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docs/data/product/dea-tasseled-cap-percentiles-landsat/_description.md

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 ## Background
 
-The Tasseled Cap (Kauth–Thomas) transformation takes satellite imagery and shows the degree of greenness, wetness and brightness across the observed area. These indexes help users understand the combinations of vegetation, water and bare areas respectively. As such the Tasseled Cap is a useful input into environmental analyses, especially where there are mixtures of all three features in the landscape, such as in wetlands.
+The Tasseled Cap transformation (Kauth and Thomas, 1976) is a method used to simplify satellite imagery by converting raw spectral data into three key indices:
+
+- Brightness – representing surface reflectance, often associated with bare soil or built environments.
+- Greenness – indicating the presence and health of vegetation.
+- Wetness – capturing moisture content in soil and vegetation.
+
+These indices help describe the composition of the landscape in terms of vegetation, water, and bare ground. The transformation is particularly useful in complex environments where these features coexist such as wetlands, floodplains, and coastal zones.
 
 ## What this product offers
 
-This product offers three percentiles per Tasseled Cap index per year. The percentiles are 10th, 50th, and 90th; the Tasseled Cap indexes are 'greenness', 'wetness', and 'brightness'; and the years are 1987 to the latest full calendar year.
+This product provides annual summaries of the Tasseled Cap indices using percentile statistics. For each calendar year from 1987 to the most recent full year, the following are available:
+
+- Three indices: Brightness, Greenness, and Wetness
+- Three percentiles per index:
+    - 10th percentile – representing lower-end conditions
+    - 50th percentile – the median or typical condition
+    - 90th percentile – representing upper-end conditions
 
-It is useful in broad environmental analyses where it is desirable to understand a mixed landscape including vegetation, water and bare areas, and as such is useful for wetlands analyses.
+Percentiles are calculated for every 30m x 30m pixel across Australia, using all available Landsat observations for the year. The product includes cloud and shadow masking and incorporates data from Landsat 5, 7, 8, and 9.
 
-It includes cloud and shadow buffering with a size of 6 pixels. This buffering is applied to Landsat 5, Landsat 7, Landsat 8, and Landsat 9 data from 2022 onwards.
 
 ## Data description
 
-Tasseled Cap percentiles are created by bringing together all individual satellite images for a year and generating the corresponding Tasseled Cap for each, before computing the 10th, 50th and 90th percentiles of their respective data ranges. The percentiles are chosen to represent minimum, middle and maximum (or general) conditions for each index per year, for every 30m x 30m pixel across Australia.
+To generate the percentile layers, all valid satellite observations for a given year are processed to compute the Tasseled Cap indices (brightness, greenness, wetness). For each pixel, the distribution of values across the year is used to calculate the 10th, 50th, and 90th percentiles. 
+
+These percentiles provide a robust summary of environmental variability, avoiding the sensitivity to outliers that can affect minimum, maximum, or mean values—especially in the presence of undetected cloud or shadow. This approach enables users to assess the range and typical conditions of the landscape over time, supporting both temporal analysis and spatial comparison.
 
-It includes cloud and shadow buffering with a size of 6 pixels and includes Landsat 5, Landsat 7, Landsat 8, and Landsat 9 (from 2022 onwards).
 
 ## Applications
 
-This product provides valuable discrimination for characterising:
+The Tasseled Cap Percentiles are useful for:
+
+- Wetland identification and monitoring
+- Characterisation of salt lakes and salt flats
+- Supporting classification of groundwater-dependant ecosystems
+- Mapping coastal and estuarine land covers and environments
 
