20251217 13301100 1.0 ISO 19139 Metadata Implementation Specification GML3.2 FALSE 150000000 5000 SWN_AGG_Tyy.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 11210500 20251219 11210500 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_Tyy.ers 1 -67.373191 -64.326352 47.010247 45.387866 This dataset represents the Tyy component of the gravity tensor derived from the SWN_NBStereo (Lantern) FTG/AGG survey, gridded at 25 m resolution in NAD83 NB... This dataset represents the Tyy component of the gravity tensor derived from the SWN_NBStereo (Lantern) FTG/AGG survey, gridded at 25 m resolution in NAD83 NB Stereographic projection.The dataset contains the Tyy tensor component extracted from the reconstructed gravity tensor of the SWN_NBStereo survey. Tyy represents the second derivative of the gravity field along the Y-axis, capturing lateral density variations in the subsurface. This component is useful for mapping faults, lithological contacts, intrusive bodies, and other structural features, supporting high-resolution structural interpretation and mineral exploration. The dataset is provided as a 25 m grid in NAD83 New Brunswick Stereographic projection.This raster was produced by processing the SWN_NBStereo FTG/AGG profile data using a density of 2.8 g/cc, reconstructing the full gravity tensor from the measured components, interpolating the tensor to a 25 m grid using a tensor-interpolation algorithm, and extracting the Tyy component. The final grid was exported in ER Mapper (.ers) format.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 69.998505 -55.136177 32 Raster Dataset dataset EPSG 6.2(9.3.0.0) 20251219 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