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
2018-06-12 10:02:12	ga_ls8c_ard_3-0-0_098068_2018-06-12_final
2018-06-12 10:02:36	ga_ls8c_ard_3-0-0_098069_2018-06-12_final
2018-06-13 10:45:28	ga_ls8c_ard_3-0-0_105068_2018-06-13_final
2018-06-13 10:45:52	ga_ls8c_ard_3-0-0_105069_2018-06-13_final
2018-06-18 11:04:04	ga_ls8c_ard_3-0-0_108068_2018-06-18_final
2018-06-18 11:04:28	ga_ls8c_ard_3-0-0_108069_2018-06-18_final
2018-06-19 10:08:28	ga_ls8c_ard_3-0-0_099068_2018-06-19_final
2018-06-19 10:08:52	ga_ls8c_ard_3-0-0_099069_2018-06-19_final
2018-06-28 10:02:22	ga_ls8c_ard_3-0-0_098068_2018-06-28_final
2018-06-28 10:02:46	ga_ls8c_ard_3-0-0_098069_2018-06-28_final
2018-06-29 10:45:39	ga_ls8c_ard_3-0-0_105068_2018-06-29_final
2018-06-29 10:46:03	ga_ls8c_ard_3-0-0_105069_2018-06-29_final
2018-07-02 11:16:35	ga_ls8c_ard_3-0-0_110068_2018-07-02_final
2018-07-02 11:16:58	ga_ls8c_ard_3-0-0_110069_2018-07-02_final
2018-07-03 10:20:58	ga_ls8c_ard_3-0-0_101068_2018-07-03_final
2018-07-03 10:21:22	ga_ls8c_ard_3-0-0_101069_2018-07-03_final
2018-07-04 09:25:21	ga_ls8c_ard_3-0-0_092068_2018-07-03_final
2018-07-04 11:04:14	ga_ls8c_ard_3-0-0_108068_2018-07-04_final
2018-07-04 11:04:38	ga_ls8c_ard_3-0-0_108069_2018-07-04_final
2018-07-05 10:08:37	ga_ls8c_ard_3-0-0_099068_2018-07-05_final
2018-07-05 10:09:01	ga_ls8c_ard_3-0-0_099069_2018-07-05_final
2018-07-22 10:52:00	ga_ls8c_ard_3-0-0_106068_2018-07-22_final
2018-07-22 10:52:24	ga_ls8c_ard_3-0-0_106069_2018-07-22_final
2018-07-23 09:56:23	ga_ls8c_ard_3-1-0_097068_2018-07-23_final
2018-07-23 09:56:47	ga_ls8c_ard_3-0-0_097069_2018-07-23_final
2018-07-24 10:39:39	ga_ls8c_ard_3-0-0_104068_2018-07-24_final
2018-07-24 10:40:03	ga_ls8c_ard_3-0-0_104069_2018-07-24_final
2018-07-30 10:02:37	ga_ls8c_ard_3-0-0_098068_2018-07-30_final
2018-07-31 10:45:54	ga_ls8c_ard_3-0-0_105068_2018-07-31_final
2018-07-31 10:46:18	ga_ls8c_ard_3-0-0_105069_2018-07-31_final
2018-08-05 11:04:29	ga_ls8c_ard_3-0-0_108068_2018-08-05_final
2018-08-05 11:04:53	ga_ls8c_ard_3-0-0_108069_2018-08-05_final
2018-08-06 10:08:52	ga_ls8c_ard_3-0-0_099068_2018-08-06_final
2018-08-06 10:09:16	ga_ls8c_ard_3-0-0_099069_2018-08-06_final
2018-08-10 11:23:05	ga_ls8c_ard_3-0-0_111068_2018-08-10_final
2018-08-10 11:23:29	ga_ls8c_ard_3-0-0_111069_2018-08-10_final
2018-08-11 10:27:28	ga_ls8c_ard_3-0-0_102068_2018-08-11_final
2018-08-11 10:27:52	ga_ls8c_ard_3-0-0_102069_2018-08-11_final
2018-08-12 09:31:51	ga_ls8c_ard_3-0-0_093068_2018-08-12_final
2018-08-12 11:10:44	ga_ls8c_ard_3-0-0_109068_2018-08-12_final
2018-08-12 11:11:08	ga_ls8c_ard_3-0-0_109069_2018-08-12_final
2018-08-13 10:15:07	ga_ls8c_ard_3-0-0_100068_2018-08-13_final
2018-08-13 10:15:31	ga_ls8c_ard_3-0-0_100069_2018-08-13_final
2018-08-15 10:02:47	ga_ls8c_ard_3-0-0_098068_2018-08-15_final
2018-08-15 10:03:11	ga_ls8c_ard_3-0-0_098069_2018-08-15_final
2018-08-16 10:46:03	ga_ls8c_ard_3-0-0_105068_2018-08-16_final
2018-08-31 10:02:54	ga_ls8c_ard_3-0-0_098068_2018-08-31_final
2018-08-31 10:03:18	ga_ls8c_ard_3-0-0_098069_2018-08-31_final
