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
2018-01-30 09:44:19	ga_ls8c_ard_3-0-0_095067_2018-01-30_final
2018-01-30 11:23:12	ga_ls8c_ard_3-0-0_111067_2018-01-30_final
2018-01-31 10:27:34	ga_ls8c_ard_3-0-0_102067_2018-01-31_final
2018-01-31 10:27:58	ga_ls8c_ard_3-1-0_102068_2018-01-31_final
2018-02-01 09:31:56	ga_ls8c_ard_3-0-0_093067_2018-02-01_final
2018-02-01 11:10:49	ga_ls8c_ard_3-0-0_109067_2018-02-01_final
2018-02-02 10:15:11	ga_ls8c_ard_3-0-0_100067_2018-02-02_final
2018-02-15 09:44:13	ga_ls8c_ard_3-0-0_095067_2018-02-15_final
2018-02-15 11:23:06	ga_ls8c_ard_3-0-0_111067_2018-02-15_final
2018-02-16 10:27:28	ga_ls8c_ard_3-0-0_102067_2018-02-16_final
2018-02-16 10:27:52	ga_ls8c_ard_3-1-0_102068_2018-02-16_final
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-17 11:10:44	ga_ls8c_ard_3-0-0_109067_2018-02-17_final
2018-02-18 10:15:06	ga_ls8c_ard_3-0-0_100067_2018-02-18_final
2018-02-22 09:50:21	ga_ls8c_ard_3-0-0_096067_2018-02-22_final
2018-02-22 11:29:14	ga_ls8c_ard_3-0-0_112067_2018-02-22_final
2018-02-23 10:33:36	ga_ls8c_ard_3-0-0_103067_2018-02-23_final
2018-02-24 09:37:58	ga_ls8c_ard_3-0-0_094067_2018-02-24_final
2018-02-24 11:16:51	ga_ls8c_ard_3-0-0_110067_2018-02-24_final
2018-02-25 10:21:14	ga_ls8c_ard_3-0-0_101067_2018-02-25_final
2018-02-26 09:25:36	ga_ls8c_ard_3-0-0_092067_2018-02-25_final
2018-03-03 09:44:06	ga_ls8c_ard_3-0-0_095067_2018-03-03_final
2018-03-03 11:22:59	ga_ls8c_ard_3-0-0_111067_2018-03-03_final
2018-03-04 10:27:21	ga_ls8c_ard_3-0-0_102067_2018-03-04_final
2018-03-04 10:27:45	ga_ls8c_ard_3-0-0_102068_2018-03-04_final
2018-03-05 09:31:43	ga_ls8c_ard_3-0-0_093067_2018-03-05_final
2018-03-05 11:10:36	ga_ls8c_ard_3-0-0_109067_2018-03-05_final
2018-03-06 10:14:58	ga_ls8c_ard_3-0-0_100067_2018-03-06_final
2018-03-19 09:43:57	ga_ls8c_ard_3-0-0_095067_2018-03-19_final
2018-03-19 11:22:50	ga_ls8c_ard_3-0-0_111067_2018-03-19_final
2018-03-20 10:27:12	ga_ls8c_ard_3-0-0_102067_2018-03-20_final
2018-03-20 10:27:36	ga_ls8c_ard_3-0-0_102068_2018-03-20_final
2018-03-21 09:31:35	ga_ls8c_ard_3-0-0_093067_2018-03-21_final
2018-03-21 11:10:28	ga_ls8c_ard_3-0-0_109067_2018-03-21_final
2018-03-22 10:14:50	ga_ls8c_ard_3-0-0_100067_2018-03-22_final
2018-04-04 09:43:50	ga_ls8c_ard_3-0-0_095067_2018-04-04_final
2018-04-04 11:22:43	ga_ls8c_ard_3-0-0_111067_2018-04-04_final
2018-04-05 10:27:05	ga_ls8c_ard_3-0-0_102067_2018-04-05_final
2018-04-06 09:31:27	ga_ls8c_ard_3-0-0_093067_2018-04-06_final
2018-04-06 11:10:20	ga_ls8c_ard_3-0-0_109067_2018-04-06_final
2018-04-07 10:14:42	ga_ls8c_ard_3-0-0_100067_2018-04-07_final
2018-04-11 09:49:57	ga_ls8c_ard_3-0-0_096067_2018-04-11_final
2018-04-11 11:28:50	ga_ls8c_ard_3-0-0_112067_2018-04-11_final
2018-04-12 10:33:12	ga_ls8c_ard_3-0-0_103067_2018-04-12_final
2018-04-13 09:37:34	ga_ls8c_ard_3-0-0_094067_2018-04-13_final
2018-04-13 11:16:27	ga_ls8c_ard_3-0-0_110067_2018-04-13_final
2018-04-14 10:20:49	ga_ls8c_ard_3-0-0_101067_2018-04-14_final
2018-04-15 09:25:11	ga_ls8c_ard_3-0-0_092067_2018-04-14_final
2018-06-30 09:49:38	ga_ls8c_ard_3-0-0_096067_2018-06-30_final
2018-06-30 09:50:02	ga_ls8c_ard_3-0-0_096068_2018-06-30_final
