This is a series comprises of vegetation condition predictions for biodiversity for the bioregions of Queensland. The datasets were created using a gradient boosting decision tree (GBDT) model based on 10 vegetation-specific remote sensing (RS) datasets and 7,938 training sites of known vegetation community and condition state across Southeast Queensland, Brigalow Belt and Central Queensland Coast bioregions. Condition score was modelled as a function of distance in the remote sensing (RS) space within homogeneous vegetation communities. The product is intended to represent predicted BioCondition for 2021 rather than any singe date. This series includes information relating the version 2.0 products of Spatial BioCondition, which have superseded the version 1.0 products (https://portal.tern.org.au/metadata/TERN/40990eec-5cef-41fe-976b-18286419da0c, https://portal.tern.org.au/metadata/TERN/2c33325c-1dd5-4674-918a-1cd5bfc1a6e3). Spatial BioCondition is not suitable for the measurement of changes in condition over time, and direct comparisons of predictions between versions 1.0 and 2.0 are not advised.

High quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the site. Two cameras were deployed from July to Dec 2018 and between March and May 2019. <br /><br /> 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/. <br /> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed under and overstorey cameras and ancillary images of flora.

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.

This collection contains the data used in the Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S) software tool. From the Data menu, explore and download individual supplementary layers, or download the entire datapack. The Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S) is a software tool developed by the Australian Bureau of Agricultural and Resource Economics and Sciences that enables multi-criteria analysis (MCA) using spatial data. It is a powerful, easy-to-use and flexible decision-support tool that promotes: - framework for assessing options <br> - common metric for classifying, ranking and weighting of the data <br> - tools to compare, combine and explore spatial data <br> - live-update of alternative scenarios and trade-offs. <br>

Vertical plant profiles for the Australian continent were derived through integration of ICESat GLAS waveforms with ALOS PALSAR and Landsat data products. Co-registered Landsat Foliage Projected Cover (FPC) and ALOS PALSAR L-band HH and HV mosaics were segmented to generate objects with similar radar backscatter and cover characteristics. Within these, height, cover, age class and L-band backscatter characteristics were summarised based on the ICESat and Landsat time-series and ALOS PALSAR datasets.

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'

<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>

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.

<br>The carbon balance of NSW forests project is part of the NSW Forest Monitoring and Improvement Program. The Mullion Group was engaged to develop a spatial time-series dataset of forest carbon history for the state of NSW at ~25&nbsp;m resolution. The project used FLINTpro software to integrate historical environmental and land management data to model carbon stock and fluxes. This dataset details the annual total forest carbon stock which is the sum of aboveground, belowground and dead organic matter carbon stocks. Aboveground biomass refers to the amount of carbon stored within aboveground forest components (pools) which includes leaves, branches, bark and stems. Belowground biomass refers to the amount of carbon stored within belowground forest components (pools) which includes coarse and fine roots. Dead organic matter refers to the amount of carbon stored within dead forest components (pools) which includes leaf litter, branch litter, bark litter, stem litter, and dead roots. Harvested wood products in use refers to the amount of carbon stored in wood products (excluding wood products in landfill). Harvested wood products in use are included in carbon stock and flux results, but excluded from spatial outputs. Carbon stored within soil is not included within any of these datasets.</br> <br>This dataset supersedes <a href="https://portal.tern.org.au/metadata/TERN/57abd38f-eb38-4868-a2ea-072aec1b9176">NSW Forest Carbon Stock - Aboveground, Belowground and Dead Organic Matter Carbon Mass 1990-2020</a></br>

<br>The NSW Carbon Monitoring project is a collaboration between the Natural Resources Commission of NSW and Mullion Group to develop a spatial time-series dataset of forest carbon history for the state of NSW at ~25m resolution. The project used FLINTpro software to integrate historical environmental and land management data to model carbon stock and fluxes. Aboveground biomass refers to the amount of carbon stored within aboveground forest components (pools) which includes leaves, branches, bark and stems. Belowground biomass refers to the amount of carbon stored within belowground forest components (pools) which includes coarse and fine roots. Dead Organic Matter refers to the amount of carbon stored within dead forest components (pools) which includes leaf litter, branch litter, bark litter, stem litter, and dead roots. Carbon stored within soil and harvested wood products is not included within any of these datasets.</br> <br>This dataset has been superseeded by <a href="https://portal.tern.org.au/metadata/TERN/b9eab336-0ccc-43cd-9d44-e1e6207a2575">NSW Forest Carbon Stock - Aboveground, Belowground and Dead Organic Matter Carbon Mass 1990-2021</a></br>