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"shortReport": "Click to highlight a hatched Waterbody polygon. View the DEA Waterbodies time series of the percentage of the waterbody surface area observed as wet and the estimated latest open water surface area.For more information and to download data, visit the DEA Waterbodies product description",
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"description": "Digital Earth Australia Waterbodies v3.0.0 provides up to date information about the extent and location of surface water, providing all Australians with a common understanding of this valuable and increasingly scarce resource. It supports users to understand and manage water across Australia. For example, users can gain insights into the severity and spatial distribution of drought or monitor critical lakes and dams, including hard-to-reach waterbodies in remote areas and on large properties. The product indicates changes in the wet surface area of waterbodies. This can be used to identify when waterbodies are increasing or decreasing in wet surface area.DEA Knowledge Hub product details: https://knowledge.dea.ga.gov.au/data/product/dea-waterbodies-landsat/?tab=overview.Scientific paper: Krause et al. 2021.DEA Website pages: https://www.dea.ga.gov.au/products/dea-waterbodies",
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},
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"content": "The accuracy of the stacked line plots is dependent on the accuracy of the underlying algorithms: Water Observations from Space (Mueller et al. 2016) and the Joint Remote Sensing Research Program's Fractional Cover algorithm (Scarth et al. 2010). The Tasseled Cap Wetness threshold used in the Wetlands Insight Tool has been compared with independent inundation data for one major wetland complex, however the Tasseled Cap Wetness index may under or overestimate the actual extent of inundation for individual wetlands. The use of a consistent threshold means that the 'precision' is high, insofar as you're measuring the same aspect of the wetland at each point in time, however the accuracy with which Tasseled Cap Wetness measures free water underneath/within wetland vegetation is not quantified.The interpretability of the results for each polygon is dependent on the accuracy of the linework that has been used to create that polygon. The line work used in the Wetlands Insight Tool (Ramsar Wetlands) comes from the 19/03/2020 revision of the Ramsar Wetlands of Australia Dataset, and has been processed by exploding large polygons into smaller polygons in QGIS. This means that sites where multiple boundaries exist have a separate plot for separate subsites, allowing users to understand the dynamics of the subsites separately. Users are able to manually combine Wetlands Insight Tool outputs accessed through DEA Maps as csvs to gain an understanding of combined sites. The 30 metre resolution of Landsat imposes an intrinsic limitation on the Wetlands Insight Tool. Wetland areas that are small, or long and narrow in nature are likely to be inaccurate (due to inclusion of neighbouring non-wetland pixels) or difficult to interpret (stack line plots for areas with a small number of pixels have sharp steps in them). The period of time between when Landsat 5 ceased operations (November 2011) and Landsat 8 data became routinely available (May 2013) is likely to be inaccurate. There will be some wetlands, close to the centre of Landsat paths where Landsat 7 continued to capture suitable (gap free) data, however it is safer, as a general rule, to consider this period as 'low data quality'. Other periods where less than four observations occur in a calendar year are also considered 'low data quality'. Regions of low data quality are hashed with a white rectangular overlay in the Wetlands Insight Tool plots."
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"content": "DEA Wetlands Insight Tool plots and data are provided under a CC BY Attribution 4.0 International License. Please comply with this licence when using the DEA Wetlands Insight Tool plots and data, and cite Dunn et al 2019 and Ai and Dunn 2021.Ramsar Wetland boundaries in the geojson vector file come from the Ramsar Wetlands of Australia Dataset under a Creative Commons Attribution 3.0 Australia Licence. We created individual wetland polygons from the multipart Ramsar polygons in the dataset, modifying the Ramsar Wetlands of Australia Dataset."
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{{year}} annual shoreline
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There are too few valid rates of change points in the {{radius_m}} metre radius around this location to calculate a reliable regional rate of change.
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"aerosol issues": "⚠️ DATA QUALITY WARNING:
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"unstable data": "⚠️ DATA QUALITY WARNING:
The accuracy of this shoreline is affected by unstable data at this location. This may be caused by errors in the tidal model used to reduce the influence of tide, the presence of gently sloping intertidal mudflats or sandbars that can lead to inaccurate shoreline mapping, or noisy satellite imagery caused by high levels of cloud.
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"insufficient observations": "⚠️ DATA QUALITY WARNING:
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"likely rocky coastline": "⚠️ DATA QUALITY WARNING:
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",
"extreme value (> 50 m)": "⚠️ DATA QUALITY WARNING:
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",
"high angular variability": "⚠️ DATA QUALITY WARNING:
This rate of coastal change is unlikely to be accurate due to high levels of angular variability from this point to each annual shoreline. This can occur in complex coastal environments like river mouths, sandbars and mudflats that do not show linear patterns of coastal change over time.
",
"baseline outlier": "⚠️ DATA QUALITY WARNING:
The baseline (i.e. most recent) annual shoreline is itself flagged as an outlier, potentially resulting in inaccurate rates of change at this location.
