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
2018-09-16 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
2019-01-06 10:03:37	ga_ls8c_ard_3-0-0_098069_2019-01-06_final
2019-01-07 10:46:28	ga_ls8c_ard_3-0-0_105068_2019-01-07_final
2019-01-07 10:46:52	ga_ls8c_ard_3-0-0_105069_2019-01-07_final
2019-08-13 11:23:49	ga_ls8c_ard_3-1-0_111068_2019-08-13_final
2019-08-13 11:24:13	ga_ls8c_ard_3-1-0_111069_2019-08-13_final
2019-08-14 10:28:12	ga_ls8c_ard_3-1-0_102068_2019-08-14_final
2019-08-14 10:28:36	ga_ls8c_ard_3-1-0_102069_2019-08-14_final
2019-08-15 09:32:35	ga_ls8c_ard_3-1-0_093068_2019-08-15_final
2019-08-15 11:11:28	ga_ls8c_ard_3-1-0_109068_2019-08-15_final
2019-08-15 11:11:52	ga_ls8c_ard_3-1-0_109069_2019-08-15_final
2019-08-16 10:15:51	ga_ls8c_ard_3-1-0_100068_2019-08-16_final
2019-08-16 10:16:15	ga_ls8c_ard_3-1-0_100069_2019-08-16_final
2019-08-17 09:20:14	ga_ls8c_ard_3-1-0_091068_2019-08-16_final
2019-10-02 11:11:41	ga_ls8c_ard_3-1-0_109068_2019-10-02_final
2019-10-02 11:12:05	ga_ls8c_ard_3-1-0_109069_2019-10-02_final
2019-10-03 10:16:04	ga_ls8c_ard_3-1-0_100068_2019-10-03_final
2019-10-03 10:16:28	ga_ls8c_ard_3-1-0_100069_2019-10-03_final
2019-10-04 09:20:27	ga_ls8c_ard_3-1-0_091068_2019-10-03_final
2022-06-15 10:52:58	ga_ls8c_ard_3-2-1_106068_2022-06-15_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-16 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-06-16_final
2022-06-16 09:57:45	ga_ls8c_ard_3-2-1_097069_2022-06-16_final
2022-06-17 10:40:37	ga_ls8c_ard_3-2-1_104068_2022-06-17_final
2022-06-17 10:41:01	ga_ls8c_ard_3-2-1_104069_2022-06-17_final
2022-07-15 11:05:46	ga_ls8c_ard_3-2-1_108069_2022-07-15_final
2022-07-16 10:09:45	ga_ls8c_ard_3-2-1_099068_2022-07-16_final
2022-07-16 10:10:09	ga_ls8c_ard_3-2-1_099069_2022-07-16_final
2022-07-17 10:53:02	ga_ls8c_ard_3-2-1_106068_2022-07-17_final
2022-07-17 10:53:25	ga_ls8c_ard_3-2-1_106069_2022-07-17_final
2022-07-18 09:57:25	ga_ls8c_ard_3-2-1_097068_2022-07-18_final
2022-07-18 09:57:49	ga_ls8c_ard_3-2-1_097069_2022-07-18_final
2022-07-19 10:40:42	ga_ls8c_ard_3-2-1_104068_2022-07-19_final
2022-07-19 10:41:06	ga_ls8c_ard_3-2-1_104069_2022-07-19_final
2022-07-20 11:23:58	ga_ls8c_ard_3-2-1_111068_2022-07-20_final
2022-07-20 11:24:22	ga_ls8c_ard_3-2-1_111069_2022-07-20_final
2022-07-21 10:28:22	ga_ls8c_ard_3-2-1_102068_2022-07-21_final
2022-07-21 10:28:46	ga_ls8c_ard_3-2-1_102069_2022-07-21_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-24 10:59:18	ga_ls8c_ard_3-2-1_107068_2022-07-24_final
2022-07-24 10:59:42	ga_ls8c_ard_3-2-1_107069_2022-07-24_final
2022-07-25 10:03:42	ga_ls8c_ard_3-2-1_098068_2022-07-25_final
2022-07-25 10:04:06	ga_ls8c_ard_3-2-1_098069_2022-07-25_final
2022-07-28 10:34:38	ga_ls8c_ard_3-2-1_103068_2022-07-28_final
