DEA Mangroves (Landsat)

Geoscience Australia Mangrove Canopy Cover Collection 3

Version:: 4.0.0 (Latest)
Product types:: Derivative, Raster
Time span:: 1987 – 2023
Update frequency:: Yearly
Product ID:: ga_ls_mangrove_cover_cyear_3

Overview

About

Tracking changes in the canopy density of mangroves, Digital Earth Australia (DEA) Mangroves reveals how these extraordinary trees may be responding to sea level rise, severe tropical cyclones, drought, climatic cycles, changing temperatures and large storm events.

This version includes breaking changes

All tile grid references have been changed to refer to a new origin point. Learn more in the Version 4.0.0 changelog.

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For help accessing the data, see the Access tab.

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Key details

Parent product(s)	DEA Fractional Cover (Landsat) and DEA Tasseled Cap Percentiles (Landsat)
Collection	Geoscience Australia Landsat Collection 3
Persistent ID	145497
Licence	Creative Commons Attribution 4.0 International Licence

Cite this product

Data citation

Lymburner, L., Lucas, R., Scarth, P., Alam, I., Phillips, C., Ticehurst, C., Held, A., Bunting, P. 2021. Geoscience Australia Mangrove Canopy Cover Collection 3. Geoscience Australia, Canberra. https://pid.geoscience.gov.au/dataset/ga/145497

Paper citation

Lymburner, L., Bunting, P., Lucas, R., Scarth, P., Alam, I., Phillips, C., Ticehurst, C. and Held, A., 2020. Mapping the multi-decadal mangrove dynamics of the Australian coastline. Remote Sensing of Environment, 238, p.111185. https://doi.org/10.1016/j.rse.2019.05.004

Publications

Lymburner, L., Bunting, P., Lucas, R., Scarth, P., Alam, I., Phillips, C., Ticehurst, C., & Held, A. (2020). Mapping the multi-decadal mangrove dynamics of the Australian coastline. Remote Sensing of Environment, 238, 111185. https://doi.org/10.1016/j.rse.2019.05.004

Details

Background

Mangroves provide a diverse array of ecosystem services but these are impacted upon by both natural and anthropogenic drivers of change. In Australia, mangroves are protected by law and hence the natural drivers predominate.

It is important to understand the canopy density of mangroves in Australia so that we can measure how mangroves are responding to sea level rise, severe tropical cyclones and climatic cycles.

What this product offers

This product provides valuable information about the extent and canopy density of mangroves for each year from 1987 for the entire Australian coastline.

The canopy cover classes are:

20-50% (pale green)
50-80% (mid green)
80-100% (dark green)

The product consists of a sequence (one per year) of 30 m resolution maps that are generated by analysing the Landsat fractional cover developed by the Joint Remote Sensing Research Program and the Global Mangrove Watch layers developed by the Japanese Aerospace Exploration Agency.

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.

Applications

The sequence of mangrove maps makes it possible to see how the canopy cover of mangroves changes over time. The maps can be used to understand how mangroves respond to disturbance events such as severe tropical cyclones. The maps can also be used to improve our representation of the ecosystem services provided by mangroves, which include:

coastal protection
carbon storage
providing nursery grounds for commercially important fish and prawn species
providing habitat for migratory and endemic bird species

Technical information

To determine annual national level changes in mangroves, changes in their canopy cover type were quantified using dense time-series (nominally every 16 days cloud permitting) of 30 m spatial resolution Landsat sensor data available within Digital Earth Australia (DEA).

The potential area that mangroves occupied over this period was established as the union of mangrove maps generated for 1996, 2007-2010 and 2015/16 through the Japanese Aerospace Exploration Agency (JAXA) Global Mangrove Watch (GMW), and then refined using tasseled cap wetness dynamics and State and Territory mangrove mapping products. Within the potential mangrove area the 10th percentile of photosynthetic vegetation (ga_ls_fc_pc_cyear_3 (pv_pc_10)) is retrieved from the DEA Fractional Cover Percentiles product and used to estimate the percentage Planimetric Canopy Cover (PCC%). PCC% is a planar unit, directly related to forest cover, representing the horizontal distribution of forest cover when determined from above, such as by Light Detection And Ranging (LiDAR) or spectral satellite. The PCC% was estimated for each Landsat pixel using a relationship between pv_pc_10 and LiDAR-derived PCC% (< 1 m resolution and based on LiDAR acquisitions from all states supporting mangroves, excluding Victoria).