",
}
},
"legends": [
{
"url": "https://dea-public-data.s3.ap-southeast-2.amazonaws.com/derivative/dea_coastlines/supplementary/deacoastlines_legend.png"
}
]
},
{
"id": "uHwXvV",
"type": "group",
"name": "Supplementary layers",
"members": [
{
"type": "wms",
"name": "DEA Coastlines annual shorelines",
"id": "dea_coastlines_annual",
"shortReport": "Zoom in to view individual annual shorelines from 1988 to the presentFor more information and to download data, visit the DEA Coastlines product description",
"url": "https://geoserver.dea.ga.gov.au/geoserver/dea/wms",
"opacity": 1,
"layers": "dea:AnnualShorelines",
"featureInfoTemplate": {
"template": "
{{#year}}
{{year}} annual shoreline
This line represents the median or 'most representative' position of the shoreline across the entire of {{year}}, corrected to approximately mean sea level tide (0 metres Above Mean Sea Level).{{#terria.partialByName}}{{certainty}}{{/terria.partialByName}}Note: Annual shorelines do not reflect short-term shoreline variability, for example changes in shoreline position between low and high tide, seasonal effects, or short-lived influences of individual storms. Annual shorelines will therefore show lower variability than the full range of short-term shoreline variability at this location.{{/year}}
The accuracy of this shoreline may be affected by aerosol issues caused by the 1991 eruption of Mount Pinatubo.
",
"insufficient data": "⚠️ DATA QUALITY WARNING:
The accuracy of this shoreline may be affected by limited good quality satellite observations at this location. This can lead to noisier and less reliable shorelines.
",
"unstable data": "⚠️ DATA QUALITY WARNING:
The accuracy of this shoreline is affected by unstable data at this location. This may be caused by errors in the tidal model used to reduce the influence of tide, the presence of gently sloping intertidal mudflats or sandbars that can lead to inaccurate shoreline mapping, or noisy satellite imagery caused by high levels of cloud.
",
}
},
},
{
"type": "wms",
"name": "DEA Coastlines rates of change statistics",
"id": "dea_coastlines_statistics",
"shortReport": "Zoom in to view detailed rates of coastal change along the Australian coastlineFor more information and to download data, visit the DEA Coastlines product description",
"url": "https://geoserver.dea.ga.gov.au/geoserver/dea/wms",
"opacity": 1,
"chartDisclaimer": "The graph below shows the distance (in metres) from each historical shoreline to the baseline (i.e. most recent) annual shoreline. Negative distances indicate a historical shoreline was located inland of the most recent shoreline.",
"layers": "dea:RateOfChangeStatistics",
"featureInfoTemplate": {
"template": "
{{^year}}
{{#wms_sig}}This {{#max_year}}coastline{{/max_year}}{{#n}}region{{/n}} has {{#wms_grew}}retreated ↓{{/wms_grew}}{{#wms_retr}}grown ↑{{/wms_retr}} by {{#terria.formatNumber}}{maximumFractionDigits:1}{{rate_time}}{{/terria.formatNumber}} metres (±{{#terria.formatNumber}}{maximumFractionDigits:1}{{wms_conf}}{{/terria.formatNumber}}) per yearon average since 1988
{{/wms_sig}}{{^wms_sig}}This coastline has remained net stable since 1988 (no significant trend of retreat or growth)Net stable includes coastlines or regions that have remained relatively unchanged since 1988, or where shorelines have fluctuated between growth and retreat over time.{{/wms_sig}}{{#max_year}}The shoreline at this location was most seaward in {{max_year}}, and most landward in {{min_year}}{{#outl_time}} (excluding outliers; see below){{/outl_time}}. Since 1988, the median annual position of the shoreline has moved over a total distance of ~{{#terria.formatNumber}}{maximumFractionDigits:0}{{sce}}{{/terria.formatNumber}} metres.{{/max_year}}Year,Distance (m)\n1988,{{dist_1988}}\n1989,{{dist_1989}}\n1990,{{dist_1990}}\n1991,{{dist_1991}}\n1992,{{dist_1992}}\n1993,{{dist_1993}}\n1994,{{dist_1994}}\n1995,{{dist_1995}}\n1996,{{dist_1996}}\n1997,{{dist_1997}}\n1998,{{dist_1998}}\n1999,{{dist_1999}}\n2000,{{dist_2000}}\n2001,{{dist_2001}}\n2002,{{dist_2002}}\n2003,{{dist_2003}}\n2004,{{dist_2004}}\n2005,{{dist_2005}}\n2006,{{dist_2006}}\n2007,{{dist_2007}}\n2008,{{dist_2008}}\n2009,{{dist_2009}}\n2010,{{dist_2010}}\n2011,{{dist_2011}}\n2012,{{dist_2012}}\n2013,{{dist_2013}}\n2014,{{dist_2014}}\n2015,{{dist_2015}}\n2016,{{dist_2016}}\n2017,{{dist_2017}}\n2018,{{dist_2018}}\n2019,{{dist_2019}}\n2020,{{dist_2020}}\n2021,{{dist_2021}}\n2022,{{dist_2022}}\n2023,{{dist_2023}}{{#outl_time}}The following years were identified as missing data or potential outliers, and should be interpreted with caution:
{{outl_time}}
{{/outl_time}}{{#terria.partialByName}}{{certainty}}{{/terria.partialByName}}{{^n}}Note: Annual shoreline positions represent the median or 'most representative' position of the shoreline for each year, corrected to approximately mean sea level tide. They do not reflect short-term shoreline variability, for example changes in shoreline position between low and high tide, seasonal effects, or short-lived influences of individual storms.{{/n}}{{#n}}Note: These regional coastal change values are based on the median of all annual shoreline positions within a {{radius_m}} metre radius around this point. Zoom into the map to view more detailed rates of change and individual annual shorelines:{{/n}}{{/year}}
There are insufficient years of good quality annual shoreline data (< 25 years) to calculate reliable rates of coastal change at this location.
