20211116 11153900 1.0 FALSE IMAGERY_LOWER_DARLING_20CM_RGB_2013_SFA201 557000.000000 656000.000000 6228000.000000 6344000.000000 1 Projected GDA2020 Linear Unit: Meter (1.000000) GDA2020_MGA_Zone_55 <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[&quot;GDA2020_MGA_Zone_55&quot;,GEOGCS[&quot;GDA2020&quot;,DATUM[&quot;GDA2020&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,500000.0],PARAMETER[&quot;False_Northing&quot;,10000000.0],PARAMETER[&quot;Central_Meridian&quot;,147.0],PARAMETER[&quot;Scale_Factor&quot;,0.9996],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,7855]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>1900</YOrigin><XYScale>450445547.3910538</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>7855</WKID><LatestWKID>7855</LatestWKID></ProjectedCoordinateSystem> 8 FALSE None 3 AMD TRUE continuous unsigned integer 15000 15000 1000 100 2048 100 75 0.1 10 600 300 FULL 0 NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None LERC,None,JPEG,LZ77 None None,Basic,Base-Top Height,Top-Top Shadow Height,Base-Top Shadow Height,3D 0 -1 0.8 1 NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None None,JPEG,LZ77,LERC None,Basic,Full NONE <_docversion_ Sync="TRUE">10 Name,MinPS,MaxPS,LowPS,HighPS,Tag,GroupName,ProductName,CenterX,CenterY,ZOrder,Shape_Length,Shape_Area 0 0 -1 1 0 Generic 43740 0.199999999999977 874.8 withheld 20211124 10481000 20211124 10481000 ISO 19139 Metadata Implementation Specification GML3.2 150000000 5000 Data Management Murray-Darling Basin Authority Spatial Data 1800 630 114 (free call) GPO Box 1801 Canberra ACT 2601 AU gis@mdba.gov.au Data Management Murray-Darling Basin Authority Spatial Data 1800 630 114 (free call) GPO Box 1801 Canberra ACT 2601 AU gis@mdba.gov.au 20cm RGB Imagery captured as part of the Lower darling DEM project. This data covers a gap between two datasets, one to the north covering the Menindee Lakes... <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Medium format digital photography was captured using the Rollie TAC AICPro camera that is integrated within the Harrier 68 Airborne LiDAR System. The images were oriented using reduced best fit trajectory from the IMU and differentially processed airborne GPS. The images were ortho-rectified against the LiDAR 1 metre DEM and automatically colour balanced and mosaiced. The ortho-photomosaic was exported to ECW and 1km x 1km tiles in GeoTIFF The photography was captured simultaneously with the LiDAR whenever conditions were suitable for LiDAR capture. As a consequence, the imagery may be affected by cloud shadow (but will not include actual clouds) and low sun angles (i.e. long shadows). The ortho-mosaic is a seamless mosaic of photogrammetric quality and no manual colour matching or manual editing of seam lines has been applied. </SPAN></P><P><SPAN>The data were transformed from the ellipsoid to the ausgeoid09 datum using the GeoscienceAustralia N Surface.Rollei AIC Digital CameraThe Harrier 68i includes a Rollei AIC, 80 mega pixel medium format camera capable of 16bit RGB and colour infra-red modes. The specifications are as follows:Model: Rollei AICOperating altitude: 0 - 6,000 mField of view: 45 degrees or 60 degreesArray size: H68_017: 39 mega-pixel; H68_038: 80 mega-pixelChannels: Three (RGB)Bit depth: 16 bitMax. Exp. rate: 2.5 sec.Image pixel size: Down to 0.03 mImage scale: 1:250 to 1:10,000Position accuracy: Down to 0.03 mCalibration: Radiometric, Geometric5.0 Vertical Accuracy Assessment 5.1 Ground points validated against the elevation of the LiDAR. This assessment is derived from ground points collected by the contractor and validated against the elevation of the LiDARᶻ. Knownᶻ is taken from a known elevation height (Ground Survey) and LiDARᶻ is taken