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The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2018-05-03 09:21:26	ga_ls8c_ard_3-0-0_090089_2018-05-02_final
2018-07-09 09:51:55	ga_ls8c_ard_3-0-0_095088_2018-07-09_final
2021-04-12 09:52:30	ga_ls8c_ard_3-2-0_095088_2021-04-12_final
2021-04-30 09:39:59	ga_ls8c_ard_3-2-0_093088_2021-04-30_final
2021-05-02 09:28:00	ga_ls8c_ard_3-2-0_091089_2021-05-01_final
2021-05-07 09:46:06	ga_ls8c_ard_3-2-0_094088_2021-05-07_final
2021-05-09 09:33:46	ga_ls8c_ard_3-2-0_092088_2021-05-09_final
2021-05-09 09:34:10	ga_ls8c_ard_3-2-0_092089_2021-05-09_final
2021-07-19 09:40:22	ga_ls8c_ard_3-2-0_093088_2021-07-19_final
2021-07-21 09:28:26	ga_ls8c_ard_3-2-0_091089_2021-07-20_final
2021-10-18 09:22:19	ga_ls8c_ard_3-2-0_090088_2021-10-17_final
2021-10-18 09:22:43	ga_ls8c_ard_3-2-0_090089_2021-10-17_final
2022-01-11 09:40:40	ga_ls8c_ard_3-2-1_093088_2022-01-11_final
2022-01-20 09:34:27	ga_ls8c_ard_3-2-1_092088_2022-01-20_final
2022-01-20 09:34:51	ga_ls8c_ard_3-2-1_092089_2022-01-20_final
2022-01-22 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-01-21_final
2022-01-22 09:22:28	ga_ls8c_ard_3-2-1_090089_2022-01-21_final
2022-01-27 09:40:34	ga_ls8c_ard_3-2-1_093088_2022-01-27_final
2022-01-29 09:28:36	ga_ls8c_ard_3-2-1_091089_2022-01-28_final
2022-01-31 09:15:51	ga_ls8c_ard_3-2-1_089088_2022-01-30_final
2022-01-31 09:16:15	ga_ls8c_ard_3-2-1_089089_2022-01-30_final
2022-02-05 09:34:23	ga_ls8c_ard_3-2-1_092088_2022-02-05_final
2022-02-05 09:34:47	ga_ls8c_ard_3-2-1_092089_2022-02-05_final
2022-02-07 09:22:01	ga_ls8c_ard_3-2-1_090088_2022-02-06_final
2022-02-07 09:22:25	ga_ls8c_ard_3-2-1_090089_2022-02-06_final
2022-02-14 09:28:33	ga_ls8c_ard_3-2-1_091089_2022-02-13_final
2022-02-16 09:16:10	ga_ls8c_ard_3-2-1_089089_2022-02-15_final
2022-02-21 09:34:17	ga_ls8c_ard_3-2-1_092088_2022-02-21_final
2022-02-21 09:34:41	ga_ls8c_ard_3-2-1_092089_2022-02-21_final
2022-02-23 09:21:55	ga_ls8c_ard_3-2-1_090088_2022-02-22_final
2022-02-23 09:22:19	ga_ls8c_ard_3-2-1_090089_2022-02-22_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-05 09:27:54	ga_ls8c_ard_3-2-1_091088_2022-05-04_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-07 09:15:34	ga_ls8c_ard_3-2-1_089088_2022-05-06_final
2022-05-07 09:15:58	ga_ls8c_ard_3-2-1_089089_2022-05-06_final
2022-05-12 09:34:09	ga_ls8c_ard_3-2-1_092088_2022-05-12_final
2022-05-12 09:34:33	ga_ls8c_ard_3-2-1_092089_2022-05-12_final
2022-05-14 09:21:49	ga_ls8c_ard_3-2-1_090088_2022-05-13_final
2022-05-14 09:22:13	ga_ls8c_ard_3-2-1_090089_2022-05-13_final
2022-05-19 09:40:22	ga_ls8c_ard_3-2-1_093088_2022-05-19_final
2022-05-28 09:34:10	ga_ls8c_ard_3-2-1_092088_2022-05-28_final
2022-05-28 09:34:34	ga_ls8c_ard_3-2-1_092089_2022-05-28_final
2022-05-30 09:21:51	ga_ls8c_ard_3-2-1_090088_2022-05-29_final
2022-05-30 09:22:15	ga_ls8c_ard_3-2-1_090089_2022-05-29_final
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-06 09:28:08	ga_ls8c_ard_3-2-1_091088_2022-06-05_final
2022-06-06 09:28:32	ga_ls8c_ard_3-2-1_091089_2022-06-05_final
2022-06-08 09:15:48	ga_ls8c_ard_3-2-1_089088_2022-06-07_final
2022-06-08 09:16:12	ga_ls8c_ard_3-2-1_089089_2022-06-07_final