",
"likely rocky coastline": "⚠️ DATA QUALITY WARNING:
This coastline has been identified as a probable rocky or cliff shoreline. Rates of coastal change at this location may be less accurate due to noisy shoreline mapping caused by dark terrain shadows.
",
"extreme value (> 50 m)": "⚠️ DATA QUALITY WARNING:
This location has been identified as having an extreme rate of coastal change (> 50 metres per year) and should be interpreted with caution.
",
"high angular variability": "⚠️ DATA QUALITY WARNING:
This rate of coastal change is unlikely to be accurate due to high levels of angular variability from this point to each annual shoreline. This can occur in complex coastal environments like river mouths, sandbars and mudflats that do not show linear patterns of coastal change over time.
",
"baseline outlier": "⚠️ DATA QUALITY WARNING:
The baseline (i.e. most recent) annual shoreline is itself flagged as an outlier, potentially resulting in inaccurate rates of change at this location.
{{data.0.bands.exposure}}% of the {{#terria.formatDateTime}}{format: \"yyyy\"}{{data.0.time}}{{/terria.formatDateTime}} analysis period
Mapped intertidal extents can be affected by biases in the tidal conditions observed by satellites. At this location, satellites observed the coastline at tide heights ranging from {{#terria.formatNumber}}{maximumFractionDigits:2}{{data.0.bands.ta_lot}}{{/terria.formatNumber}} to +{{#terria.formatNumber}}{maximumFractionDigits:2}{{data.0.bands.ta_hot}}{{/terria.formatNumber}} metres above MSL, compared to the full astronomical tide range of {{#terria.formatNumber}}{maximumFractionDigits:2}{{data.0.bands.ta_lat}}{{/terria.formatNumber}} to +{{#terria.formatNumber}}{maximumFractionDigits:2}{{data.0.bands.ta_hat}}{{/terria.formatNumber}} metres above MSL.
This resulted in satellite data observing ~{{data.0.bands.ta_spread}}% of the astronomical tide range, and failing to observe the lowest ~{{data.0.bands.ta_offset_low}}% and highest ~{{data.0.bands.ta_offset_high}}% of tides.
Digital Earth Australia Intertidal 32 km tile grid
This grid file was used to generate DEA Intertidal outputs. It contains unique 'region_code' IDs for each grid cell and access links to the data on Amazon S3.
",
},
"id": "67ttyU"
},
]
},
{
"id": "yC2aqy",
"type": "group",
"name": "DEA High and Low Tide Imagery (HLTC)",
"members": [
{
"type": "wms",
"name": "DEA Low Tide Imagery (Landsat)",
"url": "https://ows.dea.ga.gov.au/",
"opacity": 1,
"layers": "low_tide_composite",
"linkedWcsUrl": "https://ows.dea.ga.gov.au/",
"linkedWcsCoverage": "low_tide_composite",
"leafletUpdateInterval": 750,
"tileErrorHandlingOptions": {
"ignoreUnknownTileErrors": true
},
"id": "4XvQxE",
"shareKeys": [
"Root Group/Coastal/Low tide satellite images/Low tide Landsat satellite images"
]
},
{
"type": "wms",
"name": "DEA High Tide Imagery (Landsat)",
"url": "https://ows.dea.ga.gov.au/",
"opacity": 1,
"layers": "high_tide_composite",
"linkedWcsUrl": "https://ows.dea.ga.gov.au/",
"linkedWcsCoverage": "high_tide_composite",
"leafletUpdateInterval": 750,
"tileErrorHandlingOptions": {
"ignoreUnknownTileErrors": true
},
"id": "YLrxLi",
"shareKeys": [
"Root Group/Coastal/High tide satellite images/High tide Landsat satellite images"
]
},
{
"type": "geojson",
"name": "DEA Low Tide polygons for data access",
"info": [
{
"name": "Abstract",
"content": "High Tide and Low Tide Composites 2.0.0 The High and Low Tide Composites product is composed of two surface reflectance composite mosaics of Landsat TM and ETM+ (Landsat 5 and Landsat 7 respectively) and OLI (Landsat 8) surface reflectance data (Li et al., 2012). These products have been produced using Digital Earth Australia (DEA). The two mosaics allow cloud free and noise reduced visualisation of the shallow water and inter-tidal coastal regions of Australia, as observed at high and low tide respectively (Sagar et al. 2018). The composites are generated utilising the geomedian approach of Roberts et al (2017) to ensure a valid surface reflectance spectra suitable for uses such as habitat mapping. The time range used for composite generation in each polygon of the mosaic is tailored to ensure dynamic coastal features are captured whilst still allowing a clean and cloud free composite to be generated. The concepts of the Observed Tidal Range (OTR), and Highest and Lowest Observed Tide (HOT, LOT) are discussed and described fully in Sagar et al. (2017) and the product description for the ITEM v 1.0 product (Geoscience Australia, 2016)."
