Forestry fire management
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This dataset contains predictions of the aboveground biomass density (AGBD) for Australia for 2020. Data were generated by the Global Ecosystem Dynamics Investigation (GEDI) NASA mission, which used a full-waveform LIDAR attached to the International Space Station to provide the first global, high-resolution observations of forest vertical structure. Data include both Level 4A (~25 m footprints) and Gridded Level 4B (1 km x 1 km) Version 2. The Australian portion of the data was extracted from the original global datasets <a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2056">GEDI L4A Footprint Level Aboveground Biomass Density</a> and <a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2299">GEDI L4B Gridded Aboveground Biomass Density</a>.
This dataset comprises spatially and temporally dynamic estimates of the monthly latent heat flux (λE) and sensible heat flux (H) for all of Australia. The available energy (A, being net radiation [Rn] less the gound heat flux [G]) can be obtained by adding the λE and H datasets provided. Energy variables have been provided as hydrological equivalent units of depth, normalised to daily rates (mm/d). TERN OzFlux Surface Energy Balance (SEB) data were used to scale MODIS-based covariates of surface temperature less air temperature (Ts – Ta) and Rn using a Spatial and Temporal General Linear Model (ST-GLM) to third order. The ST-GLM SEB model was implemented across all of Australia on a 0.005° spatial grid (~ 500 m) on a monthly timestep from March 2000 through June 2023. Coefficients of the model were determined from the OzFlux network of eddy covariance flux tower data. Three flux tower sites were used to independently validate the accuracy of the model, being Calperum, SA, Howard Springs, NT, and Tumbarumba, NSW. The mean absolute difference (MAD) for λE, H and A was estimated as: 0.37, 0.39 and 0.34 mm/d, respectively. The relative errors determined by the MAD percentage (MADP) for λE, H, and A were estimated to be: 16%, 26%, and 9%, respectively. This dataset represents a new pathway for operational regional- to global-scale estimation of dynamic SEB variables.
This data contains vegetation cover, ground cover, tree density and stand basal area data across a multi-century time-since-fire sequence derived from growth ring-size relationships in fire-sensitive <em>Eucalyptus salubris</em> woodlands.
This data contains mortality and growth metrics such as diameter at breast height, crown height and diameter for vegetation after historic disturbances including wildfires and timber harvesting.
The dataset consists of spatial data showing locations of channel incision points (CIP) and sediment deposition in burned study sites in the Tumut and Tuross Catchment study regions.<br> This dataset includes aerial imagery captured 1-2 years after the 2019/20 bushfires of the study regions from which the locations of CIPs and sediment deposits were determined, and gridded landscape attribute information used to test the spatial association between landscape attributes and CIP density.<br> Refer to the following NRC report 'Post fire debris flow mapping - Coastal IFOA monitoring program - June 2023', which is included in the dataset, for background and further detail.
This data contains the visual assessment of fuel layers in fire-sensitive <em>Eucalyptus salubris</em> woodlands using Vesta methods across 24 sites in a multi-century (10 to 260+ years since fire) time-since-fire sequence derived from growth ring-size relationships.
<p>The dataset comprises well-designed survey data from the first fuel load survey across 192 transects within the 48 AusPlots Forests, 1-ha monitoring plots across Australia. Data includes:  Site identifiers (ID and Site Name) and site- or transect- specific notes from the fuel survey campaign;  Transect survey dates;  Transect photograph numbers and attributes (Bearing, Slope and Aspect);  Fuel measurements (Grass and Litter height; Duff depth; Fine Woody fuel counts and Coarse Woody fuel counts and diameter; Projective cover for biomass components (Grass, Litter, Herbs, Vines and Shrubs), and Mass of biomass components (Grass, Litter, Herbs and Vines));  Moisture content for biomass components (Grass, Litter, Herbs and Vines).</p> Descriptions of the data and coding protocols used in the database are explained in (a) the database itself; (b) the explanatory file attached to this dataset and (c) the Ausplots Forest Monitoring Network Manual. The protocols and coding used in this module are drawn directly from international forest fuel survey protocols and are consistent with other Australian forest fuel inventory methodologies.
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 data on the surface, near-surface, and elevated fuel loads for each of the Forest Ausplots. It includes iButton data on 1) temperature and humidity, 2) data on litterfall and 3) decomposition rates. We also provide additional information on soil nutrient data, species composition of the understorey and midstorey, and panorama photos from the plot centre. This dataset is the second version of the <i> AusPlots Forest Fuel Survey site-level data summary, 2014 - 2015. Version 1.0.0. Terrestrial Ecosystem Research Network.</i> (dataset). <em>https://doi.org/10.25901/efnh-sk06</em>