Data

AGL - 2013 Gloucester Airborne Survey

data.gov.au
Bioregional Assessment Program (Owned by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://data.gov.au/data/dataset/9ff9f257-cfa0-4f50-a7e0-ec0c279d45a3&rft.title=AGL - 2013 Gloucester Airborne Survey&rft.identifier=5cffc19a-0ff4-402c-824a-88935f70931a&rft.publisher=data.gov.au&rft.description=AGL - 2013 Gloucester Airborne Survey - Data File## **Abstract** \n\nThis dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. \n\n\n\nCollect Magnetic and Radiometric data over the Gloucester Basin in PEL285 - AGL\n\n## **Dataset History** \n\nAirborne Survey (Heli).\n\n\n\n_____________________________________________________________________\n\n \n\n \t\t\t Thomson Aviation Pty. Ltd. \n\n _______________________________________________________________________________\n\n \n\n \t\t\tGEOPHYSICAL SURVEY DATA REPORT\n\n _______________________________________________________________________________\n\n \n\n\t\t\t\t\t\t\tDate : 28 July 2013\n\n\n\n\n\n This readme file describes the equipment and specifications of a geophysical\n\n airborne survey conducted by Thomson Aviation Pty. Ltd. \n\n The readme also summarises the data processing parameters and procedures used.\n\n\n\n \n\n \n\n \n\n CLIENT DETAILS \n\n --------------- \n\n Company Flown by : Thomson Aviation Pty. Ltd\n\n Company Processed: Thomson Aviation Pty. Ltd\n\n Client : AGL Energy Limited\n\n Company Job : Thomson 13018\n\n \n\n \n\n\n\n AIRBORNE SURVEY EQUIPMENT:\n\n -------------------------\n\n \n\n Aircraft : Bell Jet Ranger\n\n Magnetometer : Geometrics G822A\n\n Magnetometer Resolution : 0.001 nT\n\n Magnetometer Compensation : Post Flight\n\n Magnetometer Sample Interval : 0.05 seconds Hz \n\n Data Acquisition : GeOZ Model 2010\n\n Spectrometer : Radiation Solutions RS 500\n\n Crystal Size : 16.5 lt downward array\n\n Spectrometer Sample Interval : 1 seconds \n\n GPS Navigation System : Novatel OEMV-1VBS GPS Receiver\n\n \n\n \n\n AIRBORNE SURVEY SPECIFICATIONS\n\n ------------------------------\n\n \n\n \n\n Area: Gloucester, NSW\n\n \n\n Flight Line Direction : 090 - 270 degrees\n\n Flight Line Separation : 50 metres\n\n Tie Line Direction : 180 - 000 degrees\n\n Tie Line Separation : 500 metres\n\n Terrain Clearance : 35 metres (MTC)\n\n Survey flown : June 2013\n\n\n\n DATUM and PROJECTION\n\n --------------------\n\n \n\n Datum : GDA94\n\n Projection : MGA56\n\n\n\n \n\n \n\n RADIOMETRIC PROCESSING PARAMETERS:\n\n ----------------------------------------\n\n \n\n Tot.Count Potassium Uranium Thorium\n\n Height Attn 0.007434 0.009432 0.008428 0.007510 \n\n CPS to Eq 29.601 111.508 10.833 5.940\n\n \n\n \n\n RADIOMETRIC STRIPPING RATIOS:\n\n ------------------------------\n\n\n\n Alpha = 0.276\t\ta = 0.048 \n\n\t\tBeta = 0.418\t\tb = 0.003 \n\n\t\tGamma = 0.759\t\tg = 0.001 \n\n\n\n\n\n_____________________________________________________________________________________________\n\n \n\n\t\t\t\tDATA PROCESSING : MAGNETIC DATA\n\n_____________________________________________________________________________________________\n\n\n\n____________________________________\n\n\n\n MAGNETIC PROCESSING FLOW\n\n____________________________________\n\n\n\n\n\nThe final magnetic data processing was performed using the following processing flow:\n\n\t- Aircraft magnetic data QC\n\n\t- Diurnal magnetic data QC\n\n\t- System parallax removal\n\n\t- Diurnal variation removal and addition of the mean diurnal base value\n\n\t- IGRF removal and addition of mean IGRF value.\n\n\t- levelling using polynomial Tie line levelling, \n\n\t- Micro levelling if required\n\n\t- Reduction to the pole.