2018-06-30 11:28:31	ga_ls8c_ard_3-0-0_112067_2018-06-30_final
2018-07-01 10:32:54	ga_ls8c_ard_3-0-0_103067_2018-07-01_final
2018-07-01 10:33:18	ga_ls8c_ard_3-0-0_103068_2018-07-01_final
2018-07-02 09:37:17	ga_ls8c_ard_3-0-0_094067_2018-07-02_final
2018-07-02 11:16:11	ga_ls8c_ard_3-0-0_110067_2018-07-02_final
2018-07-02 11:16:35	ga_ls8c_ard_3-0-0_110068_2018-07-02_final
2018-07-03 10:20:34	ga_ls8c_ard_3-0-0_101067_2018-07-03_final
2018-07-03 10:20:58	ga_ls8c_ard_3-0-0_101068_2018-07-03_final
2018-07-04 09:24:57	ga_ls8c_ard_3-0-0_092067_2018-07-03_final
2018-07-04 09:25:21	ga_ls8c_ard_3-0-0_092068_2018-07-03_final
2018-09-16 10:02:34	ga_ls8c_ard_3-0-0_098067_2018-09-16_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_2018-09-16_final
2018-09-16 11:41:28	ga_ls8c_ard_3-0-0_114067_2018-09-16_final
2018-09-17 10:45:50	ga_ls8c_ard_3-0-0_105067_2018-09-17_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2019-01-06 10:02:49	ga_ls8c_ard_3-0-0_098067_2019-01-06_final
2019-01-06 11:41:42	ga_ls8c_ard_3-0-0_114067_2019-01-06_final
2019-01-07 10:46:04	ga_ls8c_ard_3-0-0_105067_2019-01-07_final
2023-04-30 10:08:37	ga_ls8c_ard_3-2-1_099067_2023-04-30_final
2023-05-01 10:51:52	ga_ls8c_ard_3-2-1_106067_2023-05-01_final
2023-05-01 12:30:45	ga_ls8c_ard_3-2-1_122067_2023-05-01_final
2023-05-02 09:56:14	ga_ls8c_ard_3-2-1_097067_2023-05-02_final
2023-05-03 10:39:29	ga_ls8c_ard_3-2-1_104067_2023-05-03_final
2023-05-05 10:27:06	ga_ls8c_ard_3-2-1_102067_2023-05-05_final
2023-05-08 12:36:50	ga_ls8c_ard_3-2-1_123067_2023-05-08_final
2023-05-09 10:02:18	ga_ls8c_ard_3-2-1_098067_2023-05-09_final
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-16 10:08:24	ga_ls8c_ard_3-2-1_099067_2023-05-16_final
2023-05-17 10:51:39	ga_ls8c_ard_3-2-1_106067_2023-05-17_final
2023-05-17 12:30:32	ga_ls8c_ard_3-2-1_122067_2023-05-17_final
2023-05-18 09:56:01	ga_ls8c_ard_3-2-1_097067_2023-05-18_final
2023-05-18 09:56:25	ga_ls8c_ard_3-2-1_097068_2023-05-18_final
2023-05-19 10:39:18	ga_ls8c_ard_3-2-1_104067_2023-05-19_final
2023-05-19 10:39:42	ga_ls8c_ard_3-2-1_104068_2023-05-19_final
2023-05-20 11:22:58	ga_ls8c_ard_3-2-1_111068_2023-05-20_final
2023-05-21 10:26:57	ga_ls8c_ard_3-2-1_102067_2023-05-21_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_final
2023-05-24 10:58:16	ga_ls8c_ard_3-2-1_107068_2023-05-24_final
2023-05-24 12:36:46	ga_ls8c_ard_3-2-1_123067_2023-05-24_final
2023-05-25 10:02:15	ga_ls8c_ard_3-2-1_098067_2023-05-25_final
2023-05-25 10:02:39	ga_ls8c_ard_3-2-1_098068_2023-05-25_final
2023-05-26 10:45:31	ga_ls8c_ard_3-2-1_105067_2023-05-26_final
2023-05-26 10:45:55	ga_ls8c_ard_3-2-1_105068_2023-05-26_final
2023-05-28 10:33:34	ga_ls8c_ard_3-2-1_103068_2023-05-28_final
2023-06-01 10:08:26	ga_ls8c_ard_3-2-1_099067_2023-06-01_final
2023-06-01 10:08:50	ga_ls8c_ard_3-2-1_099068_2023-06-01_final
2023-06-02 10:51:42	ga_ls8c_ard_3-2-1_106067_2023-06-02_final
2023-06-02 10:52:06	ga_ls8c_ard_3-2-1_106068_2023-06-02_final
2023-06-02 12:30:35	ga_ls8c_ard_3-2-1_122067_2023-06-02_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_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