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
2018-02-13 10:04:10	ga_ls8c_ard_3-0-0_097086_2018-02-13_final
2018-02-15 09:51:48	ga_ls8c_ard_3-0-0_095086_2018-02-15_final
2018-02-15 09:52:12	ga_ls8c_ard_3-0-0_095087_2018-02-15_final
2018-04-17 09:20:23	ga_ls8c_ard_3-0-0_090086_2018-04-16_final
2018-04-17 09:20:47	ga_ls8c_ard_3-0-0_090087_2018-04-16_final
2019-07-05 09:45:44	ga_ls8c_ard_3-1-0_094086_2019-07-05_final
2019-07-05 09:46:08	ga_ls8c_ard_3-1-0_094087_2019-07-05_final
2019-07-07 09:33:22	ga_ls8c_ard_3-1-0_092086_2019-07-07_final
2019-07-07 09:33:46	ga_ls8c_ard_3-1-0_092087_2019-07-07_final
2019-07-14 09:39:34	ga_ls8c_ard_3-1-0_093086_2019-07-14_final
2019-07-14 09:39:58	ga_ls8c_ard_3-1-0_093087_2019-07-14_final
2019-07-16 09:27:13	ga_ls8c_ard_3-1-0_091086_2019-07-15_final
2019-07-16 09:27:37	ga_ls8c_ard_3-1-0_091087_2019-07-15_final
2019-08-17 09:27:25	ga_ls8c_ard_3-1-0_091086_2019-08-16_final
2019-08-17 09:27:49	ga_ls8c_ard_3-1-0_091087_2019-08-16_final
2019-08-18 10:10:41	ga_ls8c_ard_3-1-0_098086_2019-08-18_final
2019-08-19 09:15:04	ga_ls8c_ard_3-1-0_089086_2019-08-18_final
2019-08-19 09:15:28	ga_ls8c_ard_3-1-0_089087_2019-08-18_final
2019-08-20 09:58:20	ga_ls8c_ard_3-1-0_096086_2019-08-20_final
2019-08-20 09:58:44	ga_ls8c_ard_3-1-0_096087_2019-08-20_final
2019-09-12 10:04:36	ga_ls8c_ard_3-1-0_097086_2019-09-12_final
2019-09-14 09:52:15	ga_ls8c_ard_3-1-0_095086_2019-09-14_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-23 09:46:08	ga_ls8c_ard_3-1-0_094086_2019-09-23_final
2019-09-23 09:46:32	ga_ls8c_ard_3-1-0_094087_2019-09-23_final
2019-09-25 09:33:47	ga_ls8c_ard_3-1-0_092086_2019-09-25_final
2019-09-25 09:34:11	ga_ls8c_ard_3-1-0_092087_2019-09-25_final
2019-10-04 09:27:38	ga_ls8c_ard_3-1-0_091086_2019-10-03_final
2019-10-04 09:28:02	ga_ls8c_ard_3-1-0_091087_2019-10-03_final
2019-10-20 09:27:40	ga_ls8c_ard_3-1-0_091086_2019-10-19_final
2019-10-20 09:28:04	ga_ls8c_ard_3-1-0_091087_2019-10-19_final
2019-10-21 10:10:56	ga_ls8c_ard_3-1-0_098086_2019-10-21_final
2019-10-22 09:15:18	ga_ls8c_ard_3-1-0_089086_2019-10-21_final
2019-10-22 09:15:42	ga_ls8c_ard_3-1-0_089087_2019-10-21_final
2019-10-23 09:58:34	ga_ls8c_ard_3-1-0_096086_2019-10-23_final
2019-10-23 09:58:58	ga_ls8c_ard_3-1-0_096087_2019-10-23_final
2019-11-10 09:46:11	ga_ls8c_ard_3-1-0_094086_2019-11-10_final
2019-11-10 09:46:35	ga_ls8c_ard_3-1-0_094087_2019-11-10_final
2019-11-12 09:33:49	ga_ls8c_ard_3-1-0_092086_2019-11-12_final
2019-11-12 09:34:13	ga_ls8c_ard_3-1-0_092087_2019-11-12_final
2019-11-19 09:39:58	ga_ls8c_ard_3-1-0_093086_2019-11-19_final
2019-11-19 09:40:21	ga_ls8c_ard_3-1-0_093087_2019-11-19_final
2019-11-21 09:27:35	ga_ls8c_ard_3-1-0_091086_2019-11-20_final
2019-11-21 09:27:59	ga_ls8c_ard_3-1-0_091087_2019-11-20_final
