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
2018-02-19 10:59:57	ga_ls8c_ard_3-0-0_107071_2018-02-19_final
2018-03-07 10:59:49	ga_ls8c_ard_3-0-0_107071_2018-03-07_final
2018-04-08 10:59:33	ga_ls8c_ard_3-0-0_107071_2018-04-08_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_2018-09-16_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2019-01-22 10:04:21	ga_ls8c_ard_3-0-0_098071_2019-01-22_final
2019-01-23 10:47:36	ga_ls8c_ard_3-0-0_105071_2019-01-23_final
2019-01-24 09:51:59	ga_ls8c_ard_3-0-0_096071_2019-01-24_final
2019-01-24 11:30:52	ga_ls8c_ard_3-0-0_112071_2019-01-24_final
2019-01-25 10:35:14	ga_ls8c_ard_3-0-0_103071_2019-01-25_final
2019-01-30 10:53:46	ga_ls8c_ard_3-0-0_106071_2019-01-30_final
2019-01-31 09:58:08	ga_ls8c_ard_3-0-0_097071_2019-01-31_final
2019-02-01 10:41:24	ga_ls8c_ard_3-0-0_104071_2019-02-01_final
2019-02-02 09:45:46	ga_ls8c_ard_3-0-0_095071_2019-02-02_final
2019-02-02 11:24:39	ga_ls8c_ard_3-0-0_111071_2019-02-02_final
2019-02-03 10:29:02	ga_ls8c_ard_3-0-0_102071_2019-02-03_final
2019-02-04 09:33:25	ga_ls8c_ard_3-0-0_093071_2019-02-04_final
2019-02-04 11:12:18	ga_ls8c_ard_3-0-0_109071_2019-02-04_final
2019-02-05 10:16:40	ga_ls8c_ard_3-0-0_100071_2019-02-05_final
2019-02-06 10:59:56	ga_ls8c_ard_3-0-0_107071_2019-02-06_final
2019-02-07 10:04:18	ga_ls8c_ard_3-0-0_098071_2019-02-07_final
2019-02-08 10:47:34	ga_ls8c_ard_3-0-0_105071_2019-02-08_final
2019-02-09 09:51:56	ga_ls8c_ard_3-0-0_096071_2019-02-09_final
2019-02-09 11:30:50	ga_ls8c_ard_3-0-0_112071_2019-02-09_final
2019-02-10 10:35:12	ga_ls8c_ard_3-0-0_103071_2019-02-10_final
2019-03-01 09:27:09	ga_ls8c_ard_3-0-0_092071_2019-02-28_final
2019-03-01 11:06:02	ga_ls8c_ard_3-0-0_108071_2019-03-01_final
2019-03-02 10:10:24	ga_ls8c_ard_3-0-0_099071_2019-03-02_final
2019-03-03 10:53:39	ga_ls8c_ard_3-0-0_106071_2019-03-03_final
2019-03-04 09:58:02	ga_ls8c_ard_3-0-0_097071_2019-03-04_final
2019-03-04 11:36:55	ga_ls8c_ard_3-0-0_113071_2019-03-04_final
2019-03-05 10:41:17	ga_ls8c_ard_3-0-0_104071_2019-03-05_final
2019-03-11 10:04:10	ga_ls8c_ard_3-1-0_098071_2019-03-11_final
2019-03-12 10:47:25	ga_ls8c_ard_3-1-0_105071_2019-03-12_final
2019-03-13 09:51:47	ga_ls8c_ard_3-1-0_096071_2019-03-13_final
2019-03-13 11:30:40	ga_ls8c_ard_3-1-0_112071_2019-03-13_final
2019-03-14 10:35:03	ga_ls8c_ard_3-1-0_103071_2019-03-14_final
2019-04-05 09:57:53	ga_ls8c_ard_3-1-0_097071_2019-04-05_final
2019-04-05 11:36:46	ga_ls8c_ard_3-1-0_113071_2019-04-05_final
2019-04-06 10:41:09	ga_ls8c_ard_3-1-0_104071_2019-04-06_final
2019-05-05 10:10:11	ga_ls8c_ard_3-0-0_099071_2019-05-05_final
2019-05-05 10:10:35	ga_ls8c_ard_3-0-0_099072_2019-05-05_final
2019-05-06 10:53:27	ga_ls8c_ard_3-0-0_106071_2019-05-06_final
2019-05-07 09:57:51	ga_ls8c_ard_3-0-0_097071_2019-05-07_final
2019-05-07 11:36:44	ga_ls8c_ard_3-0-0_113071_2019-05-07_final
2019-05-08 10:41:07	ga_ls8c_ard_3-0-0_104071_2019-05-08_final
2019-06-05 09:27:13	ga_ls8c_ard_3-0-0_092071_2019-06-04_final
