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
2018-04-29 09:44:36	ga_ls8c_ard_3-0-0_094085_2018-04-29_final
2018-04-29 09:45:00	ga_ls8c_ard_3-0-0_094086_2018-04-29_final
2018-04-29 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-04-29_final
2018-05-01 09:32:37	ga_ls8c_ard_3-0-0_092086_2018-05-01_final
2018-05-01 11:11:06	ga_ls8c_ard_3-0-0_108085_2018-05-01_final
2018-05-15 09:44:50	ga_ls8c_ard_3-0-0_094086_2018-05-15_final
2018-05-15 11:23:19	ga_ls8c_ard_3-0-0_110085_2018-05-15_final
2018-05-17 09:32:26	ga_ls8c_ard_3-0-0_092086_2018-05-17_final
2018-06-02 09:32:14	ga_ls8c_ard_3-0-0_092086_2018-06-02_final
2018-06-02 11:10:43	ga_ls8c_ard_3-0-0_108085_2018-06-02_final
2018-06-03 10:15:06	ga_ls8c_ard_3-0-0_099085_2018-06-03_final
2018-06-04 09:19:28	ga_ls8c_ard_3-0-0_090085_2018-06-03_final
2018-06-04 09:19:52	ga_ls8c_ard_3-0-0_090086_2018-06-03_final
2018-06-05 10:02:44	ga_ls8c_ard_3-0-0_097085_2018-06-05_final
2018-06-05 10:03:08	ga_ls8c_ard_3-0-0_097086_2018-06-05_final
2018-06-11 09:25:43	ga_ls8c_ard_3-0-0_091085_2018-06-10_final
2018-06-11 09:26:07	ga_ls8c_ard_3-0-0_091086_2018-06-10_final
2018-06-11 11:04:36	ga_ls8c_ard_3-0-0_107085_2018-06-11_final
2018-07-04 09:32:08	ga_ls8c_ard_3-0-0_092085_2018-07-04_final
2018-07-04 09:32:32	ga_ls8c_ard_3-0-0_092086_2018-07-04_final
2018-07-04 11:11:01	ga_ls8c_ard_3-0-0_108085_2018-07-04_final
2018-07-05 10:15:24	ga_ls8c_ard_3-0-0_099085_2018-07-05_final
2018-07-06 09:19:47	ga_ls8c_ard_3-0-0_090085_2018-07-05_final
2018-07-06 09:20:11	ga_ls8c_ard_3-0-0_090086_2018-07-05_final
2018-07-07 10:03:03	ga_ls8c_ard_3-0-0_097085_2018-07-07_final
2018-07-07 10:03:27	ga_ls8c_ard_3-0-0_097086_2018-07-07_final
2018-07-16 09:56:57	ga_ls8c_ard_3-0-0_096085_2018-07-16_final
2018-07-16 09:57:21	ga_ls8c_ard_3-0-0_096086_2018-07-16_final
2018-07-18 09:44:36	ga_ls8c_ard_3-0-0_094085_2018-07-18_final
2018-07-18 09:45:00	ga_ls8c_ard_3-0-0_094086_2018-07-18_final
2018-07-18 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-07-18_final
2018-07-23 10:03:10	ga_ls8c_ard_3-0-0_097085_2018-07-23_final
2018-07-23 10:03:34	ga_ls8c_ard_3-0-0_097086_2018-07-23_final
2018-08-01 09:57:04	ga_ls8c_ard_3-0-0_096085_2018-08-01_final
2018-08-01 09:57:28	ga_ls8c_ard_3-0-0_096086_2018-08-01_final
2018-08-01 11:35:57	ga_ls8c_ard_3-0-0_112085_2018-08-01_final
2018-08-03 09:44:44	ga_ls8c_ard_3-0-0_094085_2018-08-03_final
2018-08-03 09:45:08	ga_ls8c_ard_3-0-0_094086_2018-08-03_final
2018-08-03 11:23:37	ga_ls8c_ard_3-0-0_110085_2018-08-03_final
2018-08-05 09:32:23	ga_ls8c_ard_3-0-0_092085_2018-08-05_final
2018-08-05 09:32:47	ga_ls8c_ard_3-0-0_092086_2018-08-05_final
2018-08-05 11:11:16	ga_ls8c_ard_3-0-0_108085_2018-08-05_final
2018-08-06 10:15:40	ga_ls8c_ard_3-0-0_099085_2018-08-06_final
2018-08-07 09:20:03	ga_ls8c_ard_3-0-0_090085_2018-08-06_final
2018-08-07 09:20:27	ga_ls8c_ard_3-0-0_090086_2018-08-06_final
2018-08-14 09:26:17	ga_ls8c_ard_3-0-0_091085_2018-08-13_final
2018-08-14 09:26:41	ga_ls8c_ard_3-0-0_091086_2018-08-13_final
2018-08-14 11:05:11	ga_ls8c_ard_3-0-0_107085_2018-08-14_final
2018-08-17 09:57:13	ga_ls8c_ard_3-0-0_096085_2018-08-17_final
