Australia-Wide 30 m Machine Learning-Derived Canopy Height Models Composites: Best Pick and Median
<p>This dataset is part of the OzTreeMap project and provides two new 30 m spatial resolution canopy height products for continental Australia: the best-pick canopy height model (pick-CHM) and the median canopy height model (med-CHM). Both products represent estimates of vegetation canopy height across Australia and were developed to improve the accuracy and consistency of existing large-scale canopy height models, which were generated by researchers to represent canopy heights from variable time periods ranging from 2007 until 2020. The best-pick and median products are composites and derive from an extensive validation of the 4 original CHMs.</p>
Each product is provided as a single-band GeoTIFF raster in the Australian Albers (EPSG:3577) coordinate reference system, with 30 m spatial resolution and float32 data type. These datasets support applications in forest structure monitoring, carbon accounting, and ecosystem assessment across Australia.
Simple
Identification info
- Date (Creation)
- 2025-01-01
- Date (Publication)
- 2025-10-29
- Date (Revision)
- 2025-12-10
- Edition
- 1
Identifier
Publisher
Co-author
CSIRO Environment - McVicar, Tim R (Research Scientist)
Clunies Ross Street, Black Mountain, 2601, Australian Capital Territory, Australia
Black Mountain
Australian Capital Territory
2601
Australia
Co-author
CSIRO Agriculture and Food - Levick, Shaun ()
Waite Road, Waite, South Australia, 5064, Australia
Waite
South Australia
5064
Australia
Co-author
Australian National University - Van Dijk, Albert (Professor of Water Science and Management)
10 East Road, Acton, 2601, Australian Capital Territory, Australia
Acton
Australian Capital Territory
2601
Australia
Funder
Australian National University
10 East Road, Acton, 2601, Australian Capital Territory, Australia
Acton
Australian Capital Territory
2601
Australia
Funder
CSIRO Environment
Clunies Ross Street, Black Mountain, 2601, Australian Capital Territory, Australia
Black Mountain
Australian Capital Territory
2601
Australia
Author
Fenner School of Environment and Society, Australian National University - Pucino, Nicolas ()
10 East Road, Acton, 2601, Australian Capital Territory, Australia
Acton
Australian Capital Territory
2601
Australia
- Website
- https://www.tern.org.au/
- Purpose
- These datasets provide better Canopy Height Model estimates as validated versus an extensive point cloud datasets, therefore, these could improve downstream modelling works where the original datasets are used.
- Credit
- We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
- Credit
- This research was conducted under the ANU-CSIRO Collaborative Research Agreement entitled ‘Spatial and vertical distributions of individual tree and shrub canopies across Australian ecosystems’. We thank Drs Libby Pinkard, Steve Roxburgh, and Glenn Newnham (all from CSIRO Environment) for their continued support.
- Status
- Completed
Point of contact
CSIRO Environment - Pucino, Nicolas ()
Clunies Ross Street, Black Mountain, 2601, Australian Capital Territory, Australia
Clunies Ross Street
Black Mountain
Australian Capital Territory
2601
Australia
Spatial resolution
- Spatial resolution
- 30
- Topic category
-
- Environment
- Elevation
Extent
- Description
- Australia-wide 30 m datasets.
N
S
E
W
))
Temporal extent
- Time period
- 2007-01-01 2020-01-01
Vertical element
- Minimum value
- 0
- Maximum value
- 9999
- Reference system identifier
- EPSG/EPSG:4939
- Reference system type
- Geodetic Geographic 3D
- Maintenance and update frequency
- Not planned
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Vertical Resolution Ranges
- GCMD Temporal Resolution Ranges
- Keywords (Discipline)
-
- CHM
Resource constraints
- Use limitation
- The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/
- File name
- 88x31.png
- File description
- CCBy Logo from creativecommons.org
- File type
- png
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 4.0
- Access constraints
- License
- Use constraints
- Other restrictions
- Other constraints
- TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. <br />Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN. <br /><br />Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting
- Other constraints
- Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.