2022-07-28 10:35:02	ga_ls8c_ard_3-2-1_103069_2022-07-28_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-07-30 10:22:41	ga_ls8c_ard_3-2-1_101069_2022-07-30_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-13 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-08-13_final
2022-08-29 10:34:47	ga_ls8c_ard_3-2-1_103068_2022-08-29_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-08-30 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-08-30_final
2022-08-31 10:22:49	ga_ls8c_ard_3-2-1_101069_2022-08-31_final
2022-09-01 11:06:05	ga_ls8c_ard_3-2-1_108069_2022-09-01_final
2022-09-02 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-09-02_final
2022-09-02 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-09-02_final
2023-01-24 10:09:53	ga_ls8c_ard_3-2-1_099068_2023-01-24_final
2023-01-24 10:10:17	ga_ls8c_ard_3-2-1_099069_2023-01-24_final
2023-01-25 10:53:09	ga_ls8c_ard_3-2-1_106068_2023-01-25_final
2023-01-25 10:53:33	ga_ls8c_ard_3-2-1_106069_2023-01-25_final
2023-01-26 09:57:32	ga_ls8c_ard_3-2-1_097068_2023-01-26_final
2023-01-26 09:57:56	ga_ls8c_ard_3-2-1_097069_2023-01-26_final
2023-05-02 09:57:02	ga_ls8c_ard_3-2-1_097069_2023-05-02_final
2023-05-03 10:39:53	ga_ls8c_ard_3-2-1_104068_2023-05-03_final
2023-05-03 10:40:17	ga_ls8c_ard_3-2-1_104069_2023-05-03_final
2023-05-10 10:45:57	ga_ls8c_ard_3-2-1_105068_2023-05-10_final
2023-05-10 10:46:21	ga_ls8c_ard_3-2-1_105069_2023-05-10_final
2023-05-12 10:33:33	ga_ls8c_ard_3-2-1_103068_2023-05-12_final
2023-05-12 10:33:57	ga_ls8c_ard_3-2-1_103069_2023-05-12_final
2023-05-14 10:21:34	ga_ls8c_ard_3-2-1_101069_2023-05-14_final
2023-05-15 11:04:49	ga_ls8c_ard_3-2-1_108069_2023-05-15_final
2023-05-16 10:08:48	ga_ls8c_ard_3-2-1_099068_2023-05-16_final
2023-05-16 10:09:12	ga_ls8c_ard_3-2-1_099069_2023-05-16_final
2023-05-17 10:52:03	ga_ls8c_ard_3-2-1_106068_2023-05-17_final
2023-05-17 10:52:27	ga_ls8c_ard_3-2-1_106069_2023-05-17_final
2023-05-18 09:56:25	ga_ls8c_ard_3-2-1_097068_2023-05-18_final
2023-05-18 09:56:49	ga_ls8c_ard_3-2-1_097069_2023-05-18_final
2023-05-19 10:39:42	ga_ls8c_ard_3-2-1_104068_2023-05-19_final
2023-05-19 10:40:06	ga_ls8c_ard_3-2-1_104069_2023-05-19_final
2023-05-20 11:22:58	ga_ls8c_ard_3-2-1_111068_2023-05-20_final
2023-05-20 11:23:22	ga_ls8c_ard_3-2-1_111069_2023-05-20_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_final
2023-05-21 10:27:45	ga_ls8c_ard_3-2-1_102069_2023-05-21_final
2023-05-22 11:11:01	ga_ls8c_ard_3-2-1_109069_2023-05-22_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
2023-06-07 11:11:07	ga_ls8c_ard_3-2-1_109069_2023-06-07_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
2023-06-11 10:46:26	ga_ls8c_ard_3-2-1_105069_2023-06-11_final
2023-06-13 10:33:42	ga_ls8c_ard_3-2-1_103068_2023-06-13_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