scholarly journals Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1865
Author(s):  
Gabriel Calassou ◽  
Pierre-Yves Foucher ◽  
Jean-François Léon
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Sequential Method ◽  
Modal Radius ◽  
Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

Nonparametric Methodology to Estimate Precipitating Ice from Multiple-Frequency Radar Reflectivity Observations

2018 ◽  
Vol 57 (11) ◽  
pp. 2605-2622 ◽  
Author(s):  
Mircea Grecu ◽  
Lin Tian ◽  
Gerald M. Heymsfield ◽  
Ali Tokay ◽  
William S. Olson ◽  
...  
Keyword(s):  
Estimation Method ◽  
Optimal Estimation ◽  
Radar Reflectivity ◽  
Nonparametric Method ◽  
Multiple Frequency ◽  
Radar Observations ◽  
Triple Frequency ◽  
Olympic Mountains ◽  
Field Campaigns

AbstractIn this study, a nonparametric method to estimate precipitating ice from multiple-frequency radar observations is investigated. The method does not require any assumptions regarding the distribution of ice particle sizes and relies on an efficient search procedure to incorporate information from observed particle size distributions (PSDs) in the estimation process. Similar to other approaches rooted in optimal-estimation theory, the nonparametric method is robust in the presence of noise in observations and uncertainties in the forward models. Over 200 000 PSDs derived from in situ observations collected during the Olympic Mountains Experiment (OLYMPEX) and Integrated Precipitation and Hydrology Experiment (IPHEX) field campaigns are used in the development and evaluation of the nonparametric estimation method. These PSDs are used to create a database of ice-related variables and associated computed radar reflectivity factors at the Ku, Ka, and W bands. The computed reflectivity factors are used to derive precipitating ice estimates and investigate the associated errors and uncertainties. The method is applied to triple-frequency radar observations collected during OLYMPEX and IPHEX. Direct comparisons of estimated ice variables with estimates from in situ instruments show results consistent with the error analysis. Global application of the method requires an extension of the supporting PSD database, which can be achieved through the processing of information from additional past and future field campaigns.

scholarly journals Global carbon monoxide vertical distributions from spaceborne high-resolution FTIR nadir measurements

2005 ◽  
Vol 5 (11) ◽  
pp. 2901-2914 ◽  
Author(s):  
B. Barret ◽  
S. Turquety ◽  
D. Hurtmans ◽  
C. Clerbaux ◽  
J. Hadji-Lazaro ◽  
...  
Keyword(s):  
High Resolution ◽  
Estimation Method ◽  
Lower Troposphere ◽  
Optimal Estimation ◽  
Vertical Distributions ◽  
Surface Measurements ◽  
The Vertical Distribution ◽  
Global Carbon ◽  
Good Agreement

Abstract. This paper presents the first global distributions of CO vertical profiles retrieved from a thermal infrared FTS working in the nadir geometry. It is based on the exploitation of the high resolution and high quality spectra measured by the Interferometric Monitor of Greenhouse gases (IMG) which flew onboard the Japanese ADEOS platform in 1996-1997. The retrievals are performed with an algorithm based on the Optimal Estimation Method (OEM) and are characterized in terms of vertical sensitivity and error budget. It is found that most of the IMG measurements contain between 1.5 and 2.2 independent pieces of information about the vertical distribution of CO from the lower troposphere to the upper troposphere-lower stratosphere (UTLS). The retrievals are validated against coincident NOAA/CMDL in situ surface measurements and NDSC/FTIR total columns measurements. The retrieved global distributions of CO are also found to be in good agreement with the distributions modeled by the GEOS-CHEM 3D CTM, highlighting the ability of IMG to capture the horizontal as well as the vertical structure of the CO distributions.

scholarly journals MODELING AND CHARACTERIZATION OF OSCILLATOR CIRCUITS BY VAN DER POL MODEL USING PARAMETER ESTIMATION

2012 ◽  
Vol 21 (05) ◽  
pp. 1250043 ◽  
Author(s):  
IULIA DUMITRESCU ◽  
SMAIL BACHIR ◽  
DAVID CORDEAU ◽  
JEAN-MARIE PAILLOT ◽  
MIHAI IORDACHE
Keyword(s):  
Parameter Estimation ◽  
Optimal Parameter ◽  
Estimation Method ◽  
Van Der Pol Oscillator ◽  
Space Representation ◽  
Model Parameters ◽  
Identification Algorithm ◽  
Van Der Pol ◽  
Oscillator Circuit

