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
2018-10-04 09:50:45	ga_ls8c_ard_3-0-0_096068_2018-10-04_final
2018-10-04 09:51:09	ga_ls8c_ard_3-0-0_096069_2018-10-04_final
2018-10-04 11:29:38	ga_ls8c_ard_3-0-0_112068_2018-10-04_final
2018-10-05 10:34:01	ga_ls8c_ard_3-0-0_103068_2018-10-05_final
2018-10-05 10:34:25	ga_ls8c_ard_3-0-0_103069_2018-10-05_final
2018-10-06 11:17:17	ga_ls8c_ard_3-0-0_110068_2018-10-06_final
2018-10-06 11:17:41	ga_ls8c_ard_3-0-0_110069_2018-10-06_final
2018-10-07 10:21:40	ga_ls8c_ard_3-0-0_101068_2018-10-07_final
2018-10-07 10:22:04	ga_ls8c_ard_3-0-0_101069_2018-10-07_final
2018-10-08 09:26:03	ga_ls8c_ard_3-0-0_092068_2018-10-07_final
2018-10-08 11:04:57	ga_ls8c_ard_3-0-0_108068_2018-10-08_final
2018-10-08 11:05:20	ga_ls8c_ard_3-0-0_108069_2018-10-08_final
2018-10-09 10:09:20	ga_ls8c_ard_3-0-0_099068_2018-10-09_final
2018-10-10 10:52:36	ga_ls8c_ard_3-0-0_106068_2018-10-10_final
2018-10-10 10:53:00	ga_ls8c_ard_3-0-0_106069_2018-10-10_final
2018-10-11 09:56:59	ga_ls8c_ard_3-0-0_097068_2018-10-11_final
2018-10-11 09:57:23	ga_ls8c_ard_3-0-0_097069_2018-10-11_final
2018-10-12 10:40:15	ga_ls8c_ard_3-0-0_104068_2018-10-12_final
2018-10-13 11:23:31	ga_ls8c_ard_3-0-0_111068_2018-10-13_final
2018-10-14 10:27:54	ga_ls8c_ard_3-0-0_102068_2018-10-14_final
2018-10-14 10:28:18	ga_ls8c_ard_3-0-0_102069_2018-10-14_final
2018-10-15 09:32:17	ga_ls8c_ard_3-0-0_093068_2018-10-15_final
2018-10-15 11:11:10	ga_ls8c_ard_3-0-0_109068_2018-10-15_final
2018-10-16 10:15:33	ga_ls8c_ard_3-0-0_100068_2018-10-16_final
2018-11-09 11:05:05	ga_ls8c_ard_3-0-0_108068_2018-11-09_final
2018-11-10 10:09:28	ga_ls8c_ard_3-0-0_099068_2018-11-10_final
2018-11-11 10:52:43	ga_ls8c_ard_3-0-0_106068_2018-11-11_final
2018-11-12 09:57:06	ga_ls8c_ard_3-0-0_097068_2018-11-12_final
2018-11-12 09:57:30	ga_ls8c_ard_3-0-0_097069_2018-11-12_final
2018-11-13 10:40:22	ga_ls8c_ard_3-0-0_104068_2018-11-13_final
2018-11-13 10:40:46	ga_ls8c_ard_3-0-0_104069_2018-11-13_final
2018-11-18 09:20:01	ga_ls8c_ard_3-0-0_091068_2018-11-17_final
2018-11-18 10:58:54	ga_ls8c_ard_3-0-0_107068_2018-11-18_final
2018-11-27 10:52:43	ga_ls8c_ard_3-0-0_106068_2018-11-27_final
2018-11-28 09:57:05	ga_ls8c_ard_3-0-0_097068_2018-11-28_final
2018-11-29 10:40:21	ga_ls8c_ard_3-0-0_104068_2018-11-29_final
2018-12-11 11:05:02	ga_ls8c_ard_3-0-0_108068_2018-12-11_final
2018-12-12 10:09:24	ga_ls8c_ard_3-0-0_099068_2018-12-12_final
2018-12-13 10:52:39	ga_ls8c_ard_3-0-0_106068_2018-12-13_final
2018-12-14 09:57:02	ga_ls8c_ard_3-0-0_097068_2018-12-14_final
2018-12-15 10:40:18	ga_ls8c_ard_3-0-0_104068_2018-12-15_final
2018-12-15 10:40:42	ga_ls8c_ard_3-0-0_104069_2018-12-15_final
2018-12-25 11:17:23	ga_ls8c_ard_3-0-0_110068_2018-12-25_final
2018-12-26 10:21:46	ga_ls8c_ard_3-0-0_101068_2018-12-26_final
2018-12-27 09:26:09	ga_ls8c_ard_3-0-0_092068_2018-12-26_final
2018-12-27 11:05:02	ga_ls8c_ard_3-0-0_108068_2018-12-27_final
2018-12-28 10:09:24	ga_ls8c_ard_3-0-0_099068_2018-12-28_final