Resource constraints
- Classification
- Unclassified
- Supplemental Information
- Link to download the tiles footprints geojson file : <a href="https://explorer.csiro.easi-eo.solutions/products/ga_ls_landcover_class_cyear_3 (regions)">Land Cover Class</a>
Distribution Information
- Distribution format
-
Distributor
Distributor
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
- OnLine resource
- Canopy Height Model Composite - Best Pick Data
- OnLine resource
- Canopy Height Model Composite - Median Data
- OnLine resource
- ro-crate-metadata.json
Resource lineage
- Statement
- <p>A total of 26,987 LiDAR and photogrammetry point cloud tiles (1–4 km² each) were obtained from the Elevation and Depth (ELVIS) and Terrestrial Ecosystem Research Network (TERN) open repositories, representing a 5% stratified sample designed to match the distribution of Australia’s 16 vegetation structure classes (Scarth et al., 2019). For each tile, a 0.5 m canopy height model (CHM) was generated using the pit-free algorithm (Khosravipour et al., 2014), and individual tree crowns were delineated with the Dalponte segmentation algorithm (Dalponte & Coomes, 2016) using vegetation-specific optimized parameters (Pucino et al., 2025, under review).</p><br></br> <p>The resulting point-cloud-derived CHMs served as reference data for evaluating the vertical accuracy of four publicly available satellite-based machine-learning or deep learning-derived CHMs: (1) Lang et al. (2023); (2) Liao et al. (2020); (3) Potapov et al. (2021); and (4) Tolan et al. (2024). All datasets were co-registered and resampled to 30 m resolution. Pixel-wise error metrics were computed, and a combined score defined for each vegetation class which publicly available dataset is the most accurate. Water bodies are masked using Digital Earth Australia Waterbodies dataset.</p> <p>Three new continental-scale 30 m CHMs were then produced: (i) a pixel-wise median composite; (ii) a vegetation-class-specific best-pick composite; and (iii) a deep-learning CHM derived from a multi-layer perceptron (MLP - not publicly available).</p> <em>Note: this document's Start Date and End Date indicate the nominal dates of the datasets we tested, not the publication dates of their associated articles.</em>
- Hierarchy level
- Dataset
- Title
- Dalponte, M., Coomes, D.A., 2016. Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data. Methods Ecol. Evol. 7, 1236–1245.
- Website
-
https://doi.org/10.1111/2041-210X.12575
Method documentation
- Title
- Khosravipour, A., Skidmore, A.K., Isenburg, M., Wang, T., Hussin, Y.A., 2014. Generating Pit-free Canopy Height Models from Airborne Lidar. Photogrammetric Engineering & Remote Sensing 80, 863–872.
- Website
-
https://doi.org/10.14358/PERS.80.9.863
Method documentation
- Title
- Lang, N., Jetz, W., Schindler, K., Wegner, J.D., 2023. A high-resolution canopy height model of the Earth. Nat Ecol Evol 7, 1778–1789.
- Website
-
https://doi.org/10.1038/s41559-023-02206-6
Method documentation
- Title
- Liao, Z., Van Dijk, A.I.J.M., He, B., Larraondo, P.R., Scarth, P.F., 2020. Woody vegetation cover, height and biomass at 25-m resolution across Australia derived from multiple site, airborne and satellite observations. Int. J. Appl. Earth Obs. Geoinf. 93, 102209.
- Website
-
https://doi.org/10.1016/j.jag.2020.102209
Method documentation
- Title
- Potapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M.C., Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C.E., Armston, J., Dubayah, R., Blair, J.B., Hofton, M., 2021. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sens. Environ. 253, 112165.
- Website
-
https://doi.org/10.1016/j.rse.2020.112165
Method documentation
- Title
- Scarth, P., Armston, J., Lucas, R., Bunting, P., 2019. A Structural Classification of Australian Vegetation Using ICESat/GLAS, ALOS PALSAR, and Landsat Sensor Data. Remote Sensing 11, 147
- Website
-
https://doi.org/10.3390/rs11020147
Method documentation
- Title
- Tolan, J., Yang, H.-I., Nosarzewski, B., Couairon, G., Vo, H.V., Brandt, J., Spore, J., Majumdar, S., Haziza, D., Vamaraju, J., Moutakanni, T., Bojanowski, P., Johns, T., White, B., Tiecke, T., Couprie, C., 2024. Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar. Remote Sens. Environ. 300, 113888.
- Website
-
https://doi.org/10.1016/j.rse.2023.113888
Method documentation
Reference System Information
- Reference system identifier
- EPSG/EPSG:3577
- Reference system type
- Geodetic Geographic 2D
Metadata
- Metadata identifier
-
urn:uuid/36c98155-39c8-4eec-9070-a978933f3fa3
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/36c98155-39c8-4eec-9070-a978933f3fa3
Point-of-truth metadata URL
- Date info (Creation)
- 2025-10-22T23:02:29.284020+00:00
- Date info (Revision)
- 2025-12-10T10:31:08.068385+00:00
Metadata standard
- Title
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- Edition
- 1
Metadata standard
- Title
- ISO/TS 19115-3:2016
- Edition
- 1.0
Metadata standard
- Title
- ISO/TS 19157-2:2016
- Edition
- 1.0
- Title
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)
- 2021
- Edition
- 1.0
Identifier
Overviews
thumbnail
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available