},
{
"name": "Overview",
"content": "Inter-tidal zones are difficult regions to characterise due to the dynamic nature of the tide. They are highly changeable environments, subject to forcings from the land, sea and atmosphere and yet they form critical habitats for a wide range of organisms from birds to fish and sea grass. By harnessing the long archive of satellite imagery over Australia's coastal zones in the DEA and pairing the images with regional tidal modelling, the archive can be sorted by tide height rather than date, enabling the inter-tidal zone to be viewed at any stage of the tide regime. The High Low Tide Composites (HLTC_25) product is composed of two mosaics, distinguished by tide height, representing a composite image of the synthetic geomedian surface reflectance from Landsats 5 TM, Landsat 7 ETM+ and Landsat 8 OLI NBAR data (Li et al., 2012; Roberts et al., 2017). Oregon State Tidal Prediction (OTPS) software (Egbert and Erofeeva, 2002, 2010) was used to generate tide heights, relative to mean sea level, for the Australian continental coastline, split into 306 distinct tidal regions. These time and date stamped tidal values were then attributed to all coastal tile observations for their time of acquisition, creating a range of observed tide heights for the Australian coastline. The two mosaics in HLTC_25 are composited from the highest and lowest 20 % of observed tide in the ensemble and are termed HOT and LOT respectively. A geomedian composite for each Landsat band is calculated from the tiles in each ensemble subset to produce the respective HOT and LOT composites. Note that Landsat 7 ETM+ observations are excluded after May 2003 due to a large number of data artefacts. The time range used for composite generation in each of the 306 polygons of the mosaics are tailored to ensure dynamic coastal features are captured whilst still allowing a clean and cloud free composite to be generated. The maximum epoch for which the products are calculated is between 1995-2017, although this varies due to data resolution and observation quality. The product also includes a count of clear observations per pixel for both mosaics and attribute summaries per polygon that include the date range, the highest and lowest modeled astronomical tide as well as the highest and lowest observed tide for that time range, the total observation count and the maximum count of observations for any one pixel in the polygon, the polygon ID number (from 1 to 306), the polygon centroid in longitude and latitude and the count of tide stages attributed to every observation used in that polygon of the mosaic. For the count of tidal stage observations, e = ebbing tide, f = flowing tide, ph = peak high tide and pl = peak low tide. The tide stages were calculated by comparison to the modeled tide data for 15 minutes either side of the observation to determine the ebb, flow or peak movement of the tide. Observations are filtered to remove poor quality observations including cloud, cloud shadow and band saturation (of any band)."
},
{
"name": "Accuracy and limitations",
"content": "The accuracy of the tide height data is limited by the accuracy of the OTPS model. Tidal modelling on self-similar coastal polygons was performed to minimise regional uncertainty. Accuracies and limitations related to geomedian compositing of observations are discussed in Roberts et al (2017). Users should beware of seasonal and diurnal effects in the imagery, especially in the north east of Australia where the footprint of the highest and lowest astronomical tides are large. Consequently, where image acquisition misses the highest astronomical tide, for example, pooling effects of water are still visible in the landscape in lowest observed tidal composite imagery. This product has been rendered in both true colour and false colour. Validation and interpretation of surface features has not been attempted here. Interpretation of surface features is at the users own discretion."
},
{
"name": "File naming",
"content": "`_______` COUNT OR COMPOSITE refers to whether pixels contain composite observation values or the count of observations at that pixel location HIGH OR LOW refers to whether the content relates to High Tide values or Low Tide values TIDAL POLYGON NUMBER relates to the id of the tidal polygon referenced by the file LONGITUDE is the longitude of the centroid of the tidal polygon LATITUDE is the latitude of the centroid of the tidal polygon START DATE is the beginning of the date range covered by the file END DATE is the end of the date range covered by the file PERCENTILE TIDE RANGE indicates the percentile value used when calculating the composites The index of downloadable GeoTIFFs can be found here: http://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/fk4/datacube/002/HLTC/HLTC_2_0/geotiff/catalog.xml"
},
{
"name": "References",
"content": "Egbert, G.D., Erofeeva, S.Y., 2002. Efficient Inverse Modeling of Barotropic Ocean Tides. J. Atmospheric Ocean. Technol. 19, 183-204. doi:10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2 Egbert, G.D., Erofeeva, S.Y., 2010. The OSU TOPEX/Poseiden Global Inverse Solution TPXO [WWW Document]. TPXO8-Atlas Version 10. URL http://volkov.oce.orst.edu/tides/global.html (accessed 2.15.16). Geoscience Australia, 2016. Intertidal Extents Model (25m) v 1.0 Product Description. doi:10.4225/25/575F683E2A3AF Li, F., Jupp, D.L.B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., Held, A., 2012. A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sens. Environ. 124, 756-770. doi:10.1016/j.rse.2012.06.018 Roberts, D., Mueller, N., McIntyre, A., 2017. High-dimensional pixel composites from Earth observation time series. IEEE Trans. Geosci. Remote Sens. In Press. Sagar, S., Roberts, D., Bala, B., Lymburner, L., 2017. Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations. Remote Sens. Environ. 195, 153-169. doi:10.1016/j.rse.2017.04.009 Sagar, S., Phillips, C., Bala, B., Roberts, D., Lymburner, L., 2018. Generating Continental Scale Pixel-Based Surface Reflectance Composites in Coastal Regions with the Use of a Multi-Resolution Tidal Model. Remote Sensing 10, 480."
