This dataset contains global dryland literature abstracts from over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging.

The physical drivers of ecosystem formation – macroclimate, lithology and landform – along with vegetation structural formations are key determinants of current ecosystem type. Each combination of these ecosystem drivers – each ‘ecological facet’ – provides a unique set of opportunities and challenges for life. <br> Management and conservation should seek to understand and take in to account these drivers of ecosystem formation. By understanding the unique combinations of these drivers management strategies can plan for their full range of variation, and conservation efforts can ensure that unique ecosystems are not lost. Unfortunately, there is currently no Australia-wide standardized map of ecological facets at management-appropriate scales. <br> By understanding the magnitude and distribution of unique combinations of these drivers, management strategies can plan for their full range of variation, and conservation efforts can ensure that unique ecosystems are not lost. Additionally, by improving our understanding of the past and present conditions that have given rise to current ecological facets this dataset could facilitate future predictive environmental modelling. Finally, this data could assisting biodiversity conservation, climate change impact studies and mitigation, ecosystem services assessment, and development planning <br> Further information about the dataset can be found at <a href="https://ternaus.atlassian.net/wiki/spaces/TERNSup/pages/2276130817/GEOSS+Ecosystem+Map">GEOSS Ecosystem Map,TERN Knowledge Base </a> .

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 is a collection of drone RGB and multispectral imagery from plots across Australia (AusPlots, SuperSites, Cal/Val sites to be established in the future). Standardised data collection and data processing protocols are used to collect drone imagery and to generate orthomosaics. The protocols developed in 2022 are based on the DJI Matrice 300 (M300) RTK drone platform. DJI Zenmuse P1 and MicaSense RedEdge-MX/Dual sensors are used with M300 to capture RGB and multispectral imagery simultaneously. The data is georeferenced using the DJI D-RTK2 base station and onboard GNSS RTK. In the processing workflow, the multispectral image positions (captured with navigation-grade accuracy) are interpolated using image timestamp and RGB image coordinates. Dense point clouds and the fine-resolution RGB smoothed surface were used to generate co-registered RGB (1 cm/pixel) and multispectral (5 cm/pixel) orthomosaics. Mission-specific metadata for each plot is provided in the imagery/metadata folder. The Drone Data Collection and RGB and Multispectral Imagery Processing protocols can be found at <em> https://www.tern.org.au/field-survey-apps-and-protocols/ </em>.

This dataset contains bird occurrence data collected at the Whroo Dry Eucalypt site in 2015.

The dataset consists of composited seasonal surface reflectance images (4 seasons per year) created from the full time series of Sentinel-2 imagery. The imagery has been composited over a season to produce imagery which is representative of that period, using techniques which will reduce contamination by cloud and other problems. This creates a regular time series of reflectance values which captures the variability at seasonal time scales. The benefits are a regular time series with minimal missing data or contamination from various sources of noise as well as data reduction. Each season has exactly one value (per band) for each pixel (or is null, i.e., missing), and the value for that season is assumed to be the representative of the whole season. The algorithm is based on the medoid (in reflectance space) over the time period (the medoid is a multi-dimensional analogue of the median), which is robust against extreme values. The seasonal surface reflectance is of the 6 TM-like bands (Blue, Green, Red, NIR, SWIR1, SWIR2), all at 10 m resolution. This dataset is intended to be a 10 m equivalent of the Landsat surface reflectance, using only Sentinel-2. The two 20m bands are resampled using cubic convolution. The pixel values are scaled reflectance, as 16-bit integers. To retrieve physical reflectance values, the pixel values should be multiplied by 0.0001.

This dataset contains bird occurrence data collected at the Robson Creek Rainforest site from 2010 - 2018.

This dataset contains bird occurrence data collected at the Daintree Rainforest, Cape Tribulation site in 2014.

This dataset is a collection of drone lidar data from plots across Australia (AusPlots, SuperSites, Cal/Val sites to be established in the future). The aim of these drone surveys is to capture vegetation structure. The standardised data collection and data processing protocols developed in 2022 are based on the DJI Matrice 300 (M300) RTK drone platform. Lidar sensor DJI Zenmuse L1 is used with DJI Matrice 300 (M300) RTK platform to capture RGB colourised 3D point clouds. The data is georeferenced using the onboard GNSS in M300 and the D-RTK 2 base station. DJI Terra software was used to generate 3D point clouds from the raw lidar data. The protocols include flight planning and data collection guidelines for a 100 x 100 m TERN plot, and the processing workflow used on DJI Terra. Mission-specific metadata for each plot is provided in the imagery/metadata folder (please refer to the imagery collection). The Drone Data Collection and Lidar Processing protocols can be found at <em> https://www.tern.org.au/field-survey-apps-and-protocols/ </em>.