from the interpolated TIN aligned with the ground control point (Knownᶻ). Where available, independent ground control points are tested against the LiDAR, usually provided where available through a state government authority. Error Mean: -0.115 Error Range: [-0.181 - 0.057] Skew*: -0.426 RMSE(z): 0.119 NMAS/VMAS Accuracy(z) (90% CI) ±0.196 ASPRS/NSSDA Accuracy(z) (95% CI) ±0.233</SPAN></P><P><SPAN>Coordinate System Projection: MGAZone: 54Horizontal Datum: GDA94Vertical Datum: AHD71 (Ausgeoid09)Spatial Services</SPAN></P><P><SPAN>The DEM accuracy will be limited by the spatial accuracy of the LiDAR point data and will contain some additional error due to interpolation, particularly in areas of dense vegetation where ground points are sparse. The may also be a small amount of error due to ground point misclassification.</SPAN></P><P><SPAN>Equipment and Software Two Airborne Trimble Harrier 68i/G1 Airborne Laser Scanning (ALS) systems were used to aquire the data for this project. The Harrier 68 ALS systems contain the following instruments• Riegl LiDAR scanning instrument,• Rollie 39 or 80 mega-pixel camera• Applanix POS/AV 410 Inertial Motion System and 12 channel, dual frequency GPS.LiDAR Scanner SpecificationsLaser instrument: Riegl LMS-Q680Beam deflection: Pyramid. Polygon MirrorField of view: ±22,5 degrees to ±30.0 degreesMeasurement rate: 266,000 HzOperating altitude: 50 m – 2,500 m AGLBeam divergence: 0.5 mradDetection Method: Full wave form processingIntensity capture: 16 bitEye safe: Class 1Swath width: 83 % of altitude (45 deg) 115 % of altitude (60 deg)Range resolution: 0.04 mCross strips form networks of, overlapping, LiDAR strips. </SPAN></P><P><SPAN /></P></DIV></DIV></DIV> Murray Darling Basin Authority RPS Services Geoscience Australia IMAGERY_LOWER_DARLING_20CM_RGB_2013_SFA201 IMAGERY ELEVATION LOWER DARLING <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Creative Commons Attribution 3.0 Australia (CC BY 3.0AU) https://creativecommons.org/licenses/by/3.0/au</SPAN></P></DIV></DIV></DIV> Creative Commons Attribution 3.0 Australia (CC BY 3.0AU) https://creativecommons.org/licenses/by/3.0/au Version 6.2 (Build 9200) ; Esri ArcGIS 10.8.1.14362 1 147.610453 148.690703 -33.031330 -34.087228 The Harrier 68i includes a Rollei AIC, 80 mega pixel medium format camera capable of 16 bit RGB and colour infra-red modes. The specifications are as follows: Model: Rollei AIC Operating altitude: 0 - 6,000 m Field of view: 45 degrees or 60 degrees Array size: H68_017: 39 mega-pixel; H68_038: 80 mega-pixel Channels: Three (RGB) Bit depth: 16 bit Max. Exp. rate: 2.5 sec. Image pixel size: Down to 0.03 m Image scale: 1:250 to 1:10,000 Position accuracy: Down to 0.03 m Calibration: Radiometric, Geometric Because the LiDAR and photography were captured simultaneously, both raw data sets have the same orientations. The following work-flow was used to generate the ortho-photo mosaic: • Calculate exterior orientations of photographic images from adjusted GPS and IMU (smoothed best estimate trajectories). • Ortho rectify images; horizontal adjustments determined from LiDAR are applied to the imagery. • QA to check misalignment on seams and colour mismatch. • QA to check horizontal displacements against ground check points • Resample imagery to the resolution of 20cm. • Produce image mosaics • Export imagery to ECW and 1km x 1km • Generate metadata • Final QA 495000 0.200000 580000 0.200000 2 1 0 557000.000000 6228000.000000 557000.000000 6344000.000000 656000.000000 6344000.000000 656000.000000 6228000.000000 606500.000000 6286000.000000 Band_1 255.000000 0.000000 8 Band_2 255.000000 0.000000 8 Band_3 255.000000 0.000000 8 EPSG 8.9.4(10.5.0) 20211124 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