2022-01-25 09:52:09	ga_ls8c_ard_3-2-1_095086_2022-01-25_final
2022-01-25 09:52:33	ga_ls8c_ard_3-2-1_095087_2022-01-25_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-10 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-04-10_final
2022-04-10 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-04-10_final
2022-04-12 09:21:19	ga_ls8c_ard_3-2-1_090087_2022-04-11_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-19 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-04-18_final
2022-04-19 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-04-18_final
2022-04-21 09:14:44	ga_ls8c_ard_3-2-1_089086_2022-04-20_final
2022-04-22 09:57:59	ga_ls8c_ard_3-2-1_096086_2022-04-22_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-26 09:33:38	ga_ls8c_ard_3-2-1_092087_2022-04-26_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 09:21:15	ga_ls8c_ard_3-2-1_090087_2022-04-27_final
2022-05-01 09:51:46	ga_ls8c_ard_3-2-1_095086_2022-05-01_final
2022-05-01 09:52:10	ga_ls8c_ard_3-2-1_095087_2022-05-01_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-08 09:58:02	ga_ls8c_ard_3-2-1_096086_2022-05-08_final
2022-05-10 09:45:42	ga_ls8c_ard_3-2-1_094086_2022-05-10_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-14 09:21:01	ga_ls8c_ard_3-2-1_090086_2022-05-13_final
2022-05-14 09:21:25	ga_ls8c_ard_3-2-1_090087_2022-05-13_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-11-27 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-11-27_final
2022-12-06 09:34:00	ga_ls8c_ard_3-2-1_092086_2022-12-06_final
2022-12-06 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-12-06_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-11 09:52:55	ga_ls8c_ard_3-2-1_095087_2022-12-11_final
2022-12-15 09:27:45	ga_ls8c_ard_3-2-1_091086_2022-12-14_final
2022-12-15 09:28:09	ga_ls8c_ard_3-2-1_091087_2022-12-14_final
2022-12-18 09:58:37	ga_ls8c_ard_3-2-1_096086_2022-12-18_final
2022-12-20 09:46:14	ga_ls8c_ard_3-2-1_094086_2022-12-20_final
2022-12-20 09:46:38	ga_ls8c_ard_3-2-1_094087_2022-12-20_final
2022-12-24 09:21:28	ga_ls8c_ard_3-2-1_090086_2022-12-23_final
2022-12-24 09:21:52	ga_ls8c_ard_3-2-1_090087_2022-12-23_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-29 09:40:02	ga_ls8c_ard_3-2-1_093086_2022-12-29_final
2022-12-29 09:40:26	ga_ls8c_ard_3-2-1_093087_2022-12-29_final
2023-01-05 09:46:13	ga_ls8c_ard_3-2-1_094086_2023-01-05_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-07 09:34:15	ga_ls8c_ard_3-2-1_092087_2023-01-07_final
2023-01-18 09:15:11	ga_ls8c_ard_3-2-1_089086_2023-01-17_final
2023-01-19 09:58:28	ga_ls8c_ard_3-2-1_096086_2023-01-19_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-21 09:46:32	ga_ls8c_ard_3-2-1_094087_2023-01-21_final
2023-01-25 09:21:27	ga_ls8c_ard_3-2-1_090086_2023-01-24_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