have been considered. The results obtained encourages the use of CTM in operational retrieval and provides an evaluation of the role of the aerosol model in the atmospheric correction process, considering the different microphysical properties impact.

scholarly journals EVALUATING THE IMPACT OF LASRC AND SEN2COR ATMOSPHERIC CORRECTION ALGORITHMS ON LANDSAT-8/OLI AND SENTINEL-2/MSI DATA OVER AERONET STATIONS IN BRAZILIAN TERRITORY

2021 ◽  
Vol V-3-2021 ◽  
pp. 271-277
Author(s):  
R. F. B. Marujo ◽  
J. G. Fronza ◽  
A. R. Soares ◽  
G. R. Queiroz ◽  
K. R. Ferreira
Keyword(s):  
Atmospheric Correction ◽  
Open Data ◽  
Image Data ◽  
Data Cube ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Landsat 8 Oli ◽  
Continental Scale ◽  
The Impact ◽  
Sentinel 2

Abstract. Accurate and consistent Surface Reflectance estimation from optical remote sensor observations is directly dependant on the used atmospheric correction processor and the differences caused by it may have implications on further processes, e.g. classification. Brazil is a continental scale country with different biomes. Recently, new initiatives, as the Brazil Data Cube Project, are emerging and using free and open data policy data, more specifically medium spatial resolution sensor images, to create image data cubes and classify the Brazilian territory crops. For this reason, the purpose of this study is to verify, on Landsat-8 and Sentinel-2 images for the Brazilian territory, the suitability of the atmospheric correction processors maintained by their image providers, LaSRC from USGS and Sen2cor from ESA, respectively. To achieve this, we tested the surface reflectance products from Landsat-8 processed through LaSRC and Sentinel-2 processed through LaSRC and Sen2cor comparing to a reference dataset computed by ARCSI and AERONET. The obtained results point that Landsat-8/OLI images atmospherically corrected using the LaSRC corrector are consistent to the surface reflectance reference and other atmospheric correction processors studies, while for Sentinel-2/MSI images, Sen2cor performed best. Although corrections over Sentinel-2/MSI data weren’t as consistent as in Landsat-8/OLI corrections, in comparison to the surface reflectance references, most of the spectral bands achieved acceptable APU results.

scholarly journals Correcciones atmosféricas relativas de imágenes de satélite: patrones invariantes y modelos atmosféricos

2018 ◽  
Vol 36 (1) ◽  
pp. 1
Author(s):  
Fernando Paz Pellat
Keyword(s):  
Spectral Band ◽  
Atmospheric Correction ◽  
Field Measurements ◽  
Atmospheric Model ◽  
Inversion Process ◽  
Aerosol Model ◽  
Soil Line ◽  
Satellite Technology ◽  
Dense Vegetation ◽  
Line Patterns

To use information obtained with satellite technology reliably, it is necessary to eliminate or reduce the disruptive effects associated with the spectral information captured by sensors on space platforms. In this paper we analyze the inversion of radiative models of the atmosphere, which consists in determining the additive and multiplicative constants in each spectral band to make the necessary atmospheric corrections. The methodology proposes the use of invariant patterns of soil lines and dense vegetation for the inversion of radiative models. The results showed that, without knowledge of the atmospheric model or the type of aerosol, soil line data were relatively insufficient (low correlation) to obtain the additive and multiplicative constants of the atmospheric inversions, with problems of multiple solutions in the inversion process. Under similar conditions, the same was found for additive constants with the dense vegetation line, but for the multiplicative constants the results were favorable (R2 > 0.9). In contrast, with the knowledge of the atmospheric model and the aerosol model, estimates of additive and multiplicative constants were highly satisfactory (R2 > 0.99) in both cases. For soil line inversions, only one constraint of the two available was used. In conclusion, the use of invariant soil-line patterns allows us to establish two basic relationships to invert the radiative simulations of the atmosphere, prior to functional compaction, and field measurements can be made so that the proposed atmospheric correction process in this work can be considered in absolute and not relative terms.

