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environment

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    High quality digital images are captured using a digital SLR camera at the plots (core 1 hectare vegetation plot and Ti Tree East) at the TERN Alice Mulga SuperSite using the panoramic photopoint method. The panoramic photopoint method may be the most informative in open forests/woodlands and rangelands. Three photopoints are established configured in an equilateral triangle (2.5m sides) with the centre marked with a star dropper and the location recorded with DGPS. At each photopoint take photographic sequences in a 360° panorama, with up to 40 photographs with a minimum 50% overlap between consecutive photographs. For more information about the method, see <a href= 'http://dx.doi.org/10.13140/2.1.4287.3607'>White, el al. (2012) AusPlots Rangelands Survey Protocols Manual Version 1.2.9.</a> <br> The Alice Mulga SuperSite was established in 2010 at Pine Hill Cattle Station with research plots located in low open woodland Mulga (Acacia aneura) and non-Acacia, hummock grassland, and river red gum forest. For additional site information, see <a href = 'https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/alice-mulga-supersite/'>https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/alice-mulga-supersite</a> . <br> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed under and overstorey cameras, five-photopoint images, and ancillary images of fauna and flora. <br><br>

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    Statewide composite of fire scars (burnt area) derived from all available Sentinel-2 images acquired over Queensland. It is available in both monthly and annual composites. Fire scars have been mapped using an automated change detection method, with supplementary manual interpretation. This data contains both automated and manually edited data.

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    High quality digital site reference images are captured for the core 1 hectare vegetation plot of the site on an annual basis to provide context for researchers to understand the general layout and vegetation of the study site, and as a visual reference to monitor any changes over time. Photopoints are taken annually using the five point photopoint method. The set of images for each year usually consists of twenty images: four images taken at each corner of the plot facing each of the four cardinal points, and four images taken from the centre of the plot facing each corner. <br /> 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 <em>Eucalyptus miniata</em>. 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/ . <br /> Phenocam images are also collected at the site.

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    Terrestrial laser scans were acquired in native Eucalypt Open Forest (dry sclerophyll Box-Ironbark forest) in Victoria, Australia. Two plots (RUSH06 and RUSH07) with a 40 m radius were established in Rushworth forest and partially harvested in May 2012 to acquire accurate estimates of above-ground biomass. The main tree species in these plots were Eucalyptus leucoxylon, Eucalyptus microcarpa and Eucalyptus tricarpa. Single trees were extracted from the TLS data and quantitative structure models were used to estimate the tree volume directly from the point cloud data. Above-ground biomass (AGB) was inferred from the derived volumes and basic wood density information, and compared with estimates of above-ground biomass derived from allometric equations and destructive sampling. See <a href="https://doi.org/10.1111/2041-210X.12301">Calders et al. (2014)</a> and <a href="http://www.vcccar.org.au/publication/final-report/comprehensive-carbon-assessment-program">Murphy et al. (2014)</a> for further information.

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    <p>Fixed cameras installed at the Wombat Stringybark Eucalypt SuperSite provide a time series of fine scale data as a long-term record of vegetation structure and condition. This dense time series of phenocam images provides data for analysis of ecological responses to climate variability, and when consolidated across the entire terrestrial ecosystem research network, supports calibration and validation of satellite-derived remote sensing data, ensuring delivery of higher quality results for broader scale environmental monitoring products.</p> <p>Images are captured half hourly during daylight hours. Images and data products, including timeseries of the Green Chromatic Coordinate (Gcc) for a region-of-interest (ROI) that delineates an area of specific vegetation type, are made available on an almost real-time basis.</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, digital cover photography (DCP), and ancillary images of fauna and flora.</p>

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    This dataset consists of images of fauna, flora, fungi or general scenery or events captured at the site on an ad-hoc basis and may provide the researcher with information regarding the species that occupy, frequent or traverse this site.<br /> <br /> The Boyagin Wandoo Woodland SuperSite was established in 2017 in Wandoo Woodland, which is surrounded by broadacre farming. About 80% of the overstorey cover is <em>Eucalyptus accedens</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/ .<br /> <br /> Other images collected at the site include digital hemispherical photography and digital cover photography.

