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 10:02:34	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
2018-09-17 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 10:03:13	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
2019-01-22 10:03:09	ga_ls8c_ard_3-0-0_098068_2019-01-22_final
2019-01-23 10:46:25	ga_ls8c_ard_3-0-0_105068_2019-01-23_final
2019-01-24 09:50:47	ga_ls8c_ard_3-0-0_096068_2019-01-24_final
2019-01-24 11:29:40	ga_ls8c_ard_3-0-0_112068_2019-01-24_final
2019-01-25 10:34:02	ga_ls8c_ard_3-0-0_103068_2019-01-25_final
2019-02-23 10:03:04	ga_ls8c_ard_3-0-0_098068_2019-02-23_final
2019-02-24 10:46:19	ga_ls8c_ard_3-0-0_105068_2019-02-24_final
2019-03-03 10:52:28	ga_ls8c_ard_3-0-0_106068_2019-03-03_final
2019-03-04 09:56:26	ga_ls8c_ard_3-0-0_097067_2019-03-04_final
2019-03-04 09:56:50	ga_ls8c_ard_3-0-0_097068_2019-03-04_final
2019-03-05 10:40:05	ga_ls8c_ard_3-0-0_104068_2019-03-05_final
2019-04-02 09:25:24	ga_ls8c_ard_3-1-0_092067_2019-04-01_final
2019-04-02 09:25:48	ga_ls8c_ard_3-1-0_092068_2019-04-01_final
2019-04-23 11:23:06	ga_ls8c_ard_3-0-0_111068_2019-04-23_final
2019-04-24 10:27:28	ga_ls8c_ard_3-0-0_102068_2019-04-24_final
2019-04-25 09:31:50	ga_ls8c_ard_3-0-0_093068_2019-04-25_final
2019-04-25 11:10:43	ga_ls8c_ard_3-0-0_109068_2019-04-25_final
2019-04-26 10:14:42	ga_ls8c_ard_3-0-0_100067_2019-04-26_final
2019-04-26 10:15:06	ga_ls8c_ard_3-0-0_100068_2019-04-26_final
2019-05-30 10:02:40	ga_ls8c_ard_3-0-0_098067_2019-05-30_final
2019-05-30 10:03:04	ga_ls8c_ard_3-0-0_098068_2019-05-30_final
2019-05-31 10:45:56	ga_ls8c_ard_3-0-0_105067_2019-05-31_final
2019-05-31 10:46:20	ga_ls8c_ard_3-0-0_105068_2019-05-31_final
2019-06-01 09:50:19	ga_ls8c_ard_3-0-0_096067_2019-06-01_final
2019-06-01 09:50:43	ga_ls8c_ard_3-0-0_096068_2019-06-01_final
2019-06-01 11:29:12	ga_ls8c_ard_3-0-0_112067_2019-06-01_final
2019-06-01 11:29:36	ga_ls8c_ard_3-0-0_112068_2019-06-01_final
2019-06-02 10:33:35	ga_ls8c_ard_3-0-0_103067_2019-06-02_final
2019-06-02 10:33:59	ga_ls8c_ard_3-0-0_103068_2019-06-02_final
2019-06-03 11:16:51	ga_ls8c_ard_3-0-0_110067_2019-06-03_final
2019-06-03 11:17:15	ga_ls8c_ard_3-0-0_110068_2019-06-03_final
2019-06-04 10:21:38	ga_ls8c_ard_3-0-0_101068_2019-06-04_final
2019-06-05 09:25:38	ga_ls8c_ard_3-0-0_092067_2019-06-04_final
2019-06-05 09:26:01	ga_ls8c_ard_3-0-0_092068_2019-06-04_final
2019-06-05 11:04:31	ga_ls8c_ard_3-0-0_108067_2019-06-05_final
2019-06-05 11:04:55	ga_ls8c_ard_3-0-0_108068_2019-06-05_final
2019-06-06 10:08:54	ga_ls8c_ard_3-0-0_099067_2019-06-06_final
2019-06-06 10:09:18	ga_ls8c_ard_3-0-0_099068_2019-06-06_final
2019-06-07 10:52:10	ga_ls8c_ard_3-0-0_106067_2019-06-07_final
2019-06-07 10:52:34	ga_ls8c_ard_3-0-0_106068_2019-06-07_final
2019-06-08 09:56:33	ga_ls8c_ard_3-0-0_097067_2019-06-08_final
2019-06-08 09:56:57	ga_ls8c_ard_3-0-0_097068_2019-06-08_final
2019-06-09 10:40:13	ga_ls8c_ard_3-0-0_104068_2019-06-09_final
