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 bird occurrence data collected at the Wombat Stringybark Eucalypt site in 2015.

This dataset contains bird occurrence data collected at the Warra Tall Eucalypt site between 2008 - 2016

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

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).

<br>Tropical rainforests play a powerful role in mediating the global climate through the exchange and storage of carbon and water. Climate change is expected to generate higher atmospheric water demand in many areas, potentially increasing the rate of evaporation. In this study, we show that higher evaporative demand may in fact lead to lower fluxes of water from tropical rainforests and a reduced capacity of these forests to store carbon.</br> The record contains meteorological and forest inventory data in addition to data on soil water potential, sapflow measurements and tree hydraulic vulnerability measures from Robson Creek and Cow Bay study sites in Far North Queensland. The measurements occurred over a period of two years form 2019 to 2020.

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 bird occurrence data collected at the Cumberland Plain site from 2015 - 2017.

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>.