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
2018-05-26 10:58:38	ga_ls8c_ard_3-0-0_107070_2018-05-26_final
2018-06-02 09:26:15	ga_ls8c_ard_3-0-0_092071_2018-06-01_final
2018-06-02 11:04:44	ga_ls8c_ard_3-0-0_108070_2018-06-02_final
2018-06-02 11:05:08	ga_ls8c_ard_3-0-0_108071_2018-06-02_final
2018-06-03 10:09:07	ga_ls8c_ard_3-0-0_099070_2018-06-03_final
2018-06-03 10:09:30	ga_ls8c_ard_3-0-0_099071_2018-06-03_final
2018-06-04 10:52:22	ga_ls8c_ard_3-0-0_106070_2018-06-04_final
2018-06-04 10:52:46	ga_ls8c_ard_3-0-0_106071_2018-06-04_final
2018-06-05 09:56:44	ga_ls8c_ard_3-0-0_097070_2018-06-05_final
2018-06-05 09:57:08	ga_ls8c_ard_3-0-0_097071_2018-06-05_final
2018-06-06 10:40:00	ga_ls8c_ard_3-0-0_104070_2018-06-06_final
2018-06-06 10:40:24	ga_ls8c_ard_3-0-0_104071_2018-06-06_final
2018-06-27 10:58:47	ga_ls8c_ard_3-0-0_107070_2018-06-27_final
2018-06-27 10:59:11	ga_ls8c_ard_3-0-0_107071_2018-06-27_final
2018-07-29 10:59:02	ga_ls8c_ard_3-0-0_107070_2018-07-29_final
2018-07-29 10:59:26	ga_ls8c_ard_3-0-0_107071_2018-07-29_final
2018-08-07 10:52:57	ga_ls8c_ard_3-0-0_106070_2018-08-07_final
2018-08-07 10:53:21	ga_ls8c_ard_3-0-0_106071_2018-08-07_final
2018-08-08 09:57:20	ga_ls8c_ard_3-0-0_097070_2018-08-08_final
2018-08-08 09:57:44	ga_ls8c_ard_3-0-0_097071_2018-08-08_final
2018-08-09 10:40:36	ga_ls8c_ard_3-0-0_104070_2018-08-09_final
2018-08-09 10:41:00	ga_ls8c_ard_3-0-0_104071_2018-08-09_final
2018-09-06 09:27:03	ga_ls8c_ard_3-0-0_092071_2018-09-05_final
2018-09-06 11:05:32	ga_ls8c_ard_3-0-0_108070_2018-09-06_final
2018-09-06 11:05:56	ga_ls8c_ard_3-0-0_108071_2018-09-06_final
2018-09-07 10:09:55	ga_ls8c_ard_3-0-0_099070_2018-09-07_final
2018-09-07 10:10:19	ga_ls8c_ard_3-0-0_099071_2018-09-07_final
2018-09-08 10:53:11	ga_ls8c_ard_3-0-0_106070_2018-09-08_final
2018-09-09 09:57:34	ga_ls8c_ard_3-1-0_097070_2018-09-09_final
2018-09-09 09:57:58	ga_ls8c_ard_3-0-0_097071_2018-09-09_final
2018-09-10 10:40:50	ga_ls8c_ard_3-0-0_104070_2018-09-10_final
2018-09-10 10:41:14	ga_ls8c_ard_3-0-0_104071_2018-09-10_final
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_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
2018-10-20 09:51:39	ga_ls8c_ard_3-0-0_096070_2018-10-20_final
2018-10-20 09:52:03	ga_ls8c_ard_3-0-0_096071_2018-10-20_final
2018-10-20 11:30:32	ga_ls8c_ard_3-0-0_112070_2018-10-20_final
2018-10-20 11:30:56	ga_ls8c_ard_3-0-0_112071_2018-10-20_final
2018-10-21 10:34:55	ga_ls8c_ard_3-0-0_103070_2018-10-21_final
2018-10-22 09:39:42	ga_ls8c_ard_3-0-0_094071_2018-10-22_final
2018-10-22 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-10-22_final
2018-10-22 11:18:35	ga_ls8c_ard_3-0-0_110071_2018-10-22_final
2018-10-23 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-10-23_final
2018-10-23 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-10-23_final
2018-11-05 09:51:43	ga_ls8c_ard_3-0-0_096070_2018-11-05_final
2018-11-05 09:52:07	ga_ls8c_ard_3-0-0_096071_2018-11-05_final