-* Vegetated wetlands
-* Salt flats
-* Salt lakes
-* Coastal land cover classes
 
 ## Technical information
 
-The Tasseled Cap (Kauth–Thomas) transform translates the six spectral bands of Landsat into a three indexes describing greenness, wetness and brightness.  These indexes can be used to help understand complex ecosystems, such as wetlands or groundwater dependent ecosystems. The Tasseled Cap Percentiles capture how the greenness, wetness and brightness of the landscape behaves over time. 
+The Tasseled Cap transformation used to generate this product implements the coefficients described by Crist et al. (1985), adapted for Landsat surface reflectance data. The Tasseled Cap Transformation (TCT) is a linear transformation that projects multispectral data into a new coordinate system defined by three components: Brightness, Greenness, and Wetness. 
+
+In other words, the transformation reduces a larger number of spectral bands into three composite indices that are easier to interpret and apply in analyses. These indices are designed to capture the dominant modes avenues spectral variation in terrestrial landscapes:
+
+- Brightness is a weighted sum of all bands and reflects overall surface albedo.
+- Greenness contrasts the visible and near-infrared bands to highlight photosynthetically active vegetation.
+- Wetness contrasts shortwave infrared bands with visible and near-infrared bands to detect moisture in soil and vegetation.
+
+
+The transformation coefficients used in this product are based on those developed by Crist et al. (1985) for Landsat Thematic Mapper (TM) data and adapted for subsequent Landsat sensors (ETM+, OLI, and OLI-2) to ensure spectral consistency across the Landsat archive
+
+### Annual summarisation using percentiles
 
-The percentiles are well suited to characterising wetlands, salt flats/salt lakes and coastal ecosystems. However, care should be applied when analysing these indexes, as soil colour and fire scars can cause misleading results. In areas of high relief caused by cliffs or steep terrain, terrain shadows can cause erroneous results.
+For each calendar year, all valid observations are processed to calculate the Tasseled Cap indices. The 10th, 50th (median), and 90th percentiles are then calculated for each Tasseled Cap index for every 30m x 30m pixel across Australia. 
 
-The 10th, 50th and 90th percentiles of the Tasseled Cap are intended to capture the extreme (10th and 90th percentile) values and long-term average (50th percentile) values of each index.  Percentiles are used in preference to minimum, maximum and mean, as the min/max/mean statistical measures are more sensitive to undetected cloud/cloud shadow, and can be misleading for non-normally distributed data.
+These percentiles summarise the distribution of index values over the calendar year and characterise the lower-bound, central tendency and upper-bound of the measures of Brightness, Greenness and Wetness.
 
-The Tasseled Cap Percentiles are intended to complement the DEA Water Observations (Water Observations from Space) and Fractional Cover algorithms. DEA WO is designed to discriminate open water, but the Tasseled Cap wetness index identifies areas of water and areas where water and vegetation are mixed together; i.e. mangroves and palustrine wetlands. Similarly Fractional Cover describes proportions of green, brown and bare areas in the landscape, and hence the Fractional Cover percentiles can be used in complement to the Tasseled Cap percentiles.
+Percentiles are used instead of minimum, maximum, or mean values because they are less sensitive to outliers and better suited to non-normally distributed data. This makes them more reliable for detecting subtle or seasonal changes in complex environments.
 
-However if you are interested in terrestrial vegetation (where water in the pixel is not a factor), use the Fractional Cover product in preference to the Tasseled Cap, which provides a better biophysical characterisation of green vegetation fraction, dry vegetation fraction and bare soil vegetation fraction.
 
-We used the Tasseled Cap transforms described in Crist et al. (1985).
+### Interpretation and use
+
+- The 10th percentile typically reflects the driest, least vegetated, or least reflective conditions observed during the year.
+- The 50th percentile represents the median state of the landscape, offering a stable reference point for long-term monitoring.
+- The 90th percentile captures peak greenness, wetness, or brightness, useful for identifying maximum vegetation productivity or episodic inundation.
+
+These percentile layers are particularly valuable for land cover classification, wetland mapping, coastal zone monitoring, and ecosystem condition assessment, especially in environments where vegetation, water, and bare ground co-occur or fluctuate seasonally.
+
+The percentile-based approach used in this dataset aligns with best practices in time-series analysis of Earth observation data, as seen in related products such as [DEA Geometric Median and Median Absolute Deviation](https://knowledge.dea.ga.gov.au/data/product/dea-geometric-median-and-median-absolute-deviation-landsat/), [DEA Fractional Cover Percentiles](https://knowledge.dea.ga.gov.au/data/product/dea-fractional-cover-percentiles-landsat/), and [DEA Water Observations from Space (WOFS)](https://knowledge.dea.ga.gov.au/data/product/dea-water-observations-statistics-landsat/). Together, these products form a complementary suite of tools for understanding landscape dynamics across Australia.
 
