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
2018-01-30 09:52:18	ga_ls8c_ard_3-0-0_095087_2018-01-30_final
2018-02-01 09:39:55	ga_ls8c_ard_3-0-0_093087_2018-02-01_final
2018-02-03 09:27:32	ga_ls8c_ard_3-0-0_091087_2018-02-02_final
2018-02-10 09:33:41	ga_ls8c_ard_3-0-0_092087_2018-02-10_final
2018-02-12 09:21:19	ga_ls8c_ard_3-0-0_090087_2018-02-11_final
2018-02-15 09:52:12	ga_ls8c_ard_3-0-0_095087_2018-02-15_final
2018-02-17 09:39:49	ga_ls8c_ard_3-0-0_093087_2018-02-17_final
2018-02-19 09:27:27	ga_ls8c_ard_3-0-0_091087_2018-02-18_final
2018-02-21 09:15:05	ga_ls8c_ard_3-0-0_089087_2018-02-20_final
2018-02-24 09:45:57	ga_ls8c_ard_3-0-0_094087_2018-02-24_final
2018-02-26 09:33:35	ga_ls8c_ard_3-0-0_092087_2018-02-26_final
2018-02-28 09:21:12	ga_ls8c_ard_3-0-0_090087_2018-02-27_final
2018-03-03 09:52:05	ga_ls8c_ard_3-0-0_095087_2018-03-03_final
2018-03-05 09:39:42	ga_ls8c_ard_3-0-0_093087_2018-03-05_final
2018-03-10 09:58:11	ga_ls8c_ard_3-0-0_096087_2018-03-10_final
2018-03-12 09:45:48	ga_ls8c_ard_3-0-0_094087_2018-03-12_final
2018-03-19 09:51:56	ga_ls8c_ard_3-0-0_095087_2018-03-19_final
2018-03-21 09:39:33	ga_ls8c_ard_3-0-0_093087_2018-03-21_final
2018-03-26 09:58:04	ga_ls8c_ard_3-0-0_096087_2018-03-26_final
2018-03-28 09:45:41	ga_ls8c_ard_3-0-0_094087_2018-03-28_final
2018-03-30 09:33:19	ga_ls8c_ard_3-0-0_092087_2018-03-30_final
2018-04-01 09:20:56	ga_ls8c_ard_3-0-0_090087_2018-03-31_final
2018-04-04 09:51:49	ga_ls8c_ard_3-0-0_095087_2018-04-04_final
2018-04-06 09:39:26	ga_ls8c_ard_3-0-0_093087_2018-04-06_final
2018-04-08 09:27:03	ga_ls8c_ard_3-1-0_091087_2018-04-07_final
2018-04-10 09:14:41	ga_ls8c_ard_3-0-0_089087_2018-04-09_final
2018-04-11 09:57:56	ga_ls8c_ard_3-0-0_096087_2018-04-11_final
2018-04-13 09:45:33	ga_ls8c_ard_3-0-0_094087_2018-04-13_final
2018-04-15 09:33:10	ga_ls8c_ard_3-0-0_092087_2018-04-15_final
2018-04-17 09:20:47	ga_ls8c_ard_3-0-0_090087_2018-04-16_final
2018-04-20 09:51:39	ga_ls8c_ard_3-0-0_095087_2018-04-20_final
2018-04-22 09:39:16	ga_ls8c_ard_3-0-0_093087_2018-04-22_final
2018-05-06 09:51:30	ga_ls8c_ard_3-0-0_095087_2018-05-06_final
2018-05-08 09:39:08	ga_ls8c_ard_3-0-0_093087_2018-05-08_final
2018-05-13 09:57:13	ga_ls8c_ard_3-0-0_096086_2018-05-13_final
2018-05-13 09:57:37	ga_ls8c_ard_3-0-0_096087_2018-05-13_final
2018-05-19 09:20:27	ga_ls8c_ard_3-0-0_090087_2018-05-18_final
2018-09-11 09:51:36	ga_ls8c_ard_3-0-0_095086_2018-09-11_final
2018-09-11 09:52:00	ga_ls8c_ard_3-0-0_095087_2018-09-11_final
2018-09-13 09:39:39	ga_ls8c_ard_3-0-0_093087_2018-09-13_final
2018-09-15 09:27:17	ga_ls8c_ard_3-0-0_091087_2018-09-14_final
2018-09-17 09:14:56	ga_ls8c_ard_3-0-0_089087_2018-09-16_final
2018-10-01 09:27:00	ga_ls8c_ard_3-0-0_091086_2018-09-30_final
2018-10-01 09:27:24	ga_ls8c_ard_3-0-0_091087_2018-09-30_final
2018-10-04 09:58:20	ga_ls8c_ard_3-0-0_096087_2018-10-04_final
2018-10-06 09:45:35	ga_ls8c_ard_3-0-0_094086_2018-10-06_final
2018-10-06 09:45:59	ga_ls8c_ard_3-0-0_094087_2018-10-06_final
2018-10-08 09:33:38	ga_ls8c_ard_3-0-0_092087_2018-10-08_final
2018-10-10 09:21:18	ga_ls8c_ard_3-0-0_090087_2018-10-09_final
2018-10-11 10:04:10	ga_ls8c_ard_3-0-0_097086_2018-10-11_final
