Improved Abel Inversion Method for Analysis of Spectral and Photo-Optical Data of Magnetic Influenced Plasma Flows

2011 ◽  
Author(s):  
Hannes Fulge ◽  
Andreas Knapp ◽  
Ricarda Wernitz ◽  
Christoph Eichhorn ◽  
Georg Herdrich ◽  
...  
Keyword(s):  
Optical Data ◽  
Inversion Method ◽  
Abel Inversion ◽  
Plasma Flows

scholarly journals High-Precision Soil Moisture Mapping Based on Multi-Model Coupling and Background Knowledge, Over Vegetated Areas Using Chinese GF-3 and GF-1 Satellite Data

2020 ◽  
Vol 12 (13) ◽  
pp. 2123 ◽  
Author(s):  
Leran Han ◽  
Chunmei Wang ◽  
Tao Yu ◽  
Xingfa Gu ◽  
Qiyue Liu
Keyword(s):  
Soil Moisture ◽  
High Precision ◽  
Satellite Data ◽  
Solution Method ◽  
Pearson Correlation ◽  
Optimal Solution ◽  
Background Knowledge ◽  
Optical Data ◽  
Inversion Method ◽  
Synthetic Aperture Radar Data

This paper proposes a combined approach comprising a set of methods for the high-precision mapping of soil moisture in a study area located in Jiangsu Province of China, based on the Chinese C-band synthetic aperture radar data of GF-3 and high spatial-resolution optical data of GF-1, in situ experimental datasets and background knowledge. The study was conducted in three stages: First, in the process of eliminating the effect of vegetation canopy, an empirical vegetation water content model and a water cloud model with localized parameters were developed to obtain the bare soil backscattering coefficient. Second, four commonly used models (advanced integral equation model (AIEM), look-up table (LUT) method, Oh model, and the Dubois model) were coupled to acquire nine soil moisture retrieval maps and algorithms. Finally, a simple and effective optimal solution method was proposed to select and combine the nine algorithms based on classification strategies devised using three types of background knowledge. A comprehensive evaluation was carried out on each soil moisture map in terms of the root-mean-square-error (RMSE), Pearson correlation coefficient (PCC), mean absolute error (MAE), and mean bias (bias). The results show that for the nine individual algorithms, the estimated model constructed using the AIEM (mv1) was significantly more accurate than those constructed using the other models (RMSE = 0.0321 cm³/cm³, MAE = 0.0260 cm³/cm³, and PCC = 0.9115), followed by the Oh model (m_v5) and LUT inversion method under HH polarization (mv2). Compared with the independent algorithms, the optimal solution methods have significant advantages; the soil moisture map obtained using the classification strategy based on the percentage content of clay was the most satisfactory (RMSE = 0.0271 cm³/cm³, MAE = 0.0225 cm³/cm³, and PCC = 0.9364). This combined method could not only effectively integrate the optical and radar satellite data but also couple a variety of commonly used inversion models, and at the same time, background knowledge was introduced into the optimal solution method. Thus, we provide a new method for the high-precision mapping of soil moisture in areas with a complex underlying surface.

scholarly journals Aerosol microphysical retrievals from Precision Filter Radiometer direct solar radiation measurements and comparison with AERONET

2014 ◽  
Vol 7 (1) ◽  
pp. 99-130 ◽  
Author(s):  
S. Kazadzis ◽  
I. Veselovskii ◽  
V. Amiridis ◽  
J. Gröbner ◽  
A. Suvorina ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Volume Concentration ◽  
Effective Radius ◽  
Optical Data ◽  
Inversion Method ◽  
High Temporal Resolution ◽  
Random Errors ◽  
Percentage Difference ◽  
Filter Radiometer ◽  
And Inversion

Abstract. Synchronized sun-photometric measurements from the AERONET-CIMEL and GAW-PFR aerosol networks are used to compare retrievals of the aerosol optical depth, effective radius and volume concentration during a high temporal resolution measurement campaign at the Athens site in the Mediterranean Basin from 14–22 July 2009. During this period, direct sun AOD retrievals from both instruments exhibited small differences in the range 0.01–0.02 despite the presence of a strong dust event. In addition to AERONET-CIMEL inversion data, an independent inversion method was applied that involves expanding the particle size distribution in terms of measurement kernels so as to estimate bulk particle parameters from a linear-estimated combination of the input optical data. AOD measurements obtained from both CIMEL and PFR instruments using this method also showed reasonable agreement. For low aerosol loads (AOD < 0.2), measurements of the effective radius by the PFR were found to be −20% to +30% different from CIMEL values for both direct sun data and inversion data. At higher loads (AOD > 0.4), measurements of the effective radius by the PFR are consistently 20% lower than CIMEL for both direct sun and inversion data. Volume concentrations at low aerosol loads from the PFR are up to 80% higher than the CIMEL for direct sun data, but inversion data suggests that volume concentrations from the PFR are up to 20% lower than the CIMEL under these same conditions. At higher loads, the percentage difference in volume concentrations from the PFR and CIMEL is systematically negative with inversion data predicting differences 30% lower than those obtained from direct sun data. An assessment of the effect of errors in the AOD retrieval on the estimation of PFR bulk parameters was made using Monte Carlo simulations and demonstrated that it is possible to estimate the effective radius with an uncertainty below 60% and the volume concentration with an uncertainty below 65% even when AOD < 0.2 and when the input errors are as high as 10%. Highlights – A comparison of high temporal resolution synchronous CIMEL and PFR direct sun AOD measurement retrievals – Calculation of bulk aerosol microphysics parameters using a linear estimation inversion technique – A comparison of retrieved aerosol volume concentrations and effective radii from CIMEL and PFR inversions – An analysis of the sensitivity of PFR retrievals to random errors on the optical input data

Abel‐inversion method for interferometry data in highly noncircular plasmas with X point in TFTR (abstract)

1992 ◽  
Vol 63 (10) ◽  
pp. 4763-4763
Author(s):  
Y. Zhao ◽  
H. K. Park ◽  
M. Bell ◽  
R. Budny
Keyword(s):  
Inversion Method ◽  
Abel Inversion

A generalized Abel inversion method for gamma-ray imaging of thermonuclear plasmas

2016 ◽  
Vol 11 (03) ◽  
pp. C03001-C03001 ◽  
Author(s):  
M. Nocente ◽  
A. Pavone ◽  
M. Tardocchi ◽  
V. Goloborod'ko ◽  
K. Schoepf ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Inversion Method ◽  
Abel Inversion ◽  
Gamma Ray Imaging
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