2018-11-05 11:30:36	ga_ls8c_ard_3-0-0_112070_2018-11-05_final
2018-11-05 11:31:00	ga_ls8c_ard_3-0-0_112071_2018-11-05_final
2018-11-06 10:34:58	ga_ls8c_ard_3-0-0_103070_2018-11-06_final
2018-11-06 10:35:22	ga_ls8c_ard_3-0-0_103071_2018-11-06_final
2018-11-07 09:39:45	ga_ls8c_ard_3-0-0_094071_2018-11-07_final
2018-11-07 11:18:14	ga_ls8c_ard_3-0-0_110070_2018-11-07_final
2018-11-07 11:18:38	ga_ls8c_ard_3-0-0_110071_2018-11-07_final
2018-11-08 10:22:37	ga_ls8c_ard_3-0-0_101070_2018-11-08_final
2018-11-08 10:23:01	ga_ls8c_ard_3-0-0_101071_2018-11-08_final
2018-12-23 09:51:40	ga_ls8c_ard_3-0-0_096070_2018-12-23_final
2018-12-23 09:52:04	ga_ls8c_ard_3-0-0_096071_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 09:39:42	ga_ls8c_ard_3-0-0_094071_2018-12-25_final
2018-12-25 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-12-25_final
2018-12-25 11:18:35	ga_ls8c_ard_3-0-0_110071_2018-12-25_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2018-12-26 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-26_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
2023-07-25 09:33:25	ga_ls8c_ard_3-2-1_093071_2023-07-25_final
2023-07-25 11:11:54	ga_ls8c_ard_3-2-1_109070_2023-07-25_final
2023-07-25 11:12:18	ga_ls8c_ard_3-2-1_109071_2023-07-25_final
2023-07-26 10:16:41	ga_ls8c_ard_3-2-1_100071_2023-07-26_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-07-27 10:59:58	ga_ls8c_ard_3-2-1_107071_2023-07-27_final
2023-08-03 09:27:19	ga_ls8c_ard_3-2-1_092071_2023-08-02_final
2023-08-03 11:05:48	ga_ls8c_ard_3-2-1_108070_2023-08-03_final
2023-08-03 11:06:12	ga_ls8c_ard_3-2-1_108071_2023-08-03_final
2023-08-04 10:10:11	ga_ls8c_ard_3-2-1_099070_2023-08-04_final
2023-08-04 10:10:35	ga_ls8c_ard_3-2-1_099071_2023-08-04_final
2023-08-06 09:57:50	ga_ls8c_ard_3-2-1_097070_2023-08-06_final
2023-08-06 09:58:13	ga_ls8c_ard_3-2-1_097071_2023-08-06_final
2023-08-07 10:41:05	ga_ls8c_ard_3-2-1_104070_2023-08-07_final
2023-08-07 10:41:29	ga_ls8c_ard_3-2-1_104071_2023-08-07_final
2023-08-08 09:45:52	ga_ls8c_ard_3-2-1_095071_2023-08-08_final
2023-08-08 11:24:21	ga_ls8c_ard_3-2-1_111070_2023-08-08_final
2023-08-08 11:24:45	ga_ls8c_ard_3-2-1_111071_2023-08-08_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-09 10:29:07	ga_ls8c_ard_3-2-1_102071_2023-08-09_final
2023-08-12 10:59:38	ga_ls8c_ard_3-2-1_107070_2023-08-12_final
2023-08-12 11:00:02	ga_ls8c_ard_3-2-1_107071_2023-08-12_final
2023-08-13 10:04:02	ga_ls8c_ard_3-2-1_098070_2023-08-13_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-14 10:47:18	ga_ls8c_ard_3-2-1_105070_2023-08-14_final
2023-08-14 10:47:42	ga_ls8c_ard_3-2-1_105071_2023-08-14_final
2023-08-15 09:51:42	ga_ls8c_ard_3-2-1_096070_2023-08-15_final
2023-08-15 09:52:06	ga_ls8c_ard_3-2-1_096071_2023-08-15_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-08-31 09:52:11	ga_ls8c_ard_3-2-1_096071_2023-08-31_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_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