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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

Title
DataCite
Code
doi:10.25901/xqv7-jk46
Codespace
http://dx.doi.org

Publisher

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
+61 7 3365 9097

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
  • FORESTS
  • VEGETATION HEIGHT
  • CANOPY CHARACTERISTICS
ANZSRC Fields of Research
  • Forest ecosystems
  • Forestry fire management
  • Forestry product quality assessment
TERN Platform Vocabulary
  • earth observation satellite
  • LANDSAT-5
  • LANDSAT-6
  • LANDSAT-7
  • LANDSAT-8
  • Sentinel-2A
  • Sentinel-2B
  • Advanced Land Observing Satellite (ALOS)
  • Ice, Cloud and Land Elevation Satellite (ICESat)
TERN Parameter Vocabulary
  • canopy height
  • Metre
QUDT Units of Measure
  • Metre
GCMD Horizontal Resolution Ranges
  • 30 meters - < 100 meters
GCMD Vertical Resolution Ranges
  • 1 meter - < 10 meters
GCMD Temporal Resolution Ranges
  • Multi-Year
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
Linkage
https://w3id.org/tern/static/cc-by/88x31.png

Title
Creative Commons Attribution 4.0 International Licence
Alternate title
CC-BY
Edition
4.0
Website
https://creativecommons.org/licenses/by/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

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
+61 7 3365 9097

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

Code
10.5281/zenodo.5652221
Website
https://github.com/ternaustralia/TERN-ISO19115/releases/tag/v1.0

 
 

Overviews

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Spatial extent

N
S
E
W


Keywords

ANZSRC Fields of Research
Forest ecosystems Forestry fire management Forestry product quality assessment
GCMD Science Keywords
CANOPY CHARACTERISTICS FORESTS VEGETATION HEIGHT

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