The dataset consists of composited seasonal surface reflectance images (4 seasons per year) created from the full time series of Landsat TM/ETM+/OLI 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 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.

The seasonal fractional ground cover product is a spatially explicit raster product that shows the proportion of bare ground, green and non-green ground cover at medium resolution (30 m per-pixel) for each 3-month calendar season for Australia from 1989 - present. It is derived directly from the seasonal fractional cover product, also produced by Queensland's Remote Sensing Centre.A 3 band (byte) image is produced:band 1 - bare ground fraction (in percent),band 2 - green vegetation fraction (in percent),band 3 - non-green vegetation fraction (in percent).The no data value is 255. The seasonal fractional cover product predicts vegetation cover, but does not distinguish tree and mid-level woody foliage and branch cover from green and dry ground cover. As a result, in areas with even minimal tree cover (>15%), estimates of ground cover become uncertain. With the development of the fractional cover time-series, it has become possible to derive an estimate of ‘persistent green’ based on time-series analysis. The persistent green vegetation product provides an estimate of the vertically-projected green-vegetation fraction where vegetation is deemed to persist over time. These areas are nominally woody vegetation. This separation of the 'persistent green' from the fractional cover product, allows for the adjustment of the underlying spectral signature of the fractional cover image and the creation of a resulting 'true' ground cover estimate for each season. The estimates of cover are restricted to areas of <60% woody vegetation.

The Seasonal ground cover statistics products are long-term temporal statistic products derived from the seasonal ground cover product for each fraction across Queensland for the 30 year timeseries. There is one raster image for each season and each bare and green fraction for the full time series of imagery available. Statistics include: band 1 – 5th percentile minimum; band 2 – mean value for pixel over full time series for that season only (percentage + 100); band 3 – median value for pixel over full time series for that season only (percentage + 100); band 4 – 95th percentile maximum; band 5 – Standard deviation - the temporal standard deviation of the full time-series for that season only; band 6 – Count - the number of observations statistics for that pixel are based on for that season only. Min/max (5th and 95th percentile) products are also made for each fraction using all seasonal ground cover images available during the long term data period (currently 1990-2020).

The seasonal fractional cover product shows representative values for the proportion of bare, green and non-green cover across a season. It is a spatially explicit raster product that predicts vegetation cover at medium resolution (30 m per-pixel) for each 3-month calendar season across Australia from 1987 to the present. The green and non-green fractions may include a mix of woody and non-woody vegetation. A 3 band (byte) image is produced: band 1 – bare ground fraction (in percent), band 2 - green vegetation fraction (in percent), band 3 – non-green vegetation fraction (in percent). The no data value is 255.

Landsat satellite data have been produced, archived, and distributed by the U.S. Geological Survey (USGS) since 1972. Users rely on these data for historical study of land surface change but shoulder the burden of post-production processing to create applications-ready data sets.

Composite top of atmosphere reflectance image using Landsat 7 ETM+ and Landsat 8 OLI data acquired between November – April each year. Individual Landsat scenes have been masked for cloud and cloud shadow and then combined to produce a gap free image of Tasmania. This image has been produced to facilitate modelling of Foliage Projective Cover and woody change detection work within the Land Cover Program at DPIPWE. This mosaic currently utilises top of atmosphere reflectance imagery with a transformation applied to OLI data. A corresponding dataset, titled Tasmania Landsat Mosaic Date Codes, can be used to identify the source date for each pixel in the scene.

Two fractional cover decile products, green cover and total cover, are currently produced from the historical timeseries of seasonal fractional cover images across Australia, available for each 3-month calendar season. These products compare, at the per-pixel level, the level of cover for the specific season of interest against the long term cover for that same season. For each pixel, all cover values for the relevant seasons within a baseline period (1990 - 2020) are classified into deciles. The cover value for the pixel in the season of interest is then classified according to the decile in which it falls. This product is based upon the JRSRP Fractional Cover 3.0 algorithm.

The Seasonal Ground Cover Summary Statistics datasets provide long-term statistical summaries derived from the seasonal ground cover v3 data, calculated separately for each fraction. Two distinct product types are available, differentiated by their seasonal aggregation and statistical content. Seasonal Statistics per Fraction (Product Code: dpi)For each season and ground cover fraction, a separate raster image is generated for the full time series of available imagery. Each image includes the following statistical layers: include:band 1 – 5th percentile minimum;band 2 – mean value for pixel over full time series;band 3 – median value for pixel over full time series;band 4 – 95th percentile maximum;band 5 – Standard deviation - the temporal standard deviation of the full time-series;band 6 – Count - the number of observations statistics for that pixel are based on. All-Seasons Percentile Summary (Product Code: dph)This product summarises the 5th and 95th percentiles across all seasons for each ground cover fraction. It is delivered as a 2-band image, capturing the overall long-term minimum and maximum percentiles across the full time series (currently 1990-2020). Version 4 update: Dataset filenames have been revised to now include fraction and season tags, replacing multiple stage codes. Related products are grouped under a single code for improved clarity and usability. Additionally, band values are now expressed as percentages (0–100) to match the parent seasonal ground cover dataset, rather than using the previous percent + 100 scaling.

The Seasonal Fractional Cover Summary Statistics datasets provide long-term statistical summaries derived from the seasonal fractional cover v3 product, calculated separately for each fraction. For each cover fraction, a separate raster image is generated for the full time series of available imagery. Each image includes the following statistical layers: 5th percentile (minimum), Mean, Median, 95th percentile (maximum), Standard deviation and Observation count.