- Catalog Owner
- Geoscience Australia
- Dataset Availability
- 1987-01-01T00:00:00Z–2022-01-01T00:00:00Z
- Dataset Provider
- Geoscience Australia NGIS
- Contact
- Geoscience Australia
- Earth Engine Snippet
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ee.ImageCollection("projects/geoscience-aus-cat/assets/ga_ls_wo_fq_cyear_3")
- Tags
Description
Digital Earth Australia (DEA) Water Observations uses an algorithm to classify each pixel from Landsat satellite imagery as 'wet', 'dry', or 'invalid'. Water Observations Statistics provides information on how many times each year the Landsat satellites were able to clearly see an area, how many times those observations were wet, and what that means for the percentage of time that water was observed in the landscape.
Combining the classified pixels into summaries covering each year gives the information on where water is usually, and where it is rarely. As no confidence filtering is applied to this product, it is affected by noise where misclassifications have occurred in the input water classifications, and can be difficult to interpret on its own.
For more information, please see the DEA Water Observations Statistics Landsat
This product is part of the Digital Earth Australia Program
Bands
Resolution
25 meters
Bands
Name | Units | Min | Max | Description |
---|---|---|---|---|
count_clear |
count | -32768* | 32767* | Clear count: how many times an area could be clearly seen. |
count_wet |
count | -32768* | 32767* | Wet count: how many times water was detected in observations that were clear. |
frequency |
% | 0 | 1 | Water frequency: what percentage of clear observations were detected as wet. |
Terms of Use
Terms of Use
Citations
Mueller, N., Lewis, A., Roberts, D., Ring, S., Melrose, R., Sixsmith, J., Lymburner, L., McIntyre, A., Tan, P., Curnow, S., & Ip, A. (2016). Water observations from space: Mapping surface water from 25 years of Landsat imagery across Australia. Remote Sensing of Environment, 174, 341-352 doi:10.1016/j.rse.2015.11.003
DOIs
Explore with Earth Engine
Code Editor (JavaScript)
var water_obs = ee.ImageCollection('projects/geoscience-aus-cat/assets/ga_ls_wo_fq_cyear_3'); var gray = 150; var background = ee.Image.rgb(gray, gray, gray).visualize({ min: 0, max: 255 }); var visualization_frequency = { bands: ['frequency'], min: 0.0, max: 1.0, palette: ['ffffff', 'ffbbbb', '0000ff'] }; var point = ee.Geometry.Point([113.651455, -26.024137]); var image = water_obs.filterBounds(point) .filterDate('2010-01-01', '2011-01-01') .first() .visualize(visualization_frequency); Map.centerObject(image, 12); var imageWithBackground = ee.ImageCollection([background, image]).mosaic(); Map.addLayer(imageWithBackground, {}, 'Water Frequency ratio');