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    <p>This data set consists of .tif files of true colour orthomosaics for expansive areas of mangroves in Kakadu National Park in Australia's Northern Territory.</p> <p>The orthomosaics were generated from 68 stereo pairs of true colour aerial photographs acquired in 1991 in the lower reaches of the East Alligator, West Alligator, South Alligator and Wildman Rivers and Field Island, Kakadu National Park, Northern Australia (Mitchell et al., 2007). The photographs were taken at a flying height of 13,000 ft (3,960 m) using a Wild CR10, a standard photogrammetric camera with a frame size of 230 x 230 mm. The focal length was 152 mm. The photographs were scanned by Airesearch (Darwin) with a photogrammetric scanner to generate digital images with a pixel resolution between 12 and 15 mm. The orthomosaics have a spatial resolution of 1 m, cover an area of approximately 742 km<sup>2</sup> and a coastal distance of 86 km. </p> <p>These orthomosaics were co-registered using ground control points identified from 1:100,000 digital topographic maps with a Universal Transverse Mercator (UTM), and subsequently co-registered to LiDAR data acquired over the same region in 2011.</p>

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    Evaporation, Transpiration, and Evapotranspiration Products for Australia based on the Maximum Entropy Production model (MEP). Introduction of a method into the MEP algorithm of estimating the required model parameters over the entire continent of Australia through the use of pedotransfer function, soil properties and remotely sensed soil moisture data. The algorithm calculates the evaporation and transpiration over Australia on daily timescales at the 0.05 degree (5 km) resolution for 2003 – 2013. The MEP evapotranspiration (ET) estimates were validated using observed ET data from 20 Eddy Covariance (EC) flux towers across 8 land cover types in Australia and compared the MEP ET at the EC flux towers with two other ET products over Australia; MOD16 and AWRA-L products. The MEP model outperformed the MOD16 and AWRA-L across the 20 EC flux sites, with average root mean square errors (RMSE), 8.21, 9.87 and 9.22 mm/8 days respectively. The average mean absolute error (MAE) for the MEP, MOD16 and AWRA-L were 6.21, 7.29 and 6.52 mm/8 days, the average correlations were 0.64, 0.57 and 0.61, respectively. The percentage bias of the MEP ET was within 20% of the observed ET at 12 of the 20 EC flux sites while the MOD16 and AWRA-L ET were within 20% of the observed ET at 4 and 10 sites respectively. The analysis showed that evaporation and transpiration contribute 38% and 62%, respectively, to the total ET across the study period which includes a significant part of the “millennium drought” period (2003 – 2009) in Australia. File naming conventions: E – Evaporation T – Transpiration ET – Evapotranspiration For the 8 day ET, Daily T and ET, the suffix nnn indicates day of year. , for example: 001 for January 1, 145 for May 25 (leap year) or 26, etc. While for the daily E, the suffix is in the format mmdd (month,day) for example 0101 for January 1, 0525 for May 25

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    This product provides locations of areas affected by fire including the approximate day of burning. Inputs are daily day time observations from MODIS sensors on Terra and Aqua. Observations are atmospherically corrected and the resulting time series is investigated for sudden changes in reflectance, persistent over multiple days. Variations in observation and illumination geometry are taken into account through application of a kernel driven Bidirectional Reflectance Distribution Function (BRDF) model.

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    Vegetation Fractional Cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. The sum of the three fractions is 100% (+/- 3%) and shown in Red/Green/Blue colors. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. This product is derived from the MODIS Nadir BRDF-Adjusted Reflectance product (MCD43A4) collection 6 and has 500 meters spatial resolution. A suite of derivative products are also produced including monthly fractional cover, total vegetation cover (PV+NPV), and anomaly of total cover against the time series. Monthly: The monthly product is aggregated from the 8-day composites using the medoid method. Anomaly: represents the difference between total vegetation cover (PV+NPV) in a given month and the mean total vegetation cover for that month in all years available, expressed in units of cover. For example, if the mean vegetation cover in January (2001-current year) was 40% and the vegetation cover for the pixel in January 2018 was 30%, the anomaly for the pixel in Jan 2018 would be -10%. Decile: represents the ranking (in ten value intervals) for the total vegetation cover in a given month in relation to the vegetation cover in that month for all years in the time-series. MODIS fractional cover has been validated for Australia.

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    These data describe the Australia-wide, monthly fraction of Photosynthetically Active Radiation absorbed by vegetation (fPAR) derived from Advance Very High Resolution Radiometer data spanning July 1981 to Oct 2011. FPAR is linearly related to fractional foliage cover. Here fPAR is split into that of persistent vegetation and of recurrent vegetation, which represent non-deciduous perennial vegetation and annual, ephemeral and deciduous vegetation, respectively. Data have been processed using the "invariant cover triangle" method to remove the majority of errors introduced by sensor calibration and change-over effects.

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    This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product at <a href="https://portal.tern.org.au/metadata/24072"</a>. The seasonal dynamic reference cover method images are created using a modified version of the dynamic reference cover method developed by <a href="https://doi.org/10.1016/j.rse.2012.02.021">Bastin et al (2012) </a>. This approach calculates a minimum ground cover image over all years to identify locations of most persistent ground cover in years with the lowest rainfall, then uses a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. The output is a difference image between the cover amount of a pixel's reference pixels and the actual cover at that pixel for the season being analysed. Negative values indicate pixels which have less cover than the reference pixels. <br> The main differences between this method and the original method are that this method uses seasonal fractional ground cover rather than the preceding ground cover index (GCI) and this method excludes cleared areas and certain landforms (undulating slopes), which are considered unsuitable for use as reference pixels.

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    This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product at https://portal.tern.org.au/metadata/24071. Long term temporal statistic products derived from the seasonal ground cover product for each fraction. Statistics include: 5th percentile minimum, mean, median, 95th percentile maximum, standard deviation and observation count. There is one raster image for each season and each bare and green fraction for the full time series of imagery available. Min/max (5th and 95th percentile) products are also made for each fraction using all seasonal ground cover images available.

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    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. 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.</br> 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.</br> 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.

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    The seasonal fractional cover product shows representative values for the proportion of bare, green and non-green cover, created from a time series of Sentinel-2 imagery. It is a spatially explicit raster product, which predicts vegetation cover at medium resolution (10 m per-pixel) for each 3-month calendar season. The green and non-green fractions may include a mix of woody and non-woody vegetation. This model was originally developed for Landsat imagery, but has been adapted for Sentinel-2 imagery to produce a 10 m resolution equivalent product. 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.

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    This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product at https://portal.tern.org.au/metadata/23880. 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, which predicts vegetation cover at medium resolution (30 m per-pixel) for each 3-month calendar season. The green and non-green fractions may include a mix of woody and non-woody vegetation.