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
2018-09-15 10:59:23	ga_ls8c_ard_3-0-0_107070_2018-09-15_final
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-09-29 11:11:51	ga_ls8c_ard_3-0-0_109070_2018-09-29_final
2018-09-30 10:16:14	ga_ls8c_ard_3-0-0_100070_2018-09-30_final
2018-10-01 10:59:30	ga_ls8c_ard_3-0-0_107070_2018-10-01_final
2018-10-04 09:51:33	ga_ls8c_ard_3-0-0_096070_2018-10-04_final
2018-10-04 11:30:26	ga_ls8c_ard_3-0-0_112070_2018-10-04_final
2018-10-05 10:34:49	ga_ls8c_ard_3-0-0_103070_2018-10-05_final
2018-10-06 11:18:05	ga_ls8c_ard_3-0-0_110070_2018-10-06_final
2018-10-07 10:22:28	ga_ls8c_ard_3-0-0_101070_2018-10-07_final
2018-10-13 09:45:26	ga_ls8c_ard_3-0-0_095070_2018-10-13_final
2018-10-13 11:24:19	ga_ls8c_ard_3-0-0_111070_2018-10-13_final
2018-10-14 10:28:42	ga_ls8c_ard_3-0-0_102070_2018-10-14_final
2018-10-15 11:11:58	ga_ls8c_ard_3-0-0_109070_2018-10-15_final
2018-10-16 10:16:21	ga_ls8c_ard_3-1-0_100070_2018-10-16_final
2018-10-17 10:59:37	ga_ls8c_ard_3-0-0_107070_2018-10-17_final
2018-10-29 09:45:31	ga_ls8c_ard_3-0-0_095070_2018-10-29_final
2018-10-29 11:24:24	ga_ls8c_ard_3-0-0_111070_2018-10-29_final
2018-10-30 10:28:46	ga_ls8c_ard_3-0-0_102070_2018-10-30_final
2018-10-31 09:33:33	ga_ls8c_ard_3-0-0_093071_2018-10-31_final
2018-10-31 11:12:02	ga_ls8c_ard_3-0-0_109070_2018-10-31_final
2018-11-01 10:16:25	ga_ls8c_ard_3-1-0_100070_2018-11-01_final
2018-11-02 10:59:41	ga_ls8c_ard_3-0-0_107070_2018-11-02_final
2018-12-07 09:51:41	ga_ls8c_ard_3-0-0_096070_2018-12-07_final
2018-12-07 11:30:34	ga_ls8c_ard_3-0-0_112070_2018-12-07_final
2018-12-08 10:34:56	ga_ls8c_ard_3-0-0_103070_2018-12-08_final
2018-12-09 09:39:43	ga_ls8c_ard_3-0-0_094071_2018-12-09_final
2018-12-09 11:18:12	ga_ls8c_ard_3-0-0_110070_2018-12-09_final
2018-12-10 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-10_final
2018-12-16 09:45:28	ga_ls8c_ard_3-0-0_095070_2018-12-16_final
2018-12-16 11:24:22	ga_ls8c_ard_3-0-0_111070_2018-12-16_final
2018-12-17 10:28:44	ga_ls8c_ard_3-0-0_102070_2018-12-17_final
2018-12-18 11:12:00	ga_ls8c_ard_3-0-0_109070_2018-12-18_final
2018-12-18 11:12:24	ga_ls8c_ard_3-0-0_109071_2018-12-18_final
2018-12-19 10:16:23	ga_ls8c_ard_3-1-0_100070_2018-12-19_final
2018-12-20 10:59:39	ga_ls8c_ard_3-0-0_107070_2018-12-20_final
2018-12-23 09:51:40	ga_ls8c_ard_3-0-0_096070_2018-12-23_final
2018-12-23 11:30:33	ga_ls8c_ard_3-0-0_112070_2018-12-23_final
2018-12-24 10:34:55	ga_ls8c_ard_3-0-0_103070_2018-12-24_final
2018-12-25 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-12-25_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-08 10:10:43	ga_ls8c_ard_3-2-1_099070_2023-01-08_final
2023-01-09 10:53:59	ga_ls8c_ard_3-2-1_106070_2023-01-09_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-11 10:41:36	ga_ls8c_ard_3-2-1_104070_2023-01-11_final
