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
2018-02-03 10:59:38	ga_ls8c_ard_3-0-0_107070_2018-02-03_final
2018-02-15 09:45:25	ga_ls8c_ard_3-0-0_095070_2018-02-15_final
2018-02-15 09:45:49	ga_ls8c_ard_3-0-0_095071_2018-02-15_final
2018-02-15 11:24:18	ga_ls8c_ard_3-0-0_111070_2018-02-15_final
2018-02-16 10:28:40	ga_ls8c_ard_3-0-0_102070_2018-02-16_final
2018-02-17 11:11:55	ga_ls8c_ard_3-0-0_109070_2018-02-17_final
2018-02-18 10:16:18	ga_ls8c_ard_3-0-0_100070_2018-02-18_final
2018-02-19 10:59:33	ga_ls8c_ard_3-0-0_107070_2018-02-19_final
2018-02-22 09:51:33	ga_ls8c_ard_3-0-0_096070_2018-02-22_final
2018-02-22 09:51:57	ga_ls8c_ard_3-0-0_096071_2018-02-22_final
2018-02-22 11:30:26	ga_ls8c_ard_3-0-0_112070_2018-02-22_final
2018-02-23 10:34:48	ga_ls8c_ard_3-0-0_103070_2018-02-23_final
2018-02-24 11:18:03	ga_ls8c_ard_3-0-0_110070_2018-02-24_final
2018-02-25 10:22:25	ga_ls8c_ard_3-0-0_101070_2018-02-25_final
2018-03-03 09:45:18	ga_ls8c_ard_3-0-0_095070_2018-03-03_final
2018-03-03 11:24:11	ga_ls8c_ard_3-0-0_111070_2018-03-03_final
2018-03-04 10:28:33	ga_ls8c_ard_3-0-0_102070_2018-03-04_final
2018-03-05 11:11:48	ga_ls8c_ard_3-0-0_109070_2018-03-05_final
2018-03-06 10:16:10	ga_ls8c_ard_3-0-0_100070_2018-03-06_final
2018-03-07 10:59:25	ga_ls8c_ard_3-0-0_107070_2018-03-07_final
2018-03-12 11:17:54	ga_ls8c_ard_3-0-0_110070_2018-03-12_final
2018-03-13 10:22:16	ga_ls8c_ard_3-0-0_101070_2018-03-13_final
2018-04-08 10:59:09	ga_ls8c_ard_3-0-0_107070_2018-04-08_final
2018-04-20 09:44:52	ga_ls8c_ard_3-0-0_095070_2018-04-20_final
2018-04-20 11:23:45	ga_ls8c_ard_3-0-0_111070_2018-04-20_final
2018-04-21 10:28:07	ga_ls8c_ard_3-0-0_102070_2018-04-21_final
2018-04-22 11:11:22	ga_ls8c_ard_3-0-0_109070_2018-04-22_final
2018-04-23 10:15:45	ga_ls8c_ard_3-0-0_100070_2018-04-23_final
2018-05-08 11:11:13	ga_ls8c_ard_3-0-0_109070_2018-05-08_final
2018-05-09 10:15:36	ga_ls8c_ard_3-1-0_100070_2018-05-09_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
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_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
2023-01-17 10:04:26	ga_ls8c_ard_3-2-1_098070_2023-01-17_final
2023-01-17 10:04:50	ga_ls8c_ard_3-2-1_098071_2023-01-17_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
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-23 09:27:49	ga_ls8c_ard_3-2-1_092071_2023-01-22_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-24 10:10:41	ga_ls8c_ard_3-2-1_099070_2023-01-24_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
2023-04-16 09:57:31	ga_ls8c_ard_3-2-1_097070_2023-04-16_final
2023-04-17 10:40:46	ga_ls8c_ard_3-2-1_104070_2023-04-17_final
2023-04-19 10:28:23	ga_ls8c_ard_3-2-1_102070_2023-04-19_final
