20251217
13264500
1.0
ISO 19139 Metadata Implementation Specification GML3.2
FALSE
150000000
5000
Ground_compiled_CompleteBoug28.ers
002
2235500.000000
2812500.000000
7229500.000000
7870500.000000
1
Projected
GCS_North_American_1983_CSRS
Linear Unit: Meter (1.000000)
NAD_1983_CSRS_New_Brunswick_Stereographic
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.8'><WKT>PROJCS["NAD_1983_CSRS_New_Brunswick_Stereographic",GEOGCS["GCS_North_American_1983_CSRS",DATUM["D_North_American_1983_CSRS",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Double_Stereographic"],PARAMETER["False_Easting",2500000.0],PARAMETER["False_Northing",7500000.0],PARAMETER["Central_Meridian",-66.5],PARAMETER["Scale_Factor",0.999912],PARAMETER["Latitude_Of_Origin",46.5],UNIT["Meter",1.0],AUTHORITY["EPSG",2953]]</WKT><XOrigin>-28216700</XOrigin><YOrigin>-23260100</YOrigin><XYScale>146555990.15834904</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>2036</WKID><LatestWKID>2953</LatestWKID></ProjectedCoordinateSystem>
32
FALSE
None
1
ER Mapper
FALSE
continuous
floating point
-999999
20251219
08570000
20251219
8582400
ISO19139
Amirabbas Karbalaeiramezanali
GSB
amirabbas.karbalaeiramezanali@gnb.ca
Serge Allard
GSB
Serge.Allard@gnb.ca
Serge Alard
Serge Allard
Serge Allard
Hernan Ugalde
hernan.ugalde@dipgeosciences.com
Version 6.2 (Build 9200) ; Esri ArcGIS 10.8.1.14362
Ground_compiled_CompleteBoug28.ers
1
-70.170234
-62.165276
49.831386
43.998311
This dataset represents the complete Bouguer gravity anomaly (density 2.8 g/cc) derived from ground gravity measurements across New Brunswick.
This dataset represents the complete Bouguer gravity anomaly (density 2.8 g/cc) derived from ground gravity measurements across New Brunswick.The dataset provides complete Bouguer anomaly values calculated from reprocessed ground gravity data collected throughout New Brunswick. The complete Bouguer anomaly incorporates the Bouguer correction and terrain correction, both computed using a reduction density of 2.8 g/cc. This anomaly enhances the accuracy of subsurface density interpretations, particularly in areas with significant topographic relief. It is well suited for regional geological mapping, structural interpretation, and mineral exploration studies. The dataset is delivered in NAD83 NB Stereographic double projection and reflects consistent recalculation of corrections using SRTM topography and standardized processing workflows.Ground gravity station data were downloaded from the GSC server and reprocessed in September 2025. Marine stations were removed, and SRTM elevation data were used to recompute Free Air and Bouguer corrections at each station using a density of 2.8 g/cc. Terrain corrections were calculated using the same DEM. The complete Bouguer anomaly was then obtained by adding the Bouguer anomaly and terrain correction. These values were exported and projected into NAD83 NB Stereographic to produce the dataset.Data created Sept 2025.
NB Dept of Natural Resources, GSB Section
577
1000.000000
641
1000.000000
2
1
0
2235500.000000 7229500.000000
2235500.000000 7870500.000000
2812500.000000 7870500.000000
2812500.000000 7229500.000000
2524000.000000 7550000.000000
Band_1
32.201607
-76.778419
32
Raster Dataset
dataset
EPSG
6.2(9.3.0.0)
20251219
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