ArcGIS REST Services Directory Login | Get Token
JSON | SOAP | WMS | WCS

Geophysics_Gravity_Gradiometry_Individual_Surveys/Bell_BMC_Tz (ImageServer)

View In:   ArcGIS JavaScript   ArcGIS Online Map Viewer   ArcGIS Earth   ArcMap

View Footprint In:   ArcGIS Online Map Viewer

Service Description: This dataset represents the Tz component of the gravity tensor derived from the Bell BMC2010 FTG/AGG survey, gridded at 25 m resolution in NAD83 NB Stereographic projection.The dataset contains the Tz tensor component extracted from the reconstructed gravity tensor of the Bell BMC2010 FTG/AGG survey. Tz represents the first vertical derivative of the gravity field and is highly sensitive to vertical density contrasts, making it particularly useful for detecting shallow intrusive bodies, faults, lithological contacts, and other subsurface structures with significant vertical variation. The dataset is provided as a 25 m grid in NAD83 New Brunswick Stereographic projection and supports detailed structural interpretation and mineral exploration.This raster was created by processing the original FTG profile data using a density of 2.8 g/cc, reconstructing the full gravity tensor from the measured components, gridding the tensor using a tensor-interpolation algorithm at 25 m resolution, and extracting the Tz component from the final tensor grid. It is delivered as an ER Mapper (.ers) raster.Data created Sept 2025.

Name: Geophysics_Gravity_Gradiometry_Individual_Surveys/Bell_BMC_Tz

Description: This dataset represents the Tz component of the gravity tensor derived from the Bell BMC2010 FTG/AGG survey, gridded at 25 m resolution in NAD83 NB Stereographic projection.The dataset contains the Tz tensor component extracted from the reconstructed gravity tensor of the Bell BMC2010 FTG/AGG survey. Tz represents the first vertical derivative of the gravity field and is highly sensitive to vertical density contrasts, making it particularly useful for detecting shallow intrusive bodies, faults, lithological contacts, and other subsurface structures with significant vertical variation. The dataset is provided as a 25 m grid in NAD83 New Brunswick Stereographic projection and supports detailed structural interpretation and mineral exploration.This raster was created by processing the original FTG profile data using a density of 2.8 g/cc, reconstructing the full gravity tensor from the measured components, gridding the tensor using a tensor-interpolation algorithm at 25 m resolution, and extracting the Tz component from the final tensor grid. It is delivered as an ER Mapper (.ers) raster.Data created Sept 2025.

Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 25.0

Pixel Size Y: 25.0

Band Count: 1

Pixel Type: F32

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "", "help": "" }]}

Mensuration Capabilities: Basic

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: NB Dept of Natural Resources, GSB Section

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: -17.990875244141

Max Values: 29.831993103027

Mean Values: -0.034417372106993

Standard Deviation Values: 7.8670412189583

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: null

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: null

Max Mosaic Image Count: null

Allow Raster Function: true

Allow Compute TiePoints: false

Supports Statistics: false

Supports Advanced Queries: false

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Histograms   Key Properties   Legend   MultiDimensionalInfo   rasterFunctionInfos

Supported Operations:   Export Image   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location