}
],
"url": "https://data.dea.ga.gov.au/LHTC_Tides/low_composite_20_maps.geojson",
"featureInfoTemplate": {
"template": "The tidal range at this location is {{modelLow}} to {{modelHigh}} meters relative to mean sea level (MSL). The low tide composite at this location was generated from imagery acquired in the lowest 20% of the observed tidal range which is between {{LIT}} and {{HIT}} meters relative to MSL, during the period of time of {{date_range}}. Observations used to generate the composite (black dots), in relation to the full modelled tidal range (blue) and complete archive (white dots) at this location Download the GeoTIFF for this polygon here: COMPOSITE_LOW_{{ID}}_{{lon}}_{{lat}}_{{start_date}}_{{end_date}}_PER_20.tif"
},
"id": "5SAK7J",
"shareKeys": [
"Root Group/Coastal/Low tide satellite images/Low Tide Polygons for data access"
]
},
{
"type": "geojson",
"name": "DEA High Tide polygons for data access",
"info": [
{
"name": "Abstract",
"content": "High Tide and Low Tide Composites 2.0.0 The High and Low Tide Composites product is composed of two surface reflectance composite mosaics of Landsat TM and ETM+ (Landsat 5 and Landsat 7 respectively) and OLI (Landsat 8) surface reflectance data (Li et al., 2012). These products have been produced using Digital Earth Australia (DEA). The two mosaics allow cloud free and noise reduced visualisation of the shallow water and inter-tidal coastal regions of Australia, as observed at high and low tide respectively (Sagar et al. 2018). The composites are generated utilising the geomedian approach of Roberts et al (2017) to ensure a valid surface reflectance spectra suitable for uses such as habitat mapping. The time range used for composite generation in each polygon of the mosaic is tailored to ensure dynamic coastal features are captured whilst still allowing a clean and cloud free composite to be generated. The concepts of the Observed Tidal Range (OTR), and Highest and Lowest Observed Tide (HOT, LOT) are discussed and described fully in Sagar et al. (2017) and the product description for the ITEM v 1.0 product (Geoscience Australia, 2016)."
},
{
"name": "Overview",
"content": "Inter-tidal zones are difficult regions to characterise due to the dynamic nature of the tide. They are highly changeable environments, subject to forcings from the land, sea and atmosphere and yet they form critical habitats for a wide range of organisms from birds to fish and sea grass. By harnessing the long archive of satellite imagery over Australia's coastal zones in the DEA and pairing the images with regional tidal modelling, the archive can be sorted by tide height rather than date, enabling the inter-tidal zone to be viewed at any stage of the tide regime. The High Low Tide Composites (HLTC_25) product is composed of two mosaics, distinguished by tide height, representing a composite image of the synthetic geomedian surface reflectance from Landsats 5 TM, Landsat 7 ETM+ and Landsat 8 OLI NBAR data (Li et al., 2012; Roberts et al., 2017). Oregon State Tidal Prediction (OTPS) software (Egbert and Erofeeva, 2002, 2010) was used to generate tide heights, relative to mean sea level, for the Australian continental coastline, split into 306 distinct tidal regions. These time and date stamped tidal values were then attributed to all coastal tile observations for their time of acquisition, creating a range of observed tide heights for the Australian coastline. The two mosaics in HLTC_25 are composited from the highest and lowest 20 % of observed tide in the ensemble and are termed HOT and LOT respectively. A geomedian composite for each Landsat band is calculated from the tiles in each ensemble subset to produce the respective HOT and LOT composites. Note that Landsat 7 ETM+ observations are excluded after May 2003 due to a large number of data artefacts. The time range used for composite generation in each of the 306 polygons of the mosaics are tailored to ensure dynamic coastal features are captured whilst still allowing a clean and cloud free composite to be generated. The maximum epoch for which the products are calculated is between 1995-2017, although this varies due to data resolution and observation quality. The product also includes a count of clear observations per pixel for both mosaics and attribute summaries per polygon that include the date range, the highest and lowest modeled astronomical tide as well as the highest and lowest observed tide for that time range, the total observation count and the maximum count of observations for any one pixel in the polygon, the polygon ID number (from 1 to 306), the polygon centroid in longitude and latitude and the count of tide stages attributed to every observation used in that polygon of the mosaic. For the count of tidal stage observations, e = ebbing tide, f = flowing tide, ph = peak high tide and pl = peak low tide. The tide stages were calculated by comparison to the modeled tide data for 15 minutes either side of the observation to determine the ebb, flow or peak movement of the tide. Observations are filtered to remove poor quality observations including cloud, cloud shadow and band saturation (of any band)."