2018-08-17 09:57:37	ga_ls8c_ard_3-0-0_096086_2018-08-17_final
2018-08-17 11:36:06	ga_ls8c_ard_3-0-0_112085_2018-08-17_final
2018-08-19 09:44:52	ga_ls8c_ard_3-0-0_094085_2018-08-19_final
2018-08-19 09:45:16	ga_ls8c_ard_3-0-0_094086_2018-08-19_final
2018-08-19 11:23:45	ga_ls8c_ard_3-0-0_110085_2018-08-19_final
2018-08-30 09:26:25	ga_ls8c_ard_3-0-0_091085_2018-08-29_final
2018-08-30 09:26:49	ga_ls8c_ard_3-0-0_091086_2018-08-29_final
2018-08-30 11:05:18	ga_ls8c_ard_3-0-0_107085_2018-08-30_final
2018-09-06 09:32:38	ga_ls8c_ard_3-0-0_092085_2018-09-06_final
2018-09-06 09:33:02	ga_ls8c_ard_3-0-0_092086_2018-09-06_final
2018-09-06 11:11:31	ga_ls8c_ard_3-0-0_108085_2018-09-06_final
2018-09-07 10:15:54	ga_ls8c_ard_3-0-0_099085_2018-09-07_final
2018-09-08 09:20:17	ga_ls8c_ard_3-0-0_090085_2018-09-07_final
2018-09-08 09:20:41	ga_ls8c_ard_3-0-0_090086_2018-09-07_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-16 10:10:09	ga_ls8c_ard_3-0-0_098086_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2018-09-17 09:14:32	ga_ls8c_ard_3-0-0_089086_2018-09-16_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-06 10:10:24	ga_ls8c_ard_3-0-0_098086_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-01-07 09:14:46	ga_ls8c_ard_3-0-0_089086_2019-01-06_final
2023-09-16 09:57:50	ga_ls8c_ard_3-2-1_096085_2023-09-16_final
2023-09-16 09:58:14	ga_ls8c_ard_3-2-1_096086_2023-09-16_final
2023-09-18 09:45:29	ga_ls8c_ard_3-2-1_094085_2023-09-18_final
2023-09-18 09:45:53	ga_ls8c_ard_3-2-1_094086_2023-09-18_final
2023-09-18 11:24:22	ga_ls8c_ard_3-2-1_110085_2023-09-18_final
2023-09-20 09:33:07	ga_ls8c_ard_3-2-1_092085_2023-09-20_final
2023-09-20 09:33:31	ga_ls8c_ard_3-2-1_092086_2023-09-20_final
2023-09-21 10:16:23	ga_ls8c_ard_3-2-1_099085_2023-09-21_final
2023-09-22 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-09-21_final
2023-09-22 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-09-21_final
2023-09-23 10:04:01	ga_ls8c_ard_3-2-1_097085_2023-09-23_final
2023-09-25 09:51:41	ga_ls8c_ard_3-2-1_095085_2023-09-25_final
2023-09-25 09:52:05	ga_ls8c_ard_3-2-1_095086_2023-09-25_final
2023-10-13 09:39:24	ga_ls8c_ard_3-2-1_093085_2023-10-13_final
2023-10-13 09:39:48	ga_ls8c_ard_3-2-1_093086_2023-10-13_final
2023-10-15 09:27:02	ga_ls8c_ard_3-2-1_091085_2023-10-14_final
2023-10-15 09:27:26	ga_ls8c_ard_3-2-1_091086_2023-10-14_final
2024-02-23 09:57:49	ga_ls8c_ard_3-2-1_096085_2024-02-23_final
2024-02-23 09:58:13	ga_ls8c_ard_3-2-1_096086_2024-02-23_final
2024-02-25 09:45:27	ga_ls8c_ard_3-2-1_094085_2024-02-25_final
2024-02-25 09:45:51	ga_ls8c_ard_3-2-1_094086_2024-02-25_final
2024-02-25 11:24:20	ga_ls8c_ard_3-2-1_110085_2024-02-25_final
2024-02-27 09:33:04	ga_ls8c_ard_3-2-1_092085_2024-02-27_final
2024-02-27 09:33:28	ga_ls8c_ard_3-2-1_092086_2024-02-27_final
2024-02-28 10:16:19	ga_ls8c_ard_3-2-1_099085_2024-02-28_final
2024-02-29 09:20:41	ga_ls8c_ard_3-2-1_090085_2024-02-28_final
2024-02-29 09:21:05	ga_ls8c_ard_3-2-1_090086_2024-02-28_final
2024-03-01 10:03:55	ga_ls8c_ard_3-2-1_097085_2024-03-01_final
2024-03-03 09:51:32	ga_ls8c_ard_3-2-1_095085_2024-03-03_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