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
2018-05-26 09:18:58	ga_ls8c_ard_3-0-0_091068_2018-05-25_final
2018-05-26 10:57:50	ga_ls8c_ard_3-0-0_107068_2018-05-26_final
2018-06-04 10:51:34	ga_ls8c_ard_3-0-0_106068_2018-06-04_final
2018-06-04 10:51:58	ga_ls8c_ard_3-0-0_106069_2018-06-04_final
2018-06-05 09:55:57	ga_ls8c_ard_3-0-0_097068_2018-06-05_final
2018-06-05 09:56:21	ga_ls8c_ard_3-0-0_097069_2018-06-05_final
2018-06-06 10:39:12	ga_ls8c_ard_3-0-0_104068_2018-06-06_final
2018-06-06 10:39:36	ga_ls8c_ard_3-0-0_104069_2018-06-06_final
2018-06-27 09:19:06	ga_ls8c_ard_3-0-0_091068_2018-06-26_final
2018-06-27 10:57:59	ga_ls8c_ard_3-0-0_107068_2018-06-27_final
2018-06-27 10:58:23	ga_ls8c_ard_3-0-0_107069_2018-06-27_final
2018-07-29 09:19:21	ga_ls8c_ard_3-0-0_091068_2018-07-28_final
2018-07-29 10:58:14	ga_ls8c_ard_3-0-0_107068_2018-07-29_final
2018-07-29 10:58:38	ga_ls8c_ard_3-0-0_107069_2018-07-29_final
2018-09-06 11:04:44	ga_ls8c_ard_3-0-0_108068_2018-09-06_final
2018-09-07 10:09:07	ga_ls8c_ard_3-0-0_099068_2018-09-07_final
2018-09-07 10:09:31	ga_ls8c_ard_3-0-0_099069_2018-09-07_final
2018-09-08 10:52:23	ga_ls8c_ard_3-0-0_106068_2018-09-08_final
2018-09-08 10:52:47	ga_ls8c_ard_3-0-0_106069_2018-09-08_final
2018-09-09 09:56:46	ga_ls8c_ard_3-0-0_097068_2018-09-09_final
2018-09-09 09:57:10	ga_ls8c_ard_3-0-0_097069_2018-09-09_final
2018-09-10 10:40:02	ga_ls8c_ard_3-0-0_104068_2018-09-10_final
2018-09-10 10:40:26	ga_ls8c_ard_3-0-0_104069_2018-09-10_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
2018-10-20 09:50:51	ga_ls8c_ard_3-0-0_096068_2018-10-20_final
2018-10-20 11:29:44	ga_ls8c_ard_3-0-0_112068_2018-10-20_final
2018-10-20 11:30:08	ga_ls8c_ard_3-0-0_112069_2018-10-20_final
2018-10-21 10:34:07	ga_ls8c_ard_3-0-0_103068_2018-10-21_final
2018-10-22 11:17:23	ga_ls8c_ard_3-0-0_110068_2018-10-22_final
2018-10-23 10:21:46	ga_ls8c_ard_3-0-0_101068_2018-10-23_final
2018-10-23 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-10-23_final
2018-10-24 09:26:09	ga_ls8c_ard_3-0-0_092068_2018-10-23_final
2018-11-05 09:50:55	ga_ls8c_ard_3-0-0_096068_2018-11-05_final
2018-11-05 09:51:19	ga_ls8c_ard_3-0-0_096069_2018-11-05_final
2018-11-05 11:29:48	ga_ls8c_ard_3-0-0_112068_2018-11-05_final
2018-11-05 11:30:12	ga_ls8c_ard_3-0-0_112069_2018-11-05_final
2018-11-06 10:34:11	ga_ls8c_ard_3-0-0_103068_2018-11-06_final
2018-11-06 10:34:34	ga_ls8c_ard_3-0-0_103069_2018-11-06_final
2018-11-07 11:17:26	ga_ls8c_ard_3-0-0_110068_2018-11-07_final
2018-11-08 10:21:49	ga_ls8c_ard_3-0-0_101068_2018-11-08_final
2018-11-08 10:22:13	ga_ls8c_ard_3-0-0_101069_2018-11-08_final
2018-11-09 09:26:12	ga_ls8c_ard_3-0-0_092068_2018-11-08_final
2018-12-23 09:50:52	ga_ls8c_ard_3-0-0_096068_2018-12-23_final
2018-12-23 11:29:45	ga_ls8c_ard_3-0-0_112068_2018-12-23_final
2018-12-24 10:34:08	ga_ls8c_ard_3-0-0_103068_2018-12-24_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