},
{
"name": "Accuracy and limitations",
"content": "The accuracy of the tide height data is limited by the accuracy of the OTPS model. Tidal modelling on self-similar coastal polygons was performed to minimise regional uncertainty. Accuracies and limitations related to geomedian compositing of observations are discussed in Roberts et al (2017). Users should beware of seasonal and diurnal effects in the imagery, especially in the north east of Australia where the footprint of the highest and lowest astronomical tides are large. Consequently, where image acquisition misses the highest astronomical tide, for example, pooling effects of water are still visible in the landscape in lowest observed tidal composite imagery. This product has been rendered in both true colour and false colour. Validation and interpretation of surface features has not been attempted here. Interpretation of surface features is at the users own discretion."
},
{
"name": "File naming",
"content": "`_______` COUNT OR COMPOSITE refers to whether pixels contain composite observation values or the count of observations at that pixel location HIGH OR LOW refers to whether the content relates to High Tide values or Low Tide values TIDAL POLYGON NUMBER relates to the id of the tidal polygon referenced by the file LONGITUDE is the longitude of the centroid of the tidal polygon LATITUDE is the latitude of the centroid of the tidal polygon START DATE is the beginning of the date range covered by the file END DATE is the end of the date range covered by the file PERCENTILE TIDE RANGE indicates the percentile value used when calculating the composites The index of downloadable GeoTIFFs can be found here: http://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/fk4/datacube/002/HLTC/HLTC_2_0/geotiff/catalog.xml"
},
{
"name": "References",
"content": "Egbert, G.D., Erofeeva, S.Y., 2002. Efficient Inverse Modeling of Barotropic Ocean Tides. J. Atmospheric Ocean. Technol. 19, 183-204. doi:10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2 Egbert, G.D., Erofeeva, S.Y., 2010. The OSU TOPEX/Poseiden Global Inverse Solution TPXO [WWW Document]. TPXO8-Atlas Version 10. URL http://volkov.oce.orst.edu/tides/global.html (accessed 2.15.16). Geoscience Australia, 2016. Intertidal Extents Model (25m) v 1.0 Product Description. doi:10.4225/25/575F683E2A3AF Li, F., Jupp, D.L.B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., Held, A., 2012. A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sens. Environ. 124, 756-770. doi:10.1016/j.rse.2012.06.018 Roberts, D., Mueller, N., McIntyre, A., 2017. High-dimensional pixel composites from Earth observation time series. IEEE Trans. Geosci. Remote Sens. In Press. Sagar, S., Roberts, D., Bala, B., Lymburner, L., 2017. Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations. Remote Sens. Environ. 195, 153-169. doi:10.1016/j.rse.2017.04.009 Sagar, S., Phillips, C., Bala, B., Roberts, D., Lymburner, L., 2018. Generating Continental Scale Pixel-Based Surface Reflectance Composites in Coastal Regions with the Use of a Multi-Resolution Tidal Model. Remote Sensing 10, 480."
}
],
"url": "https://data.dea.ga.gov.au/LHTC_Tides/high_composite_20_maps.geojson",
"featureInfoTemplate": {
"template": "The tidal range at this location is {{modelLow}} to {{modelHigh}} meters relative to mean sea level (MSL). The high tide composite at this location was generated from imagery acquired in the top 20% of the observed tidal range which is between {{LIT}} and {{HIT}} meters relative to MSL, during the period of time of {{date_range}}. Observations used to generate the composite (black dots), in relation to the full modelled tidal range (blue) and complete archive (white dots) at this location Download the GeoTIFF for this polygon here: COMPOSITE_HIGH_{{ID}}_{{lon}}_{{lat}}_{{start_date}}_{{end_date}}_PER_20.tif"
},
"id": "IjP3T7",
"shareKeys": [
"Root Group/Coastal/High tide satellite images/High Tide Polygons for data access"
]
}
],
"shareKeys": [
"Root Group/Coastal/High tide satellite images"
]
},
{
"id": "bsRRuv",
"type": "group",
"name": "Other",
"members": [
{
"type": "wms",
"name": "DEA Intertidal Elevation (Landsat)",
"url": "https://ows.dea.ga.gov.au/",
"opacity": 1,
"layers": "NIDEM",
"linkedWcsUrl": "https://ows.dea.ga.gov.au/",
