This dataset contains UAV RGB imagery collected as part of a field trial to test the Uncrewed Aerial System to be used for the TERN Drone project. The UAS platform is DJI Matrice 300 RTK with 2 sensors: Zenmuse P1 (35 mm) RGB mapping camera and Micasense RedEdge-MX Dual (10-band multispectral sensor). P1 imagery were georeferenced using the onboard GNSS in M300 and the D-RTK 2 Mobile Station. Camera positions were post-processed using <a href="https://www.ga.gov.au/scientific-topics/positioning-navigation/geodesy/auspos">AUSPOS</a>. Flight conducted between 10:26 am and 10:47 am AEDT at flying height 80 m, forward and side overlap set to 80%. <br><br> RGB orthomosaic (resolution: 1 cm. CRS: EPSG 7855 - GDA2020 MGA Zone 55) generated using Agisoft Metashape Professional, and a cloud optimised GeoTIFF was created using rio command line interface.

This dataset contains UAV RGB imagery collected as part of a field trial to test the Uncrewed Aerial System to be used for the TERN Drone project. The UAS platform is DJI Matrice 300 RTK with 2 sensors: Zenmuse P1 (35 mm) RGB mapping camera and Micasense RedEdge-MX (5-band multispectral sensor). P1 imagery were georeferenced using the onboard GNSS in M300 and the D-RTK 2 Mobile Station. Camera positions were post-processed using <a href="https://www.ga.gov.au/scientific-topics/positioning-navigation/geodesy/auspos">AUSPOS</a>. The flight took place between 14:00 and 14:08 at a height of 80m with a flying speed set to 5 m/s. Forward and side overlaps of photographs were set to 80%. <br><br> Agisoft Metashape was used to generate this RGB orthomosaic (resolution 1 cm). This cloud optimised GeoTIFF was created using rio command line interface. The coordinate reference system of the orthomosaic is EPSG 7855 - GDA2020 MGA Zone 55.

This dataset contains UAV multispectral imagery collected as part of a field trial to test the Unmanned Aerial System to be used for the TERN Drone project. The UAS platform is DJI Matrice 300 RTK with 2 sensors: Zenmuse P1 (35 mm) RGB mapping camera and Micasense RedEdge-MX (5-band multispectral sensor). P1 imagery were geo-referenced using the onboard GNSS in M300 and the D-RTK 2 Mobile Station. P1 Camera positions were post-processed using <a href="https://www.ga.gov.au/scientific-topics/positioning-navigation/geodesy/auspos">AUSPOS</a>. The flights took place between 14:58 and 03:08 at a height of 80m with a flying speed set to 5 m/s. Forward and side overlaps of photographs were set to 80%. <br><br> Micasense multispectral sensor positions were interpolated using P1, following which a standard workflow was followed in Agisoft Metashape to generate this orthomosaic (resolution 5 cm). Reflectance calibration was performed using captures of the MicaSense Calibration Panel taken before the flight. The orthomosaic raster has the relative reflectance (no unit) for the 5 bands (B, G, R, RedEdge, NIR). This cloud optimised (COG) GeoTIFF was created using rio command line interface. The coordinate reference system of the COG is EPSG 7855 - GDA2020 MGA Zone 55. <br><br> In the raw data RedEdge-MX image file suffixes correspond to bands like so - 1: Blue, 2: Green, 3: Red, 4: NIR, 5: Red Edge. However, in the processed Orthomoasic GeoTIFF, the bands are ordered in the wavelength order (Blue, Green, Red, Red Edge, NIR).

This dataset contains UAV multispectral imagery collected as part of a field trial to test the Uncrewed Aerial System to be used for the TERN Drone project. The UAS platform is DJI Matrice 300 RTK with 2 sensors: Zenmuse P1 (35 mm) RGB mapping camera and Micasense RedEdge-MX Dual (10-band multispectral sensor). P1 imagery were geo-referenced using the onboard GNSS in M300 and the D-RTK 2 Mobile Station. P1 Camera positions were post-processed using <a href="https://www.ga.gov.au/scientific-topics/positioning-navigation/geodesy/auspos">AUSPOS</a>. Flight conducted between 10:26 am and 10:47 am AEDT at flying height 80 m, forward and side overlaps for Zenmuse P1 set to 80%. MicaSense RedEdge-MX Dual triggered using timer mode (every second). <br><br> Micasense multispectral sensor positions were interpolated using P1, following which a standard workflow was followed in Agisoft Metashape to generate this orthomosaic (resolution 5 cm). Reflectance calibration was performed using captures of the MicaSense Calibration Panel taken before the flight. The orthomosaic raster has the relative reflectance (no unit) for the 10 bands (Coastal Blue, Blue, Green 531, Green, Red 650, Red, RedEdge 705, RedEdge, RedEdge 740, NIR). The cloud optimised (COG) GeoTIFF was created using rio command line interface. The coordinate reference system of the COG is EPSG 7855 - GDA2020 MGA Zone 55. <br><br> In the raw data RedEdge-MX image file suffixes correspond to bands like so - 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. However, in the processed Orthomoasic GeoTIFF, the bands 1-10 are ordered as per the Central Wavelength (Coastal Blue, Blue, Green 531, Green, Red 650, Red, RedEdge 705, RedEdge, RedEdge 740, NIR).

The Soil Moisture Integration and Prediction System (SMIPS) produces national extent daily estimates of volumetric soil moisture at a resolution of approximately 1km or 0.01 decimal degrees. SMIPS also generates an index of between 0-1 which approximates how full the 90cm metre soil moisture store is at a particular location and time. The SMIPS model itself consists of two linked soil moisture stores, a shallow quick responding 10cm upper store and a deeper, slower responding 80cm store. SMIPS is parameterised using physical properties from the <a href ='https://www.clw.csiro.au/aclep/soilandlandscapegrid/'>Soil and Landscape Grid of Australia </a>and takes a data model fusion approach for model forcing. Version 1.0 of the SMIPS model uses precipitation and potential evapotranspiration data from the Bureau of Meteorology’s <a href="http://www.bom.gov.au/water/landscape/assets/static/publications/AWRALv6_Model_Description_Report.pdf">AWRA Model</a>. In addition to version 1.0 of the model, an experimental version of the model is available for user testing. This version of the model uses precipitation data supplied by an experimental CSIRO daily rainfall surface generated using spatial data from the NASA Global Precipitation Mission as a base and enhanced using rainfall observations from the Bureau of Meteorology (BoM) rainfall gauge network, and various landscape covariates, processed using a machine learning approach. <br> To help increase model accuracy, the internal SMIPS model states are adjusted or ‘bumped’ by daily observational data from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) satellite mission.

This data contains vegetation structure, species composition, cover and species basal area data collected at seven sites within the Samford Ecological Research Facility (SERF) in 2010