In this paper, we present a new method for the modeling and characterization of oscillator circuit with a Van Der Pol (VDP) model using parameter identification. We also discussed and investigated the problem of estimation in nonlinear system based on time domain data. The approach is based on an appropriate state space representation of Van der Pol oscillator that allows an optimal parameter estimation. Using sampled output voltage signal, model parameters are obtained by an iterative identification algorithm based on Output Error method. Normalization issues are fixed by an appropriate transformation allowing a quickly global minimum search. Finally, the proposed estimation method is tested and validated using simulation data from a 1 GHz oscillator circuit in GaAs technology.

scholarly journals Validation of stratospheric water vapour measurements from the airborne microwave radiometer AMSOS

2008 ◽  
Vol 8 (1) ◽  
pp. 1635-1671 ◽  
Author(s):  
S. C. Müller ◽  
N. Kämpfer ◽  
D. G. Feist ◽  
A. Haefele ◽  
M. Milz ◽  
...  
Keyword(s):  
Water Vapour ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Horizontal Resolution ◽  
Polar Regions ◽  
Upper Troposphere ◽  
Vertical Range ◽  
Stratospheric Water Vapour

Abstract. We present the validation of a water vapour dataset obtained by the Airborne Microwave Stratospheric Observing System AMSOS, a passive microwave radiometer operating at 183 GHz. Vertical profiles are retrieved from spectra by an optimal estimation method. The useful vertical range lies in the upper troposphere up to the mesosphere with an altitude resolution of 8 to 16 km and a horizontal resolution of about 57 km. Flight campaigns were performed once a year from 1998 to 2006 measuring the latitudinal distribution of water vapour from the tropics to the polar regions. The obtained profiles show clearly the main features of stratospheric water vapour in all latitudinal regions. Data are validated against a set of instruments comprising satellite, ground-based, airborne remote sensing and in-situ instruments. It appears that AMSOS profiles have a dry bias of 3–20%, when compared to satellite experiments. A good agreement with a difference of 3.3% was found between AMSOS and in-situ hygrosondes FISH and FLASH and an excellent matching of the lidar measurements from the DIAL instrument in the short overlap region in the upper troposphere.

scholarly journals Retrieval and mapping of chlorophyll-a concentration from Sentinel-2 images in an urban river in the semiarid region of Brazil

2020 ◽  
Vol 15 (2) ◽  
pp. 1
Author(s):  
Alessandro Rhadamek Alves Pereira ◽  
João Batista Lopes ◽  
Giovana Mira de Espindola ◽  
Carlos Ernando da Silva
Keyword(s):  
Chlorophyll A ◽  
River Mouth ◽  
Water Quality Monitoring ◽  
Semiarid Region ◽  
Surface Reflectance ◽  
Chlorophyll A Concentration ◽  
In Situ Data ◽  
Sentinel 2A ◽  
Sentinel 2

Recently, the Poti river mouth region has experienced environmental impacts that resulted in a change of landscape in its dry season, highlighting the eutrophication and proliferation of phytoplankton, algae, cyanobacteria and aquatic plants. Considering the aspects related to water-quality monitoring in the semiarid region of Brazil from remote sensing, this study aimed to evaluate the performance of Sentinel-2A satellite data in the retrieval of chlorophyll-a concentration in Poti River in Teresina, Piaui, Brazil. The chlorophyll-a concentration retrieval and mapping methodology involved the study of the water surface reflectance in Sentinel-2A images and their correlation with the chlorophyll-a data collected in situ during the years 2016 and 2017. The results generated by the Chl-1, Ha et al. (2017), Chl-2, Page et al. (2018), and Chl-3, Kuhn et al. (2019) equations show the need for calibrating the algorithms used for the Poti River water components. However, the empirical algorithm Chl-2 shows a correlation has been established to identify the spatiotemporal variation of chlorophyll-a concentration along the Poti River broadly and not punctually. The spatial distribution of this pigment in maps derived from Sentinel-2A is consistent with the pattern of occurrence determined by the in situ data. Therefore, the MSI sensor proved to be a tool suitable for the retrieval and monitoring of chlorophyll-a concentration along the Poti River.