"linkedWcsCoverage": "NIDEM",
"leafletUpdateInterval": 750,
"tileErrorHandlingOptions": {
"ignoreUnknownTileErrors": true
},
"shortReport": "For more information and to download data, visit the DEA Intertidal Elevation product description",
"featureInfoTemplate": {
"template": "
Digital Earth Australia Intertidal Elevation
Elevation relative to Mean Sea Level (approximately equivelent to AHD):
"
},
"id": "bWICtK",
"shareKeys": [
"Root Group/Coastal/National Intertidal Digital Elevation Model"
]
},
{
"type": "wms",
"name": "DEA Intertidal Extents (Landsat)",
"url": "https://ows.dea.ga.gov.au/",
"opacity": 1,
"layers": "ITEM_V2.0.0",
"linkedWcsUrl": "https://ows.dea.ga.gov.au/",
"linkedWcsCoverage": "ITEM_V2.0.0",
"leafletUpdateInterval": 750,
"tileErrorHandlingOptions": {
"ignoreUnknownTileErrors": true
},
"id": "cXSDLg",
"shareKeys": [
"Root Group/Coastal/Intertidal extent model/Intertidal Extent"
]
},
{
"type": "wms",
"name": "DEA Intertidal Extents confidence",
"url": "https://ows.dea.ga.gov.au/",
"opacity": 1,
"layers": "ITEM_V2.0.0_Conf",
"linkedWcsUrl": "https://ows.dea.ga.gov.au/",
"linkedWcsCoverage": "ITEM_V2.0.0_Conf",
"leafletUpdateInterval": 750,
"tileErrorHandlingOptions": {
"ignoreUnknownTileErrors": true
},
"id": "6E5V7V",
"shareKeys": [
"Root Group/Coastal/Intertidal extent model/Intertidal Extent Confidence"
]
},
{
"type": "geojson",
"name": "DEA Intertidal Extents polygons for data access",
"info": [
{
"name": "Abstract",
"content": "The Intertidal Extents Model (ITEM v2.0) product analyses GA's historic archive of satellite imagery to derive a model of the spatial extents of the intertidal zone throughout the tidal cycle. The model can assist in understanding the relative elevation profile of the intertidal zone, delineating exposed areas at differing tidal heights and stages. The product differs from previous methods used to map the intertidal zone which have been predominately focused on analysing a small number of individual satellite images per location (e.g Ryu et al., 2002; Murray et al., 2012). By utilising a full 30 year time series of observations and a global tidal model (Egbert and Erofeeva, 2002), the methodology enables us to overcome the requirement for clear, high quality observations acquired concurrent to the time of high and low tide."
},
{
"name": "Overview",
"content": "The Intertidal Extents Model product is a national scale gridded dataset characterising the spatial extents of the exposed intertidal zone, at intervals of the observed tidal range (Sagar et al. 2017). The current version (2.0) utilises all Landsat observations (5, 7, and 8) for Australian coastal regions (excluding off-shore Territories) between 1986 and 2016 (inclusive). ITEM v2.0 has implemented an improved tidal modelling framework (see Sagar et al. 2018) over that utilised in ITEM v1.0. The expanded Landsat archive within the Digital Earth Australia (DEA) has also enabled the model extent to be increased to cover a number of offshore reefs, including the full Great Barrier Reef and southern sections of the Torres Strait Islands. The DEA archive and new tidal modelling framework has improved the coverage and quality of the ITEM v2.0 relative extents model, particularly in regions where AGDC cell boundaries in ITEM v1.0 produced discontinuities or the imposed v1.0 cell structure resulted in poor quality tidal modelling (see Sagar et al. 2017). Examples of regions in ITEM v2.0 where these significant improvements have been noted include:
Dampier Peninsula and King Sound, WA. Improved modelling within King Sound has removed the discontinuities seen at cell boundaries in ITEM v1.0, and expanded the extent of intertidal region being mapped.
Tiwi Islands, Coburg Peninsula and Croker Island, NT. Poor spatial representation of the regions tidal regimes in ITEM v1.0 has been improved in v2.0 resulting in extensive onshore reefs and mudflats now being mapped.
The full Great Barrier Reef has been mapped, detailing reef structures which expose at low tide. Algorithm amendments have reduced the false positive exposed surface detections resulting from glint and sun glitter.
Broad Sound, QLD. Improved tidal modelling has resulted in a smoother intertidal extent map, and a greatly improved confidence layer value for the region.
