Search ga_ls8c_ard_3 whole collection

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
2016-01-13 09:28:33	ga_ls8c_ard_3-0-0_091089_2016-01-12_final
2016-01-15 09:16:11	ga_ls8c_ard_3-0-0_089089_2016-01-14_final
2016-01-22 09:22:22	ga_ls8c_ard_3-1-0_090089_2016-01-21_final
2016-02-07 09:22:18	ga_ls8c_ard_3-0-0_090089_2016-02-06_final
2016-02-14 09:28:25	ga_ls8c_ard_3-0-0_091089_2016-02-13_final
2016-03-01 09:28:22	ga_ls8c_ard_3-0-0_091089_2016-02-29_final
2016-03-03 09:16:00	ga_ls8c_ard_3-0-0_089089_2016-03-02_final
2016-03-10 09:22:09	ga_ls8c_ard_3-0-0_090089_2016-03-09_final
2016-03-26 09:22:01	ga_ls8c_ard_3-0-0_090089_2016-03-25_final
2018-10-17 09:28:19	ga_ls8c_ard_3-0-0_091089_2018-10-16_final
2018-10-17 09:28:43	ga_ls8c_ard_3-0-0_091090_2018-10-16_final
2019-01-07 09:15:58	ga_ls8c_ard_3-0-0_089089_2019-01-06_final
2021-02-02 09:34:46	ga_ls8c_ard_3-2-0_092089_2021-02-02_final
2021-02-04 09:22:24	ga_ls8c_ard_3-2-0_090089_2021-02-03_final
2021-02-11 09:28:34	ga_ls8c_ard_3-2-0_091089_2021-02-10_final
2021-02-18 09:34:43	ga_ls8c_ard_3-2-0_092089_2021-02-18_final
2021-02-20 09:22:20	ga_ls8c_ard_3-2-0_090089_2021-02-19_final
2021-03-06 09:34:35	ga_ls8c_ard_3-2-0_092089_2021-03-06_final
2021-03-15 09:28:19	ga_ls8c_ard_3-2-0_091089_2021-03-14_final
2021-03-15 09:28:43	ga_ls8c_ard_3-2-0_091090_2021-03-14_final
2021-03-17 09:15:56	ga_ls8c_ard_3-2-0_089089_2021-03-16_final
2021-03-22 09:34:28	ga_ls8c_ard_3-2-0_092089_2021-03-22_final
2021-03-24 09:22:06	ga_ls8c_ard_3-2-0_090089_2021-03-23_final
2021-03-31 09:28:15	ga_ls8c_ard_3-2-0_091089_2021-03-30_final
2021-04-02 09:15:53	ga_ls8c_ard_3-2-0_089089_2021-04-01_final
2021-04-23 09:34:16	ga_ls8c_ard_3-2-0_092089_2021-04-23_final
2022-02-16 09:16:10	ga_ls8c_ard_3-2-1_089089_2022-02-15_final
2022-04-03 09:28:12	ga_ls8c_ard_3-2-1_091089_2022-04-02_final
2022-04-05 09:15:52	ga_ls8c_ard_3-2-1_089089_2022-04-04_final
2022-04-10 09:34:27	ga_ls8c_ard_3-2-1_092089_2022-04-10_final
2022-04-12 09:22:07	ga_ls8c_ard_3-2-1_090089_2022-04-11_final
2022-04-19 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-04-18_final
2022-04-19 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-04-18_final
2022-04-21 09:15:56	ga_ls8c_ard_3-2-1_089089_2022-04-20_final
2022-04-21 09:16:19	ga_ls8c_ard_3-2-1_089090_2022-04-20_final
2022-04-26 09:34:26	ga_ls8c_ard_3-2-1_092089_2022-04-26_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-28 09:22:03	ga_ls8c_ard_3-2-1_090089_2022-04-27_final
2022-04-28 09:22:27	ga_ls8c_ard_3-2-1_090090_2022-04-27_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-05 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-05-04_final
2022-05-07 09:15:58	ga_ls8c_ard_3-2-1_089089_2022-05-06_final
2022-05-07 09:16:22	ga_ls8c_ard_3-2-1_089090_2022-05-06_final
2022-05-14 09:22:13	ga_ls8c_ard_3-2-1_090089_2022-05-13_final
2022-07-10 09:16:21	ga_ls8c_ard_3-2-1_089089_2022-07-09_final
2022-07-10 09:16:45	ga_ls8c_ard_3-2-1_089090_2022-07-09_final
2022-07-15 09:34:52	ga_ls8c_ard_3-2-1_092089_2022-07-15_final
2022-07-15 09:35:16	ga_ls8c_ard_3-2-1_092090_2022-07-15_final
2022-11-13 09:29:03	ga_ls8c_ard_3-2-1_091089_2022-11-12_final
2022-11-13 09:29:27	ga_ls8c_ard_3-2-1_091090_2022-11-12_final