Motion Model Parameters Estimation for Electronic Image Stabilization Instrument

2013 ◽  
Vol 325-326 ◽  
pp. 1543-1546
Author(s):  
Xun Yu Zhong ◽  
Tian Hui Ren
Keyword(s):  
Motion Estimation ◽  
Least Squares Method ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Block Matching ◽  
Parameters Estimation ◽  
Transformation Model ◽  
Image Motion ◽  
Model Parameters ◽  
Image Stabilization

Fast and optimal motion estimation method is proposed for electronic image stabilization. First, an approach for macro-block judgment is presented. Before motion vectors calculation, gradient information is analyzed, only useful reference blocks that are indispensable for accurate motion estimation are selected, by which the number of macro-blocks for subsequent calculation is reduced. Second, in the block matching, an improved SSDA is used to reduce computing cost. Finally, the affine transformation model and similarity transformation model of image motion are created and using least squares method for solving the optimal estimation of model parameters. Experimental results show the accuracy and fast computing speed of the proposed method.

scholarly journals Semi-Empirical Capacity Fading Model for SoH Estimation of Li-Ion Batteries

2019 ◽  
Vol 9 (15) ◽  
pp. 3012 ◽  
Author(s):  
Preetpal Singh ◽  
Che Chen ◽  
Cher Ming Tan ◽  
Shyh-Chin Huang
Keyword(s):  
Lithium Ion Battery ◽  
Estimation Method ◽  
Lithium Ion ◽  
Model Parameters ◽  
Capacity Fading ◽  
Discharge Cycle ◽  
On Line ◽  
Semi Empirical

A fast and accurate capacity estimation method for lithium-ion batteries is developed. This method applies our developed semi-empirical model to a discharge curve of a lithium-ion battery for the determination of its maximum stored charge capacity after each discharge cycle. This model provides an accurate state-of-health (SoH) estimation with a difference of less than 2.22% when compared with the electrochemistry-based electrical (ECBE) SoH calculation. The model parameters derived from a lithium-ion battery can also be applied to other cells in the same pack with less than 2.5% difference from the complex ECBE model, showing the extendibility of the model. The parameters (k1, k2, and k3) calculated in the work can also be used to study the changes in battery internal structure, such as capacity losses at normal conditions, as well as cycling at high temperatures. The time for estimation after each discharge cycle is only 5 s, making it is suitable for on-line in-situ estimation.

scholarly journals Validation of Space-Based Albedo Products from Upscaled Tower-Based Measurements Over Heterogeneous and Homogeneous Landscapes

2020 ◽  
Vol 12 (5) ◽  
pp. 833
Author(s):  
Rui Song ◽  
Jan-Peter Muller ◽  
Said Kharbouche ◽  
Feng Yin ◽  
William Woodgate ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Albedo ◽  
Spatial Scales ◽  
Atmospheric Correction ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Hemispherical Reflectance ◽  
Land Surfaces ◽  
Sentinel 2