2018-12-29 10:52:40	ga_ls8c_ard_3-0-0_106068_2018-12-29_final
2018-12-30 09:57:03	ga_ls8c_ard_3-0-0_097068_2018-12-30_final
2018-12-30 09:57:26	ga_ls8c_ard_3-0-0_097069_2018-12-30_final
2018-12-31 10:40:18	ga_ls8c_ard_3-0-0_104068_2018-12-31_final
2018-12-31 10:40:42	ga_ls8c_ard_3-0-0_104069_2018-12-31_final
2019-01-05 09:19:57	ga_ls8c_ard_3-0-0_091068_2019-01-04_final
2019-01-05 10:58:50	ga_ls8c_ard_3-0-0_107068_2019-01-05_final
2019-01-05 10:59:14	ga_ls8c_ard_3-0-0_107069_2019-01-05_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
2019-01-14 10:52:38	ga_ls8c_ard_3-0-0_106068_2019-01-14_final
2019-01-15 09:57:00	ga_ls8c_ard_3-0-0_097068_2019-01-15_final
2019-01-16 10:40:16	ga_ls8c_ard_3-0-0_104068_2019-01-16_final
2021-11-01 11:05:35	ga_ls8c_ard_3-2-0_108068_2021-11-01_final
2021-11-01 11:05:58	ga_ls8c_ard_3-2-0_108069_2021-11-01_final
2021-11-02 10:09:57	ga_ls8c_ard_3-2-0_099068_2021-11-02_final
2021-11-02 10:10:21	ga_ls8c_ard_3-2-0_099069_2021-11-02_final
2021-11-03 10:53:13	ga_ls8c_ard_3-2-0_106068_2021-11-03_final
2021-11-04 09:57:35	ga_ls8c_ard_3-2-0_097068_2021-11-04_final
2021-11-06 11:24:06	ga_ls8c_ard_3-2-0_111068_2021-11-06_final
2021-11-07 10:28:28	ga_ls8c_ard_3-2-0_102068_2021-11-07_final
2021-11-08 09:32:51	ga_ls8c_ard_3-2-0_093068_2021-11-08_final
2022-04-15 11:23:32	ga_ls8c_ard_3-2-1_111068_2022-04-15_final
2022-04-15 11:23:56	ga_ls8c_ard_3-2-1_111069_2022-04-15_final
2022-04-16 10:27:54	ga_ls8c_ard_3-2-1_102068_2022-04-16_final
2022-04-16 10:28:18	ga_ls8c_ard_3-2-1_102069_2022-04-16_final
2022-04-19 10:58:48	ga_ls8c_ard_3-2-1_107068_2022-04-19_final
2022-04-20 10:03:10	ga_ls8c_ard_3-2-1_098068_2022-04-20_final
2022-04-23 10:34:03	ga_ls8c_ard_3-2-1_103068_2022-04-23_final
2022-04-23 10:34:27	ga_ls8c_ard_3-2-1_103069_2022-04-23_final
2022-04-24 11:17:42	ga_ls8c_ard_3-2-1_110069_2022-04-24_final
2022-04-25 10:22:05	ga_ls8c_ard_3-2-1_101069_2022-04-25_final
2022-04-27 10:09:18	ga_ls8c_ard_3-2-1_099068_2022-04-27_final
2022-04-28 10:52:33	ga_ls8c_ard_3-2-1_106068_2022-04-28_final
2022-04-28 10:52:57	ga_ls8c_ard_3-2-1_106069_2022-04-28_final
2022-04-29 09:56:55	ga_ls8c_ard_3-2-1_097068_2022-04-29_final
2022-04-29 09:57:19	ga_ls8c_ard_3-2-1_097069_2022-04-29_final
2022-05-09 10:34:08	ga_ls8c_ard_3-2-1_103068_2022-05-09_final
2022-05-09 10:34:32	ga_ls8c_ard_3-2-1_103069_2022-05-09_final
2022-05-11 10:22:11	ga_ls8c_ard_3-2-1_101069_2022-05-11_final
2022-05-14 10:52:43	ga_ls8c_ard_3-2-1_106068_2022-05-14_final
2022-05-14 10:53:07	ga_ls8c_ard_3-2-1_106069_2022-05-14_final
2022-07-26 10:46:58	ga_ls8c_ard_3-2-1_105068_2022-07-26_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
2022-08-01 10:09:57	ga_ls8c_ard_3-2-1_099068_2022-08-01_final
2022-08-02 10:53:13	ga_ls8c_ard_3-2-1_106068_2022-08-02_final
2022-08-02 10:53:37	ga_ls8c_ard_3-2-1_106069_2022-08-02_final
2022-08-04 10:40:53	ga_ls8c_ard_3-2-1_104068_2022-08-04_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