Murray Global Tidal Wetland Change v1.0 (1999-2019)

JCU/Murray/GIC/global_tidal_wetland_change/2019
Dataset Availability
1999-01-01T00:00:00Z–2019-12-31T00:00:00
Dataset Provider
Earth Engine Snippet
ee.Image("JCU/Murray/GIC/global_tidal_wetland_change/2019")
Tags
coastal ecosystem intertidal landsat-derived mangrove murray saltmarsh tidal-flat tidal-marsh

Description

The Murray Global Tidal Wetland Change Dataset contains maps of the global extent of tidal wetlands and their change. The maps were developed from a three stage classification that sought to (i) estimate the global distribution of tidal wetlands (defined as either tidal marsh, tidal flat or mangrove ecosystems), (ii) detect their change over the study period, and (iii) estimate the ecosystem type and timing of tidal wetland change events.

The dataset was produced by combining observations from 1,166,385 satellite images acquired by Landsat 5 to 8 with environmental data of variables known to influence the distributions of each ecosystem type, including temperature, slope, and elevation. The image contains bands for a tidal wetland extent product (random forest probability of tidal wetland occurrence) for the start and end time-steps of the study period and a tidal wetland change product over the full study period (loss and gain of tidal wetlands).

Please see the usage notes on the project website. A full description of the methods, validation, and limitations of the data produced by this software is available in the associated scientific paper.

See also UQ/murray/Intertidal/v1_1/global_intertidal for global maps of the distribution of tidal flat ecosystems.

Bands

Resolution
30 meters

Bands

Name Description
loss

Set to 1 for loss locations, masked out otherwise.

lossYear

Integer representing the end year of the time-step of loss analysis (e.g., 19 = 2017-2019).

lossType

Loss type

  • 2 - Tidal Flat
  • 3 - Mangrove
  • 5 - Tidal Marsh
gain

Set to 1 for gain locations, masked out otherwise.

gainYear

Integer representing the end year of the time-step of gain analysis (e.g., 19 = 2017-2019).

gainType

Gain type:

  • 2 - Tidal Flat
  • 3 - Mangrove
  • 5 - Tidal Marsh
twprobabilityStart

Random forest agreement of the overarching tidal wetland class for the first time step (1999-2001). Integer between 0 and 100.

twprobabilityEnd

Random forest agreement of the overarching tidal wetland class for the last time step (2017-2019). Integer between 0 and 100.

Terms of Use

Terms of Use

CC-BY-4.0

Citations

Citations:
  • Murray, N.J., Worthington, T.A., Bunting, P., Duce, S., Hagger, V., Lovelock, C.E., Lucas, R., Saunders, M.I., Sheaves, M., Spalding, M., Waltham, N.J., Lyons, M.B., 2022. High-resolution mapping of losses and gains of Earth's tidal wetlands. Science. doi:10.1126/science.abm9583

DOIs

Explore in Earth Engine

var dataset = ee.Image('JCU/Murray/GIC/global_tidal_wetland_change/2019');

Map.setCenter(103.7, 1.3, 12);
Map.setOptions('SATELLITE');

var plasma = [
  '0d0887', '3d049b', '6903a5', '8d0fa1', 'ae2891', 'cb4679', 'df6363',
  'f0844c', 'faa638', 'fbcc27', 'f0f921'
];
Map.addLayer(
    dataset.select('twprobabilityStart'), {palette: plasma, min: 0, max: 100},
    'twprobabilityStart', false, 1);
Map.addLayer(
    dataset.select('twprobabilityEnd'), {palette: plasma, min: 0, max: 100},
    'twprobabilityEnd', false, 1);

var lossPalette = ['FE4A49'];
var gainPalette = ['2AB7CA'];
Map.addLayer(
    dataset.select('loss'), {palette: lossPalette, min: 1, max: 1},
    'Tidal wetland loss', true, 1);
Map.addLayer(
    dataset.select('gain'), {palette: gainPalette, min: 1, max: 1},
    'Tidal wetland gain', true, 1);

var viridis = ['440154', '414487', '2a788e', '22a884', '7ad151', 'fde725'];
Map.addLayer(
    dataset.select('lossYear'), {palette: viridis, min: 4, max: 19},
    'Year of loss', false, 0.9);
Map.addLayer(
    dataset.select('gainYear'), {palette: viridis, min: 4, max: 19},
    'Year of gain', false, 0.9);

// ecosystem type
var classPalette = ['9e9d9d', 'ededed', 'FF9900', '009966', '960000', '006699'];
var classNames =
    ['null', 'null', 'Tidal flat', 'Mangrove', 'null', 'Tidal marsh'];
Map.addLayer(
    dataset.select('lossType'), {palette: classPalette, min: 0, max: 5},
    'Loss type', false, 0.9);
Map.addLayer(
    dataset.select('gainType'), {palette: classPalette, min: 0, max: 5},
    'Gain type', false, 0.9);