Improvements in the coverage of the DEA archive has allowed many regions unresolved in ITEM v1.0 and showing as 'no data' to be modelled successfully in ITEM 2.0. For example, Mornington Island, QLD, Eastern sections of Fraser Island, QLD and peninsulas in Bowling Green Bay National Park near Townsville, QLD
"
},
{
"name": "Accuracy and limitations",
"content": "Due the sun-synchronous nature of the various Landsat sensor observations; it is unlikely that the full physical extents of the tidal range in any cell will be observed. Hence, terminology has been adopted for the product to reflect the highest modelled tide observed in a given cell (HOT) and the lowest modelled tide observed (LOT) (see Sagar et al. 2017). These measures are relative to Mean Sea Level, and have no consistent relationship to Lowest (LAT) and Highest Astronomical Tide (HAT). The inclusion of the lowest (LMT) and highest (HMT) modelled tide values for each tidal polygon indicates the highest and lowest tides modelled for that location across the full time series by the OTPS model. The relative difference between the LOT and LMT (and HOT and HMT) heights gives an indication of the extent of the tidal range represented in the Relative Extents Model. As in ITEM v1.0, v2.0 contains some false positive land detection in open ocean regions. These are a function of the lack of data at the extremes of the observed tidal range, and features like glint and undetected cloud in these data poor regions/intervals. Methods to isolate and remove these features are in development for future versions. Issues in the DEA archive and data noise in the Esperance, WA region off Cape Le Grande and Cape Arid (Polygons 236,201,301) has resulted in significant artefacts in the model, and use of the model in this area is not recommended. The Confidence layer is designed to assess the reliability of the Relative Extent Model. Within each tidal range percentile interval, the pixel-based standard deviation of the NDWI values for all observations in the interval subset is calculated. The average standard deviation across all tidal range intervals is then calculated and retained as a quality indicator in this product layer. The Confidence Layer reflects the pixel based consistency of the NDWI values within each subset of observations, based on the tidal range. Higher standard deviation values indicate water classification changes not based on the tidal cycle, and hence lower confidence in the extent model. Possible drivers of these changes include:
Inadequacies of the tidal model, due perhaps to complex coastal bathymetry or estuarine structures not captured in the model. These effects have been reduced in ITEM v2.0 compared to previous versions, through the use of an improved tidal modelling framework
Change in the structure and exposure of water/non-water features NOT driven by tidal variation. For example, movement of sand banks in estuaries, construction of man-made features (ports etc.).
Terrestrial/Inland water features not influenced by the tidal cycle.
"
},
{
"name": "File naming",
"content": "
THE RELATIVE EXTENTS MODEL v2.0
ITEM_REL_<TIDAL POLYGON NUMBER>_<LONGITUDE>_<LATITUDE> TIDAL POLYGON NUMBER relates to the id of the tidal polygon referenced by the file LONGITUDE is the longitude of the centroid of the tidal polygon LATITUDE is the latitude of the centroid of the tidal polygon
THE CONFIDENCE LAYER v2.0
ITEM_STD_<TIDAL POLYGON NUMBER>_<LONGITUDE>_<LATITUDE> TIDAL POLYGON NUMBER relates to the id of the tidal polygon referenced by the file LONGITUDE is the longitude of the centroid of the tidal polygon LATITUDE is the latitude of the centroid of the tidal polygon The index of downloadable GeoTIFFs can be found here: http://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalogs/fk4/item_2_0.xml"
},
{
"name": "References",
"content": "Egbert, G.D., Erofeeva, S.Y., 2002. Efficient Inverse Modeling of Barotropic Ocean Tides. J. Atmos. Oceanic Technol. 19, 183–204. Murray, N.J., Phinn, S.R., Clemens, R.S., Roelfsema, C.M., Fuller, R.A., 2012. Continental Scale Mapping of Tidal Flats across East Asia Using the Landsat Archive. Remote Sensing 4, 3417–3426. Ryu, J.-H., Won, J.-S., Min, K.D., 2002. Waterline extraction from Landsat TM data in a tidal flat: A case study in Gomso Bay, Korea. Remote Sensing of Environment 83, 442–456. Sagar, S., Roberts, D., Bala, B., Lymburner, L., 2017. Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations. Remote Sensing of Environment 195, 153–169. Sagar, S., Phillips, C., Bala, B., Roberts, D., Lymburner, L., 2018. Generating Continental Scale Pixel-Based Surface Reflectance Composites in Coastal Regions with the Use of a Multi-Resolution Tidal Model. Remote Sensing 10, 480."
}
],
"url": "https://data.dea.ga.gov.au/ITEM_V2/Itemv2.geojson",
"featureInfoTemplate": {
"template": "The ITEM v2.0 relative model displays the modelled extents of the exposed intertidal zone, at percentile intervals of the observed tidal range (OTR), derived from Landsat imagery acquired between 1986 and 2016. The full tidal range at this location is {{LMT}} to {{HMT}} metres relative to mean sea level (MSL), and the OTR at this location is between {{LOT}} and {{HOT}} relative to MSL. The ITEM v2.0 confidence layer displays the standard deviation of the water index values (NDWI) derived across the tidal intervals used in generating the core ITEM relative product. High values indicate regions where inundation patterns are not driven by tidal influences. This can be a result of change (shoreline, geomorphic, anthropogenic), or caused by errors in the underlying tidal model. Coloured bars corresponding to the legend highlight the observations (black dots) and tidal range used to generate each ITEM interval, compared to the full modelled tidal range (light grey) at this location Download the GeoTIFF products for this polygon here: ITEM_REL_{{ID}}_{{lon}}_{{lat}}.tifITEM_STD_{{ID}}_{{lon}}_{{lat}}.tif",
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{
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"info": [
{
"name": "Important information",
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],
"shortReport": "Note: This is a provisional layer intended to replace the existing DEA Summary Product Grid (Collection 3) in 2024 by updating region code IDs to account for new satellite data processed over Australia's external territories.",
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