![UQ/murray/Intertidal/v1_1/qa_pixel_count](https://developers.google.com/earth-engine/datasets/images/UQ/UQ_murray_Intertidal_v1_1_qa_pixel_count_sample.png?authuser=0000)
- Dataset Availability
- 1984-01-01T00:00:00Z–2017-01-01T00:00:00Z
- Dataset Provider
- Murray/UQ/Google/USGS/NASA
- Earth Engine Snippet
-
ee.ImageCollection("UQ/murray/Intertidal/v1_1/qa_pixel_count")
- Tags
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)
The number of Landsat images used to develop the Landsat covariate layers in each time step of the tidal flat classification. Each image in the image collection refers to a single time step.
Bands
Resolution
30 meters
Bands
Name | Units | Min | Max | Description |
---|---|---|---|---|
pixel_count |
count | 0 | 400 | Input image count. |
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
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.
DOIs
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.ImageCollection('UQ/murray/Intertidal/v1_1/qa_pixel_count'); var visualization = { bands: ['pixel_count'], min: 0, max: 300, palette: ['000000', 'ffffff'] }; Map.setCenter(126.6339, 37.4394, 10); Map.addLayer(dataset, visualization, 'QA Pixel Count');