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
2023-07-18 11:05:15	ga_ls8c_ard_3-2-1_108069_2023-07-18_final
2023-07-19 10:09:14	ga_ls8c_ard_3-2-1_099068_2023-07-19_final
2023-07-19 10:09:38	ga_ls8c_ard_3-2-1_099069_2023-07-19_final
2023-07-20 10:52:29	ga_ls8c_ard_3-2-1_106068_2023-07-20_final
2023-07-20 10:52:53	ga_ls8c_ard_3-2-1_106069_2023-07-20_final
2023-07-21 09:56:52	ga_ls8c_ard_3-2-1_097068_2023-07-21_final
2023-07-21 09:57:16	ga_ls8c_ard_3-2-1_097069_2023-07-21_final
2023-07-23 11:23:26	ga_ls8c_ard_3-2-1_111068_2023-07-23_final
2023-07-24 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-07-24_final
2023-07-27 10:58:46	ga_ls8c_ard_3-2-1_107068_2023-07-27_final
2023-07-29 10:46:25	ga_ls8c_ard_3-2-1_105068_2023-07-29_final
2023-07-31 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-07-31_final
2023-07-31 10:34:29	ga_ls8c_ard_3-2-1_103069_2023-07-31_final
2023-08-02 10:22:08	ga_ls8c_ard_3-2-1_101069_2023-08-02_final
2023-08-05 10:52:39	ga_ls8c_ard_3-2-1_106068_2023-08-05_final
2023-08-05 10:53:03	ga_ls8c_ard_3-2-1_106069_2023-08-05_final
2023-08-06 09:57:02	ga_ls8c_ard_3-2-1_097068_2023-08-06_final
2023-08-18 10:22:14	ga_ls8c_ard_3-2-1_101069_2023-08-18_final
2023-08-20 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-08-20_final
2023-08-28 10:58:58	ga_ls8c_ard_3-2-1_107068_2023-08-28_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_final
2023-09-08 10:40:24	ga_ls8c_ard_3-2-1_104068_2023-09-08_final
2023-09-09 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-09-09_final
2023-09-09 11:24:05	ga_ls8c_ard_3-2-1_111069_2023-09-09_final
2023-09-10 10:28:05	ga_ls8c_ard_3-2-1_102068_2023-09-10_final
2023-09-11 11:11:45	ga_ls8c_ard_3-2-1_109069_2023-09-11_final
2023-09-15 10:46:40	ga_ls8c_ard_3-2-1_105068_2023-09-15_final
2023-09-15 10:47:04	ga_ls8c_ard_3-2-1_105069_2023-09-15_final
2023-09-17 10:34:19	ga_ls8c_ard_3-2-1_103068_2023-09-17_final
2023-09-17 10:34:43	ga_ls8c_ard_3-2-1_103069_2023-09-17_final
2023-09-18 11:17:59	ga_ls8c_ard_3-2-1_110069_2023-09-18_final
2023-09-21 10:09:36	ga_ls8c_ard_3-2-1_099068_2023-09-21_final
2023-09-22 10:52:51	ga_ls8c_ard_3-2-1_106068_2023-09-22_final
2023-09-22 10:53:15	ga_ls8c_ard_3-2-1_106069_2023-09-22_final
2023-09-23 09:57:14	ga_ls8c_ard_3-2-1_097068_2023-09-23_final
2023-09-24 10:40:31	ga_ls8c_ard_3-2-1_104068_2023-09-24_final
2023-09-24 10:40:55	ga_ls8c_ard_3-2-1_104069_2023-09-24_final
2023-09-25 11:23:47	ga_ls8c_ard_3-2-1_111068_2023-09-25_final
2023-09-26 10:28:10	ga_ls8c_ard_3-2-1_102068_2023-09-26_final
2023-09-29 10:59:05	ga_ls8c_ard_3-2-1_107068_2023-09-29_final
2023-09-29 10:59:29	ga_ls8c_ard_3-2-1_107069_2023-09-29_final
2023-09-30 10:03:28	ga_ls8c_ard_3-2-1_098068_2023-09-30_final
2023-10-01 10:46:44	ga_ls8c_ard_3-2-1_105068_2023-10-01_final
2023-10-12 10:28:14	ga_ls8c_ard_3-2-1_102068_2023-10-12_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