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.

<p>This data set consists of .tif files of true colour orthomosaics for expansive areas of mangroves in Kakadu National Park in Australia's Northern Territory.</p> <p>The orthomosaics were generated from 68 stereo pairs of true colour aerial photographs acquired in 1991 in the lower reaches of the East Alligator, West Alligator, South Alligator and Wildman Rivers and Field Island, Kakadu National Park, Northern Australia (Mitchell et al., 2007). The photographs were taken at a flying height of 13,000 ft (3,960 m) using a Wild CR10, a standard photogrammetric camera with a frame size of 230 x 230 mm. The focal length was 152 mm. The photographs were scanned by Airesearch (Darwin) with a photogrammetric scanner to generate digital images with a pixel resolution between 12 and 15 mm. The orthomosaics have a spatial resolution of 1 m, cover an area of approximately 742 km² and a coastal distance of 86 km. </p> <p>These orthomosaics were co-registered using ground control points identified from 1:100,000 digital topographic maps with a Universal Transverse Mercator (UTM), and subsequently co-registered to LiDAR data acquired over the same region in 2011.</p>

The forest fuel survey dataset comprises site-level summary data from the well-designed fuel load surveys across 48 AusPlots Forests- 1-ha monitoring plots across Australia. Data presented here includes: [1] Site identifiers (ID and Site Name) and site location and site-specific notes from fuel survey campaign; [2] site survey dates (start date and end date); [3] Site climatic information (air temperature and relative humidity); [4] Average height of plants and the stem densities in those sites; [5] Fuel bed biomass measurements that include live or dead grass, shrub, vines cover; [6] Litter, Fine Woody and Coarse Woody Debris stocks and production; [7] Soil Nutrient concentration (Soil Carbon, Soil Hydrogen and Soil Nitrogen contents); [8] Duff depth and cover.

This dataset contains UAS RGB and multispectral raw images and orthomosaics of Calperum plot SASRIV0002. The drone platform used was DJI Matrice 300 (M300) RTK. Two sensors were flown simultaneously: Zenmuse P1 (35 mm) RGB mapping camera and MicaSense RedEdge-MX (5-band multispectral sensor). The RGB images were geo-referenced using the onboard GNSS in M300 and the D-RTK 2 base station. In the processing workflow, the multispectral image positions (captured with navigation-grade accuracy) were interpolated using image timestamp and RGB image coordinates. Dense point clouds and the fine-resolution RGB smoothed surface were used to generate both the RGB (1 cm/pixel) and multispectral (5 cm/pixel) orthomosaics. rio-cogeo plugin was used to generate Cloud Optimised GeoTIFFs. Details of the data collection settings and processing workflow are described in further sections. Note on multispectral data: in the raw data image file suffixes correspond to bands - 1: Blue, 2: Green, 3: Red, 4: NIR, 5: Red Edge. In the orthomosaic, the bands (1-5) are ordered by the Central Wavelength (Blue, Green, Red, RedEdge, NIR).

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.3) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /><br /> The Great Western Woodlands (GWW) comprise a 16 million hectare mosaic of temperate woodland, shrubland and mallee vegetation in south-west Western Australia. The region has remained relatively intact since European settlement, owing to the variable rainfall and lack of readily accessible groundwater. The woodland component is globally unique in that nowhere else do woodlands occur at as little as 220 mm mean annual rainfall. Further, other temperate woodlands around the world have typically become highly fragmented and degraded through agricultural use. 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 characterised by <em>Eucalyptus salmonophloia</em> (salmon gum), with <em>Eucalyptus salubris</em> and <em>Eucalyptus clelandii</em> dominating other research plots. The flux station is located in Salmon gum woodland. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/great-western-woodlands-supersite/ . <br /><br />

This dataset contains UAS RGB and multispectral raw images and orthomosaics of Calperum plots SASMDD0010 and SASMDD0018. The drone platform used was DJI Matrice 300 (M300) RTK. Two sensors were flown simultaneously: Zenmuse P1 (35 mm) RGB mapping camera and MicaSense RedEdge-MX Dual (10-band multispectral sensor). The RGB images were geo-referenced using the onboard GNSS in M300 and the D-RTK 2 base station. In the processing workflow, the multispectral image positions (captured with navigation-grade accuracy) were interpolated using image timestamp and RGB image coordinates. Dense point clouds and the fine-resolution RGB smoothed surface were used to generate both the RGB (1 cm/pixel) and multispectral (5 cm/pixel) orthomosaics. rio-cogeo plugin was used to generate Cloud Optimised GeoTIFFs. Details of the data collection settings and processing workflow are described in further sections. Note on multispectral data: in the raw data image file suffixes correspond to bands - 1: Blue, 2: Green, 3: Red, 4: NIR, 5: Red Edge, 6: Coastal Blue, 7: Green 531, 8: Red 650, 9: RedEdge 705, 10: RedEdge 740. In the orthomosaic, the bands (1-10) are ordered by the Central Wavelength (Coastal Blue, Blue, Green 531, Green, Red 650, Red, RedEdge 705, RedEdge, RedEdge 740, NIR).