2018-09-01 10:46:10	ga_ls8c_ard_3-0-0_105068_2018-09-01_final
2018-09-01 10:46:34	ga_ls8c_ard_3-0-0_105069_2018-09-01_final
2018-09-02 09:50:33	ga_ls8c_ard_3-0-0_096068_2018-09-02_final
2018-09-02 11:29:26	ga_ls8c_ard_3-0-0_112068_2018-09-02_final
2018-09-02 11:29:50	ga_ls8c_ard_3-0-0_112069_2018-09-02_final
2018-09-03 10:33:49	ga_ls8c_ard_3-0-0_103068_2018-09-03_final
2018-09-03 10:34:13	ga_ls8c_ard_3-0-0_103069_2018-09-03_final
2018-09-04 11:17:05	ga_ls8c_ard_3-0-0_110068_2018-09-04_final
2018-09-04 11:17:29	ga_ls8c_ard_3-0-0_110069_2018-09-04_final
2018-09-05 10:21:28	ga_ls8c_ard_3-0-0_101068_2018-09-05_final
2018-09-06 09:25:51	ga_ls8c_ard_3-0-0_092068_2018-09-05_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_2018-09-16_final
2018-09-16 10:03:22	ga_ls8c_ard_3-0-0_098069_2018-09-16_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2019-01-06 10:03:13	ga_ls8c_ard_3-0-0_098068_2019-01-06_final
2019-01-07 10:46:28	ga_ls8c_ard_3-0-0_105068_2019-01-07_final
2022-08-19 09:57:42	ga_ls8c_ard_3-2-1_097068_2022-08-19_final
2022-08-19 09:58:06	ga_ls8c_ard_3-2-1_097069_2022-08-19_final
2022-08-21 11:24:14	ga_ls8c_ard_3-2-1_111068_2022-08-21_final
2022-08-21 11:24:38	ga_ls8c_ard_3-2-1_111069_2022-08-21_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-09-23 10:28:43	ga_ls8c_ard_3-2-1_102068_2022-09-23_final
2022-09-23 10:29:07	ga_ls8c_ard_3-2-1_102069_2022-09-23_final
2022-09-26 10:59:37	ga_ls8c_ard_3-2-1_107068_2022-09-26_final
2022-09-27 10:04:00	ga_ls8c_ard_3-2-1_098068_2022-09-27_final
2022-09-28 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-09-28_final
2022-09-28 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-09-28_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-04 10:10:33	ga_ls8c_ard_3-2-1_099069_2022-10-04_final
2022-10-05 10:53:24	ga_ls8c_ard_3-2-1_106068_2022-10-05_final
2022-10-06 09:57:46	ga_ls8c_ard_3-2-1_097068_2022-10-06_final
2022-10-06 09:58:10	ga_ls8c_ard_3-2-1_097069_2022-10-06_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-07 10:41:25	ga_ls8c_ard_3-2-1_104069_2022-10-07_final
2022-10-08 11:24:16	ga_ls8c_ard_3-2-1_111068_2022-10-08_final
2022-10-08 11:24:40	ga_ls8c_ard_3-2-1_111069_2022-10-08_final
2022-10-09 10:28:38	ga_ls8c_ard_3-2-1_102068_2022-10-09_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-21 10:53:22	ga_ls8c_ard_3-2-1_106068_2022-10-21_final
2022-10-22 09:57:45	ga_ls8c_ard_3-2-1_097068_2022-10-22_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2023-06-16 11:05:01	ga_ls8c_ard_3-2-1_108069_2023-06-16_final
2023-06-17 10:09:00	ga_ls8c_ard_3-2-1_099068_2023-06-17_final
2023-06-17 10:09:24	ga_ls8c_ard_3-2-1_099069_2023-06-17_final
2023-06-19 09:56:38	ga_ls8c_ard_3-2-1_097068_2023-06-19_final
2023-06-19 09:57:02	ga_ls8c_ard_3-2-1_097069_2023-06-19_final
2023-07-07 11:23:22	ga_ls8c_ard_3-2-1_111068_2023-07-07_final
2023-07-07 11:23:46	ga_ls8c_ard_3-2-1_111069_2023-07-07_final
2023-07-08 10:27:45	ga_ls8c_ard_3-2-1_102068_2023-07-08_final
2023-07-08 10:28:09	ga_ls8c_ard_3-2-1_102069_2023-07-08_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