Mineral Resources On-Line Spatial Data
Mineral Resources > Online Spatial Data
Modifications have been made to reflect the use of this on the Mineral Resource Spatial Data website (mrdata.usgs.gov) in such areas as projection and image resolution. The image and grid available on <http://mrdata.usgs.gov/> is the one referred to as USmag_hp500.grd.
Viki Bankey (USGS) Alejandro Cuevas (CRM) David Daniels (USGS) Carol A. Finn (USGS) Israel Hernandez (CRM) Patricia Hill (USGS) Robert Kucks (USGS) Warner Miles (GSC) Mark Pilkington (GSC) Carter Roberts (USGS) Walter Roest (GSC) Victoria Rystrom (USGS) Sarah Shearer (USGS) Stephen Snyder (USGS) Ronald Sweeney (USGS) Julio Velez (CRM) Jeffrey Phillips (USGS) D.K.A. Ravat (Southern Illinois University)
<http://www.geosoft.com/pinfo/free/>
This interface can export grids to many other common formats.
Data are available either on a DVD or online at the address below.
The grids presented in this report were made from numerous individual grids that were mathematically merged together using standard techniques. Individual metadata files exist for USGS gridded data created from digital flight-line data (see USGS Open-File Report 02-0361).
The data in the original grids have been processed using formulas and methods that are not usually documented but that represent industry standard practices for airborne data reduction.
The data used to make these grids were collected using different instruments (magnetometers, altimeters, navigational systems) throughout the survey, but were usually consistent within each survey.
Survey contracts specified the conditions and specifications under which these data were collected. Standard industry practices of the time were followed in data collection and processing.
Flight Path Recovery - before about 1990 Horizontal position of the survey aircraft used to collect data were determined using aircraft navigational aids such as line-of-sight electronic systems that measure the distances from each of two ground stations to the aircraft using microwave or radio transmitters.
Flight Path Recovery - after about 1990 Horizontal position of the survey aircraft used to collect data were determined using GPS satellite navigation.
Radar altimeters are estimated to have an error of 2-5% of the altitude (Richard Hansen, PRJ, Inc., written communication).
Barometric altimeters are quite accurate, but are typically operated in an uncorrected mode. The diurnal variation in air pressure over the course of a flight can produce a 50-100 ft error in the barometric altimeter reading. In addition, pressure microcells create short-period air pressure changes equivalent to about 10 ft under typical conditions (Richard Hansen, PRJ, Inc., written communication)
The magnetometer was carried on a "stinger" that was attached to the aircraft or was carried in a bird towed on a line that was below the aircraft. The bird as it is towed is slightly behind the aircraft and therefore the vertical distance between the magnetometer and the aircraft is slightly less than the length of the line but remains constant for the survey.
Data were either collected at a fixed barometric altitude or were collected as a draped survey having an average terrain clearance above the ground. Because aircraft, especially airplanes, cannot safely maintain a constant terrain clearance, error in vertical position is introduced.
Details of data acquisition are described in the booklet that accompanies the printed map.
The marine data were obtained from the National Geophysical Data Center of the National Oceanic and Atmospheric Administration spanned the years 1958 through 1997.
- The DGRF, updated to survey date, was removed
- The flight elevation was used to mathematically calculate the equivalent magnetic field at 1,000 ft. above terrain
- obvious errors were corrected
- x-y locations were calculated for the described DNAG projection
- data were gridded at 1/3 - 1/4 of the flight-line spacing, then regridded to 1 km.
Procedures and software used to compile the 1-km grid of magnetic data for Canada are detailed on the Geophysical Data Centre website <http://gdcinfo.agg.nrcan.gc.ca>
Because wavelengths greater than roughly 150 km are unreliable in the compilation, applying a high-pass wavelength filter would appear to be a viable solution to remove these unreliable wavelengths. However, removing wavelengths less than 500 km from the merged grid creates artifacts, such as spurious separation of continuous anomalies. Therefore, we removed anomalies with wavelengths greater than 500 km from the merged grid to reduce the effects caused by the erroneous long wavelengths but maintaining continuity of anomalies. The correction was accomplished by transforming the merged grid to the frequency domain, filtering the transformed data with a long-wavelength cutoff at 500 km, and subtracting the long-wavelength data grid from the merged grid.