Processing steps

The product development methodology is outlined in the following steps:

Calculate the green fractional cover (pv_pc) from all available cloud-free Landsat pixels for each year of observation and compare these over an annual time series to identify areas where green cover persists throughout the year.
Establish a relationship between the 10th percentile of green fraction (pv_pc_10) observed within a year and Planimetric Canopy Cover percentage (PCC%) derived from < 1 m spatial resolution canopy masks derived from Light Detection And Ranging (LiDAR) with this representing a unit that relates directly to forest cover.
Constrain the PCC% estimates to areas known to contain mangroves, with reference to the Japanese Aerospace Exploration Agency’s (JAXA) Kyoto and Carbon (K&C) Initiative Global Mangrove Watch (GMW) thematic layers for 1996, 2007-10 and 2015/16 with additional areas identified using tasseled cap wetness and State and Territory mangrove mapping products.
Apply PCC% thresholds to map mangrove forest extent (based on a pre-determined 20 PCC% threshold) and differentiate structural categories, namely, woodland (20-50 %), open forest (50-80 %), and closed forest (> 80 %).
Quantify the change in the relative extent of mangrove forest and canopy cover types over the period 1987 to the latest full calendar year at a national scale and establish relevance at regional (e.g., State/Territory) and local levels.

References

Quality

Accuracy

The following limitations reported for this product are relative to the DEA Landsat Collection 2 version 2.0.2 of the mangroves dataset. The current DEA Mangroves version 4.0.0 product was produced with input datasets from DEA Landsat Collection 3. The similarities and differences between these two foundation dataset collections can be reviewed here. The primary impact on the Collection 3 mangroves product is the change in pixel resolution from 25m to 30m and use of the updated Collection 3 Fractional Cover data product. Due to the increase in pixel spatial resolution, the reported accuracies and errors will be similar to those reported previously but not identical.

During the upgrade process from Collection 2 to Collection 3, the mangrove thresholds for different classes were adjusted to more closely align with the Collection 2 version of the products. The current thresholds are set at (14, 40, 62).

The Global Mangrove Watch (GMW) polygon that was created using the methods described in Lucas et al. 2014 (https://doi.org/10.1071/MF13177) was used to provide a consistent reference frame. However this product has limitations that will impact the DEA Mangroves product. Areas that were mangrove prior to 2010 but were not identified as mangrove in 2010 may be omitted from this sequence of maps. Likewise some small areas of coastal non-mangrove woody vegetation (Casuarina and Melaleuca) are included in the GMW mangrove extent polygons. Whilst all reasonable efforts have been taken to minimise this, some errors of commission (non mangrove being identified as mangrove) will still occur.

For more information, see Lymburner et al. (2020).

Quality assurance

The quality of this product is related to the quality of the Fractional Cover product. During periods when only one satellite is operating (1987 to 2003, and 2011/12) the 10th percentile will sometimes contain cloud/cloud shadow artefacts due to the low number of observations per year in these years. This is typically problematic in cloud prone areas such as the Wet Tropics.

Access

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History

Old versions

View previous versions of this data product.

3.0.0: DEA Mangrove Canopy Cover (Landsat)

2.0.2: DEA Mangrove Canopy Cover (Landsat)

Changelog

Version 4.0.0

Breaking change: Shift in grid origin point — The south-west origin point of the DEA Summary Product Grid has been shifted 18 tiles west and 15 tiles south. Therefore, all tile grid references have been changed. For instance, a tile reference of x10y10 has changed to x28y25. The tile grid references of all derivative products generated from 2024 onwards will also be changed; however, Analysis Ready Data products will not be affected.
Enhanced cloud masking to reduce noise — An enhancement to cloud masking has reduced cloud and shadow noise. This enhancement (known as ‘cloud buffering’) involved cleaning cloud masks using a 6-pixel dilation on cloud and shadows. Note that some areas of very high surface reflectance (e.g. sand dunes and ocean areas) may exhibit worsened noise or data gaps, but these are infrequent occurrences with low impact.
Landsat 9 product — Landsat 9 is processed from 2022 onwards.

Credits

Acknowledgments

Landsat data is provided by the United States Geological Survey (USGS) through direct reception of the data at Geoscience Australias satellite reception facility or download.

The fractional cover algorithm was developed by the Joint Remote Sensing Research Program (JRSRP) and is described in Scarth et al. (2010). While originally calibrated in Queensland, a large collaborative effort between the Department of Agriculture, the Australian Bureau of Agricultural and Resource Economics (ABARES) and State and Territory governments to collect additional calibration data has enabled the calibration to extend to the entire Australian continent. DEA Fractional Cover was made possible by new scientific and technical capabilities, the collaborative framework established by the Terrestrial Ecosystem Research Network (TERN) through the National Collaborative Research Infrastructure Strategy (NCRIS), and collaborative effort between state and Commonwealth governments.

This product is the result of a collaboration between Geoscience Australia, the University of Aberyswyth, CSIRO, the Joint Remote Sensing Research Program and the Terrestrial Ecosystem Research Network.

License and copyright

Released under Creative Commons Attribution 4.0 International Licence.