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<p>Hemispherical photography has been collected across Australia to characterise plant canopy cover and structure, and to study leaf area index. Hemispherical photography is a technique for quantifying plant canopies via photographs captured through a digital camera with hemispherical or fisheye lens. Such photographs can be captured from beneath the canopy, looking upwards, (orientated towards zenith) or above the canopy looking downwards. These measurements have typically been collected in conjunction with the Statewide Landcover and Trees Study (SLATS) star transects field data together with plant canopy analysers such as LAI-2200 and CI-110.</p> <p>Data can be downloaded from https://field.jrsrp.com/ by selecting the combination Field and Hemispheric imagery. Photographs can be accesed through the right-hand side panel, or by finding the file_loc attribute in the csv file. </p>
This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product here <a href="https://portal.tern.org.au/metadata/24072">Seasonal dynamic reference cover method - Landsat, JRSRP algorithm version 3.0, Queensland Coverage</a>. The seasonal dynamic reference cover method images are created using a modified version of the dynamic reference cover method developed by <a href="https://doi.org/10.1016/j.rse.2012.02.021">Bastin et al (2012)</a>. This approach calculates a minimum ground cover image over all years to identify locations of most persistent ground cover in years with the lowest rainfall, then uses a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. The output is a difference image between the cover amount of a pixel's reference pixels and the actual cover at that pixel for the season being analysed. Negative values indicate pixels which have less cover than the reference pixels. <br> The main differences between this method and the original method are that this method uses seasonal fractional ground cover rather than the preceding ground cover index (GCI) and this method excludes cleared areas and certain landforms (undulating slopes), which are considered unsuitable for use as reference pixels.
The climate adjusted linear seasonal persistent green trend is derived from analysis of the linear seasonal persistent green trend, adjusted for rainfall. The current version is based on the 1987-2014 period. <br> Seasonal persistent green cover is derived from seasonal 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 summarised using simple linear regression, and the slope of the fitted line is captured in the linear seasonal persistent green product. This product is further processed to produce a climate-adjusted version.
<p>Digital Cover Photography (DCP) upward-looking images are collected to capture vegetation cover within the core hectare at the Litchfield Savanna SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). </p><p> The Litchfield Savanna SuperSite was established in 2013 in Litchfield National Park. Site selection was influenced by the history of long-term monitoring work undertaken in this area by the Darwin Centre for Bushfire Research (formerly Bushfires NT). The core 1ha plot is dominated by Eucalyptus miniata. The site is representative of the dominant ecosystem type across northern Australia: frequently burnt tropical savanna in high rainfall areas. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/litchfield-savanna-supersite/ . </p><p> Photopoints are also collected at the site. </p>
<p> Digital Cover Photography (DCP) upward-looking images are collected at least twice per year to capture vegetation cover at Calperum 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.</p> <p> The Calperum Mallee SuperSite was established in 2011 and is located on Calperum Station with research plots located in mallee woodland (burnt in 2014), Callitris woodland and a river floodplain (recovering from extensive grazing), consisting of black box, river red gum and lignum. The core 1 ha plot is located in mallee woodland. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/calperum-mallee-supersite/ .</p> <p> 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>
<p>Digital Hemispherical Photography (DHP) upward-looking images are collected up to twice per year to capture vegetation and crown cover at Wombat Stringybark Eucalypt SuperSite. These images are used to estimate Leaf area index (LAI). The images are captured at the times of estimated maximum and minimum LAI. </p><p> The site was established in 2010 in the Wombat State Forest in Central Victoria. The site is dry eucalypt forest with main species <em>Eucalyptus obliqua</em>, <em>Eucalyptus radiata</em> and <em>Euclayptus rubida</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/wombat-stringybark-eucalypt-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>
The Sentinel-2 seasonal fractional ground cover product shows the proportion of bare ground, green and non-green ground cover and is derived directly from the Sentinel-2 seasonal fractional cover product, also produced by Queensland's Remote Sensing Centre. The seasonal fractional cover product is a spatially explicit raster product, which predicts vegetation cover at medium resolution (10 m per-pixel) for each 3-month calendar season. However, the seasonal fractional cover product does not distinguish tree and mid-level woody foliage and branch cover from green and dry ground cover. As a result, in areas with even minimal tree cover (>15%), estimates of ground cover become uncertain. With the development of the fractional cover time-series, it has become possible to derive an estimate of ‘persistent green’ based on time-series analysis. The persistent green vegetation product provides an estimate of the vertically-projected green-vegetation fraction where vegetation is deemed to persist over time. These areas are nominally woody vegetation. This separation of the 'persistent green' from the fractional cover product, allows for the adjustment of the underlying spectral signature of the fractional cover image and the creation of a resulting 'true' ground cover estimate for each season. The estimates of cover are restricted to areas of <60% woody vegetation. Currently, the persistent green product has only been produced at 30 m pixel resolution based on Landsat imagery, resulting in this Sentinel-2 seasonal ground cover product having a medium 30 m pixel resolution also. This is an experimental product which has not been fully validated. This product is similar to the <a href="https://portal.tern.org.au/metadata/23884 ">Seasonal ground cover - Landsat, JRSRP algorithm Version 3.0, Australia Coverage</a> which is based on a different satellite sensor.
<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>
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 (dp1) time series. A single band image is produced: persistent green vegetation cover (in percent). The no data value is 255.
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.