We produced an aeromagnetic grid in which the wavelengths longer than 500 km have been replaced by downward-continued CHAMP satellite data. Steps 0 and 6 were performed by Bob Kucks. Steps 1-4 were performed by Tiku Ravat. Step 5 was performed by Jeff Phillips.
0. The North American 1 km merged grid was decimated to 5 km.
1. This 5 km grid was converted to a 0.05 degree grid. This grid was low-pass filtered using a Gaussian filter with a 500 km cutoff, then decimated to 1 degree.
2. A joint inversion of this 1 degree low-pass aeromagnetic grid and CHAMP satellite data, with the aeromagnetic data weighted very low, produced a stabilized downward continuation of the CHAMP data.
3. The inverted data were interpolated to 0.05 degree and again low-pass filtered using the same Gaussian 500 km filter to remove
4. The low-pass grid from step 1 was subtracted from the original 0.05 degree aeromagnetic grid to create a 500 km high-pass aeromagnetic grid. This grid was added to the low-pass inverted grid from step 3 to get a corrected 0.05 degree aeromagnetic grid.
5. The corrected 0.05 aeromagnetic degree grid was projected to the DNAG projection and regridded to 5 km. This was subtracted from the decimated 5 km aeromagnetic grid to generate a 5 km correction grid. A matched filter was used to remove short-wavelength artifacts resulting from the projection and regridding process.
6. The resulting 5 km correction grid was regridded to the original 1 km grid and subtracted from the original 1 km aeromagnetic grid to generate the final 1 km corrected aeromagnetic grid.
The total magnetic value minus a geomagnetic reference field (GRF), which is a long-wavelength regional magnetic field. The most commonly used reference field is determined from a model developed by the International Association of Geomagnetism and Aeronomy (IAGA). The International Geomagnetic Reference Field (IGRF), is a predictive model adopted at the beginning of a model period (e.g. in 1989 for 1990-1995). After the model period, a revised definitive model is adopted, the DGRF. This is the preferred model to use for removing regional magnetic fields
A description of magnetometers and how they measure the total magnetic field can be found in:
Dobrin, M.B., 1976, Introduction to Geophysical Prospecting: New York, McGraw-Hill Book Company, p. 505-517.
Because wavelengths greater than roughly 150 km are unreliable in the compilation, applying a high-pass wavelength filter would appear to be a viable solution to remove these unreliable wavelengths. However, removing wavelengths less than 500 km from the merged grid creates artifacts, such as spurious separation of continuous anomalies. Therefore, we removed anomalies with wavelengths greater than 500 km from the merged grid to reduce the effects caused by the erroneous long wavelengths but maintaining continuity of anomalies. The correction was accomplished by transforming the merged grid to the frequency domain, filtering the transformed data with a long-wavelength cutoff at 500 km, and subtracting the long-wavelength data grid from the merged grid.
We produced an aeromagnetic grid in which the wavelengths longer than 500 km have been replaced by downward-continued CHAMP satellite data. Steps 0 and 6 were performed by Bob Kucks. Steps 1-4 were performed by Tiku Ravat. Step 5 was performed by Jeff Phillips.
0. The North American 1 km merged grid was decimated to 5 km.
1. This 5 km grid was converted to a 0.05 degree grid. This grid was low-pass filtered using a Gaussian filter with a 500 km cutoff, then decimated to 1 degree.
2. A joint inversion of this 1 degree low-pass aeromagnetic grid and CHAMP satellite data, with the aeromagnetic data weighted very low, produced a stabilized downward continuation of the CHAMP data.
3. The inverted data were interpolated to 0.05 degree and again low-pass filtered using the same Gaussian 500 km filter to remove
4. The low-pass grid from step 1 was subtracted from the original 0.05 degree aeromagnetic grid to create a 500 km high-pass aeromagnetic grid. This grid was added to the low-pass inverted grid from step 3 to get a corrected 0.05 degree aeromagnetic grid.
5. The corrected 0.05 aeromagnetic degree grid was projected to the DNAG projection and regridded to 5 km. This was subtracted from the decimated 5 km aeromagnetic grid to generate a 5 km correction grid. A matched filter was used to remove short-wavelength artifacts resulting from the projection and regridding process.
6. The resulting 5 km correction grid was regridded to the original 1 km grid and subtracted from the original 1 km aeromagnetic grid to generate the final 1 km corrected aeromagnetic grid.
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Page Last Modified: Tuesday, 11-Dec-2012 15:29:19 MST