2022-06-13 09:34:24	ga_ls8c_ard_3-2-1_092088_2022-06-13_final
2022-06-13 09:34:48	ga_ls8c_ard_3-2-1_092089_2022-06-13_final
2022-06-15 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-06-14_final
2022-06-15 09:22:27	ga_ls8c_ard_3-2-1_090089_2022-06-14_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-22 09:28:17	ga_ls8c_ard_3-2-1_091088_2022-06-21_final
2022-06-22 09:28:41	ga_ls8c_ard_3-2-1_091089_2022-06-21_final
2022-06-24 09:15:56	ga_ls8c_ard_3-2-1_089088_2022-06-23_final
2022-06-24 09:16:20	ga_ls8c_ard_3-2-1_089089_2022-06-23_final
2022-07-10 09:15:57	ga_ls8c_ard_3-2-1_089088_2022-07-09_final
2022-07-10 09:16:21	ga_ls8c_ard_3-2-1_089089_2022-07-09_final
2022-07-15 09:34:52	ga_ls8c_ard_3-2-1_092089_2022-07-15_final
2022-07-17 09:22:07	ga_ls8c_ard_3-2-1_090088_2022-07-16_final
2022-07-17 09:22:31	ga_ls8c_ard_3-2-1_090089_2022-07-16_final
2022-07-22 09:40:44	ga_ls8c_ard_3-2-1_093088_2022-07-22_final
2022-07-24 09:28:24	ga_ls8c_ard_3-2-1_091088_2022-07-23_final
2022-07-24 09:28:48	ga_ls8c_ard_3-2-1_091089_2022-07-23_final
2022-07-26 09:16:04	ga_ls8c_ard_3-2-1_089088_2022-07-25_final
2022-07-26 09:16:28	ga_ls8c_ard_3-2-1_089089_2022-07-25_final
2022-07-31 09:34:40	ga_ls8c_ard_3-2-1_092088_2022-07-31_final
2022-07-31 09:35:04	ga_ls8c_ard_3-2-1_092089_2022-07-31_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_final
2022-09-10 09:28:40	ga_ls8c_ard_3-2-1_091088_2022-09-09_final
2022-09-10 09:29:04	ga_ls8c_ard_3-2-1_091089_2022-09-09_final
2022-09-12 09:16:19	ga_ls8c_ard_3-2-1_089088_2022-09-11_final
2022-09-12 09:16:43	ga_ls8c_ard_3-2-1_089089_2022-09-11_final
2022-09-26 09:28:43	ga_ls8c_ard_3-2-1_091088_2022-09-25_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-09-28 09:16:21	ga_ls8c_ard_3-2-1_089088_2022-09-27_final
2022-09-28 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-09-27_final
2022-10-03 09:34:52	ga_ls8c_ard_3-2-1_092088_2022-10-03_final
2022-10-03 09:35:16	ga_ls8c_ard_3-2-1_092089_2022-10-03_final
2022-10-05 09:22:30	ga_ls8c_ard_3-2-1_090088_2022-10-04_final
2022-10-05 09:22:54	ga_ls8c_ard_3-2-1_090089_2022-10-04_final
2022-10-12 09:28:59	ga_ls8c_ard_3-2-1_091089_2022-10-11_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-19 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-10-19_final
2022-10-21 09:22:28	ga_ls8c_ard_3-2-1_090088_2022-10-20_final
2022-10-21 09:22:52	ga_ls8c_ard_3-2-1_090089_2022-10-20_final
2022-10-26 09:41:03	ga_ls8c_ard_3-2-1_093088_2022-10-26_final
2022-11-20 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-11-20_final
2022-11-20 09:35:10	ga_ls8c_ard_3-2-1_092089_2022-11-20_final
2022-11-22 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-11-21_final
2022-11-22 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-11-21_final
2022-11-29 09:28:38	ga_ls8c_ard_3-2-1_091088_2022-11-28_final
2022-11-29 09:29:02	ga_ls8c_ard_3-2-1_091089_2022-11-28_final
2022-12-01 09:16:16	ga_ls8c_ard_3-2-1_089088_2022-11-30_final
2022-12-01 09:16:40	ga_ls8c_ard_3-2-1_089089_2022-11-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2023-01-02 09:16:08	ga_ls8c_ard_3-2-1_089088_2023-01-01_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years