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
2014-10-07 10:04:44	ga_ls8c_ard_3-0-0_098071_2014-10-07_final
2014-10-07 10:05:08	ga_ls8c_ard_3-0-0_098072_2014-10-07_final
2014-10-08 10:48:00	ga_ls8c_ard_3-0-0_105071_2014-10-08_final
2014-10-08 10:48:24	ga_ls8c_ard_3-0-0_105072_2014-10-08_final
2014-10-09 09:52:23	ga_ls8c_ard_3-0-0_096071_2014-10-09_final
2014-10-09 09:52:47	ga_ls8c_ard_3-0-0_096072_2014-10-09_final
2014-10-09 11:31:16	ga_ls8c_ard_3-0-0_112071_2014-10-09_final
2014-10-09 11:31:40	ga_ls8c_ard_3-0-0_112072_2014-10-09_final
2014-10-10 10:35:39	ga_ls8c_ard_3-0-0_103071_2014-10-10_final
2014-10-10 10:36:03	ga_ls8c_ard_3-0-0_103072_2014-10-10_final
2014-10-11 09:40:02	ga_ls8c_ard_3-0-0_094071_2014-10-11_final
2014-10-11 09:40:26	ga_ls8c_ard_3-0-0_094072_2014-10-11_final
2014-10-11 11:18:55	ga_ls8c_ard_3-0-0_110071_2014-10-11_final
2014-10-11 11:19:19	ga_ls8c_ard_3-0-0_110072_2014-10-11_final
2014-10-12 10:23:18	ga_ls8c_ard_3-0-0_101071_2014-10-12_final
2014-10-12 10:23:42	ga_ls8c_ard_3-1-0_101072_2014-10-12_final
2014-12-16 09:27:58	ga_ls8c_ard_3-0-0_092072_2014-12-15_final
2014-12-16 11:06:27	ga_ls8c_ard_3-0-0_108071_2014-12-16_final
2014-12-16 11:06:51	ga_ls8c_ard_3-0-0_108072_2014-12-16_final
2014-12-17 10:10:51	ga_ls8c_ard_3-0-0_099071_2014-12-17_final
2014-12-17 10:11:14	ga_ls8c_ard_3-0-0_099072_2014-12-17_final
2014-12-18 10:54:06	ga_ls8c_ard_3-0-0_106071_2014-12-18_final
2014-12-18 10:54:30	ga_ls8c_ard_3-0-0_106072_2014-12-18_final
2017-07-04 09:58:09	ga_ls8c_ard_3-0-0_097071_2017-07-04_final
2017-07-04 09:58:33	ga_ls8c_ard_3-0-0_097072_2017-07-04_final
2017-07-04 11:37:26	ga_ls8c_ard_3-0-0_113072_2017-07-04_final
2017-07-05 10:41:25	ga_ls8c_ard_3-0-0_104071_2017-07-05_final
2017-07-05 10:41:49	ga_ls8c_ard_3-0-0_104072_2017-07-05_final
2017-07-06 09:45:48	ga_ls8c_ard_3-0-0_095071_2017-07-06_final
2017-07-06 09:46:12	ga_ls8c_ard_3-0-0_095072_2017-07-06_final
2017-07-06 11:24:41	ga_ls8c_ard_3-0-0_111071_2017-07-06_final
2017-07-06 11:25:05	ga_ls8c_ard_3-0-0_111072_2017-07-06_final
2017-07-07 10:29:04	ga_ls8c_ard_3-0-0_102071_2017-07-07_final
2017-07-07 10:29:28	ga_ls8c_ard_3-0-0_102072_2017-07-07_final
2017-07-08 09:33:26	ga_ls8c_ard_3-0-0_093071_2017-07-08_final
2017-07-08 09:33:50	ga_ls8c_ard_3-0-0_093072_2017-07-08_final
2017-07-08 11:12:19	ga_ls8c_ard_3-0-0_109071_2017-07-08_final
2017-07-08 11:12:43	ga_ls8c_ard_3-0-0_109072_2017-07-08_final
2017-07-09 10:16:42	ga_ls8c_ard_3-0-0_100071_2017-07-09_final
2017-07-09 10:17:06	ga_ls8c_ard_3-0-0_100072_2017-07-09_final
2017-07-14 10:35:15	ga_ls8c_ard_3-0-0_103071_2017-07-14_final
2017-07-14 10:35:39	ga_ls8c_ard_3-0-0_103072_2017-07-14_final
2017-07-15 09:39:39	ga_ls8c_ard_3-0-0_094071_2017-07-15_final
2017-07-15 09:40:03	ga_ls8c_ard_3-0-0_094072_2017-07-15_final
2017-07-15 11:18:32	ga_ls8c_ard_3-0-0_110071_2017-07-15_final
2017-07-15 11:18:56	ga_ls8c_ard_3-0-0_110072_2017-07-15_final
2017-07-16 10:22:55	ga_ls8c_ard_3-0-0_101071_2017-07-16_final
2017-07-16 10:23:19	ga_ls8c_ard_3-0-0_101072_2017-07-16_final
2018-04-22 09:32:53	ga_ls8c_ard_3-0-0_093071_2018-04-22_final