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    This dataset lists land surface substrate characteristics observed in Rangeland sites across Australia by the TERN Surveillance Monitoring team, using standardised AusPlots methodologies. <br /> Land surface substrate observations are collected at each site as part of the AusPlots <a href="http://linked.data.gov.au/def/ausplots-cv/c5a32483-bf2f-421d-b03d-6d81e1195de2">Point intercept</a> method. At each site, observations on the substrate type (e.g. rock, coarse woody debris, litter) are recorded on transect laid out on the plots see AusPlots <a href="http://linked.data.gov.au/def/ausplots-cv/c5a32483-bf2f-421d-b03d-6d81e1195de2">Point intercept</a> method. These records form the basis for ground cover derivation, see the Ausplots <a href="http://linked.data.gov.au/def/tern-cv/1ae719f6-93f2-494c-822d-2631b1d3e6c3">Ground cover</a> and <a href="http://linked.data.gov.au/def/ausplots-cv/c5a32483-bf2f-421d-b03d-6d81e1195de2">Point intercept</a> methods.<br />

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    <p>Fixed cameras installed at the Gingin Banksia Woodland SuperSite provide a time series of fine scale data as a long-term record of vegetation structure and condition. This dense time series of phenocam images provides data for analysis of ecological responses to climate variability, and when consolidated across the entire terrestrial ecosystem research network, supports calibration and validation of satellite-derived remote sensing data, ensuring delivery of higher quality results for broader scale environmental monitoring products.</p> <p>Images are captured hourly during daylight hours. Images and data products, including timeseries of the Green Chromatic Coordinate (Gcc) for a region-of-interest (ROI) that delineates an area of specific vegetation type, are made available on an almost real-time basis.</p> <p>The Gingin Banksia Woodland SuperSite was established in 2011 and is located in a natural woodland of high species diversity with an overstorey dominated by Banksia species. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/gingin-banksia-woodland-supersite/.</p> <p>Other images collected at the site include photopoints, hemispherical upward photographs, and ancillary images of fauna and flora. </p>

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    <p>Fixed cameras installed at the Boyagin SuperSite provide a time series of fine scale data as a long-term record of vegetation structure and condition. This dense time series of phenocam images provides data for analysis of ecological responses to climate variability, and when consolidated across the entire terrestrial ecosystem research network, supports calibration and validation of satellite-derived remote sensing data, ensuring delivery of higher quality results for broader scale environmental monitoring products.</p> <p>Images are captured half hourly during daylight hours. Images and data products, including timeseries of the Green Chromatic Coordinate (Gcc) for a region-of-interest (ROI) that delineates an area of specific vegetation type, are made available on an almost real-time basis. </p> <p>The Boyagin Wandoo Woodland SuperSite was established in 2017 at the Boyagin Nature Reserve with research plots located in Wandoo woodland (<em>Eucalypt sp.</em>). The core 1 ha plot is located in a dense Eucalypt woodland. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/ .</p> <p> Other images collected at the site include digital cover and hemispherical photography (DCP and DHP) and ancillary images of fauna and flora.</p>

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    <p>This data set consists of a shapefile/kml of mangrove extent and dominant species for Kakadu National Park mangroves generated from true colour aerial photographs acquired in 1991.</p> <p>From true color 1991 orthomosaics of Field Island and the Wildman, West, and South Alligator Rivers, mangroves were mapped by first applying a fine scale spectral difference segmentation within eCognition to all three visible bands (blue, green, and red). A maximum likelihood (ML) algorithm within the environment for visualizing images (ENVI) software was then used to classify all segments using training areas associated with mangroves, but also water, mudflats, sandflats, and coastal woodlands. These were identified through visual interpretation of the imagery. Segmentation was necessary as 1) the diversity of structures and shadows within and between tree crowns limited the application of pixel-based classification procedures and 2) the color balance between the different photographs comprising the orthomosaics varied. All segments were examined individually and methodically to determine whether they should be reallocated to a non-mangrove class (e.g., mudflats) or confirmed as mangroves. Open woodlands dominated by Eucalyptus species could also be visually identified within the aerial photography (AP) orthoimages, although their discrimination was assisted by only considering areas where the underlying LiDAR DTM (Digital Terrain Model) exceeded 10 m, assuming this excludes tidally inundated sections.</p>