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
2015-01-14 10:35:29	ga_ls8c_ard_3-0-0_103071_2015-01-14_final
2015-01-14 10:35:53	ga_ls8c_ard_3-0-0_103072_2015-01-14_final
2015-01-15 09:39:51	ga_ls8c_ard_3-0-0_094071_2015-01-15_final
2015-01-15 09:40:15	ga_ls8c_ard_3-0-0_094072_2015-01-15_final
2015-01-15 11:18:44	ga_ls8c_ard_3-0-0_110071_2015-01-15_final
2015-01-15 11:19:08	ga_ls8c_ard_3-0-0_110072_2015-01-15_final
2015-01-16 10:23:06	ga_ls8c_ard_3-0-0_101071_2015-01-16_final
2015-01-16 10:23:30	ga_ls8c_ard_3-0-0_101072_2015-01-16_final
2015-01-17 09:27:53	ga_ls8c_ard_3-0-0_092072_2015-01-16_final
2015-01-17 11:06:22	ga_ls8c_ard_3-0-0_108071_2015-01-17_final
2015-01-17 11:06:46	ga_ls8c_ard_3-0-0_108072_2015-01-17_final
2015-01-18 10:11:08	ga_ls8c_ard_3-0-0_099072_2015-01-18_final
2015-01-19 10:54:23	ga_ls8c_ard_3-0-0_106072_2015-01-19_final
2015-02-16 09:39:38	ga_ls8c_ard_3-0-0_094071_2015-02-16_final
2015-02-16 09:40:02	ga_ls8c_ard_3-0-0_094072_2015-02-16_final
2015-02-16 11:18:55	ga_ls8c_ard_3-0-0_110072_2015-02-16_final
2015-02-17 10:23:18	ga_ls8c_ard_3-0-0_101072_2015-02-17_final
2015-02-18 09:27:40	ga_ls8c_ard_3-0-0_092072_2015-02-17_final
2015-02-18 11:06:33	ga_ls8c_ard_3-0-0_108072_2015-02-18_final
2015-02-19 10:10:56	ga_ls8c_ard_3-0-0_099072_2015-02-19_final
2015-02-20 10:54:12	ga_ls8c_ard_3-0-0_106072_2015-02-20_final
2015-02-28 10:04:19	ga_ls8c_ard_3-1-0_098071_2015-02-28_final
2015-02-28 10:04:43	ga_ls8c_ard_3-0-0_098072_2015-02-28_final
2015-03-01 10:47:59	ga_ls8c_ard_3-1-0_105072_2015-03-01_final
2015-03-19 10:35:26	ga_ls8c_ard_3-0-0_103072_2015-03-19_final
2015-03-20 11:18:41	ga_ls8c_ard_3-0-0_110072_2015-03-20_final
2015-03-21 10:23:03	ga_ls8c_ard_3-0-0_101072_2015-03-21_final
2017-04-02 10:29:14	ga_ls8c_ard_3-0-0_102072_2017-04-02_final
2017-04-03 09:33:36	ga_ls8c_ard_3-0-0_093072_2017-04-03_final
2017-04-03 11:12:29	ga_ls8c_ard_3-0-0_109072_2017-04-03_final
2017-04-04 10:16:51	ga_ls8c_ard_3-0-0_100072_2017-04-04_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
2017-07-14 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
2019-07-11 10:41:34	ga_ls8c_ard_3-1-0_104071_2019-07-11_final
2019-07-11 10:41:58	ga_ls8c_ard_3-1-0_104072_2019-07-11_final
2019-07-12 09:45:56	ga_ls8c_ard_3-1-0_095071_2019-07-12_final
2019-07-12 09:46:20	ga_ls8c_ard_3-1-0_095072_2019-07-12_final
2019-07-12 11:24:50	ga_ls8c_ard_3-1-0_111071_2019-07-12_final
2019-07-12 11:25:13	ga_ls8c_ard_3-1-0_111072_2019-07-12_final
2019-09-06 10:35:40	ga_ls8c_ard_3-1-0_103071_2019-09-06_final
2019-09-06 10:36:03	ga_ls8c_ard_3-1-0_103072_2019-09-06_final
2019-09-07 09:40:03	ga_ls8c_ard_3-1-0_094071_2019-09-07_final
2019-09-07 09:40:27	ga_ls8c_ard_3-1-0_094072_2019-09-07_final
2019-09-07 11:18:56	ga_ls8c_ard_3-1-0_110071_2019-09-07_final
2019-09-07 11:19:20	ga_ls8c_ard_3-1-0_110072_2019-09-07_final
2019-09-08 10:23:19	ga_ls8c_ard_3-1-0_101071_2019-09-08_final
2019-09-08 10:23:43	ga_ls8c_ard_3-1-0_101072_2019-09-08_final
2019-10-24 10:36:14	ga_ls8c_ard_3-1-0_103072_2019-10-24_final
2019-10-25 09:40:37	ga_ls8c_ard_3-1-0_094072_2019-10-25_final
2019-10-25 11:19:06	ga_ls8c_ard_3-1-0_110071_2019-10-25_final
2019-10-25 11:19:30	ga_ls8c_ard_3-1-0_110072_2019-10-25_final
2019-10-26 10:23:29	ga_ls8c_ard_3-1-0_101071_2019-10-26_final
2019-10-26 10:23:53	ga_ls8c_ard_3-1-0_101072_2019-10-26_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 11:25:21	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 09:34:05	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 10:17:12	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
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_final
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_nrt
2023-10-14 10:17:28	ga_ls8c_ard_3-2-1_100072_2023-10-14_nrt
2023-10-15 09:21:51	ga_ls8c_ard_3-2-1_091072_2023-10-14_nrt
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_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
2023-10-16 10:04:42	ga_ls8c_ard_3-2-1_098071_2023-10-16_final
2023-10-16 10:05:06	ga_ls8c_ard_3-2-1_098072_2023-10-16_final
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 09:40:21	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