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
2018-07-04 09:24:57	ga_ls8c_ard_3-0-0_092067_2018-07-03_final
2018-07-16 09:49:46	ga_ls8c_ard_3-0-0_096067_2018-07-16_final
2018-07-16 09:50:10	ga_ls8c_ard_3-0-0_096068_2018-07-16_final
2018-07-16 11:28:39	ga_ls8c_ard_3-0-0_112067_2018-07-16_final
2018-07-16 11:29:03	ga_ls8c_ard_3-0-0_112068_2018-07-16_final
2018-07-17 10:33:02	ga_ls8c_ard_3-0-0_103067_2018-07-17_final
2018-07-17 10:33:26	ga_ls8c_ard_3-0-0_103068_2018-07-17_final
2018-07-18 09:37:25	ga_ls8c_ard_3-0-0_094067_2018-07-18_final
2018-07-18 11:16:18	ga_ls8c_ard_3-0-0_110067_2018-07-18_final
2018-07-19 10:20:41	ga_ls8c_ard_3-0-0_101067_2018-07-19_final
2018-07-19 10:21:05	ga_ls8c_ard_3-0-0_101068_2018-07-19_final
2018-07-20 09:25:04	ga_ls8c_ard_3-0-0_092067_2018-07-19_final
2018-07-20 09:25:28	ga_ls8c_ard_3-0-0_092068_2018-07-19_final
2018-08-01 09:49:53	ga_ls8c_ard_3-0-0_096067_2018-08-01_final
2018-08-01 09:50:17	ga_ls8c_ard_3-0-0_096068_2018-08-01_final
2018-08-01 11:28:46	ga_ls8c_ard_3-0-0_112067_2018-08-01_final
2018-08-01 11:29:10	ga_ls8c_ard_3-0-0_112068_2018-08-01_final
2018-08-02 10:33:09	ga_ls8c_ard_3-0-0_103067_2018-08-02_final
2018-08-02 10:33:33	ga_ls8c_ard_3-0-0_103068_2018-08-02_final
2018-08-03 09:37:33	ga_ls8c_ard_3-0-0_094067_2018-08-03_final
2018-08-03 11:16:26	ga_ls8c_ard_3-0-0_110067_2018-08-03_final
2018-08-03 11:16:50	ga_ls8c_ard_3-0-0_110068_2018-08-03_final
2018-08-04 10:20:49	ga_ls8c_ard_3-0-0_101067_2018-08-04_final
2018-08-04 10:21:13	ga_ls8c_ard_3-0-0_101068_2018-08-04_final
2018-08-05 09:25:12	ga_ls8c_ard_3-0-0_092067_2018-08-04_final
2018-08-05 09:25:36	ga_ls8c_ard_3-0-0_092068_2018-08-04_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
2020-03-29 10:02:41	ga_ls8c_ard_3-1-0_098067_2020-03-29_final
2020-03-29 11:41:34	ga_ls8c_ard_3-1-0_114067_2020-03-29_final
2020-03-30 10:45:56	ga_ls8c_ard_3-1-0_105067_2020-03-30_final
2020-03-31 09:50:18	ga_ls8c_ard_3-1-0_096067_2020-03-31_final
2020-03-31 11:29:11	ga_ls8c_ard_3-1-0_112067_2020-03-31_final
2020-04-01 10:33:33	ga_ls8c_ard_3-1-0_103067_2020-04-01_final
2020-04-05 10:08:48	ga_ls8c_ard_3-1-0_099067_2020-04-05_final
2020-04-06 10:52:03	ga_ls8c_ard_3-1-0_106067_2020-04-06_final
2020-04-06 12:30:56	ga_ls8c_ard_3-2-1_122067_2020-04-06_final
2020-04-07 09:56:25	ga_ls8c_ard_3-1-0_097067_2020-04-07_final
2020-04-07 11:35:18	ga_ls8c_ard_3-1-0_113067_2020-04-07_final
2020-04-08 10:39:41	ga_ls8c_ard_3-1-0_104067_2020-04-08_final
2020-04-09 09:44:03	ga_ls8c_ard_3-1-0_095067_2020-04-09_final
2020-04-09 11:22:56	ga_ls8c_ard_3-1-0_111067_2020-04-09_final
2020-04-10 10:27:18	ga_ls8c_ard_3-1-0_102067_2020-04-10_final
2020-04-11 09:31:41	ga_ls8c_ard_3-1-0_093067_2020-04-11_final
2020-04-11 11:10:34	ga_ls8c_ard_3-1-0_109067_2020-04-11_final
2020-04-12 10:14:56	ga_ls8c_ard_3-1-0_100067_2020-04-12_final