\n\n\t- Gridding using Minimum Curvature algorithm \n\n\n\n\n\nMAGNETIC QUALITY CONTROL\n\n------------------------\n\nThe processing of the magnetic data firstly involved the routine quality control in the field \n\nof both the aeromagnetic and diurnal data during the acquisition phase. Any data found not \n\nmeeting the required specifications were reflown. \n\n\n\n\n\nMAGNETIC PARALLAX CORRECTION\n\n----------------------------\n\nThe total magnetic intensity aircraft data was firstly corrected for the effects of system \n\nparallax. The parallax parameters were determined and checked from the results of opposing \n\ntest line flights.\n\n\n\n\n\nMAGNETIC DIURNAL CORRECTION\n\n---------------------------\n\nThe base station magnetometer data was edited and merged into the main database. The \n\naeromagnetic data was corrected for diurnal variations by subtracting the observed magnetic \n\nbase station deviations. There were no magnetic storms recorded by the diurnal monitoring \n\nstation during the survey. The mean value was then added back to the data. \n\n\n\n\n\nMAGNETIC IGRF CORRECTION\n\n------------------------\n\nThe data was corrected for the regional gradient of the International Geomagnetic Reference \n\nField (IGRF). The IGRF was calculated for every point along the lines with respect to\n\nGPS height using the IGRF Model for 2005 with secular variation applied. The mean IGRF \n\nvalue was then added back to the data.\n\n\n\n\n\nMAGNETIC PROFILE LEVELLING\n\n--------------------------\n\nThe magnetic traverse line data was then statistically levelled from the tie line data using \n\nIntrepid polynomial levelling. The steps involved in the tie line levelling were as \n\nfollows: \n\n\n\n\t- A primary tie line was chosen as a reference tie.\n\n\t- All other ties were levelled to this tie line using 1st degree polynomial adjustment.\n\n\t- lines were adjusted individually to minimize crossover differences, using 2nd degree \n\n \t polynomial adjustments.\n\n\n\nAny residual flight line effects were removed using Intrepid micro levelling techniques and \n\nthe resultant line data saved as a separate field.\n\n\n\n\n\nMAGNETIC GRIDDING\n\n-----------------\n\nThe data was gridded to a cell size of 20% of line spacing using a Minimum Curvature algorithm.\n\n\n\n\n\n\n\n_____________________________________________________________________________________________\n\n \n\n\t\t\tDATA PROCESSING : RADIOMETRIC DATA\n\n_____________________________________________________________________________________________\n\n\n\n \n\n\n\n____________________________________\n\n\n\n RADIOMETRIC PROCESSING FLOW \n\n____________________________________\n\n \n\nRadiometric data processing consists of the following processing flow:\n\n\n\n\n\n\tFull spectrum 256 channel Overview:\n\n\n\n\n\n\t- Noise Adjusted Singular Value Deconvolution (NASVD) noise reduction \n\n\t- Dead Time correction \n\n\t- Energy calibration \n\n\t- Cosmic and Aircraft background Removal.\n\n\t- Radon background Removal \n\n\t- Extraction of IAEA Window data\n\n\n\n\n\n\tWindowed data processing Overview:\n\n\n\n\t- Compton Stripping correction.\n\n\t- Height Attenuation correction using IAEA coefficients. \n\n\t- Gridding\n\n\n\nThe specific processing steps are described below:\n\n\n\n\n\n____________________________________\n\n\n\n 256 CHANNEL PROCESSING\n\n____________________________________\n\n\n\n\n\nNASVD Noise Reduction:\n\n---------------------\n\nNoise-Adjusted Singular Value Decomposition (NASVD) Smoothing. Correction of the radiometric \n\ndata involved the reduction of the 256 channels of raw gamma spectrometer data using Noise-Adjusted\n\nSingular Value Decomposition (NASVD) noise reduction method. The signal to noise ratio of the \n\nmulti channel spectra can be substantially enhanced using Noise-Adjusted