2018-10-13 09:52:13	ga_ls8c_ard_3-0-0_095087_2018-10-13_final
2018-10-15 09:39:52	ga_ls8c_ard_3-0-0_093087_2018-10-15_final
2018-10-17 09:27:07	ga_ls8c_ard_3-0-0_091086_2018-10-16_final
2018-10-17 09:27:31	ga_ls8c_ard_3-0-0_091087_2018-10-16_final
2018-11-02 09:27:35	ga_ls8c_ard_3-0-0_091087_2018-11-01_final
2018-11-09 09:33:47	ga_ls8c_ard_3-0-0_092087_2018-11-09_final
2018-11-11 09:21:25	ga_ls8c_ard_3-0-0_090087_2018-11-10_final
2018-11-12 10:04:17	ga_ls8c_ard_3-0-0_097086_2018-11-12_final
2018-11-14 09:52:20	ga_ls8c_ard_3-0-0_095087_2018-11-14_final
2018-11-16 09:39:58	ga_ls8c_ard_3-0-0_093087_2018-11-16_final
2018-11-18 09:27:12	ga_ls8c_ard_3-0-0_091086_2018-11-17_final
2018-11-18 09:27:36	ga_ls8c_ard_3-1-0_091087_2018-11-17_final
2018-12-04 09:27:35	ga_ls8c_ard_3-0-0_091087_2018-12-03_final
2018-12-20 09:27:33	ga_ls8c_ard_3-0-0_091087_2018-12-19_final
2019-01-05 09:27:32	ga_ls8c_ard_3-0-0_091087_2019-01-04_final
2019-01-07 09:15:10	ga_ls8c_ard_3-0-0_089087_2019-01-06_final
2019-01-12 09:33:42	ga_ls8c_ard_3-0-0_092087_2019-01-12_final
2019-01-14 09:21:20	ga_ls8c_ard_3-0-0_090087_2019-01-13_final
2019-02-11 09:45:58	ga_ls8c_ard_3-0-0_094087_2019-02-11_final
2019-02-13 09:33:36	ga_ls8c_ard_3-0-0_092087_2019-02-13_final
2019-03-31 09:45:45	ga_ls8c_ard_3-1-0_094087_2019-03-31_final
2019-04-02 09:33:23	ga_ls8c_ard_3-1-0_092087_2019-04-02_final
2019-05-02 09:45:38	ga_ls8c_ard_3-0-0_094087_2019-05-02_final
2019-05-04 09:33:18	ga_ls8c_ard_3-0-0_092087_2019-05-04_final
2019-05-18 09:45:49	ga_ls8c_ard_3-0-0_094087_2019-05-18_final
2019-05-20 09:33:28	ga_ls8c_ard_3-0-0_092087_2019-05-20_final
2023-07-02 09:33:28	ga_ls8c_ard_3-2-1_092087_2023-07-02_final
2023-07-04 09:20:44	ga_ls8c_ard_3-2-1_090086_2023-07-03_final
2023-07-04 09:21:08	ga_ls8c_ard_3-2-1_090087_2023-07-03_final
2023-07-07 09:52:04	ga_ls8c_ard_3-2-1_095087_2023-07-07_final
2023-07-09 09:39:43	ga_ls8c_ard_3-2-1_093087_2023-07-09_final
2023-07-11 09:27:22	ga_ls8c_ard_3-2-1_091087_2023-07-10_final
2023-07-16 09:45:55	ga_ls8c_ard_3-2-1_094087_2023-07-16_final
2023-07-18 09:33:33	ga_ls8c_ard_3-2-1_092087_2023-07-18_final
2023-07-20 09:20:47	ga_ls8c_ard_3-2-1_090086_2023-07-19_final
2023-07-20 09:21:11	ga_ls8c_ard_3-2-1_090087_2023-07-19_final
2023-07-23 09:52:07	ga_ls8c_ard_3-2-1_095087_2023-07-23_final
2023-12-27 09:21:41	ga_ls8c_ard_3-2-1_090087_2023-12-26_final
2023-12-30 09:52:33	ga_ls8c_ard_3-2-1_095087_2023-12-30_final
2024-01-01 09:40:10	ga_ls8c_ard_3-2-1_093087_2024-01-01_final
2024-01-03 09:27:46	ga_ls8c_ard_3-2-1_091087_2024-01-02_final
2024-01-08 09:46:18	ga_ls8c_ard_3-2-1_094087_2024-01-08_final
2024-01-10 09:33:58	ga_ls8c_ard_3-2-1_092087_2024-01-10_final
2024-01-12 09:21:37	ga_ls8c_ard_3-2-1_090087_2024-01-11_final
2024-01-17 09:40:09	ga_ls8c_ard_3-2-1_093087_2024-01-17_final
2024-02-09 09:46:19	ga_ls8c_ard_3-2-1_094087_2024-02-09_final
2024-03-12 09:46:03	ga_ls8c_ard_3-2-1_094087_2024-03-12_final
2024-03-14 09:33:41	ga_ls8c_ard_3-2-1_092087_2024-03-14_final
2024-03-21 09:39:47	ga_ls8c_ard_3-2-1_093087_2024-03-21_final
2024-03-28 09:45:48	ga_ls8c_ard_3-2-1_094087_2024-03-28_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