Brief description
The Advanced Very High Resolution Radiometer (AVHRR) and AVHRR/3 sensors have been carried on the US NOAA polar orbiting satellites since the 1980s. These data have been acquired via direct reception from the satellite by reception stations located in Australia. CSIRO has stitched together data received by different stations and agencies to compile a national high quality data set. The daylight satellite overpasses have been extracted from this data set for each day in the 30 year period commencing 1 April 1992. The data have been geolocated, and calibrated to produce imagery channels of solar reflectance and brightness temperature using community published methods. Satellite view and sun illumination angles for each pixel are provided, together with a preliminary cloud mask based on the CLAVR algorithm. The spatial resolution is ~1 km and temporal coverage is daily. The reprojected data set (in EPSG:4326, lon-lat) is available via the CSIRO EASI hub.Notes
Data ProcessingThe original data set is held in ASDA (Australian Satellite Data Archive) format by CSIRO. The processing codes have been developed in Python at CSIRO, building on CSIRO's CAPS (Common AVHRR Processing System) software and the Pygac packages. The bulk of the processing was undertaken at the NCI (National Computational Infrastructure) in Canberra.
Provides ~1 km resolution daily coverage of top of atmosphere reflectance and brightness temperature for the greater Australasian region. The data are suitable for applications requiring moderate resolution (~1 km) daily coverage, that are not sensitive to atmospheric correction.
Lineage
High resolution picture transmission (HRPT) data received in Australia by multiple agencies/institutions and stitched into continent-spanning super-overpasses by CSIRO. Processed to geophysical top-of-atmosphere parameters using geolocation code based on CSIRO's original CAPS software and calibration methods based on the original NOAA-recommended approach for brightness temperature and the Heidinger et al., 2010 method for reflectance (calibration as implemented in GitHub.
Notes
CreditWe at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
This work was funded by the Terrestrial Ecosystem Research Network (TERN), while compilation of the underlying raw data set has been supported by CSIRO and the Integrated Marine Observing System (IMOS). TERN and IMOS are Australian Government NCRIS enabled projects, and are supported by the use of TERN and IMOS infrastructure.
The brightness temperature data are usable for sea and land surface temperature monitoring, while the reflectance imagery enable vegetation and surface cover detection and quantification. Cloud properties can also be deduced from these data.
Data Quality Assessment Scope
local :
dataset
The underlying stitched High resolution picture transmission (HRPT) data set is the highest quality raw data available, with many artefacts arising from single-station reception having been eliminated (except at the start and end of the stitched super-passes). The geolocation accuracy is generally better than 1 pixel, while the calibration is at least nominal. The Heidinger et al. reflectance calibration is the most consistent up to data whole-of-time series set available. Missing lines are flagged in the data but extreme values within lines arising from interference in data transmission are not uniformly flagged.
Data Quality Assessment Result
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Quality Result
This data is usable with moderate caution, but is expected to demonstrate the scope and capability of these data pending future reprocessings with enhanced QC.
Created: 2023-06-28
Issued: 2024-10-01
Modified: 2024-10-01
Data time period: 1992-04-01
Spatial Coverage And Location
text: Greater Australasian Region.
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- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/db451646-cfd3-4457-95ca-5d452d2683a0
- global : db451646-cfd3-4457-95ca-5d452d2683a0