Singular Value \n\nDecomposition (NASVD) as described by Hovgaard and Grasty (1997), Schneider (1998) and Minty (1998). \n\nThis method involves a general linear transformation of groups of spectra (a whole line or flight), \n\nusing NASVD to compute the different spectral shapes that make up the measured multi-channel \n\nspectra. New multi-channel spectra are created by recombining the statistically significant \n\nspectral components. Each spectral component contributes an unequal amount to the features \n\nobserved in the measured multi-channel spectrum, until a point is reached where the spectral \n\ncomponents represent only noise.\n\n\n\nThe 1st spectral component is the spectral shape that represents most of the features in the \n\nmeasured multi-channel spectra. The 2nd spectral component represents those features not \n\ndescribed by the 1st spectral component, etc. By excluding from the recombination those spectral \n\ncomponents that do not represent significant features in the measured multi-channel spectra, the \n\nresulting reconstructed multi-channel spectra have a much larger signal to noise ratio than the \n\nmeasured multi-channel spectra.\n\n \n\n\n\nDead Time Corrections:\n\n----------------------\n\nThe raw 256 channel spectra were corrected for spectrometer dead time using the recorded live time \n\nand the standard formula.\n\n\t\t\t\n\n\t\tN = n / (1 - t) \n\n\t\n\n\tN\t= \tcorrected counts in each second;\n\n\tn\t=\tall counts processed in each second by the ADC; and\n\n\tt\t=\tthe recorded dead time\n\n\n\nWhere the live time (L) is recorded, the dead time t is replaced by (1 - L).\n\n\n\n\n\nEnergy Calibration:\n\n-------------------\n\nEnergy calibration was undertaken line by line using a maximum of 3 calibration peaks; and a \n\nminimum of 2 calibration peaks dependent upon their clear identification in the spectra. The 3 \n\ncalibration peaks used were Bi 214 at 0.609 Mev, K-40 at 1.46 Mev and Tl-208 at 2.615 Mev\n\n\n\n\n\nCosmic and Aircraft Background Correction: \n\n------------------------------------------\n\nCosmic and aircraft background removal utilised the data recorded from a series of calibration flights \n\nover water. These flight produce a normalised cosmic spectra for the system installation, together with\n\na 256ch spectra for the aircraft background.\n\nThe combined correction is calculated using:\n\n\n\n\tN\t=\ta + bC,\n\nwhere:\n\n\tN\t=\tthe combined cosmic and aircraft background in each spectral window;\n\n\ta\t=\tthe aircraft background in the window \n\n\tC\t=\tthe cosmic channel count; and\n\n\tb\t=\tthe cosmic stripping factor for the window.\n\n\n\nThe values of a and b for each window are determined from the calibration flights over the sea. \n\nCosmic coefficients and aircraft background coefficients were derived using INTREPID CAL256 program. \n\n\n\n\n\nAtmospheric Radon: \n\n------------------\n\nThe influence of atmospheric radon has been minimised using the spectral ratio method described by \n\nMinty (1992). However the effect of radon in the Uranium channel can be considerable; and some \n\neffects of the radon are visable in the character of the final processed data. \n\n \n\n\n\nExtraction of Four Standard Windows:\n\n------------------------------------\n\nThe fully processed 256 channel spectra were reduced to the four IAEA (1991) standard windows or \n\nRegions of Interest (ROI): As given by the following Energy windows and channel numbers:\n\n\n\n\tTotal Count\t0.41 to\t2.81 Mev (channels 33 to 238)\n\n\tPotassium\t1.37 to\t1.57 Mev (channels 116 to 133)\n\n\tUranium \t1.66 to\t1.86 Mev (channels 140 to 158)\n\n\tThorium \t2.41 to\t2.81 Mev (channels 205 to 238)\n\n\n\n\n\n____________________________________\n\n\n\n\tWINDOW