remote sensing of biophysical parameters: linking field, airborne and continental scale...
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Remote Sensing of Biophysical Parameters: Linking Field, Airborne
and Continental Scale DataPresentation by: Kasper Johansen1,2 and Stuart Phinn1,2
1The University of Queensland ([email protected])2 Joint Remote Sensing Research Program
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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
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Plot locations of the ASN
Australian Supersites Network (ASN) and AusCover
Plot locations of AusCover
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Australian Supersites Network and AusCover
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AusCover Activities and Products
A nationally consistent approach to deliver, calibrate and validate satellite image based data sets designed for Australian conditions.
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Field-based Measurements Satellite Based MeasurementsAirborne Measurements
AusCover Activities and Products:AusCover Field and Airborne Campaigns
Time-Series Measurements
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Field and Airborne Data Collection Design
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• 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
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• 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
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Field and Airborne Data Collection Design
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Field Data Collection Processes:Ground, mid-storey and over-storey
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Field Data Collection Processes:Basal area
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Field Data Collection Processes:Hemispherical photos
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Field Data Collection Processes:Leaf area index
Digital Plant Canopy Imager (CI-110)
Licor Plant Canopy Analyser LAI-2200
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Field Data Collection Processes:Terrestrial laser scanning
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Field Data Collection Processes:Terrestrial laser scanning
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Field Data Collection Processes:Terrestrial laser scanning
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Field Data Collection Processes:Leaf samples and chemistry
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Field Data Collection Processes:Phenology
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Field Data Collection Processes:Spectrometer measurements
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Field Data Collection Processes:Atmospheric measurements
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Field Data Collection Processes:Accessing the field data
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Airborne Data Collection Processes:LiDAR and hyper-spectral data
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Airborne Data Collection Processes:LiDAR and hyper-spectral data
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Airborne Data Collection Processes:LiDAR and hyper-spectral data
Siterapid1
PAI3.673067
rapid2 3.363939rapid3 2.279929rapid4 2.62392rapid5 4.901737rapid6 3.14998rapid7 3.335957rapid8 3.652275rapid9 3.190056rapid10 6.049383rapid11 2.897515rapid12 3.360222
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Airborne Data Collection Processes:LiDAR and hyper-spectral data
200 m
100 m
50 m
2 km
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Airborne Data Collection Processes:LiDAR and hyper-spectral data
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AusCover Products
• The vertically-projected fraction of long-term, persistent green vegetation (nominally woody vegetation) cover
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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
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Landsat Time-Series of Persistent Green-Vegetation Fraction for Australia
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maskNon-PGV
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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
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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)
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Accessing the Persistent Green Vegetation Fraction Product
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Future Work & ConclusionsFuture 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
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AcknowledgementsAGENCY 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
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Remote Sensing of Biophysical Parameters: Linking Field, Airborne
and Continental Scale DataPresentation by: Kasper Johansen1,2 and Stuart Phinn1,2
1The University of Queensland ([email protected])2 Joint Remote Sensing Research Program