2021-22 DTV LiDAR - Tallarook
project:
cep15b-2021-22_dtv_lidar_tallarook
This LiDAR survey was undertaken as part of a larger DTV LiDAR capture project in operation between 2022 and 2024. The DTV LiDAR Project comprises of almost 60 separate LiDAR survey blocks totaling over 60,000 square kilometres within Victoria. The project was managed by the Coordinated Imagery Program on behalf of the Digital Twin Victoria (DTV) program, a four-year $37.4 million State Government investment designed to fast track the adoption of new geospatial data and emerging technologies. When completed, the LiDAR capture project will have achieved coverage of over 99 percent of the population and 95 per cent of the buildings in the Victoria.
The primary use of the data is the creation of a ‘bare earth’ digital elevation model (DEM) that will underpin the DTV geospatial data platform. Numerous other important secondary uses will also benefit from the data collected such as river health monitoring, vegetation analysis and heritage cultural mapping.
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Citation proposal Citation proposal
(2022) 2021-22 DTV LiDAR - Tallarook https://uat-metashare.maps.vic.gov.au/geonetwork/srv/eng/catalog.search#/metadata/57cabcd9-b7bc-56a0-be1e-dab3f1e3882f |
- Description
- Temporal
- Spatial
- Maintenance
- Format
- Contacts
- Keywords
- Resource Constraints
- Lineage
- Metadata Constraints
- Quality
- Acquisition Info
- Raster Data Details
- Raster Type Details
- Point Cloud Data Details
- Contour Data Details
- Survey Details
Simple
Description
- Title
- 2021-22 DTV LiDAR - Tallarook
- Alternate title
- cep15b-2021-22_dtv_lidar_tallarook
- Purpose
- The primary purpose is the generation of a state wide 1m DEM
Temporal
- Time period
- 20212022
Spatial
Maintenance
Format
Contacts
Point of contact
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No information provided.
Cited responsible party
No information provided.
Keywords
- Topic category
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- Imagery base maps earth cover
Resource Constraints
- Use limitation
- General
- Classification
- Unclassified
Lineage
Metadata Constraints
- Classification
- Unclassified
Quality
Attribute Quality
Positional Accuracy
Conceptual Consistency
Missing Data
Excess Data
Acquisition Info
Raster Data Details
Point Cloud Data Details
Contour Data Details
Survey Details
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57cabcd9-b7bc-56a0-be1e-dab3f1e3882f
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