Authors / CoAuthors
Abstract
Background This report describes a project which involved the capture and processing of LiDAR and coincident imagery and resultant derived products for the lower reaches of the Darling River. The data joins two existing LiDAR datasets, one to the north covering the Menindee Lakes and the other in the south along the Murray River corridor. It is intended to provide the Murray-Darling Basin Authority with a very accurate, quality assured measurement of topography in order to accurately model the flow and volume of water in the floodplains within the project area. The LiDAR was captured in April and May 2013 at a point density of two 1st return points per square metre within swath, (equivalent to two outgoing laser pulses per square metre at ground level). The specified accuracies; 30cm vertical and 80cm horizontal, were achieved and verified through a rigorous network of ground check points and base stations. A set of seamless products were produced including hydro-flattened bare earth DEMs, DSMs and cartographic contours. The outputs of the project are compliant with National ICSM LiDAR Product Specifications and the NEDF.
Product Type
dataset
eCat Id
78360
Contact for the resource
Custodian
Owner
Owner
Custodian
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Keywords
- Australian and New Zealand Standard Research Classification (ANZSRC)
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- Earth Sciences
- ( {1} )
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- HVC_144648
- ( {1} )
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- Airborne Digital Data
- ( {1} )
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- Published_External
Publication Date
2013-01-01T00:00:00
Creation Date
Security Constraints
Legal Constraints
Status
Purpose
Maintenance Information
asNeeded
Topic Category
elevation
Series Information
Lineage
Unclassified Point Cloud The IMU and post processed airborne GPS logs were used to generate the LiDAR point cloud from the waveform instrument data. Raw LiDAR strips were levelled to establish internal consistency, merged and 1km x 1km tiles in LAS v1.2 format were created. An automatic classification algorithm was applied in TerraScan software to produce an initial classification of ground (2) and unclassified (1). High and low point noise were The ground classification was improved manually by visually scanning the ground surface and reassigning points from ground to unclassified to remove spikes and by assigning unclassified points to ground where the ground surface lacked sufficient detail to describe the terrain (ie large TIN triangles). Level 3 Classified LiDAR Point Data The IMU and post processed airborne GPS logs were used to generate the LiDAR point cloud from the waveform instrument data. Raw LiDAR strips were levelled to establish internal consistency, merged and 1km x 1km tiles in LAS v1.2 format were created. An automatic classification algorithm was applied in TerraScan software to produce an initial classification of ground (2) and unclassified (1). High and low noise points were automatically classified. In accordance with Appendix B of the Statement of Requirement, in areas of overlapping swaths, points from the swath with the lowest off-nadir angle were classified to class 12 (overlap). The ground classification was improved manually by visually scanning the ground surface and reassigning points from ground to unclassified to remove spikes and by assigning unclassified points to ground where the ground surface lacked sufficient detail to describe the terrain (ie large TIN triangles). On completion of the ground classification automatic algorithms were used to classify unclassified points to low vegetation (3), medium vegetation (4), high vegetation (5) and buildings (10). The workflow and quality assurance processes were designed to achieve the Level 3 requirement for 'removal of significant anomalies which remain in the ground class (2) and achieve a ground point misclassification rate of 2% or less. The classification accuracy was not measured. LiDAR Intensity Image Intensity images with a ground pixel spacing of one metre were generated from the LiDAR point cloud using an RPS algorithm that calculates the intensity image as the mean intensity of the first return points or last return points falling on each pixel. Both first and last return images were produced. The intensity images were converted to ECW using ERMapper software and also exported as 1km x 1km tiles in GeoTIFF format. Digital Elevation Model (DEM) A DEM with a ground pixel spacing of one metre was generated from the LiDAR ground points. The method of deriving the height for each grid point is by triangulation between the three nearest LiDAR ground points. Hydro flattening was applied using waterlines (break lines) that were manually digitised using the LiDAR and ortho photography as reference for areas of non-tidal water greater than 625 square metres and watercourses nominally greater than 30 metres in width. The DEM was exported to ESRI Binary grid as 1km by 1km tiles in accordance with ICSM specifications (December 2012). 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.
Parent Information
Extents
[0, 0, 0, 0]
Reference System
Spatial Resolution
Service Information
Associations
Source Information
Background This report describes a project which involved the capture and processing of LiDAR and coincident imagery and resultant derived products for the lower reaches of the Darling River. The data joins two existing LiDAR datasets, one to the north covering the Menindee Lakes and the other in the south along the Murray River corridor. It is intended to provide the Murray-Darling Basin Authority with a very accurate, quality assured measurement of topography in order to accurately model the flow and volume of water in the floodplains within the project area. The LiDAR was captured in April and May 2013 at a point density of two 1st return points per square metre within swath, (equivalent to two outgoing laser pulses per square metre at ground level). The specified accuracies; 30cm vertical and 80cm horizontal, were achieved and verified through a rigorous network of ground check points and base stations. A set of seamless products were produced including hydro-flattened bare earth DEMs, DSMs and artographic contours. The outputs of the project are compliant with National ICSM LiDAR Product Specifications and the NEDF.