2023-04-20 11:11:38	ga_ls8c_ard_3-2-1_109070_2023-04-20_final
2023-04-24 10:46:56	ga_ls8c_ard_3-2-1_105070_2023-04-24_final
2023-05-02 09:57:26	ga_ls8c_ard_3-2-1_097070_2023-05-02_final
2023-05-03 10:40:41	ga_ls8c_ard_3-2-1_104070_2023-05-03_final
2023-05-06 11:11:32	ga_ls8c_ard_3-2-1_109070_2023-05-06_final
2023-05-08 10:59:09	ga_ls8c_ard_3-2-1_107070_2023-05-08_final
2023-05-09 10:03:30	ga_ls8c_ard_3-2-1_098070_2023-05-09_final
2023-05-10 10:46:45	ga_ls8c_ard_3-2-1_105070_2023-05-10_final
2023-05-11 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-11_final
2023-05-12 10:34:21	ga_ls8c_ard_3-2-1_103070_2023-05-12_final
2023-05-14 10:21:58	ga_ls8c_ard_3-2-1_101070_2023-05-14_final
2023-05-15 11:05:13	ga_ls8c_ard_3-2-1_108070_2023-05-15_final
2023-05-16 10:09:36	ga_ls8c_ard_3-2-1_099070_2023-05-16_final
2023-05-22 09:32:56	ga_ls8c_ard_3-2-1_093071_2023-05-22_final
2023-05-24 10:59:04	ga_ls8c_ard_3-2-1_107070_2023-05-24_final
2023-05-25 10:03:27	ga_ls8c_ard_3-2-1_098070_2023-05-25_final
2023-05-25 10:03:51	ga_ls8c_ard_3-2-1_098071_2023-05-25_final
2023-05-26 10:46:43	ga_ls8c_ard_3-2-1_105070_2023-05-26_final
2023-05-26 10:47:07	ga_ls8c_ard_3-2-1_105071_2023-05-26_final
2023-05-27 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-27_final
2023-05-28 10:34:22	ga_ls8c_ard_3-2-1_103070_2023-05-28_final
2023-05-28 10:34:45	ga_ls8c_ard_3-2-1_103071_2023-05-28_final
2023-05-29 11:17:37	ga_ls8c_ard_3-2-1_110070_2023-05-29_final
2023-05-29 11:18:01	ga_ls8c_ard_3-2-1_110071_2023-05-29_final
2023-05-30 10:22:00	ga_ls8c_ard_3-2-1_101070_2023-05-30_final
2023-05-30 10:22:24	ga_ls8c_ard_3-2-1_101071_2023-05-30_final
2023-05-31 09:26:46	ga_ls8c_ard_3-2-1_092071_2023-05-30_final
2023-05-31 11:05:15	ga_ls8c_ard_3-2-1_108070_2023-05-31_final
2023-05-31 11:05:39	ga_ls8c_ard_3-2-1_108071_2023-05-31_final
2023-06-01 10:09:38	ga_ls8c_ard_3-2-1_099070_2023-06-01_final
2023-06-01 10:10:02	ga_ls8c_ard_3-2-1_099071_2023-06-01_final
2023-06-02 10:52:54	ga_ls8c_ard_3-2-1_106070_2023-06-02_final
2023-06-02 10:53:18	ga_ls8c_ard_3-2-1_106071_2023-06-02_final
2023-06-23 11:11:36	ga_ls8c_ard_3-2-1_109070_2023-06-23_final
2023-07-12 10:03:51	ga_ls8c_ard_3-2-1_098070_2023-07-12_final
2023-07-12 10:04:15	ga_ls8c_ard_3-2-1_098071_2023-07-12_final
2023-07-15 10:34:45	ga_ls8c_ard_3-2-1_103070_2023-07-15_final
2023-07-15 10:35:09	ga_ls8c_ard_3-2-1_103071_2023-07-15_final
2023-07-16 09:39:32	ga_ls8c_ard_3-2-1_094071_2023-07-16_final
2023-07-16 11:18:01	ga_ls8c_ard_3-2-1_110070_2023-07-16_final
2023-07-16 11:18:25	ga_ls8c_ard_3-2-1_110071_2023-07-16_final
2023-07-17 10:22:24	ga_ls8c_ard_3-2-1_101070_2023-07-17_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