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
2018-06-14 09:49:52	ga_ls8c_ard_3-0-0_096068_2018-06-14_final
2018-06-14 11:28:45	ga_ls8c_ard_3-0-0_112068_2018-06-14_final
2018-06-14 11:29:09	ga_ls8c_ard_3-0-0_112069_2018-06-14_final
2018-06-15 10:33:08	ga_ls8c_ard_3-0-0_103068_2018-06-15_final
2018-06-16 11:16:25	ga_ls8c_ard_3-0-0_110068_2018-06-16_final
2018-06-16 11:16:49	ga_ls8c_ard_3-0-0_110069_2018-06-16_final
2018-06-17 10:20:48	ga_ls8c_ard_3-0-0_101068_2018-06-17_final
2018-06-17 10:21:12	ga_ls8c_ard_3-0-0_101069_2018-06-17_final
2018-06-18 09:25:11	ga_ls8c_ard_3-0-0_092068_2018-06-17_final
2018-06-30 09:50:02	ga_ls8c_ard_3-0-0_096068_2018-06-30_final
2018-06-30 09:50:26	ga_ls8c_ard_3-0-0_096069_2018-06-30_final
2018-06-30 11:28:55	ga_ls8c_ard_3-0-0_112068_2018-06-30_final
2018-06-30 11:29:19	ga_ls8c_ard_3-0-0_112069_2018-06-30_final
2018-07-01 10:33:18	ga_ls8c_ard_3-0-0_103068_2018-07-01_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
2018-08-17 09:50:26	ga_ls8c_ard_3-0-0_096068_2018-08-17_final
2018-08-17 09:50:50	ga_ls8c_ard_3-0-0_096069_2018-08-17_final
2018-08-17 11:29:19	ga_ls8c_ard_3-0-0_112068_2018-08-17_final
2018-08-18 10:33:42	ga_ls8c_ard_3-0-0_103068_2018-08-18_final
2018-08-18 10:34:06	ga_ls8c_ard_3-0-0_103069_2018-08-18_final
2018-08-19 11:16:58	ga_ls8c_ard_3-0-0_110068_2018-08-19_final
2018-08-20 10:21:22	ga_ls8c_ard_3-0-0_101068_2018-08-20_final
2018-08-21 09:25:45	ga_ls8c_ard_3-0-0_092068_2018-08-20_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
2022-08-21 11:24:14	ga_ls8c_ard_3-2-1_111068_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
2022-10-05 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
2022-10-07 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
2022-10-12 10:59:29	ga_ls8c_ard_3-2-1_107068_2022-10-12_final
2022-10-12 10:59:53	ga_ls8c_ard_3-2-1_107069_2022-10-12_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-16 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-10-16_final
2022-10-17 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-10-17_final
2022-10-20 10:10:06	ga_ls8c_ard_3-2-1_099068_2022-10-20_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
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-07 09:57:48	ga_ls8c_ard_3-2-1_097068_2022-11-07_final
2022-11-07 09:58:12	ga_ls8c_ard_3-2-1_097069_2022-11-07_final
2022-11-08 10:41:03	ga_ls8c_ard_3-2-1_104068_2022-11-08_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-08 10:09:56	ga_ls8c_ard_3-2-1_099068_2023-01-08_final
2023-01-09 10:53:11	ga_ls8c_ard_3-2-1_106068_2023-01-09_final
2023-01-10 09:57:33	ga_ls8c_ard_3-2-1_097068_2023-01-10_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-12 11:24:03	ga_ls8c_ard_3-2-1_111068_2023-01-12_final
2023-01-16 10:59:16	ga_ls8c_ard_3-2-1_107068_2023-01-16_final
2023-01-17 10:03:38	ga_ls8c_ard_3-2-1_098068_2023-01-17_final
2023-01-18 10:46:53	ga_ls8c_ard_3-2-1_105068_2023-01-18_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-24 10:09:53	ga_ls8c_ard_3-2-1_099068_2023-01-24_final
2023-01-25 10:53:09	ga_ls8c_ard_3-2-1_106068_2023-01-25_final
2023-01-29 10:28:27	ga_ls8c_ard_3-2-1_102068_2023-01-29_final
2023-02-03 10:46:59	ga_ls8c_ard_3-2-1_105068_2023-02-03_final
2023-02-05 10:34:37	ga_ls8c_ard_3-2-1_103068_2023-02-05_final
2023-02-10 10:53:07	ga_ls8c_ard_3-2-1_106068_2023-02-10_final
2023-02-17 10:59:12	ga_ls8c_ard_3-2-1_107068_2023-02-17_final
2023-02-21 10:34:24	ga_ls8c_ard_3-2-1_103068_2023-02-21_final
2023-02-26 10:52:51	ga_ls8c_ard_3-2-1_106068_2023-02-26_final
2023-02-27 09:57:14	ga_ls8c_ard_3-2-1_097068_2023-02-27_final
2023-04-06 10:58:39	ga_ls8c_ard_3-2-1_107068_2023-04-06_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-08 10:46:15	ga_ls8c_ard_3-2-1_105068_2023-04-08_final
2023-04-10 10:33:50	ga_ls8c_ard_3-2-1_103068_2023-04-10_final
2023-04-14 10:09:05	ga_ls8c_ard_3-2-1_099068_2023-04-14_final
2023-04-15 10:52:20	ga_ls8c_ard_3-2-1_106068_2023-04-15_final
2023-06-04 10:39:46	ga_ls8c_ard_3-2-1_104068_2023-06-04_final
2023-06-04 10:40:10	ga_ls8c_ard_3-2-1_104069_2023-06-04_final
2023-06-05 11:23:03	ga_ls8c_ard_3-2-1_111068_2023-06-05_final
2023-06-05 11:23:27	ga_ls8c_ard_3-2-1_111069_2023-06-05_final
2023-06-06 10:27:26	ga_ls8c_ard_3-2-1_102068_2023-06-06_final
2023-06-06 10:27:50	ga_ls8c_ard_3-2-1_102069_2023-06-06_final
2023-06-09 10:58:23	ga_ls8c_ard_3-2-1_107068_2023-06-09_final
2023-06-09 10:58:47	ga_ls8c_ard_3-2-1_107069_2023-06-09_final
2023-06-10 10:02:46	ga_ls8c_ard_3-2-1_098068_2023-06-10_final
2023-06-10 10:03:10	ga_ls8c_ard_3-2-1_098069_2023-06-10_final
2023-06-11 10:46:02	ga_ls8c_ard_3-2-1_105068_2023-06-11_final
2023-06-13 10:33:42	ga_ls8c_ard_3-2-1_103068_2023-06-13_final
2023-06-13 10:34:06	ga_ls8c_ard_3-2-1_103069_2023-06-13_final
2023-07-22 10:40:09	ga_ls8c_ard_3-2-1_104068_2023-07-22_final
2023-07-22 10:40:33	ga_ls8c_ard_3-2-1_104069_2023-07-22_final
2023-07-23 11:23:26	ga_ls8c_ard_3-2-1_111068_2023-07-23_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