Murray Global Intertidal Change Data Mask

UQ/murray/Intertidal/v1_1/data_mask
Dataset Availability
1984-01-01T00:00:00Z–2017-01-01T00:00:00Z
Dataset Provider
Earth Engine Snippet
ee.Image("UQ/murray/Intertidal/v1_1/data_mask")

Description

The Murray Global Intertidal Change Dataset contains global maps of tidal flat ecosystems produced via a supervised classification of 707,528 Landsat Archive images. Each pixel was classified into tidal flat, permanent water or other with reference to a globally distributed set of training data.

The classification was implemented along the entire global coastline between 60° North and 60° South from 1 January 1984 to 31 December 2016. The image collection consists consists of a time-series of 11 global maps of tidal flats at 30m pixel resolution for set time-periods (1984-1986; 1987-1989; 1990-1992; 1993-1995; 1996-1998; 1999-2001; 2002-2004; 2005-2007; 2008-2010; 2011-2013; 2014-2016)

Flag indicating the spatial limits of the implementation of the tidal flat classifier as defined by altitudinal (+100m) and bathymetric (-100m) limits.

Bands

Resolution
30 meters

Bands

Name Units Description
datamask occurrence

A flag to indicate data inclusion.

Terms of Use

Terms of Use

This work is licensed under a Creative Commons Attribution 4.0 International License.

Any use of the intertidal data must include proper acknowledgement, including citing the associated journal article.

Citations

Citations:
  • Murray, N.J., Phinn, S.R., DeWitt, M., Ferrari, R., Johnston, R., Lyons, M.B., Clinton, N., Thau, D. & Fuller, R.A. (2019) The global distribution and trajectory of tidal flats. Nature, 565, 222-225. doi:10.1038/s41586-018-0805-8,

  • Murray, N. J., Phinn, S. P., Fuller, R. A., DeWitt, M., Ferrari, R., Johnston, R., Clinton, N., & Lyons, M. B. (2022). High-resolution global maps of tidal flat ecosystems from 1984 to 2019. Scientific Data, 9(1). doi:10.1038/s41597-022-01635-5,

DOIs

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Code Editor (JavaScript)

var dataset = ee.Image('UQ/murray/Intertidal/v1_1/data_mask');

var visualization = {
  bands: ['datamask'],
  min: 0,
  max: 1,
  palette: ['000000', 'ffffff']
};

Map.setCenter(126.6339, 37.4394, 10);

Map.addLayer(dataset, visualization, 'Data mask');
Open in Code Editor