Google Earth engine (GEE) - Murray global tidal wetland change V1 (1999-2019) data set

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.

The Murray global tidal wetland change data set contains a map of the global tidal wetland range and its changes . These maps are developed according to three-stage classification , Aimed at (i) Estimate tidal wetlands （ It is defined as tidal swamp 、 Tidal flat or mangrove ecosystem ） Global distribution of ,(ii) Detect their changes during the study , as well as (iii) ) Estimate the ecosystem type and time of tidal wetland change events .

This data set is created by adding Landsat 5 To 8 Acquired 1,166,385 Observations from satellite images and environmental data on variables known to affect the distribution of each ecosystem type （ Including temperature 、 Slope and altitude ） Combined to produce . This image contains tidal wetland range products at the beginning and end time steps of the study period （ Random forest probability of tidal wetland occurrence ） And the wave band of tidal wetland change products throughout the study period （ Loss and gain of tidal wetlands ） .

see also Project website   Upper Instructions . Relevant scientific papers provide methods for data generated by the software 、 A complete description of the validation and limitations .

See also  UQ/murray/Intertidal/v1_1/global_intertidal  Understand the global tidal flat ecosystem distribution map .

Dataset availability

1999-01-01T00:00:00Z - 2019-12-31T00:00:00

Data set provider

Murray /JCU

Earth engine

ee.ImageCollection("JCU/Murray/GIC/global_tidal_wetland_change/2019"

The resolution of the
30 rice

Band

full name	describe
loss	Set the missing location to 1, Otherwise it will be shielded .
lossYear	An integer representing the end year of the loss analysis time step （ for example ,19 = 2017-2019）.
lossType	The type of loss 2 - The beach 3 - mangrove 5 - Tidal swamp
gain	The gain position is set to 1, Otherwise it will be shielded .
gainYear	An integer representing the end year of the gain analysis time step （ for example ,19 = 2017-2019）.
gainType	Gain type ： 2 - The beach 3 - mangrove 5 - Tidal swamp
twprobabilityStart	The first time step （1999-2001） Random forest protocol for total tidal wetlands .0 To 100 Integer between .
twprobabilityEnd	Last time step （2017-2019） Random forest protocol for the overall tidal wetland category .0 To 100 Integer between .

Code ：

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);

Terms of Use

CC-BY-4.0

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