PROCESSING\n\n____________________________________\n\n\n\n\n\nSpectral Stripping of Standard Window Data:\n\n-------------------------------------------\n\n\n\nCorrections for Compton stripping and height attenuation were applied to the windowed \n\ndata using constants supplied by Radiation Solutions Inc. \n\nDue to scattering of gamma rays in the air, the three principle stripping ratios \n\n( Alpha, Beta and Gamma) increase with altitude above the ground:\n\n\n\nStripping Ratio\tIncrease at STP per metre\n\n \t Alpha 0.00049\n\n \t Beta 0.00065\n\n \t Gamma 0.00069\n\n\n\nFollowing adjustment of the stripping ratios for altitude, the technique for producing the corrected \n\n(stripped) count rates in the potassium, uranium and thorium channels (NKC, NUC and NThC) are given \n\nby Grasty and Minty (1995)\n\n\n\nThe Compton coefficients for the system are given above: \n\n\t\n\n\t\n\n \n\nHeight Corrections\n\n-------------------\n\nThe stripped count rates vary exponentially with aircraft altitude. Adjustments for variation \n\nin altitude were made using the formula:\n\n\n\n\tNc\t= No e^ -u(H-h)\n\n\n\nWhere \tNo\t= uncorrected counts,\n\n\tNc\t= count rate normalised to height H,\n\n\th\t= measured height above the ground,\n\n\tH\t= nominal flight height,\n\n\tu\t= attenuation coefficient for the channel being corrected.\n\n\n\n\n\nCalculation of Effective Height\n\n-------------------------------\n\nThe Effective Height, which is the aircraft terrain clearance corrected to Standard Temperature \n\nand Pressure was determined as follows:\n\n\n\n\t- Filtering of the temperature field was applied to remove spikes and smooth out the \n\n\t instrument noise.\n\n\t- Filtering of the barometric pressure field was applied to remove spikes and to smooth \n\n\t out the instrument noise.\n\n\t- Filtering of the radar altimeter was applied to remove spikes, spurious reflections from\n\n \t groups of tree and very narrow gullies and to smooth out the instrument noise.\n\n\t- The formula option in the spread sheet editor was used to combine the terrain clearance,\n\n \t pressure and temperature.\n\n\n\n\t\t\th x P x 273\n\n\tE_height = _____________________\n\n\t\t\t1013 x (T + 273)\n\n\tWhere:\n\n\n\n\tE_height=\tthe effective height;\n\n\th\t=\tthe observed radar altitude in metres;\n\n\tT\t=\tthe measured air temperature in degrees C;\n\n\tP\t=\tthe barometric pressure in millibars.\n\n\n\nReduction to Ground Concentrations:\n\n-----------------------------------\n\n\n\nThe fully corrected window data is then converted to effective ground concentrations by dividing \n\nby the conversion coefficient to produce the following equivalent concentrations for each element.\n\n \n\n\tTotal Count\t: Dose Rate\n\n\tPotassium\t: Percent\n\n\tUranium\t \t: PPM\n\n\tThorium \t: PPM\n\n\n\n\n\nRadiometric gridding\n\n---------------------\n\nThe data was gridded to a cell size of 20% of line spacing using a Minimum Curvature algorithm.\n\n## **Dataset Citation** \n\nAGL (2014) AGL - 2013 Gloucester Airborne Survey. Bioregional Assessment Source Dataset. Viewed 31 May 2018, http://data.bioregionalassessments.gov.au/dataset/5cffc19a-0ff4-402c-824a-88935f70931a.&rft.creator=Bioregional Assessment Program&rft.date=2022&rft.coverage=POLYGON ((0 0, 0 0, 0 0, 0 0))&rft_rights=Creative Commons Attribution 3.0 Australia, http://creativecommons.org/licenses/by/3.0/au/, (c) AGL Energy Ltd&rft_subject=Gloucester subregion&rft_subject=New South Wales&rft_subject=elevation&rft_subject=geoscientificInformation&rft_subject=imageryBaseMapsEarthCover&rft_subject=planningCadastre&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 3.0 Australia, Http://creativecommons.org/licenses/by/3.0/au/, (c) Agl Energy Ltd