The Laryngeal Epithelium in Reflux

2011 ◽  
Vol 21 (3) ◽  
pp. 112-117 ◽  
Author(s):  
Elizabeth Erickson-Levendoski ◽  
Mahalakshmi Sivasankar
Keyword(s):  
Laryngopharyngeal Reflux ◽  
Critical Role ◽  
Structure And Function ◽  
Laryngeal Disease ◽  
Health And Disease ◽  
And Function ◽  
The Impact

The epithelium plays a critical role in the maintenance of laryngeal health. This is evident in that laryngeal disease may result when the integrity of the epithelium is compromised by insults such as laryngopharyngeal reflux. In this article, we will review the structure and function of the laryngeal epithelium and summarize the impact of laryngopharyngeal reflux on the epithelium. Research investigating the ramifications of reflux on the epithelium has improved our understanding of laryngeal disease associated with laryngopharyngeal reflux. It further highlights the need for continued research on the laryngeal epithelium in health and disease.

scholarly journals The lung–gut axis during viral respiratory infections: the impact of gut dysbiosis on secondary disease outcomes

2021 ◽  
Author(s):  
Valentin Sencio ◽  
Marina Gomes Machado ◽  
François Trottein
Keyword(s):  
Gut Microbiota ◽  
Bacterial Infections ◽  
Respiratory Infections ◽  
Critical Role ◽  
Good Health ◽  
Disease Outcomes ◽  
And Function ◽  
Viral Respiratory Infections ◽  
The Impact ◽  
Viral Respiratory

AbstractBacteria that colonize the human gastrointestinal tract are essential for good health. The gut microbiota has a critical role in pulmonary immunity and host’s defense against viral respiratory infections. The gut microbiota’s composition and function can be profoundly affected in many disease settings, including acute infections, and these changes can aggravate the severity of the disease. Here, we discuss mechanisms by which the gut microbiota arms the lung to control viral respiratory infections. We summarize the impact of viral respiratory infections on the gut microbiota and discuss the potential mechanisms leading to alterations of gut microbiota’s composition and functions. We also discuss the effects of gut microbial imbalance on disease outcomes, including gastrointestinal disorders and secondary bacterial infections. Lastly, we discuss the potential role of the lung–gut axis in coronavirus disease 2019.

scholarly journals Methionine Diet Evoked Hyperhomocysteinemia Causes Hippocampal Alterations, Metabolomics Plasma Changes and Behavioral Pattern in Wild Type Rats

2021 ◽  
Vol 22 (9) ◽  
pp. 4961
Author(s):  
Maria Kovalska ◽  
Eva Baranovicova ◽  
Dagmar Kalenska ◽  
Anna Tomascova ◽  
Marian Adamkov ◽  
...  
Keyword(s):  
Morphological Changes ◽  
Brain Area ◽  
Critical Role ◽  
Cerebrovascular Diseases ◽  
Behavioral Pattern ◽  
Cell Physiology ◽  
Male Wistar Rats ◽  
High Level ◽  
Hippocampal Alterations ◽  
The Impact

L-methionine, an essential amino acid, plays a critical role in cell physiology. High intake and/or dysregulation in methionine (Met) metabolism results in accumulation of its intermediate(s) or breakdown products in plasma, including homocysteine (Hcy). High level of Hcy in plasma, hyperhomocysteinemia (hHcy), is considered to be an independent risk factor for cerebrovascular diseases, stroke and dementias. To evoke a mild hHcy in adult male Wistar rats we used an enriched Met diet at a dose of 2 g/kg of animal weight/day in duration of 4 weeks. The study contributes to the exploration of the impact of Met enriched diet inducing mild hHcy on nervous tissue by detecting the histo-morphological, metabolomic and behavioural alterations. We found an altered plasma metabolomic profile, modified spatial and learning memory acquisition as well as remarkable histo-morphological changes such as a decrease in neurons’ vitality, alterations in the morphology of neurons in the selective vulnerable hippocampal CA 1 area of animals treated with Met enriched diet. Results of these approaches suggest that the mild hHcy alters plasma metabolome and behavioural and histo-morphological patterns in rats, likely due to the potential Met induced changes in “methylation index” of hippocampal brain area, which eventually aggravates the noxious effect of high methionine intake.

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