The datasets in this series comprise predictions of biocondition for Queensland's Bioregions. The datasets are created using a gradient boosting decision tree (GBDT) model based on eight vegetation specific remote sensing (RS) datasets and 17,000 training sites of known vegetation community and condition state. Condition score was modelled as of the difference in the RS space within homogeneous vegetation communities. The product is intended to represent predicted BioCondition for year 2019 rather than any single date.

<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>

This dataset contains spatial layers describing Forest Connectivity from 1995-2019, in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. Forest Connectivity accounts for the general quality of terrestrial habitats supporting biodiversity at each location, the fragmentation of habitat within its neighbourhood and how its position in the landscape contributes to connectivity among the habitats across a region. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. <br> Forest Connectivity, including canopy cover connectivity and fragmentation is concerned and linked to forest condition. Concepts applied are to be aligned with definitions as found in the NSW Biodiversity Indicator Program (BIP) and the Spatial Links methodology for calculating connectivity.<br> Base cover extent grids used are from the NSW RFA Historic Forest Canopy Cover Extent – 1995 to 2019 product. <br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Connectivity - 1995 to 2020'

This dataset contains spatial layers describing Forest Canopy Loss and Recovery from 1998-2019 in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. <br> For this dataset product and the processing of metrics, aspects of canopy loss and disturbances in the forest estate were investigated. Measures of canopy loss and recovery are seen as one of the multiple indicators of forest health. This is related to agents or pressures that affect the capacity of native forests and commercial operations to maintain normal ecosystem functions and sustainably provide productive capacity. <br> To attribute disturbances, as a driver of change, a Multiple Lines of Evidence (MLE) approach was used that leveraged available spatial datasets. This allowed for a project-wide disturbance and disturbance context layer to be generated. This information can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest loss can be potentially assigned or at the very least investigated. <br> The time taken, in terms of years, for areas to recover from losses in forest canopy cover extent can has also been determined. This process identifies the time taken for a patch of forest to return to a 20% canopy cover threshold, and other characteristics such as the forest type and likely disturbance or loss event. <br> Forest Canopy Loss and Recovery uses measures of canopy loss and disturbances which can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest canopy loss can be potentially assigned or at the very least investigated. Time taken in years for areas to recover for losses has also been determined, as-well as other characteristics such as forest type and likely disturbance/loss event. <br> Base cover extent grids used are from the NSW RFA Historic Forest Canopy Cover Extent – 1995 to 2019 product. Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Canopy Loss and Recovery - 1998 to 2020'

This dataset contains bird occurrence data collected at the Cumberland Plain site from 2015 - 2017.

This dataset contains spatial layers describing Forest Canopy Extent from 1995-2019 in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. Forest Canopy Extent is the likelihood that a certain area has forest at any given time. Forest Canopy is defined in accordance with the National State of the Forests Report which defines forests as containing as a minimum, a mature or potentially mature stand height exceeding 2 metres, stands dominated by trees usually having a single stem, where the mature or potentially mature stand component comprises 20% canopy coverage using a Crown Projective Cover (CPC) measure. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. <br> To calculate forest canopy extent, these base grids have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage.<br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Canopy Cover Extent - 1995 to 2020'

High quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the Robson Creek site. Two camera traps were deployed at the site between 17-03-2018 and 25-07-2018. The first camera located in proximity to the acoustic sensor SM2/SM4 which is around 100m from the flux tower and at a height of 1.5 meter above ground, on a star picket. The second camera located for a short while near the tower (10 meter) and was attached on a bungy cord tied to a tree, at a height of 0.3 meter above ground.<br><br> The Robson Creek site lies on the Atherton Tablelands in the wet tropical rain forests of Australia at 680-740 m elevation. It is situated in Danbulla National Park within the Wet Tropics World Heritage Area. The Wet Tropics Bioregion of Australia is situated on the north-eastern coast of Queensland, between Cooktown to the north and Townsville to the south. Approximately 40% (7200 km2) of the region is covered by rain forest. Features of the region include very high plant and animal endemism, characteristics of both Gondwanan and Indo-Malaysian forests, and frequent cyclonic disturbance. The site includes core 1 ha plot (100 m x 100 m) which is located within the fetch of the flux tower and is the focal site of recurrent monitoring, and 25 ha vegetation survey plot. The vegetation survey plot has been set up for inclusion in the Smithsonian Tropical Research Institute’s Center for Tropical Forest Science – Forest Global Earth Observatory (CTFS-ForestGEO) global network of forest research plots. <br><br> For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/robson-creek-rainforest-supersite/ . <br /><br /> Other images collected at the site include time-lapse images taken from 3 phenocams (above canopy). <br /><br /> <iframe allow="autoplay; encrypted-media" allowfullscreen="" frameborder="0" src="https://www.youtube.com/watch?v=WW-cpPMhMz4" title="TERN Robson Creek SuperSite Wildlife 2017" style="height:248px;width:462px;"></iframe> <br />Camera trap results for the TERN FNQ Rainforest SuperSite - Robson Creek, Jan - Feb 2017.

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&nbsp;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>This data set provides the photosynthetic pathways for 2428 species recorded across 541 plots surveyed by Australia’s Terrestrial Ecosystem Research Network (TERN) between 2011 and 2017 (inclusive). TERN survey plots are 1 ha (100 x 100 m) permanently established sites located in a homogeneous area of terrestrial vegetation. At each plot, TERN survey teams record vegetation composition and structural characteristics and collect a range of plant samples using a point-intercept method. Species were assigned a photosynthetic pathway using literature and carbon stable isotope analysis of bulk tissue collected by TERN at the survey plots. </p><p>The data set is comprised of two data tables and one data descriptor that defines the values in the two data tables. The first table contains a list of each species and its photosynthetic pathway. The second table includes a list of all the peer-reviewed sources used to create this data set. </p><p>This data set will be updated on an annual basis as TERN’s plot network expands and new information becomes available. </p>

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 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/ . <br /> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed under and overstorey cameras, panoramic landscape and photopoint images. <br /><br /> <iframe src="https://maps.google.com/maps?layer=c&amp;panoid=VNc5-dZcKkoAAAGuqlmVHw&amp;ie=UTF8&amp;source=embed&amp;output=svembed&amp;cbp=13%2C208.3252%2C%2C0%2C0" title="Photosphere view of the mallee at Calperum SuperSite (photo J. Armston 2014)" style="height:248px;width:462px;"></iframe> <br />Photosphere view of the mallee at Calperum SuperSite (photo J. Armston 2014)<br />