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Foliage Projective Cover - Landsat, DETSI Algorithm, QLD Coverage 

Ver: 1.0
Status of Data: completed
Update Frequency: notPlanned
Security Classification: unclassified
Record Last Modified: 2025-12-02
Viewed 5864 times
Accessed 300 times
Dataset Created: 2017-01-19
Dataset Published: 2021-11-11
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLHTTPCloud Optimised GeoTIFFs - FPC layers in bespoke Albers projection for QueenslandHTTPCloud Optimised GeoTIFFs - Associated corrections layer for FPCHTTPCloud Optimised GeoTIFFs - FPC layers in Australian Albers projectionHTTPLandscape Data VisualiserHTTPfpc_landsat_filenaming_convention.txtHTTPro-crate-metadata.jsonWMSlztmre_qld_e8814_dhxa2
How to cite this collection:
Department of the Environment, T. (2021). Foliage Projective Cover - Landsat, DETSI Algorithm, QLD Coverage. Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/508f322a-a9fd-459f-9122-df52e2b6579e 
Foliage Projective Cover (FPC) is the percentage of ground area occupied by the vertical projection of foliage. The Remote Sensing Centre FPC mapping is based on regression models applied to dry season (May to October) Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 OLI imagery for the period 1988-2014. An annual woody spectral index image is created for each year using a multiple regression model trained from field data collected mostly over the period 1996-1999. A robust regression of the time series of the annual woody spectral index is then performed. The estimated foliage projective cover is the prediction at the date of the selected dry season image for 2014. Where this deviates significantly from the woody spectral index for that date, further tests are undertaken before this estimate is accepted. In some cases, the final estimate is the woody spectral index value rather than the robust regression prediction. The product is further masked to remove areas classified as non-woody. 
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. This product was produced in collaboration with the Joint Remote Sensing Research Program (JRSRP) using satellite imagery obtained from the United States Geological Survey (USGS). 
Purpose
Data not provided. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure Steps

1. 

Algorithm: FPC is the percentage of ground area occupied by the vertical projection of foliage. Image value = FPC + 100 (i.e. FPC of 5% = image value of 105). The pixel values in the QLD_FPC_X data set represent the predicted FPC values. Range is 100-200 which is equivalent to 0-100% FPC. Values erroneously predicted above 100% or below 0% have been classed as 200 and 100 respectively. Zero values indicate null data. 

2. 

Masks: A number of datasets have been used to mask out certain features from the FPC dataset: 1) Non-woody vegetation has been masked using the 2014 Woody Vegetation Extent dataset. 2) Cropping and plantation areas have been masked using the 1999 Queensland Land Use Mapping Program (QLUMP) dataset (https://www.qld.gov.au/environment/land/management/mapping/statewide-monitoring/qlump). 3) A Landsat-derived water index was used to mask water bodies from each individual FPC image (Danaher and Collett 2006). An additional mask is applied for areas with persistent inundation based on multi-temporal analysis of the water index. 4) A topographic correction based on the 1 second SRTM derived Digital Surface Model, Version 1.0, was applied to misclassified steep east-facing slopes. The SRTM data consisted of a DEM and slope layer as processed by Geosciences Australia. 

Queensland
Temporal Coverage
From 1988-01-01 to 2014-12-31 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Data Quality Assessment Scope
Corrections have been applied to remove errors due to topographic effects, cloud, cloud shadow, water, cropping, and regrowth following clearing. Some errors may remain. 
Data Quality Report
Data not provided. 
Data Quality Assessment Outcome
Comparison of overstorey FPC estimates with independent field estimates of perennial FPC acquired for a range of vegetation types over Queensland, show very good agreement (r2=0.84). Further independent quantitative validation of the final FPC product showed good agreement with field sites (r2=0.78) and lidar data (r2=0.93) estimates of FPC. 
ANZSRC - FOR
Climate change impacts and adaptation
GCMD Sciences
BIOSPHERE - VEGETATION COVER
Horizontal Resolution
1 meter - < 30 meters
Instruments
ETM+
OLI
TM
Parameters
vegetation area fraction
Platforms
LANDSAT-5
LANDSAT-7
LANDSAT-8
Temporal Resolution
Weekly - < Monthly
Topic
environment
imageryBaseMapsEarthCover
Author
Department of the Environment, Tourism, Science and Innovation, Queensland Government
Contact Point
Data Enquiries, Earth Observation and Social Sciences (EOSS)
Publisher
Terrestrial Ecosystem Research Network
Armston, J. D., et al. (2002). Geometric correction of Landsat MSS, TM, and ETM+ imagery for mapping of woody vegetation cover and change detection in Queensland.
Armston, J.D., Denham, R.J., Danaher, T.J., Scarth, P.F. and Moffiet, T. (2008). Prediction and validation of foliage projective cover from Landsat-5 TM and Landsat-7 ETM+ im;agery for Queensland, Australia.
Storey, J., Choate, M., and Lee, K. (2014). Landsat 8 operational land imagery on-orbit geometric calibration and performance.
de Vries, C., Danaher, T., Denham, R., Scarth, P. & Phinn, S. (2007). An operational radiometric calibration procedure for the Landsat sensors based on pseudo-invariant target sites.
Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery.
Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013). An operational scheme for deriving standardised surface reflectance from Landsat TM/ETM+ and SPOT HRG imagery for Eastern Australia.
Danaher, T., et al. (2010). Ecosystem Function in Savannas: Measurement and Modelling at Landscape to Global Scales. Vol. Section 3. Remote Sensing of Biophysical and Biochemical Characteristics in Savannas.
Kitchen, J., et al. (2010). Operational use of annual Landsat-5 TM and Landsat-7 ETM+ image time-series for mapping wooded extent and foliage projective cover in north-eastern Australia.
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