For some time, Remote Sensing Sciences, has produced Foliage Projective Cover (FPC) using a model applied to Landsat surface reflectance imagery, calibrated by field observations. An updated model was developed which relates field measurements of FPC to 2-year time series of Normalized Difference Vegetation Index (NDVI) computed from Landsat seasonal surface reflectance composites. The model is intended to be applied to Landsat and Sentinel-2 satellite imagery, given their similar spectral characteristics. However, due to insufficient field data coincident with the Sentinel-2 satellite program, the model was fitted on Landsat imagery using a significantly expanded, national set of field data than was used for the previous Landsat FPC model fitting. The FPC model relates the field measured green fraction of mid- and over-storey foliage cover to the minimum value of NDVI calculated from 2-years of Landsat seasonal surface reflectance composites. NDVI is a standard vegetation index used in remote sensing which is highly correlated with vegetation photosynthesis. The model is then applied to analogous Sentinel-2 seasonal surface reflectance composites to produce an FPC image at Sentinel-2 spatial resolution (i.e. 10 m) using the radiometric relationships established between Sentinel-2 and Landsat in Flood (2017). This is intended to represent the FPC for that 2-year period rather than any single date, hence the date range in the dataset file name. The dataset is generally expected to provide a reasonable estimate of the range of FPC values for any given stand of woody vegetation, but it is expected there will be over- and under-estimation of absolute FPC values for any specific location (i.e. pixel) due to a range of factors. The FPC model is sensitive to fluctuations in vegetation greenness, leading to anomalies such as high FPC on irrigated pastures or locations with very green herbaceous or grass understoreys. A given pixel in the FPC image, represents the predicted FPC in the season with the least green/driest vegetation cover over the 2-year period assumed to be that with the least influence of seasonally variable herbaceous vegetation and grasses on the more seasonally stable woody FPC estimates. The two-year period was used partly because it represents a period relative to tree growth but was also constrained due to the limited availability of imagery in the early Sentinel-2 time series. The FPC dataset is constrained by the woody vegetation extent dataset for the FPC year.

<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>

<p>Digital Hemispherical Photography (DHP) upward-looking images were collected annually to capture vegetation and crown cover at Whroo Dry Eucalypt SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). </p><p> The site was established in 2010 in box woodland dominated by <em>Eucalyptus microcarpa</em> (grey box) and <em>eucalyptus leucoxylon</em> (yellow gum). For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/whroo-dry-eucalypt-supersite/. </p><p> Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed overstorey cameras and ancilliary images of fauna and flora. </p>

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.

This dataset contains maps of woody vegetation extent and woody foliage projective cover (FPC) for New South Wales at 5 metre resolution. <br /><br /> Woody vegetation is a key feature of our landscape and an integral part of our society. We value it because it contributes to the economy, protects the land, provides us with recreation, and gives refuge to the unique and diverse range of fauna that we regard so highly. Yet it poses a significant threat to us in times of fire and storm. So information about trees is vital for a range of business, property planning, monitoring, risk assessment, and conservation activities. <br /><br /> The datasets are: <br /> Woody vegetation extent. A presence/absence map showing areas of trees and shrubs, taller than two metres, that are visible at the resolution of the imagery used in the analysis. This shows the location, extent, and density of foliage cover for stands of woody vegetation, enabling identification of small features such as trees in paddocks and scattered woodlands through to the largest expanses of forest in the State. Woody extent products contain 'bcu' in the file name.<br /><br /> Woody foliage projective cover (FPC). FPC is a measure of the proportion of the ground area covered by foliage (or photosynthetic tissue) held in a vertical plane and is a measure of canopy density. Woody FPC products contain 'bcv' in the file name. <br /><br /> Both mosaics and tiles are available, along with a shape file that identifies the location of the tiles.

<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>

The dataset consists of species identity and projective foliage cover (PFC) of ground layer vascular plants from five sites located near Mareeba, in northern Queensland. The sites are located in eucalypt communities with altitudes ranging from 380 to 840 m. Data have been collected annually since 1992, in April and May, i.e. during the annual peak of plant species richness. At each site, data collection is carried out using ten 0.5 m² quadrats deployed within a permanently marked 50 x 10 m plot. For each quadrat, all plant species visible above ground are identified and sampled. PFC data for each species from the ten quadrats are averaged. Any additional species occurring within the 50 x 10 m plot is also recorded and assigned a PFC of 0.1% (Neldner and Butler, 2021).

Digital Cover Photography (DCP) upward-looking images are collected ideally twice per year (depending upon travel availability) to capture vegetation cover at Alice Mulga SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). The Alice Mulga SuperSite was established in 2010 at Pine Hill Cattle Station with research plots located in low open woodland Mulga (<em>Acacia aneura</em>) and non-Acacia, hummock grassland, and river red gum forest. The core 1 ha plot is located in a dense Mulga woodland (cover 70–80%). For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/alice-mulga-supersite/ . Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras, panoramic landscape and ancillary images of fauna and flora.

<p>Digital Cover Photography (DCP) upward-looking images are collected twice per year in the core monitoring plot to capture vegetation cover at Great Western Woodlands Site. 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.</p><p> The Great Western Woodlands Site was established in 2012 in the Credo Conservation Reserve. The site is in semi-arid woodland and was operated as a pastoral lease from 1907 to 2007. The core 1 ha plot is characterized by <em>Eucalyptus salmonophloia</em> (salmon gum), with <em>Eucalyptus salubris</em> and <em>Eucalyptus clelandii</em> dominating other research plots. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/great-western-woodlands-supersite/ . </p><p> Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras, panoramic images and ancillary images of fauna and flora.</p>

The TREND (PSRF)- Terrestrial Ecosystems project initiated a landscape-scale monitoring transect along the Adelaide Geosyncline region in southern Australia, initially spanning approximately 550 km. The aim was to examine spatial drivers of species composition and to isolate the influence of climate on whole vegetation community composition and therefore inform on-going monitoring of the impact of climate change. Specific questions were: 1. What are the most important spatial drivers of species and phylogenetic composition along landscape-scale environmental gradients? 2. Can the answer to Question 1. inform selection of suitable spatial analogues for climate change? 3. How can a framework for assessing spatial drivers be used to monitor and interpret shifts in species composition due to climate change? The dataset consists of site and species records (see attachments) for plots established along the Adelaide Geosyncline for the TREND project. Data consist of vascular plant species composition (presence-abundance/absence) within 900m² plots plus site data, including aspect and soil properties. Data have been used to analyze changes in composition with geographic and environmental differences and as a baseline for monitoring.