1. Remote Sensing of Biophysical
Parameters: Linking Field, Airborne
and Continental Scale Data
Presentation by: Kasper Johansen1,2 and Stuart Phinn1,2
1The University of Queensland (k.johansen@uq.edu.au)
2 Joint Remote Sensing Research Program

2. Outline
1. Introduction: Australian Supersites Network and
AusCover
2. AusCover Activities and Products
3. AusCover Data Collection
4. Linking Field, Airborne and Satellite Image Data

3. Plot locations of the ASN
Australian Supersites Network (ASN)
and AusCover
Plot locations of AusCover

4. Australian Supersites Network and
AusCover

5. AusCover Activities and Products
A nationally consistent approach to deliver, calibrate and validate satellite
image based data sets designed for Australian conditions.

6. Field-based Measurements Satellite Based MeasurementsAirborne Measurements
AusCover Activities and Products:
AusCover Field and Airborne Campaigns
Time-Series Measurements

7. Field and Airborne Data Collection Design
• Each site represents dominant
biome or environment with
high conservation value
• Homogenous 5 x 5 km sites
• Capture variability within site
• Rapid sites (TLS, hemispherical
photos, GPS)
• Field data collection
influenced by accessibility and
type of environment

8. • Homogenous plots
• Ground, mid-storey and
over-storey
• Basal area
• Vegetation structure
• LAI (LAI-2200)
• Hemispherical photos
• Terrestrial Laser Scanning
• Leaf samples and species
ID
• Phenology photos
Field and Airborne Data Collection Design

9. Field and Airborne Data Collection Design

10. Field Data Collection Processes:
Ground, mid-storey and over-storey

11. Field Data Collection Processes:
Basal area

12. Field Data Collection Processes:
Hemispherical photos

13. Field Data Collection Processes:
Leaf area index
Digital Plant Canopy Imager (CI-110)
Licor Plant Canopy Analyser LAI-2200

14. Field Data Collection Processes:
Terrestrial laser scanning

15. Field Data Collection Processes:
Terrestrial laser scanning

16. Field Data Collection Processes:
Terrestrial laser scanning

17. Field Data Collection Processes:
Leaf samples and chemistry

18. Field Data Collection Processes:
Phenology

19. Field Data Collection Processes:
Spectrometer measurements

20. Field Data Collection Processes:
Atmospheric measurements

21. Field Data Collection Processes:
Accessing the field data

22. Airborne Data Collection Processes:
LiDAR and hyper-spectral data

23. Airborne Data Collection Processes:
LiDAR and hyper-spectral data

24. Airborne Data Collection Processes:
LiDAR and hyper-spectral data
Site
rapid1
PAI
3.673067
rapid2 3.363939
rapid3 2.279929
rapid4 2.62392
rapid5 4.901737
rapid6 3.14998
rapid7 3.335957
rapid8 3.652275
rapid9 3.190056
rapid10 6.049383
rapid11 2.897515
rapid12 3.360222

25. Airborne Data Collection Processes:
LiDAR and hyper-spectral data
200 m
100 m
50 m
2 km

26. Airborne Data Collection Processes:
LiDAR and hyper-spectral data

27. AusCover Products
• The vertically-projected fraction of long-term, persistent green
vegetation (nominally woody vegetation) cover

28. Landsat Time-Series of Persistent Green-
Vegetation Fraction for Australia
SOURCE DESCRIPTION
QLD DSITIA Fractional-cover field sites
ABARES Fractional-cover field sites
NSW OEH SPOT-5 Image-interpretation
NT Bushfires DBH field sites
NT NRETAS Fractional-cover field sites
ACRIS Locations of low-foliage scrub
WA Woody-vegetation sampling sites
QLD Herbarium Biomass field sites
• Field data from 800 sites collected using nationally consistent protocol, RMSE of 11%
• Decision tree classifier based on robust regression statistics used to classify each pixel
as persistent or non-persistent green vegetation

29. Landsat Time-Series of Persistent Green-
Vegetation Fraction for Australia
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1000 2000 3000 4000
day
greenfraction
min
max
mask
Non-PGV

30. Persistent Green Vegetation Fraction –
Airborne LiDAR Validation
• Collation of Riegl LMS-Q560 and Riegl LMS-Q680i waveform LiDAR datasets
captured within the temporal extent of the product (2000-2010)
• Woody Foliage Projective Cover estimates from field calibration of LiDAR Pgap
• Comparison with Landsat persistent green extent and cover fractions

31. Persistent Green Vegetation Fraction –
Airborne LiDAR Validation
• The mean RMSE and Pearson correlation coefficient across all flight
paths were 0.13±0.076 and 0.71±0.15, respectively.
• Herbaceous and woody understorey not included in LiDAR FPC (<0.5m)

32. Accessing the Persistent Green
Vegetation Fraction Product

33. Future Work & Conclusions
Future Work
• Research linking both ASN and AusCover field, airborne and satellite
image data and flux measurements (e.g. for productivity, biomass,
time-series change, vegetation structure and phenology assessment)
• Expand data collection over time
Conclusions
• Unique data sets available for selected supersites across Australia
• Will support research and ecosystem science in Australia in selected
biomes
• Working with state and federal government agencies and researchers
associated with AusCover and TERN enabled this work

34. Acknowledgements
AGENCY PEOPLE
ABARES Jasmine Rickards
NT Bushfires Andrew Edwards
NT NRETAS Nick Cuff
ACRIS / CSIRO Gary Bastin, Matt Bradform
WA DEC Graeme Behn
Airborne Research Australia Jorg Hacker
Monash Jason Beringer
CDU Stefan Maier
QLD Herbarium
NSW Office of Environment and Heritage Tim Danaher
JCU Mike Liddell
Individual AusCover nodes
TERN in general

35. Remote Sensing of Biophysical
Parameters: Linking Field, Airborne
and Continental Scale Data
Presentation by: Kasper Johansen1,2 and Stuart Phinn1,2
1The University of Queensland (k.johansen@uq.edu.au)
2 Joint Remote Sensing Research Program