2019-06-05 11:06:06	ga_ls8c_ard_3-0-0_108071_2019-06-05_final
2019-06-06 10:10:29	ga_ls8c_ard_3-0-0_099071_2019-06-06_final
2019-06-07 10:53:46	ga_ls8c_ard_3-0-0_106071_2019-06-07_final
2019-06-08 09:58:09	ga_ls8c_ard_3-0-0_097071_2019-06-08_final
2019-06-08 11:37:02	ga_ls8c_ard_3-0-0_113071_2019-06-08_final
2019-06-09 10:41:25	ga_ls8c_ard_3-0-0_104071_2019-06-09_final
2020-03-13 10:04:25	ga_ls8c_ard_3-1-0_098071_2020-03-13_final
2020-03-14 10:47:40	ga_ls8c_ard_3-1-0_105071_2020-03-14_final
2020-04-09 09:45:39	ga_ls8c_ard_3-1-0_095071_2020-04-09_final
2020-04-09 11:24:32	ga_ls8c_ard_3-1-0_111071_2020-04-09_final
2020-04-10 10:28:54	ga_ls8c_ard_3-1-0_102071_2020-04-10_final
2020-04-11 09:33:16	ga_ls8c_ard_3-1-0_093071_2020-04-11_final
2020-04-11 11:12:09	ga_ls8c_ard_3-1-0_109071_2020-04-11_final
2020-04-12 10:16:32	ga_ls8c_ard_3-1-0_100071_2020-04-12_final
2020-04-13 10:59:47	ga_ls8c_ard_3-1-0_107071_2020-04-13_final
2020-04-14 10:04:09	ga_ls8c_ard_3-1-0_098071_2020-04-14_final
2020-04-27 11:12:02	ga_ls8c_ard_3-1-0_109071_2020-04-27_final
2020-04-28 10:16:24	ga_ls8c_ard_3-1-0_100071_2020-04-28_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-21 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-08-21_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-22 10:29:48	ga_ls8c_ard_3-2-1_102071_2022-08-22_final
2022-08-23 09:34:11	ga_ls8c_ard_3-2-1_093071_2022-08-23_final
2022-08-23 11:13:04	ga_ls8c_ard_3-2-1_109071_2022-08-23_final
2022-08-24 10:17:27	ga_ls8c_ard_3-2-1_100071_2022-08-24_final
2022-08-25 11:00:42	ga_ls8c_ard_3-2-1_107071_2022-08-25_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-08-29 10:35:59	ga_ls8c_ard_3-2-1_103071_2022-08-29_final
2022-08-30 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-30_final
2022-09-10 11:00:46	ga_ls8c_ard_3-2-1_107071_2022-09-10_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-10-04 10:11:20	ga_ls8c_ard_3-2-1_099071_2022-10-04_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-06 11:38:15	ga_ls8c_ard_3-2-1_113072_2022-10-06_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-08 09:46:35	ga_ls8c_ard_3-2-1_095071_2022-10-08_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-10 09:34:12	ga_ls8c_ard_3-2-1_093071_2022-10-10_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-11 10:17:26	ga_ls8c_ard_3-2-1_100071_2022-10-11_final
2022-10-28 11:00:48	ga_ls8c_ard_3-2-1_107071_2022-10-28_final
2022-10-29 10:05:11	ga_ls8c_ard_3-2-1_098071_2022-10-29_final
2022-10-30 10:48:27	ga_ls8c_ard_3-2-1_105071_2022-10-30_final
2022-10-31 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-10-31_final
2022-11-01 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-11-01_final
2022-11-02 09:40:28	ga_ls8c_ard_3-2-1_094071_2022-11-02_final
2022-11-02 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-11-02_final
2022-11-03 10:23:44	ga_ls8c_ard_3-2-1_101071_2022-11-03_final
2022-11-04 09:28:06	ga_ls8c_ard_3-2-1_092071_2022-11-03_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