20251217
13302000
1.0
ISO 19139 Metadata Implementation Specification GML3.2
FALSE
150000000
5000
SWN_AGG_Tz.ers
002
2433602.500000
2665327.500000
7378582.500000
7556717.500000
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
TRUE
continuous
floating point
-999999
20251219
11232200
20251219
11232200
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
SWN_AGG_Tz.ers
1
-67.373191
-64.326352
47.010247
45.387866
This dataset represents the Tz (vertical gravity) component derived from the SWN_NBStereo (Lantern) FTG/AGG survey, gridded at 25 m resolution in NAD83 NB...
This dataset represents the Tz (vertical gravity) component derived from the SWN_NBStereo (Lantern) FTG/AGG survey, gridded at 25 m resolution in NAD83 NB Stereographic projection.The dataset contains the vertical gravity component (Tz) reconstructed from the gravity tensor of the SWN_NBStereo survey. Tz highlights vertical density variations in the subsurface and is useful for mapping faults, lithological contacts, intrusive bodies, and other geological structures. This high-resolution dataset supports detailed structural interpretation and mineral exploration and is delivered as a 25 m grid in NAD83 New Brunswick Stereographic projection.This raster was produced by reconstructing Tz from the measured tensor components (Txz, Tyz, and Tzz) of the SWN_NBStereo FTG/AGG survey, gridding the resulting Tz field at 25 m resolution using a tensor-interpolation algorithm, and exporting it as an ER Mapper (.ers) raster.Data created Sept 2025.
NB Dept of Natural Resources, GSB Section
2015
115.000000
1549
115.000000
2
1
0
2433602.500000 7378582.500000
2433602.500000 7556717.500000
2665327.500000 7556717.500000
2665327.500000 7378582.500000
2549465.000000 7467650.000000
Band_1
32.998650
-27.322258
32
Raster Dataset
dataset
EPSG
6.2(9.3.0.0)
20251219
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