Surface albedo is a fundamental radiative parameter as it controls the Earth’s energy budget and directly affects the Earth’s climate. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their continuous global coverage. However, space-based albedo products are often affected by errors in the atmospheric correction, multi-angular bi-directional reflectance distribution function (BRDF) modelling, as well as spectral conversions. To validate space-based albedo products, an in situ tower albedometer is often used to provide continuous “ground truth” measurements of surface albedo over an extended area. Since space-based albedo and tower-measured albedo are produced at different spatial scales, they can be directly compared only for specific homogeneous land surfaces. However, most land surfaces are inherently heterogeneous with surface properties that vary over a wide range of spatial scales. In this work, tower-measured albedo products, including both directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), are upscaled to coarse satellite spatial resolutions using a new method. This strategy uses high-resolution satellite derived surface albedos to fill the gaps between the albedometer’s field-of-view (FoV) and coarse satellite scales. The high-resolution surface albedo is generated from a combination of surface reflectance retrieved from high-resolution Earth Observation (HR-EO) data and moderate resolution imaging spectroradiometer (MODIS) BRDF climatology over a larger area. We implemented a recently developed atmospheric correction method, the Sensor Invariant Atmospheric Correction (SIAC), to retrieve surface reflectance from HR-EO (e.g., Sentinel-2 and Landsat-8) top-of-atmosphere (TOA) reflectance measurements. This SIAC processing provides an estimated uncertainty for the retrieved surface spectral reflectance at the HR-EO pixel level and shows excellent agreement with the standard Landsat 8 Surface Reflectance Code (LaSRC) in retrieving Landsat-8 surface reflectance. Atmospheric correction of Sentinel-2 data is vastly improved by SIAC when compared against the use of in situ AErosol RObotic NETwork (AERONET) data. Based on this, we can trace the uncertainty of tower-measured albedo during its propagation through high-resolution EO measurements up to coarse satellite scales. These upscaled albedo products can then be compared with space-based albedo products over heterogeneous land surfaces. In this study, both tower-measured albedo and upscaled albedo products are examined at Ground Based Observation for Validation (GbOV) stations (https://land.copernicus.eu/global/gbov/), and used to compare with satellite observations, including Copernicus Global Land Service (CGLS) based on ProbaV and VEGETATION 2 data, MODIS and multi-angle imaging spectroradiometer (MISR).

scholarly journals Evaluation of Surface Reflectance Products Based on Optimized 6S Model Using Synchronous In Situ Measurements

2021 ◽  
Vol 14 (1) ◽  
pp. 83
Author(s):  
Xiaocheng Zhou ◽  
Xueping Liu ◽  
Xiaoqin Wang ◽  
Guojin He ◽  
Youshui Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Landsat 8 Oli ◽  
Auxiliary Data ◽  
Sentinel 2

Surface reflectance (SR) estimation is the most essential preprocessing step for multi-sensor remote sensing inversion of geophysical parameters. Therefore, accurate and stable atmospheric correction is particularly important, which is the premise and basis of the quantitative application of remote sensing. It can also be used to directly compare different images and sensors. The Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi-Spectral Instrument (MSI) surface reflectance products are publicly available and demonstrate high accuracy. However, there is not enough validation using synchronous spectral measurements over China’s land surface. In this study, we utilized Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric products reconstructed by Categorical Boosting (CatBoost) and 30 m ASTER Global Digital Elevation Model (ASTER GDEM) data to adjust the relevant parameters to optimize the Second Simulation of Satellite Signal in the Solar Spectrum (6S) model. The accuracy of surface reflectance products obtained from the optimized 6S model was compared with that of the original 6S model and the most commonly used Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) model. Surface reflectance products were validated and evaluated with synchronous in situ measurements from 16 sites located in five provinces of China: Fujian, Gansu, Jiangxi, Hunan, and Guangdong. Through the indirect and direct validation across two sensors and three methods, it provides evidence that the synchronous measurements have the higher and more reliable validation accuracy. The results of the validation indicated that, for Landsat-8 OLI and Sentinel-2 MSI SR products, the overall root mean square error (RMSE) calculated results of optimized 6S, original 6S and FLAASH across all spectral bands were 0.0295, 0.0378, 0.0345, and 0.0313, 0.0450, 0.0380, respectively. R2 values reached 0.9513, 0.9254, 0.9316 and 0.9377, 0.8822, 0.9122 respectively. Compared with the original 6S model and FLAASH model, the mean percent absolute error (MPAE) of the optimized 6S model was reduced by 32.20% and 15.86% for Landsat-8 OLI, respectively. On the other, for the Sentinel-2 MSI SR product, the MPAE value was reduced by 33.56% and 33.32%. For the two kinds of data, the accuracy of each band was improved to varying extents by the optimized 6S model with the auxiliary data. These findings support the hypothesis that reliable auxiliary data are helpful in reducing the influence of the atmosphere on images and restoring reality as much as is feasible.

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