Creative Commons Attribution 3.0 Australia, http://creativecommons.org/licenses/by/3.0/au/, (c) AGL Energy Ltd

Brief description

## **Abstract**

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.



Collect Magnetic and Radiometric data over the Gloucester Basin in PEL285 - AGL

## **Dataset History**

Airborne Survey (Heli).



_____________________________________________________________________



\t\t\t Thomson Aviation Pty. Ltd.

_______________________________________________________________________________



\t\t\tGEOPHYSICAL SURVEY DATA REPORT

_______________________________________________________________________________



\t\t\t\t\t\t\tDate : 28 July 2013





This readme file describes the equipment and specifications of a geophysical

airborne survey conducted by Thomson Aviation Pty. Ltd.

The readme also summarises the data processing parameters and procedures used.









CLIENT DETAILS

---------------

Company Flown by : Thomson Aviation Pty. Ltd

Company Processed: Thomson Aviation Pty. Ltd

Client : AGL Energy Limited

Company Job : Thomson 13018







AIRBORNE SURVEY EQUIPMENT:

-------------------------



Aircraft : Bell Jet Ranger

Magnetometer : Geometrics G822A

Magnetometer Resolution : 0.001 nT

Magnetometer Compensation : Post Flight

Magnetometer Sample Interval : 0.05 seconds Hz

Data Acquisition : GeOZ Model 2010

Spectrometer : Radiation Solutions RS 500

Crystal Size : 16.5 lt downward array

Spectrometer Sample Interval : 1 seconds

GPS Navigation System : Novatel OEMV-1VBS GPS Receiver





AIRBORNE SURVEY SPECIFICATIONS

------------------------------





Area: Gloucester, NSW



Flight Line Direction : 090 - 270 degrees

Flight Line Separation : 50 metres

Tie Line Direction : 180 - 000 degrees

Tie Line Separation : 500 metres

Terrain Clearance : 35 metres (MTC)

Survey flown : June 2013



DATUM and PROJECTION

--------------------



Datum : GDA94

Projection : MGA56







RADIOMETRIC PROCESSING PARAMETERS:

----------------------------------------



Tot.Count Potassium Uranium Thorium

Height Attn 0.007434 0.009432 0.008428 0.007510

CPS to Eq 29.601 111.508 10.833 5.940





RADIOMETRIC STRIPPING RATIOS:

------------------------------



Alpha = 0.276\t\ta = 0.048

\t\tBeta = 0.418\t\tb = 0.003

\t\tGamma = 0.759\t\tg = 0.001





_____________________________________________________________________________________________



\t\t\t\tDATA PROCESSING : MAGNETIC DATA

_____________________________________________________________________________________________



____________________________________



MAGNETIC PROCESSING FLOW

____________________________________





The final magnetic data processing was performed using the following processing flow:

\t- Aircraft magnetic data QC

\t- Diurnal magnetic data QC

\t- System parallax removal

\t- Diurnal variation removal and addition of the mean diurnal base value

\t- IGRF removal and addition of mean IGRF value.

\t- levelling using polynomial Tie line levelling,

\t- Micro levelling if required

\t- Reduction to the pole.

\t- Gridding using Minimum Curvature algorithm





MAGNETIC QUALITY CONTROL

------------------------

The processing of the magnetic data firstly involved the routine quality control in the field

of both the aeromagnetic and diurnal data during the acquisition phase. Any data found not

meeting the required specifications were reflown.





MAGNETIC PARALLAX CORRECTION

----------------------------

The total magnetic intensity aircraft data was firstly corrected for the effects of system

parallax. The parallax parameters were determined and checked from the results of opposing

test line flights.





MAGNETIC DIURNAL CORRECTION

---------------------------

The base station magnetometer data was edited and merged into the main database. The

aeromagnetic data was corrected for diurnal variations by subtracting the observed magnetic

base station deviations. There were no magnetic storms recorded by the diurnal monitoring

station during the survey. The mean value was then added back to the data.





MAGNETIC IGRF CORRECTION

------------------------

The data was corrected for the regional gradient of the International Geomagnetic Reference

Field (IGRF). The IGRF was calculated for every point along the lines with respect to

GPS height using the IGRF Model for 2005 with secular variation applied. The mean IGRF

value was then added back to the data.