2019-12-08 10:03:40	ga_ls8c_ard_3-1-0_098068_2019-12-08_final
2019-12-09 10:46:55	ga_ls8c_ard_3-1-0_105068_2019-12-09_final
2019-12-10 09:51:18	ga_ls8c_ard_3-1-0_096068_2019-12-10_final
2019-12-10 11:29:47	ga_ls8c_ard_3-1-0_112067_2019-12-10_final
2019-12-10 11:30:11	ga_ls8c_ard_3-1-0_112068_2019-12-10_final
2019-12-11 10:34:33	ga_ls8c_ard_3-1-0_103068_2019-12-11_final
2020-02-20 10:40:27	ga_ls8c_ard_3-1-0_104068_2020-02-20_final
2020-02-21 11:23:42	ga_ls8c_ard_3-1-0_111068_2020-02-21_final
2020-02-22 10:28:04	ga_ls8c_ard_3-1-0_102068_2020-02-22_final
2020-02-23 09:32:27	ga_ls8c_ard_3-1-0_093068_2020-02-23_final
2022-07-20 11:23:58	ga_ls8c_ard_3-2-1_111068_2022-07-20_final
2022-07-21 10:27:58	ga_ls8c_ard_3-2-1_102067_2022-07-21_final
2022-07-21 10:28:22	ga_ls8c_ard_3-2-1_102068_2022-07-21_final
2022-07-24 10:59:18	ga_ls8c_ard_3-2-1_107068_2022-07-24_final
2022-07-24 12:37:48	ga_ls8c_ard_3-2-1_123067_2022-07-24_final
2022-07-25 10:03:18	ga_ls8c_ard_3-2-1_098067_2022-07-25_final
2022-07-25 10:03:42	ga_ls8c_ard_3-2-1_098068_2022-07-25_final
2022-07-26 10:46:34	ga_ls8c_ard_3-2-1_105067_2022-07-26_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
2022-08-01 10:09:33	ga_ls8c_ard_3-2-1_099067_2022-08-01_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 12:31:43	ga_ls8c_ard_3-2-1_122067_2022-08-02_final
2022-08-03 09:57:37	ga_ls8c_ard_3-2-1_097068_2022-08-03_final
2022-08-04 10:40:29	ga_ls8c_ard_3-2-1_104067_2022-08-04_final
2022-08-04 10:40:53	ga_ls8c_ard_3-2-1_104068_2022-08-04_final
2023-06-03 09:56:06	ga_ls8c_ard_3-2-1_097067_2023-06-03_final
2023-06-03 09:56:30	ga_ls8c_ard_3-2-1_097068_2023-06-03_final
2023-06-04 10:39:46	ga_ls8c_ard_3-2-1_104068_2023-06-04_final
2023-06-06 10:27:03	ga_ls8c_ard_3-2-1_102067_2023-06-06_final
2023-06-06 10:27:26	ga_ls8c_ard_3-2-1_102068_2023-06-06_final
2023-07-04 12:30:55	ga_ls8c_ard_3-2-1_122067_2023-07-04_final
2023-07-05 09:56:25	ga_ls8c_ard_3-2-1_097067_2023-07-05_final
2023-07-05 09:56:49	ga_ls8c_ard_3-2-1_097068_2023-07-05_final
2023-07-06 10:39:42	ga_ls8c_ard_3-2-1_104067_2023-07-06_final
2023-07-06 10:40:05	ga_ls8c_ard_3-2-1_104068_2023-07-06_final
2023-07-27 12:37:15	ga_ls8c_ard_3-2-1_123067_2023-07-27_final
2023-07-28 10:02:45	ga_ls8c_ard_3-2-1_098067_2023-07-28_final
2023-07-28 10:03:09	ga_ls8c_ard_3-2-1_098068_2023-07-28_final
2023-07-29 10:46:02	ga_ls8c_ard_3-2-1_105067_2023-07-29_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
2023-08-05 10:52:15	ga_ls8c_ard_3-2-1_106067_2023-08-05_final
2023-08-05 10:52:39	ga_ls8c_ard_3-2-1_106068_2023-08-05_final
2023-08-12 10:58:50	ga_ls8c_ard_3-2-1_107068_2023-08-12_final
2023-08-12 12:37:20	ga_ls8c_ard_3-2-1_123067_2023-08-12_final
2023-08-13 10:02:50	ga_ls8c_ard_3-2-1_098067_2023-08-13_final
2023-08-13 10:03:14	ga_ls8c_ard_3-2-1_098068_2023-08-13_final
2023-08-14 10:46:07	ga_ls8c_ard_3-2-1_105067_2023-08-14_final
2023-08-14 10:46:31	ga_ls8c_ard_3-2-1_105068_2023-08-14_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