2023-01-12 11:24:51	ga_ls8c_ard_3-2-1_111070_2023-01-12_final
2023-01-13 10:29:13	ga_ls8c_ard_3-2-1_102070_2023-01-13_final
2023-01-14 11:12:28	ga_ls8c_ard_3-2-1_109070_2023-01-14_final
2023-01-16 11:00:04	ga_ls8c_ard_3-2-1_107070_2023-01-16_final
2023-01-18 10:47:41	ga_ls8c_ard_3-2-1_105070_2023-01-18_final
2023-01-19 09:52:05	ga_ls8c_ard_3-2-1_096070_2023-01-19_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-25 10:53:57	ga_ls8c_ard_3-2-1_106070_2023-01-25_final
2023-01-26 09:58:20	ga_ls8c_ard_3-2-1_097070_2023-01-26_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-01 11:00:09	ga_ls8c_ard_3-2-1_107070_2023-02-01_final
2023-02-02 10:04:32	ga_ls8c_ard_3-2-1_098070_2023-02-02_final
2023-02-03 10:47:47	ga_ls8c_ard_3-2-1_105070_2023-02-03_final
2023-02-04 09:52:10	ga_ls8c_ard_3-2-1_096070_2023-02-04_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-08 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-02-08_final
2023-02-09 10:10:40	ga_ls8c_ard_3-2-1_099070_2023-02-09_final
2023-02-10 10:53:55	ga_ls8c_ard_3-2-1_106070_2023-02-10_final
2023-02-11 09:58:17	ga_ls8c_ard_3-2-1_097070_2023-02-11_final
2023-02-12 10:41:32	ga_ls8c_ard_3-2-1_104070_2023-02-12_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-02-18 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-02-18_final
2023-02-19 10:47:36	ga_ls8c_ard_3-2-1_105070_2023-02-19_final
2023-02-20 09:51:58	ga_ls8c_ard_3-2-1_096070_2023-02-20_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-23 10:22:47	ga_ls8c_ard_3-2-1_101070_2023-02-23_final
2023-02-24 11:06:01	ga_ls8c_ard_3-2-1_108070_2023-02-24_final
2023-02-25 10:10:23	ga_ls8c_ard_3-2-1_099070_2023-02-25_final
2023-02-26 10:53:39	ga_ls8c_ard_3-2-1_106070_2023-02-26_final
2023-02-27 09:58:01	ga_ls8c_ard_3-2-1_097070_2023-02-27_final
2023-02-28 10:41:17	ga_ls8c_ard_3-2-1_104070_2023-02-28_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-25 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-03-25_final
2023-03-26 11:18:08	ga_ls8c_ard_3-2-1_110070_2023-03-26_final
2023-03-27 10:22:31	ga_ls8c_ard_3-2-1_101070_2023-03-27_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-03-29 10:10:08	ga_ls8c_ard_3-2-1_099070_2023-03-29_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-03-31 09:57:45	ga_ls8c_ard_3-2-1_097070_2023-03-31_final
2023-04-01 10:41:00	ga_ls8c_ard_3-2-1_104070_2023-04-01_final
2023-04-06 10:59:27	ga_ls8c_ard_3-2-1_107070_2023-04-06_final
2023-04-07 10:03:48	ga_ls8c_ard_3-2-1_098070_2023-04-07_final
2023-04-10 10:34:38	ga_ls8c_ard_3-2-1_103070_2023-04-10_final
2023-04-11 11:17:52	ga_ls8c_ard_3-2-1_110070_2023-04-11_final
2023-04-12 10:22:15	ga_ls8c_ard_3-2-1_101070_2023-04-12_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