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ImageryServices/TLC_Imagery2015_D_WM (ImageServer)

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Service Description: Our 2015 high-resolution (0.5 ft. per pixel) orthoimagery is available in Natural Color (Red, Green, Blue). This aerial imagery was captured by our vendor Merrick and Co. The imagery was collected from January 18, 2015 to February 5, 2015. Prior to delivery, the vendor geometrically corrected (orthorectified) the imagery such that the its scale is uniform and any distortions have been corrected. This process allows for an accurate representation of the earth's surface that can be used to measure true distances and extract GIS features. After delivery, TLCGIS staff performed additional quality control and enhancement processes to prepare the imagery for publication. This Natural Color (RGB) imagery shows the colors visible to the human eye. This is high-resolution imagery and you will appreciate the fine details visible in these images. Acquisition Information: This dataset is part of a regularly scheduled update of LiDAR and digital orthotography products. The dataset was created from source imagery acquired by a Trimble TAC80 natural color digital camera and LAS data acquired by a Optech ALTM HA500 (Pegasus) LIDAR sensor from January 18, 2015 to February 5, 2015.

Name: ImageryServices/TLC_Imagery2015_D_WM

Description: Our 2015 high-resolution (0.5 ft. per pixel) orthoimagery is available in Natural Color (Red, Green, Blue). This aerial imagery was captured by our vendor Merrick and Co. The imagery was collected from January 18, 2015 to February 5, 2015. Prior to delivery, the vendor geometrically corrected (orthorectified) the imagery such that the its scale is uniform and any distortions have been corrected. This process allows for an accurate representation of the earth's surface that can be used to measure true distances and extract GIS features. After delivery, TLCGIS staff performed additional quality control and enhancement processes to prepare the imagery for publication. This Natural Color (RGB) imagery shows the colors visible to the human eye. This is high-resolution imagery and you will appreciate the fine details visible in these images. Acquisition Information: This dataset is part of a regularly scheduled update of LiDAR and digital orthotography products. The dataset was created from source imagery acquired by a Trimble TAC80 natural color digital camera and LAS data acquired by a Optech ALTM HA500 (Pegasus) LIDAR sensor from January 18, 2015 to February 5, 2015.

Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 0.15240030480060887

Pixel Size Y: 0.1524003048006092

Band Count: 3

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "A No-Op Function.", "help": "" }]}

Mensuration Capabilities: None

Has Histograms: false

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text:

Service Data Type: esriImageServiceDataTypeProcessed

Min Values: N/A

Max Values: N/A

Mean Values: N/A

Standard Deviation Values: N/A

Object ID Field: OBJECTID

Fields: Default Mosaic Method: Northwest

Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: 1000

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: null

Allow Analysis: null

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Key Properties   Legend   Raster Function Infos

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