2022-11-15 09:16:39	ga_ls8c_ard_3-2-1_089089_2022-11-14_final
2022-11-29 09:29:02	ga_ls8c_ard_3-2-1_091089_2022-11-28_final
2022-12-01 09:16:40	ga_ls8c_ard_3-2-1_089089_2022-11-30_final
2022-12-01 09:17:04	ga_ls8c_ard_3-2-1_089090_2022-11-30_final
2022-12-08 09:22:50	ga_ls8c_ard_3-2-1_090089_2022-12-07_final
2022-12-17 09:16:34	ga_ls8c_ard_3-2-1_089089_2022-12-16_final
2022-12-24 09:22:40	ga_ls8c_ard_3-2-1_090089_2022-12-23_final
2023-01-02 09:16:31	ga_ls8c_ard_3-2-1_089089_2023-01-01_final
2023-04-29 09:34:08	ga_ls8c_ard_3-2-1_092089_2023-04-29_final
2023-05-01 09:21:46	ga_ls8c_ard_3-2-1_090089_2023-04-30_final
2023-05-08 09:27:51	ga_ls8c_ard_3-2-1_091089_2023-05-07_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-15 09:33:55	ga_ls8c_ard_3-2-1_092089_2023-05-15_final
2023-05-17 09:21:33	ga_ls8c_ard_3-2-1_090089_2023-05-16_final
2023-05-24 09:27:46	ga_ls8c_ard_3-2-1_091089_2023-05-23_final
2023-05-24 09:28:10	ga_ls8c_ard_3-2-1_091090_2023-05-23_final
2023-05-26 09:15:25	ga_ls8c_ard_3-2-1_089089_2023-05-25_final
2023-05-26 09:15:49	ga_ls8c_ard_3-2-1_089090_2023-05-25_final
2023-06-02 09:21:36	ga_ls8c_ard_3-2-1_090089_2023-06-01_final
2023-06-02 09:22:00	ga_ls8c_ard_3-2-1_090090_2023-06-01_final
2023-07-20 09:21:59	ga_ls8c_ard_3-2-1_090089_2023-07-19_final
2023-07-27 09:28:16	ga_ls8c_ard_3-2-1_091089_2023-07-26_final
2023-07-27 09:28:40	ga_ls8c_ard_3-2-1_091090_2023-07-26_final
2023-09-20 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-09-20_final
2023-09-20 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-09-20_final
2023-09-22 09:22:21	ga_ls8c_ard_3-2-1_090089_2023-09-21_final
2023-09-29 09:28:35	ga_ls8c_ard_3-2-1_091089_2023-09-28_final
2023-09-29 09:28:59	ga_ls8c_ard_3-2-1_091090_2023-09-28_final
2023-10-01 09:16:14	ga_ls8c_ard_3-2-1_089089_2023-09-30_final
2023-10-01 09:16:38	ga_ls8c_ard_3-2-1_089090_2023-09-30_final
2023-10-08 09:22:25	ga_ls8c_ard_3-2-1_090089_2023-10-07_final
2023-10-15 09:28:38	ga_ls8c_ard_3-2-1_091089_2023-10-14_final
2023-10-15 09:29:02	ga_ls8c_ard_3-2-1_091090_2023-10-14_final
2023-12-04 09:16:15	ga_ls8c_ard_3-2-1_089089_2023-12-03_final
2023-12-20 09:16:20	ga_ls8c_ard_3-2-1_089089_2023-12-19_final
2023-12-25 09:34:51	ga_ls8c_ard_3-2-1_092089_2023-12-25_final
2024-01-28 09:22:18	ga_ls8c_ard_3-2-1_090089_2024-01-27_final
2024-02-04 09:28:33	ga_ls8c_ard_3-2-1_091089_2024-02-03_final
2024-02-06 09:16:12	ga_ls8c_ard_3-2-1_089089_2024-02-05_final
2024-02-11 09:34:45	ga_ls8c_ard_3-2-1_092089_2024-02-11_final
2024-02-13 09:22:22	ga_ls8c_ard_3-2-1_090089_2024-02-12_final
2024-02-22 09:16:10	ga_ls8c_ard_3-2-1_089089_2024-02-21_final
2024-02-27 09:34:40	ga_ls8c_ard_3-2-1_092089_2024-02-27_final
2024-02-29 09:22:16	ga_ls8c_ard_3-2-1_090089_2024-02-28_final
2024-03-07 09:28:20	ga_ls8c_ard_3-2-1_091089_2024-03-06_final
2024-03-23 09:28:11	ga_ls8c_ard_3-2-1_091089_2024-03-22_final
2024-03-25 09:15:46	ga_ls8c_ard_3-2-1_089089_2024-03-24_final
2024-04-10 09:15:42	ga_ls8c_ard_3-2-1_089089_2024-04-09_final
2024-04-15 09:34:11	ga_ls8c_ard_3-2-1_092089_2024-04-15_final
2024-04-17 09:21:47	ga_ls8c_ard_3-2-1_090089_2024-04-16_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years