500 meters - < 1 km
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The record contains information on the Digital Elevation Model of the Alice Mulga site. Information an Airborne full waveform lidar and hyperspectral data in the VNIR bands was collected using the research aircraft of Flinders University – Airborne Research Australia (ARA).
The MODIS Land Condition Index (LCI) is an index of total vegetation cover (green and non-photosynthetic vegetation ), and so is also an index of soil exposure. The LCI is a normalised difference index based on MODIS bands in the mid-infrared portion of the spectrum. The index is produced from 500-m MODIS nadir BRDF adjusted reflectance (NBAR) data. As with all products derived from passive remote sensing imagery, this product represents the world as seen from above. Therefore, the cover recorded by this product represent what would be observed from a birds-eye-view. Therefore, dense canopy may prevent observation of significant soil exposure.
The dataset contains information on the abundance of hollow bearing trees in the Karawatha Peri-Urban site recorded from between 2006 and 2009. There is information on the tree species name, diameter at breast height, tree alive status, and a number of attributes related to the hollows, such as its location, height, length, width and the type.
This dataset contains bird occurrence data collected at the Cumberland Plain site from 2015 - 2017.
The record contains images of elevation profile of the Tumbarumba Wet Eucalypt Site obtained from Airborne full waveform lidar and hyperspectral data in the VNIR bands using the a research aircraft of Flinders University – Airborne Research Australia (ARA).
The record contains information on rainfall data recorded between 1995-2011 from 17 rain gauges across the Calperum Mallee Site, Calperum Station, South Australia. Data on mean monthly and annual rainfall and standard deviation is provided for each site, along with annual rainfall totals.
RSMA measures change in the relative contributions of photosynthetic vegetation (PV, or GV green vegetation), non-photosynthetic vegetation (NPV) and soil reflectance compared to a baseline date. These spectral changes correspond to changes in fractional cover relative to the baseline date. Full details on the RSMA method are presented in Okin (2007). One of the key advantages of the RSMA, its insensitivity to changes in soil spectra, is a result of the fact that it does not require us to know the soil reflectance profile for a region. This strength is also the cause of a major weakness in RSMA. Since the measure is relative to a baseline date, and the absolute cover levels for every pixel are unknown at the baseline, the RSMA does not convey the absolute cover levels at any other point in time. However, if the absolute cover levels are known at any point in time, it is theoretically possible to convert the RSMA to absolute relative spectral mixture analysis (ARSMA).<br> As with all products derived from passive remote sensing imagery, this product represents the world as seen from above. Therefore, the cover recorded by this product represent what would be observed from a bird's-eye-view. Therefore, dense canopy may prevent observation of significant soil exposure.
This is the base geographical data for the Robson creek 25 ha plot. The data sets contain the 100 m grid, 20 m grid, 100 m points, 20 m points, major tracks and creeks. Data format is both Google earth KML and ESRI shapefile.
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 dataset contains bird occurrence data collected at the Daintree Rainforest, Cape Tribulation site in 2014.