This dataset contains UAS RGB and multispectral raw images and orthomosaics of Calperum plot SASMDD0012. The drone platform used was DJI Matrice 300 (M300) RTK. Two sensors were flown simultaneously: Zenmuse P1 (35 mm) RGB mapping camera and MicaSense RedEdge-MX Dual (10-band multispectral sensor). The RGB images were geo-referenced using the onboard GNSS in M300 and the D-RTK 2 base station. In the processing workflow, the multispectral image positions (captured with navigation-grade accuracy) were interpolated using image timestamp and RGB image coordinates. Dense point clouds and the fine-resolution RGB smoothed surface were used to generate both the RGB (1 cm/pixel) and multispectral (5 cm/pixel) orthomosaics. rio-cogeo plugin was used to generate Cloud Optimised GeoTIFFs. Details of the data collection settings and processing workflow are described in further sections. Note on multispectral data: in the raw data image file suffixes correspond to bands - 1: Blue, 2: Green, 3: Red, 4: NIR, 5: Red Edge, 6: Coastal Blue, 7: Green 531, 8: Red 650, 9: RedEdge 705, 10: RedEdge 740. In the orthomosaic, the bands (1-10) are ordered by the Central Wavelength (Coastal Blue, Blue, Green 531, Green, Red 650, Red, RedEdge 705, RedEdge, RedEdge 740, NIR).

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.3) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The Tumbarumba flux station is located in the Bago State Forest in south eastern New South Wales. It was established in 2000 and is managed by CSIRO Marine and Atmospheric Research. The forest is classified as wet sclerophyll, the dominant species is Eucalyptus delegatensis, and average tree height is 40m. Elevation of the site is 1200m and mean annual precipitation is 1000mm. The Bago and Maragle State Forests are adjacent to the south west slopes of southern New South Wales and the 48,400 ha of native forest have been managed for wood production for over 100 years. The instrument mast is 70m tall. Fluxes of heat, water vapour and carbon dioxide are measured using the open-path eddy flux technique. Supplementary measurements above the canopy include temperature, humidity, wind speed, wind direction, rainfall, incoming and reflected shortwave radiation and net radiation. Profiles of temperature, humidity and CO2 are measured at seven levels within the canopy. Soil moisture content is measured using Time Domain reflectometry, while soil heat fluxes and temperature are also measured. Hyper-spectral radiometric measurements are being used to determine canopy leaf-level properties. The Tumbarumba flux station is supported by TERN and the DCCEE through the ACCSP. <br />For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/tumbarumba-wet-eucalypt-supersite/. <br /><br />

This dataset contains UAS RGB and multispectral raw images and orthomosaics of the Calperum Mallee SuperSite SASMDD0001. The drone platform used was DJI Matrice 300 (M300) RTK. Two sensors were flown simultaneously: Zenmuse P1 (35 mm) RGB mapping camera and MicaSense RedEdge-MX Dual (10-band multispectral sensor). The RGB images were geo-referenced using the onboard GNSS in M300 and the D-RTK 2 base station. In the processing workflow, the multispectral image positions (captured with navigation-grade accuracy) were interpolated using image timestamp and RGB image coordinates. Dense point clouds and the fine-resolution RGB smoothed surface were used to generate both the RGB (1 cm/pixel) and multispectral (5 cm/pixel) orthomosaics. rio-cogeo plugin was used to generate Cloud Optimised GeoTIFFs. Details of the data collection settings and processing workflow are described in further sections. Note on multispectral data: in the raw data image file suffixes correspond to bands - 1: Blue, 2: Green, 3: Red, 4: NIR, 5: Red Edge, 6: Coastal Blue, 7: Green 531, 8: Red 650, 9: RedEdge 705, 10: RedEdge 740. In the orthomosaic, the bands (1-10) are ordered by the Central Wavelength (Coastal Blue, Blue, Green 531, Green, Red 650, Red, RedEdge 705, RedEdge, RedEdge 740, NIR).

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.3) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>.<br /> <br />The Alice Springs Mulga flux station is located on Pine Hill cattle station, near Alice Springs in the Northern Territory. The woodland is characterized by the Acacia aneura canopy, which is 6.5m tall on average. Elevation of the site is 606m above sea level, and the terrain is flat. Mean annual precipitation at the nearby (45km distant) Bureau of Meteorology station is 305.9mm but ranges between 100mm in 2009 to 750mm in 2010. Predominant wind directions are from the southeast and east.The extent of the woodland is 11km to the east of the flux station and 16km to the south. The soil is red sandy clay (50:50 sand:clay) overlying a 49m deep water table. Pine Hill Station is a functioning cattle station that has been in operation for longer than 50 years.The instrument mast is 13.7m tall. Fluxes of heat, water vapour and carbon are measured using the open-path eddy covariance technique at 11.6m. Supplementary measurements above the canopy include temperature and humidity (11.6m), windspeed and wind direction (9.25m), downwelling and upwelling shortwave and longwave radiation (12.2m). Precipitation is monitored in a canopy gap (2.5m). Supplementary measurements within and below the canopy include barometric pressure (1m), wind speed (2m, 4.25m and 6.5m), and temperature and humidity (2m, 4.25m and 6m). Below ground soil measurements are made in bare soil, mulga, and understory habitats and include ground heat flux (0.08m), soil temperature (0.02m – 0.06m) and soil moisture (0 – 0.1m, 0.1 – 0.3m, 0.6 – 0.8m and 1.0 – 1.2m). Ancillary measurements include soil water and carbon fluxes, leaf water potential, leaf gas exchange, stem basal area, stem growth, litter production, leaf area index, stem hydraulic conductance, and carbon and water stable isotope ratios. The site was established in September 2010 in conjunction with the Woodforde River NGCRT Superscience Site and is managed by the University of Technology Sydney.<br />For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/alice-mulga-supersite/ <br /><br />