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
2018-06-09 11:09:45	ga_ls8c_ard_3-0-0_109067_2018-06-09_final
2018-06-10 10:14:08	ga_ls8c_ard_3-0-0_100067_2018-06-10_final
2018-06-23 09:43:23	ga_ls8c_ard_3-0-0_095067_2018-06-23_final
2018-06-23 11:22:16	ga_ls8c_ard_3-0-0_111067_2018-06-23_final
2018-06-24 10:26:39	ga_ls8c_ard_3-0-0_102067_2018-06-24_final
2018-06-24 10:27:03	ga_ls8c_ard_3-0-0_102068_2018-06-24_final
2018-06-25 09:31:03	ga_ls8c_ard_3-0-0_093067_2018-06-25_final
2018-06-25 11:09:56	ga_ls8c_ard_3-0-0_109067_2018-06-25_final
2018-06-26 10:14:19	ga_ls8c_ard_3-0-0_100067_2018-06-26_final
2018-06-26 10:14:43	ga_ls8c_ard_3-0-0_100068_2018-06-26_final
2018-07-09 09:43:32	ga_ls8c_ard_3-0-0_095067_2018-07-09_final
2018-07-09 11:22:25	ga_ls8c_ard_3-0-0_111067_2018-07-09_final
2018-07-10 10:26:48	ga_ls8c_ard_3-0-0_102067_2018-07-10_final
2018-07-10 10:27:12	ga_ls8c_ard_3-0-0_102068_2018-07-10_final
2018-07-11 09:31:11	ga_ls8c_ard_3-0-0_093067_2018-07-11_final
2018-07-11 09:31:35	ga_ls8c_ard_3-0-0_093068_2018-07-11_final
2018-07-11 11:10:04	ga_ls8c_ard_3-0-0_109067_2018-07-11_final
2018-07-12 10:14:27	ga_ls8c_ard_3-0-0_100067_2018-07-12_final
2018-08-26 09:43:55	ga_ls8c_ard_3-0-0_095067_2018-08-26_final
2018-08-26 11:22:49	ga_ls8c_ard_3-0-0_111067_2018-08-26_final
2018-08-27 10:27:12	ga_ls8c_ard_3-0-0_102067_2018-08-27_final
2018-08-27 10:27:35	ga_ls8c_ard_3-0-0_102068_2018-08-27_final
2018-08-28 09:31:35	ga_ls8c_ard_3-0-0_093067_2018-08-28_final
2018-08-28 11:10:28	ga_ls8c_ard_3-0-0_109067_2018-08-28_final
2018-08-29 10:14:51	ga_ls8c_ard_3-0-0_100067_2018-08-29_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
2018-10-04 09:50:21	ga_ls8c_ard_3-0-0_096067_2018-10-04_final
2018-10-04 11:29:14	ga_ls8c_ard_3-0-0_112067_2018-10-04_final
2018-10-05 10:33:37	ga_ls8c_ard_3-0-0_103067_2018-10-05_final
2018-10-05 10:34:01	ga_ls8c_ard_3-0-0_103068_2018-10-05_final
2018-10-06 09:38:00	ga_ls8c_ard_3-0-0_094067_2018-10-06_final
2018-10-06 11:16:53	ga_ls8c_ard_3-0-0_110067_2018-10-06_final
2018-10-07 10:21:16	ga_ls8c_ard_3-0-0_101067_2018-10-07_final
2018-10-08 09:25:40	ga_ls8c_ard_3-0-0_092067_2018-10-07_final
2018-12-23 09:50:28	ga_ls8c_ard_3-0-0_096067_2018-12-23_final
2018-12-23 11:29:21	ga_ls8c_ard_3-0-0_112067_2018-12-23_final
2018-12-24 10:33:44	ga_ls8c_ard_3-0-0_103067_2018-12-24_final
2018-12-24 10:34:08	ga_ls8c_ard_3-0-0_103068_2018-12-24_final
2018-12-25 09:38:06	ga_ls8c_ard_3-0-0_094067_2018-12-25_final
2018-12-25 11:16:59	ga_ls8c_ard_3-0-0_110067_2018-12-25_final
2018-12-26 10:21:22	ga_ls8c_ard_3-0-0_101067_2018-12-26_final
2018-12-27 09:25:45	ga_ls8c_ard_3-0-0_092067_2018-12-26_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
2019-11-22 10:03:16	ga_ls8c_ard_3-1-0_098067_2019-11-22_final
2019-11-22 11:42:09	ga_ls8c_ard_3-1-0_114067_2019-11-22_final
2019-11-23 10:46:32	ga_ls8c_ard_3-1-0_105067_2019-11-23_final