MAGNETIC PROFILE LEVELLING

--------------------------

The magnetic traverse line data was then statistically levelled from the tie line data using

Intrepid polynomial levelling. The steps involved in the tie line levelling were as

follows:



\t- A primary tie line was chosen as a reference tie.

\t- All other ties were levelled to this tie line using 1st degree polynomial adjustment.

\t- lines were adjusted individually to minimize crossover differences, using 2nd degree

\t polynomial adjustments.



Any residual flight line effects were removed using Intrepid micro levelling techniques and

the resultant line data saved as a separate field.





MAGNETIC GRIDDING

-----------------

The data was gridded to a cell size of 20% of line spacing using a Minimum Curvature algorithm.







_____________________________________________________________________________________________



\t\t\tDATA PROCESSING : RADIOMETRIC DATA

_____________________________________________________________________________________________







____________________________________



RADIOMETRIC PROCESSING FLOW

____________________________________



Radiometric data processing consists of the following processing flow:





\tFull spectrum 256 channel Overview:





\t- Noise Adjusted Singular Value Deconvolution (NASVD) noise reduction

\t- Dead Time correction

\t- Energy calibration

\t- Cosmic and Aircraft background Removal.

\t- Radon background Removal

\t- Extraction of IAEA Window data





\tWindowed data processing Overview:



\t- Compton Stripping correction.

\t- Height Attenuation correction using IAEA coefficients.

\t- Gridding



The specific processing steps are described below:





____________________________________



256 CHANNEL PROCESSING

____________________________________





NASVD Noise Reduction:

---------------------

Noise-Adjusted Singular Value Decomposition (NASVD) Smoothing. Correction of the radiometric

data involved the reduction of the 256 channels of raw gamma spectrometer data using Noise-Adjusted

Singular Value Decomposition (NASVD) noise reduction method. The signal to noise ratio of the

multi channel spectra can be substantially enhanced using Noise-Adjusted Singular Value

Decomposition (NASVD) as described by Hovgaard and Grasty (1997), Schneider (1998) and Minty (1998).

This method involves a general linear transformation of groups of spectra (a whole line or flight),

using NASVD to compute the different spectral shapes that make up the measured multi-channel

spectra. New multi-channel spectra are created by recombining the statistically significant

spectral components. Each spectral component contributes an unequal amount to the features

observed in the measured multi-channel spectrum, until a point is reached where the spectral

components represent only noise.



The 1st spectral component is the spectral shape that represents most of the features in the

measured multi-channel spectra. The 2nd spectral component represents those features not

described by the 1st spectral component, etc. By excluding from the recombination those spectral

components that do not represent significant features in the measured multi-channel spectra, the

resulting reconstructed multi-channel spectra have a much larger signal to noise ratio than the

measured multi-channel spectra.





Dead Time Corrections:

----------------------

The raw 256 channel spectra were corrected for spectrometer dead time using the recorded live time

and the standard formula.

\t\t\t

\t\tN = n / (1 - t)

\t

\tN\t= \tcorrected counts in each second;

\tn\t=\tall counts processed in each second by the ADC; and

\tt\t=\tthe recorded dead time



Where the live time (L) is recorded, the dead time t is replaced by (1 - L).





Energy Calibration:

-------------------

Energy calibration was undertaken line by line using a maximum of 3 calibration peaks; and a

minimum of 2 calibration peaks dependent upon their clear identification in the spectra. The 3

calibration peaks used were Bi 214 at 0.609 Mev, K-40 at 1.46 Mev and Tl-208 at 2.615 Mev





Cosmic and Aircraft Background Correction:

------------------------------------------

Cosmic and aircraft background removal utilised the data recorded from a series of calibration flights

over water. These flight produce a normalised cosmic spectra for the system installation, together with

a 256ch spectra for the aircraft background.

