Near-surface sensitivity suppression way for diffuse reflective optical tomography: simulation and a phantom study

2007 ◽  
Author(s):  
Keiko Fukuda ◽  
Mamiko Fujii
Keyword(s):  
Optical Tomography ◽  
Phantom Study ◽  
Near Surface ◽  
Surface Sensitivity

Transient electromagnetic smoke rings in a halfspace during active transmitter excitation

Geophysics ◽  
2021 ◽  
pp. 1-38
Author(s):  
Adam Smiarowski ◽  
Greg Hodges
Keyword(s):  
Current Distribution ◽  
Current System ◽  
Primary Field ◽  
Depth Of Penetration ◽  
Near Surface ◽  
Surface Sensitivity ◽  
Field Coupling ◽  
Transient Electromagnetic ◽  
Smoke Ring ◽  
Off Time

The smoke ring concept is a useful device for understanding how the electromagnetic fields induced in a 1-D earth propagate and diffuse through a medium. Aside from facilitating a physical understanding of field propagation, the smoke ring concept has been used to interpret behavior of vertical and radial magnetic fields at the surface and used to estimate depth of penetration for conductivity-depth transforms. Past studies have focused on the current distribution during the off-time. We calculate and illustrate the current in a halfspace from a half-sine excitation (which provides a continuous induction). In comparison, the current pattern from a continuously excited waveform is more densely distributed near-surface than the off-time current system, suggesting that measurements during a continuously excited on-time are more sensitive to shallow targets. For airborne applications, where the primary field coupling changes and is an important noise source, a primary field-stripping algorithm impacts the current distribution but does not deleteriously affect near-surface sensitivity.

scholarly journals Assessing the near surface sensitivity of SCIAMACHY atmospheric CO<sub>2</sub> retrieved using (FSI) WFM-DOAS

2007 ◽  
Vol 7 (13) ◽  
pp. 3597-3619 ◽  
Author(s):  
M. P. Barkley ◽  
P. S. Monks ◽  
A. J. Hewitt ◽  
T. Machida ◽  
A. Desai ◽  
...  
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Correlation Coefficients ◽  
The United States ◽  
Atmospheric Co2 ◽  
Carbon Surface ◽  
Near Surface ◽  
Surface Sensitivity ◽  
Vegetation Activity

Abstract. Satellite observations of atmospheric CO2 offer the potential to identify regional carbon surface sources and sinks and to investigate carbon cycle processes. The extent to which satellite measurements are useful however, depends on the near surface sensitivity of the chosen sensor. In this paper, the capability of the SCIAMACHY instrument on board ENVISAT, to observe lower tropospheric and surface CO2 variability is examined. To achieve this, atmospheric CO2 retrieved from SCIAMACHY near infrared (NIR) spectral measurements, using the Full Spectral Initiation (FSI) WFM-DOAS algorithm, is compared to in-situ aircraft observations over Siberia and additionally to tower and surface CO2 data over Mongolia, Europe and North America. Preliminary validation of daily averaged SCIAMACHY/FSI CO2 against ground based Fourier Transform Spectrometer (FTS) column measurements made at Park Falls, reveal a negative bias of about −2.0% for collocated measurements within ±1.0° of the site. However, at this spatial threshold SCIAMACHY can only capture the variability of the FTS observations at monthly timescales. To observe day to day variability of the FTS observations, the collocation limits must be increased. Furthermore, comparisons to in-situ CO2 observations demonstrate that SCIAMACHY is capable of observing a seasonal signal that is representative of lower tropospheric variability on (at least) monthly timescales. Out of seventeen time series comparisons, eleven have correlation coefficients of 0.7 or more, and have similar seasonal cycle amplitudes. Additional evidence of the near surface sensitivity of SCIAMACHY, is provided through the significant correlation of FSI derived CO2 with MODIS vegetation indices at over twenty selected locations in the United States. The SCIAMACHY/MODIS comparison reveals that at many of the sites, the amount of CO2 variability is coincident with the amount of vegetation activity. The presented analysis suggests that SCIAMACHY has the potential to detect CO2 variability within the lowermost troposphere arising from the activity of the terrestrial biosphere.

scholarly journals Assessing the near surface sensitivity of SCIAMACHY atmospheric CO<sub>2</sub> retrieved using (FSI) WFM-DOAS

2007 ◽  
Vol 7 (1) ◽  
pp. 2477-2530 ◽  
Author(s):  
M. P. Barkley ◽  
P. S. Monks ◽  
A. J. Hewitt ◽  
T. Machida ◽  
A. Desai ◽  
...  
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Correlation Coefficients ◽  
The United States ◽  
Atmospheric Co2 ◽  
Carbon Surface ◽  
Near Surface ◽  
Surface Sensitivity ◽  
Vegetation Activity

Abstract. Satellite observations of atmospheric CO2 offer the potential to identify regional carbon surface sources and sinks and to investigate carbon cycle processes. The extent to which satellite measurements are useful however, depends on the near surface sensitivity of the chosen sensor. In this paper, the capability of the SCIAMACHY instrument on board ENVISAT, to observe lower tropospheric and surface CO2 variability is examined. To achieve this, atmospheric CO2 retrieved from SCIAMACHY near infrared (NIR) spectral measurements, using the Full Spectral Initiation (FSI) WFM-DOAS algorithm, is compared to in situ aircraft observations over Siberia and additionally to tower and surface CO2 data over Mongolia, Europe and North America. Preliminary validation of daily averaged SCIAMACHY/FSI CO2 against ground based Fourier Transform Spectrometer (FTS) column measurements made at Park Falls, reveal a negative bias of about −2.0% for collocated measurements within ±1.0\\degree of the site. However, at this spatial threshold SCIAMACHY can only capture the variability of the FTS observations at monthly timescales. To observe day to day variability of the FTS observations, the collocation limits must be increased. Furthermore, comparisons to in-situ CO2 observations demonstrate that SCIAMACHY is capable of observing lower tropospheric variability on (at least) monthly timescales. Out of seventeen time series comparisons, eleven have correlation coefficients of 0.7 or more, and have similar seasonal cycle amplitudes. Additional evidence of the near surface sensitivity of SCIAMACHY, is provided through the significant correlation of FSI derived CO2 with MODIS vegetation indices at over twenty selected locations in the United States. The SCIAMACHY/MODIS comparison reveals that at many of the sites, the amount of CO2 variability is coincident with the amount of vegetation activity. It is evident, from this analysis, that SCIAMACHY therefore has the potential to detect CO2 variability within the lowermost troposphere arising from the activity of the terrestrial biosphere.

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