2019-11-28 11:05:04	ga_ls8c_ard_3-1-0_108067_2019-11-28_final
2019-11-29 10:09:27	ga_ls8c_ard_3-1-0_099067_2019-11-29_final
2019-11-30 10:52:43	ga_ls8c_ard_3-1-0_106067_2019-11-30_final
2019-11-30 12:31:36	ga_ls8c_ard_3-2-1_122067_2019-11-30_final
2019-12-01 09:57:05	ga_ls8c_ard_3-1-0_097067_2019-12-01_final
2019-12-01 09:57:29	ga_ls8c_ard_3-1-0_097068_2019-12-01_final
2019-12-01 11:35:58	ga_ls8c_ard_3-1-0_113067_2019-12-01_final
2019-12-02 10:40:21	ga_ls8c_ard_3-1-0_104067_2019-12-02_final
2019-12-12 11:17:25	ga_ls8c_ard_3-1-0_110067_2019-12-12_final
2019-12-13 10:21:47	ga_ls8c_ard_3-2-0_101067_2019-12-13_final
2019-12-14 09:26:10	ga_ls8c_ard_3-2-0_092067_2019-12-13_final
2019-12-14 11:05:03	ga_ls8c_ard_3-2-0_108067_2019-12-14_final
2019-12-15 10:09:26	ga_ls8c_ard_3-2-0_099067_2019-12-15_final
2019-12-16 10:52:41	ga_ls8c_ard_3-2-0_106067_2019-12-16_final
2019-12-16 12:31:34	ga_ls8c_ard_3-2-1_122067_2019-12-16_final
2019-12-17 09:57:04	ga_ls8c_ard_3-2-0_097067_2019-12-17_final
2019-12-17 11:35:57	ga_ls8c_ard_3-2-0_113067_2019-12-17_final
2019-12-18 10:40:19	ga_ls8c_ard_3-2-0_104067_2019-12-18_final
2019-12-19 09:44:41	ga_ls8c_ard_3-2-0_095067_2019-12-19_final
2019-12-19 11:23:34	ga_ls8c_ard_3-2-0_111067_2019-12-19_final
2019-12-22 10:15:35	ga_ls8c_ard_3-1-0_100067_2019-12-22_final
2019-12-23 10:58:50	ga_ls8c_ard_3-1-0_107067_2019-12-23_final
2019-12-23 12:37:43	ga_ls8c_ard_3-2-1_123067_2019-12-23_final
2019-12-24 10:03:13	ga_ls8c_ard_3-1-0_098067_2019-12-24_final
2019-12-24 11:42:06	ga_ls8c_ard_3-1-0_114067_2019-12-24_final
2020-02-02 10:52:28	ga_ls8c_ard_3-1-0_106067_2020-02-02_final
2020-02-02 12:31:21	ga_ls8c_ard_3-2-1_122067_2020-02-02_final
2020-02-03 09:56:51	ga_ls8c_ard_3-1-0_097067_2020-02-03_final
2020-02-03 11:35:44	ga_ls8c_ard_3-1-0_113067_2020-02-03_final
2020-02-04 10:40:06	ga_ls8c_ard_3-1-0_104067_2020-02-04_final
2023-02-02 10:03:20	ga_ls8c_ard_3-2-1_098067_2023-02-02_final
2023-02-03 10:46:36	ga_ls8c_ard_3-2-1_105067_2023-02-03_final
2023-08-28 10:58:58	ga_ls8c_ard_3-2-1_107068_2023-08-28_final
2023-08-28 12:37:27	ga_ls8c_ard_3-2-1_123067_2023-08-28_final
2023-08-29 10:02:57	ga_ls8c_ard_3-2-1_098067_2023-08-29_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-06 10:52:21	ga_ls8c_ard_3-2-1_106067_2023-09-06_final
2023-09-06 12:31:14	ga_ls8c_ard_3-2-1_122067_2023-09-06_final
2023-11-12 11:23:51	ga_ls8c_ard_3-2-1_111068_2023-11-12_final
2023-11-16 12:37:40	ga_ls8c_ard_3-2-1_123067_2023-11-16_final
2023-11-17 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-11-17_final
2023-11-18 10:46:26	ga_ls8c_ard_3-2-1_105067_2023-11-18_final
2023-11-24 10:09:23	ga_ls8c_ard_3-2-1_099067_2023-11-24_final
2023-11-25 12:31:32	ga_ls8c_ard_3-2-1_122067_2023-11-25_final
2023-11-26 09:57:01	ga_ls8c_ard_3-2-1_097067_2023-11-26_final
2023-11-27 10:40:16	ga_ls8c_ard_3-2-1_104067_2023-11-27_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