Little Desert - LiDAR
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  Little Desert - LiDAR

dataset
Dataset: Little Desert - LiDAR Assembly: Single
 
Citation proposal Citation proposal

Little Desert - LiDAR

Department of Transport and Planning

https://metashare.maps.vic.gov.au/geonetwork/srv/eng/catalog.search#/metadata/302e50db-1644-5c82-8c36-3f155641fce7
 
  • Description
  • Temporal
  • Spatial
  • Maintenance
  • Format
  • Contacts
  • Keywords
  • Resource Constraints
  • Lineage
  • Metadata Constraints
  • Quality

Description

Title
Little Desert - LiDAR 
Resource Type
Dataset  
 
 

Temporal

 
 

Spatial

Spatial representation type
Point Cloud  
Horizontal Accuracy
0.3m  
Code
MGA Zone 54 GDA94 
 

 

Maintenance

 
 

Format

Title
LAS 1.3, Waveform Packets 
 
 

Contacts

  Point of contact

Department of Transport and Planning - Coordinated Imagery Program  
PO Box 500
East Melbourne
Victoria
3002
Australia
 
 

Keywords

Topic category
  • Elevation
 
 

Resource Constraints

Use limitation
General 
Classification
Unclassified  
 
 

Lineage

Description
LiDAR was acquired over the project area. An instrument calibration issue was encountered with the LiDAR system during initial pre-processing. The issue was caused by an internal calibration error between channel 1 and channel 2. It manifested itself by producing a fluctuating, vertical, misalignment between both channels in the range of 0.05 - 0.20m (relative accuracy). It was resolved by an internal calibration correction (provided by sensor manufacturer) being applied to all flights of LiDAR data in this project. The acquired LiDAR strikes were transformed into an ellipsoid point cloud using a solution obtained from the onboard IMU and GPS and Victorian CORS network. The point cloud was then adjusted to AHD using AusGeoid09. Checks against an network of surveyed ground control resulted in further general and local adjustments where required. Reduction of the LiDAR data proceeded without any significant problems. Laser returns were classified into ground and non ground classes using a single algorithm tailored to the project before further automatic classification was performed to differentiate non ground features into their respective classes. Following this, manual checking and editing was undertaken to improve the classification of the ground class. 
 
 

Metadata Constraints

Classification
Unclassified  
 
 

Quality

Attribute Quality
Positional Accuracy
Conceptual Consistency
Comments
Accuracy of the ground surface under dense canopy may be reduced due to diminished returns. Laser accuracy at swath edges may be reduced. Classification algorithms have been tailored for common terrain/vegetation combinations across the project area. Classification accuracy and ground definition may be less accurate in uncommon or mixed terrain/vegetation/land use combinations. The Riegl Q1560 LiDAR sensor is an extremely sensitive system and also contains a unique functionality with ¿multi-time-around¿ technology. The combination of these two factors increases the number of high/low outliers compared to other LiDAR sensors. 
Missing Data
Comments
Gaps may occur due to the multi-time-around technology of the Reigl Q1560 LiDAR Sensor, or from diminished returns over water, under canopy and on materials with low laser reflectivity, such as black roofing, swimming pools. 
Excess Data
 
 

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  Associated resources

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