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VEGETATION COVER

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    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.

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    The MODIS Land Condition Index (LCI) is an index of total vegetation cover (green and non-photosynthetic vegetation ), and so is also an index of soil exposure. The LCI is a normalised difference index based on MODIS bands in the mid-infrared portion of the spectrum. The index is produced from 500-m MODIS nadir BRDF adjusted reflectance (NBAR) data. As with all products derived from passive remote sensing imagery, this product represents the world as seen from above. Therefore, the cover recorded by this product represent what would be observed from a birds-eye-view. Therefore, dense canopy may prevent observation of significant soil exposure.

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    The data set is a statewide annual composite of fire scars (burnt area) derived from all available Landsat 5, 7 and 8 images acquired over the period January to December using time series change detection. Fire scars are automatically detected and mapped using dense time series of Landsat imagery acquired over the period 1987 - present. In addition, from 2013, products have undergone significant quality assessment and manual editing. The automated Landsat fire scar map products covering the period 1987-2012 were validated using a Landsat-derived data set of over 500,000 random points sampling the spatial and temporal variability. On average, over 80% of fire scars captured in Landsat imagery have been correctly mapped with less than 30% false fire rate. These error rates are significantly reduced in the edited 2013-2016 fire scar data sets, although this has not been quantified. <br> For the 2016 annual fire scar composite, the manual editing stage incorporated Landsat and Sentinel 2A imagery (resampled to match Landsat spatial resolution), allowing for increased cloud-free ground observations, and an associated reduction in the number of missed fires (not quantified). Sentinel 2A images were primarily used to map fire scars that were otherwise undetectable in the Landsat sequence due to cloud cover/Landsat revisit time. Additionally, Landsat-7 SLC-Off imagery (affected by striping) was excluded from the 2016 annual composite. It is expected that these modifications should result in improved mapping accuracy for the 2016 period.<br> A new fire scar detection algorithm has been developed, with a new edited product implemented in 2021.

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    Three maps are available: 1) foliage projective cover, 2) forest extent, attributed with the foliage projective cover and 3) accuracy of the extent maps, which also acts as masks of forest and other wooded lands. Each pixel in map 1 estimates the fraction of the ground covered by green foliage. Each pixel in map 2 shows two pieces of information. The first is a classification of whether the vegetation is forest or not. The pixels classified as forest are attributed with the second piece of information: the foliage projective cover. Each pixel in map 3 is a class that provides information on the classification accuracies of the woody extent. These maps are derived from Landsat.

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    The linear seasonal persistent green trend is derived from analysis of the seasonal persistent green product over time. The current version is based on the 1987-2014 period. <br> Seasonal persistent green cover is derived from seasonal fractional cover using a weighted smooth spline fitting routine. This weights a smooth line to the minimum values of the seasonal green cover. This smooth minimum is designed to represent the slower changing green component, ideally consisting of perennial vegetation including over-storey, mid-storey and persistent ground cover. The seasonal persistent green is then summarized using simple linear regression, and the slope of the fitted line is captured in this product. The original units are percentage points per year. Values are later truncated and scaled.

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    <p>Digital Cover Photography (DCP) upward-looking images are collected twice per year to capture vegetation cover within the core hectare at Cumberland Plain SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). The images are captured at the times of estimated maximum and minimum LAI. In addition, DCP images have been taken on a monthly basis from 2018-2020 at a subset of sites in the core hectare, co-located with litterfall traps and under-canopy radiation sensors, to evaluate more detailed seasonal dynamics of LAI and other aspects of canopy growth. </p><p>The Cumberland Plain SuperSite was established in 2012 in endangered remnant Eucalyptus woodland and is subject to pressure from invasive weeds, altered fire regimes, urban development, conversion to agriculture and extreme climate events. However, the woodland is in excellent condition with the exception of edge effects. The site is located on the Hawkesbury Campus of the University of Western Sydney in New South Wales. For additional site information, see https://deims.org/a1bb29d8-197c-4181-90d8-76083afd44bb/ . </p><p>Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed overstorey cameras, and ancillary images of fauna and flora. </p>

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    An estimate of persistent green cover per season. This is intended to estimate the portion of vegetation that does not completely senesce within a year, which primarily consists of woody vegetation (trees and shrubs), although there are exceptions where non-woody cover remains green all year round. It is derived by fitting a multi-iteration minimum weighted smoothing spline through the green fraction of the seasonal fractional cover (dim) time series.

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    <p>Digital Hemispherical Photography (DHP) upward-looking images were collected annually to capture vegetation and crown cover at Daintree Rainforest SuperSite. These images are used to estimate Leaf Area Index (LAI). </p><p> The site is located in lowland complex mesophyll vine forest near Cape Tribulation. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/daintree-rainforest-supersite/ . </p><p> Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras and ancilliary images of fauna and flora. </p>

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    Field spectroradiometer measurements have been collected at several locations across Australia (formally known as the AusCover Supersites) to relate field based measurements to satellite data products, such as Landsat and MODIS NBAR products. The Hyperspectral ground-based data is used for calibration and validation of at-surface reflectance of airborne hyper-spectral image data. Once the at-surface reflectance values of the hyper-spectral image data have been validated, the data can be used for up-scaling to medium spatial resolution Landsat and MODIS data for cal/val of NBAR products.

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    <p>Digital Cover Photography (DCP) upward-looking images are collected up to twice per year to capture vegetation cover at Tumbarumba Wet Eucalypt SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). </p><p> The Tumbarumba Flux site was established in 2000 and started measuring in 2001. The 1 hectare (ha) SuperSite plot was established in 2015. Preliminary images have been captured since 2000 using various sampling strategies and protocols. Since 2015 the 1 ha Supersite has had a consistent DCP protocol implemented twice per year. The overstorey is dominated by <em>Eucalyptus delegatensis</em> and <em>Eucalyptus dalrympleana</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/tumbarumba-wet-eucalypt-supersite/ .</p><p> Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras, and ancillary images of fauna and flora. </p>