2018-04-22 09:33:17	ga_ls8c_ard_3-0-0_093072_2018-04-22_final
2018-04-22 11:12:10	ga_ls8c_ard_3-0-0_109072_2018-04-22_final
2018-04-23 10:16:33	ga_ls8c_ard_3-0-0_100072_2018-04-23_final
2018-04-24 09:20:55	ga_ls8c_ard_3-0-0_091072_2018-04-23_final
2018-04-24 10:59:48	ga_ls8c_ard_3-0-0_107072_2018-04-24_final
2018-07-14 10:03:42	ga_ls8c_ard_3-1-0_098071_2018-07-14_final
2018-07-14 10:04:06	ga_ls8c_ard_3-1-0_098072_2018-07-14_final
2018-07-15 10:46:58	ga_ls8c_ard_3-0-0_105071_2018-07-15_final
2018-07-15 10:47:22	ga_ls8c_ard_3-0-0_105072_2018-07-15_final
2018-07-16 09:51:21	ga_ls8c_ard_3-0-0_096071_2018-07-16_final
2018-07-16 09:51:45	ga_ls8c_ard_3-0-0_096072_2018-07-16_final
2018-07-16 11:30:15	ga_ls8c_ard_3-0-0_112071_2018-07-16_final
2018-07-16 11:30:39	ga_ls8c_ard_3-0-0_112072_2018-07-16_final
2018-07-20 09:26:40	ga_ls8c_ard_3-0-0_092071_2018-07-19_final
2018-07-20 09:27:04	ga_ls8c_ard_3-0-0_092072_2018-07-19_final
2018-07-20 11:05:33	ga_ls8c_ard_3-0-0_108071_2018-07-20_final
2018-07-20 11:05:57	ga_ls8c_ard_3-0-0_108072_2018-07-20_final
2018-07-21 10:09:56	ga_ls8c_ard_3-0-0_099071_2018-07-21_final
2018-07-21 10:10:20	ga_ls8c_ard_3-0-0_099072_2018-07-21_final
2018-07-22 10:53:12	ga_ls8c_ard_3-0-0_106071_2018-07-22_final
2018-07-22 10:53:36	ga_ls8c_ard_3-0-0_106072_2018-07-22_final
2023-02-04 09:52:58	ga_ls8c_ard_3-2-1_096072_2023-02-04_final
2023-02-04 11:31:51	ga_ls8c_ard_3-2-1_112072_2023-02-04_final
2023-03-01 09:46:28	ga_ls8c_ard_3-2-1_095072_2023-03-01_final
2023-03-01 11:24:57	ga_ls8c_ard_3-2-1_111071_2023-03-01_final
2023-03-01 11:25:21	ga_ls8c_ard_3-2-1_111072_2023-03-01_final
2023-03-02 10:29:43	ga_ls8c_ard_3-2-1_102072_2023-03-02_final
2023-03-03 09:33:41	ga_ls8c_ard_3-2-1_093071_2023-03-03_final
2023-03-03 09:34:05	ga_ls8c_ard_3-2-1_093072_2023-03-03_final
2023-03-03 11:12:58	ga_ls8c_ard_3-2-1_109072_2023-03-03_final
2023-03-04 10:16:57	ga_ls8c_ard_3-2-1_100071_2023-03-04_final
2023-03-04 10:17:21	ga_ls8c_ard_3-2-1_100072_2023-03-04_final
2023-03-19 09:33:57	ga_ls8c_ard_3-2-1_093072_2023-03-19_final
2023-03-19 11:12:50	ga_ls8c_ard_3-2-1_109072_2023-03-19_final
2023-03-20 10:16:48	ga_ls8c_ard_3-2-1_100071_2023-03-20_final
2023-03-20 10:17:12	ga_ls8c_ard_3-2-1_100072_2023-03-20_final
2023-03-23 10:48:03	ga_ls8c_ard_3-2-1_105072_2023-03-23_final
2023-03-24 09:52:01	ga_ls8c_ard_3-2-1_096071_2023-03-24_final
2023-03-24 09:52:25	ga_ls8c_ard_3-2-1_096072_2023-03-24_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_nrt
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_nrt
2023-10-19 10:35:35	ga_ls8c_ard_3-2-1_103071_2023-10-19_final
2023-10-19 10:35:59	ga_ls8c_ard_3-2-1_103072_2023-10-19_final
2023-10-20 09:39:58	ga_ls8c_ard_3-2-1_094071_2023-10-20_final
2023-10-20 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-20_final
2023-10-20 11:18:51	ga_ls8c_ard_3-2-1_110071_2023-10-20_final
2023-10-20 11:19:15	ga_ls8c_ard_3-2-1_110072_2023-10-20_final
2023-10-21 10:23:14	ga_ls8c_ard_3-2-1_101071_2023-10-21_final
2023-10-21 10:23:38	ga_ls8c_ard_3-2-1_101072_2023-10-21_final
2023-10-22 09:27:38	ga_ls8c_ard_3-2-1_092071_2023-10-21_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years