The combined correction is calculated using:



\tN\t=\ta + bC,

where:

\tN\t=\tthe combined cosmic and aircraft background in each spectral window;

\ta\t=\tthe aircraft background in the window

\tC\t=\tthe cosmic channel count; and

\tb\t=\tthe cosmic stripping factor for the window.



The values of a and b for each window are determined from the calibration flights over the sea.

Cosmic coefficients and aircraft background coefficients were derived using INTREPID CAL256 program.





Atmospheric Radon:

------------------

The influence of atmospheric radon has been minimised using the spectral ratio method described by

Minty (1992). However the effect of radon in the Uranium channel can be considerable; and some

effects of the radon are visable in the character of the final processed data.





Extraction of Four Standard Windows:

------------------------------------

The fully processed 256 channel spectra were reduced to the four IAEA (1991) standard windows or

Regions of Interest (ROI): As given by the following Energy windows and channel numbers:



\tTotal Count\t0.41 to\t2.81 Mev (channels 33 to 238)

\tPotassium\t1.37 to\t1.57 Mev (channels 116 to 133)

\tUranium \t1.66 to\t1.86 Mev (channels 140 to 158)

\tThorium \t2.41 to\t2.81 Mev (channels 205 to 238)





____________________________________



\tWINDOW PROCESSING

____________________________________





Spectral Stripping of Standard Window Data:

-------------------------------------------



Corrections for Compton stripping and height attenuation were applied to the windowed

data using constants supplied by Radiation Solutions Inc.

Due to scattering of gamma rays in the air, the three principle stripping ratios

( Alpha, Beta and Gamma) increase with altitude above the ground:



Stripping Ratio\tIncrease at STP per metre

\t Alpha 0.00049

\t Beta 0.00065

\t Gamma 0.00069



Following adjustment of the stripping ratios for altitude, the technique for producing the corrected

(stripped) count rates in the potassium, uranium and thorium channels (NKC, NUC and NThC) are given

by Grasty and Minty (1995)



The Compton coefficients for the system are given above:

\t

\t



Height Corrections

-------------------

The stripped count rates vary exponentially with aircraft altitude. Adjustments for variation

in altitude were made using the formula:



\tNc\t= No e^ -u(H-h)



Where \tNo\t= uncorrected counts,

\tNc\t= count rate normalised to height H,

\th\t= measured height above the ground,

\tH\t= nominal flight height,

\tu\t= attenuation coefficient for the channel being corrected.





Calculation of Effective Height

-------------------------------

The Effective Height, which is the aircraft terrain clearance corrected to Standard Temperature

and Pressure was determined as follows:



\t- Filtering of the temperature field was applied to remove spikes and smooth out the

\t instrument noise.

\t- Filtering of the barometric pressure field was applied to remove spikes and to smooth

\t out the instrument noise.

\t- Filtering of the radar altimeter was applied to remove spikes, spurious reflections from

\t groups of tree and very narrow gullies and to smooth out the instrument noise.

\t- The formula option in the spread sheet editor was used to combine the terrain clearance,

\t pressure and temperature.



\t\t\th x P x 273

\tE_height = _____________________

\t\t\t1013 x (T + 273)

\tWhere:



\tE_height=\tthe effective height;

\th\t=\tthe observed radar altitude in metres;

\tT\t=\tthe measured air temperature in degrees C;

\tP\t=\tthe barometric pressure in millibars.



Reduction to Ground Concentrations:

-----------------------------------



The fully corrected window data is then converted to effective ground concentrations by dividing

by the conversion coefficient to produce the following equivalent concentrations for each element.



\tTotal Count\t: Dose Rate

\tPotassium\t: Percent

\tUranium\t \t: PPM

\tThorium \t: PPM





Radiometric gridding

---------------------

The data was gridded to a cell size of 20% of line spacing using a Minimum Curvature algorithm.

## **Dataset Citation**

AGL (2014) AGL - 2013 Gloucester Airborne Survey. Bioregional Assessment Source Dataset. Viewed 31 May 2018, http://data.bioregionalassessments.gov.au/dataset/5cffc19a-0ff4-402c-824a-88935f70931a.

Full description

AGL - 2013 Gloucester Airborne Survey - Data File

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ACN 633 798 857