 ## Lineage
 
-The lineage of this product is inherited from its sole input, the terrain corrected surface reflectance product [Surface Reflectance NBART Collection 3 (Landsat)](https://knowledge.dea.ga.gov.au/data/category/dea-surface-reflectance/).
+The Tasseled Cap Percentiles are derived from Landsat surface reflectance data from the [Surface Reflectance NBART Collection 3 (Landsat)](https://knowledge.dea.ga.gov.au/data/category/dea-surface-reflectance/). This input dataset includes terrain-corrected, analysis-ready data (ARD) from Landsat 5, Landsat 7, Landsat 8, and Landsat 9.
+
+To ensure data quality, all input imagery is masked for cloud and shadow contamination, with a 6-pixel buffer applied around detected cloud and shadow areas. This step reduces the influence of atmospheric interference and improves the reliability of the percentile calculations.
+
+For each calendar year, all valid observations are processed to compute the Tasseled Cap indices using the transformation coefficients described by Crist et al. (1985). These indices are calculated for every 30m x 30m pixel across Australia.
+
+The 10th, 50th, and 90th percentiles are then computed from the full time series of index values for each pixel. These percentiles are statistical summaries, not direct satellite observations. They represent synthetic values that describe the distribution of environmental conditions over the year.
+
+The resulting dataset is a synthetic summary of observed conditions, designed to support environmental monitoring, classification, and change detection across a wide range of Australian ecosystems.
+
 
 % ## Processing steps
 
 % ## Software
 
 ## References
 
+Kauth R. J. & G. S. Thomas (1976). The Tasselled Cap - A Graphic Description of the Spectral-Temporal Development of Agricultural Crops as Seen by LANDSAT. *Proceedings of the Symposium on Machine Processing of Remotely Sensed Data*
+
+
 Crist, E. P. (1985). A TM Tasseled Cap equivalent transformation for reflectance factor data. *Remote Sensing of Environment*, *17*(3), 301–306. [https://doi.org/10.1016/0034-4257(85)90102-6](https://doi.org/10.1016/0034-4257(85)90102-6 )
 

docs/data/product/dea-tasseled-cap-percentiles-landsat/_overview_1.md

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 ## About
 
-Tasseled Cap percentiles provide an annual summary of how the environment has varied through a year. The Tasseled Cap percentiles provide the upper, lower and middle conditions as described by the 90th, 10th and 50th percentiles respectively, of greenness, wetness and brightness across the landscape.
+The DEA Tasseled Cap Percentiles product provides an annual summary of environmental conditions across the Australian landscape using Tasseled Cap indices, a method that transforms raw reflectance data into three components:
+
+ - Brightness: Indicates the overall reflectivity of the land surface, often highlighting bare soil, urban areas or dry conditions.
+ - Greenness: Reflects the presence and vigor of photosynthetic vegetation.
+ - Wetness: Captures moisture content in soil and vegetation, helping to identify waterlogged or saturated areas.
+
+These percentile summaries are useful for identifying and monitoring environmental features such as wetlands, groundwater-dependent ecosystems, salt lakes, clay pans, and coastal landforms. They are designed to support environmental classification, change detection, and long-term landscape monitoring.
 
-These percentiles are intended for use as inputs into classification algorithms to identify such environmental features as wetlands and groundwater dependent ecosystems, and characterise salt flats, clay pans, salt lakes and coastal land forms.
 
 :::{admonition} This version includes breaking changes
 :class: note