2020-04-21 10:08:41	ga_ls8c_ard_3-1-0_099067_2020-04-21_final
2020-04-22 10:51:56	ga_ls8c_ard_3-1-0_106067_2020-04-22_final
2020-04-22 12:30:49	ga_ls8c_ard_3-2-1_122067_2020-04-22_final
2020-04-23 09:56:18	ga_ls8c_ard_3-1-0_097067_2020-04-23_final
2020-04-23 11:35:12	ga_ls8c_ard_3-1-0_113067_2020-04-23_final
2020-04-24 10:39:34	ga_ls8c_ard_3-1-0_104067_2020-04-24_final
2020-04-27 11:10:26	ga_ls8c_ard_3-1-0_109067_2020-04-27_final
2020-04-28 10:14:48	ga_ls8c_ard_3-1-0_100067_2020-04-28_final
2020-06-01 10:02:27	ga_ls8c_ard_3-1-0_098067_2020-06-01_final
2020-06-01 11:41:20	ga_ls8c_ard_3-1-0_114067_2020-06-01_final
2020-06-02 10:45:43	ga_ls8c_ard_3-1-0_105067_2020-06-02_final
2020-06-02 10:46:07	ga_ls8c_ard_3-1-0_105068_2020-06-02_final
2020-06-03 09:50:07	ga_ls8c_ard_3-1-0_096067_2020-06-03_final
2020-06-03 11:29:00	ga_ls8c_ard_3-1-0_112067_2020-06-03_final
2020-06-03 11:29:24	ga_ls8c_ard_3-1-0_112068_2020-06-03_final
2020-06-04 10:33:23	ga_ls8c_ard_3-1-0_103067_2020-06-04_final
2020-06-04 10:33:47	ga_ls8c_ard_3-1-0_103068_2020-06-04_final
2023-01-16 12:37:45	ga_ls8c_ard_3-2-1_123067_2023-01-16_final
2023-01-17 10:03:14	ga_ls8c_ard_3-2-1_098067_2023-01-17_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-29 10:28:03	ga_ls8c_ard_3-2-1_102067_2023-01-29_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
2023-02-03 10:46:59	ga_ls8c_ard_3-2-1_105068_2023-02-03_final
2023-02-12 10:40:20	ga_ls8c_ard_3-2-1_104067_2023-02-12_final
2023-02-17 12:37:41	ga_ls8c_ard_3-2-1_123067_2023-02-17_final
2023-02-18 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-02-18_final
2023-02-19 10:46:24	ga_ls8c_ard_3-2-1_105067_2023-02-19_final
2023-02-19 10:46:48	ga_ls8c_ard_3-2-1_105068_2023-02-19_final
2023-02-25 10:09:11	ga_ls8c_ard_3-2-1_099067_2023-02-25_final
2023-02-26 10:52:27	ga_ls8c_ard_3-2-1_106067_2023-02-26_final
2023-02-26 12:31:20	ga_ls8c_ard_3-2-1_122067_2023-02-26_final
2023-02-27 09:56:50	ga_ls8c_ard_3-2-1_097067_2023-02-27_final
2023-02-28 10:40:05	ga_ls8c_ard_3-2-1_104067_2023-02-28_final
2023-03-05 12:37:29	ga_ls8c_ard_3-2-1_123067_2023-03-05_final
2023-03-06 10:02:58	ga_ls8c_ard_3-2-1_098067_2023-03-06_final
2023-03-07 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-03-07_final
2023-04-06 12:37:08	ga_ls8c_ard_3-2-1_123067_2023-04-06_final
2023-04-07 10:02:36	ga_ls8c_ard_3-2-1_098067_2023-04-07_final
2023-04-15 10:51:57	ga_ls8c_ard_3-2-1_106067_2023-04-15_final
2023-04-15 12:30:50	ga_ls8c_ard_3-2-1_122067_2023-04-15_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-05 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-09-05_final
2023-09-08 10:40:01	ga_ls8c_ard_3-2-1_104067_2023-09-08_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
2023-10-10 10:40:11	ga_ls8c_ard_3-2-1_104067_2023-10-10_final
2023-10-10 10:40:35	ga_ls8c_ard_3-2-1_104068_2023-10-10_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