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
2018-02-15 09:45:49	ga_ls8c_ard_3-0-0_095071_2018-02-15_final
2018-02-15 09:46:13	ga_ls8c_ard_3-0-0_095072_2018-02-15_final
2018-02-15 11:24:42	ga_ls8c_ard_3-0-0_111071_2018-02-15_final
2018-02-16 10:29:04	ga_ls8c_ard_3-0-0_102071_2018-02-16_final
2018-02-17 09:33:26	ga_ls8c_ard_3-0-0_093071_2018-02-17_final
2018-02-17 11:12:19	ga_ls8c_ard_3-0-0_109071_2018-02-17_final
2018-02-18 10:16:42	ga_ls8c_ard_3-0-0_100071_2018-02-18_final
2018-02-18 10:17:06	ga_ls8c_ard_3-0-0_100072_2018-02-18_final
2018-02-22 09:51:57	ga_ls8c_ard_3-0-0_096071_2018-02-22_final
2018-02-22 11:30:50	ga_ls8c_ard_3-0-0_112071_2018-02-22_final
2018-02-22 11:31:14	ga_ls8c_ard_3-0-0_112072_2018-02-22_final
2018-02-23 10:35:12	ga_ls8c_ard_3-0-0_103071_2018-02-23_final
2018-02-24 09:39:34	ga_ls8c_ard_3-0-0_094071_2018-02-24_final
2018-02-24 11:18:27	ga_ls8c_ard_3-0-0_110071_2018-02-24_final
2018-02-24 11:18:51	ga_ls8c_ard_3-0-0_110072_2018-02-24_final
2018-02-25 10:22:49	ga_ls8c_ard_3-0-0_101071_2018-02-25_final
2018-03-03 09:45:41	ga_ls8c_ard_3-0-0_095071_2018-03-03_final
2018-03-03 11:24:34	ga_ls8c_ard_3-0-0_111071_2018-03-03_final
2018-03-04 10:28:57	ga_ls8c_ard_3-0-0_102071_2018-03-04_final
2018-03-05 09:33:19	ga_ls8c_ard_3-0-0_093071_2018-03-05_final
2018-03-05 11:12:12	ga_ls8c_ard_3-0-0_109071_2018-03-05_final
2018-03-06 10:16:34	ga_ls8c_ard_3-0-0_100071_2018-03-06_final
2018-04-04 09:45:26	ga_ls8c_ard_3-0-0_095071_2018-04-04_final
2018-04-04 11:24:19	ga_ls8c_ard_3-0-0_111071_2018-04-04_final
2018-04-05 10:28:41	ga_ls8c_ard_3-0-0_102071_2018-04-05_final
2018-04-06 09:33:03	ga_ls8c_ard_3-0-0_093071_2018-04-06_final
2018-04-06 11:11:56	ga_ls8c_ard_3-0-0_109071_2018-04-06_final
2018-04-07 10:16:18	ga_ls8c_ard_3-0-0_100071_2018-04-07_final
2018-04-11 09:51:33	ga_ls8c_ard_3-0-0_096071_2018-04-11_final
2018-04-11 09:51:56	ga_ls8c_ard_3-0-0_096072_2018-04-11_final
2018-04-11 11:30:26	ga_ls8c_ard_3-0-0_112071_2018-04-11_final
2018-04-11 11:30:49	ga_ls8c_ard_3-0-0_112072_2018-04-11_final
2018-04-12 10:34:48	ga_ls8c_ard_3-0-0_103071_2018-04-12_final
2018-04-13 09:39:10	ga_ls8c_ard_3-0-0_094071_2018-04-13_final
2018-04-13 11:18:03	ga_ls8c_ard_3-0-0_110071_2018-04-13_final
2018-04-14 10:22:25	ga_ls8c_ard_3-0-0_101071_2018-04-14_final
2018-05-07 10:28:22	ga_ls8c_ard_3-0-0_102071_2018-05-07_final
2018-05-08 09:32:44	ga_ls8c_ard_3-0-0_093071_2018-05-08_final
2018-05-08 11:11:37	ga_ls8c_ard_3-0-0_109071_2018-05-08_final
2018-05-09 10:15:59	ga_ls8c_ard_3-0-0_100071_2018-05-09_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
2018-07-17 10:34:38	ga_ls8c_ard_3-0-0_103071_2018-07-17_final
2018-07-17 10:35:02	ga_ls8c_ard_3-0-0_103072_2018-07-17_final
2018-07-18 09:39:01	ga_ls8c_ard_3-0-0_094071_2018-07-18_final
2018-07-18 09:39:25	ga_ls8c_ard_3-0-0_094072_2018-07-18_final
2018-07-18 11:17:54	ga_ls8c_ard_3-0-0_110071_2018-07-18_final
2018-07-18 11:18:18	ga_ls8c_ard_3-0-0_110072_2018-07-18_final
2018-07-19 10:22:17	ga_ls8c_ard_3-0-0_101071_2018-07-19_final
2018-07-19 10:22:41	ga_ls8c_ard_3-0-0_101072_2018-07-19_final
2018-08-03 09:39:08	ga_ls8c_ard_3-0-0_094071_2018-08-03_final
2018-08-03 09:39:32	ga_ls8c_ard_3-0-0_094072_2018-08-03_final
2018-08-03 11:18:01	ga_ls8c_ard_3-0-0_110071_2018-08-03_final
2018-08-03 11:18:25	ga_ls8c_ard_3-0-0_110072_2018-08-03_final
2018-08-04 10:22:25	ga_ls8c_ard_3-0-0_101071_2018-08-04_final
2018-08-04 10:22:49	ga_ls8c_ard_3-0-0_101072_2018-08-04_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_2018-09-16_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-06 10:04:48	ga_ls8c_ard_3-0-0_098072_2019-01-06_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2019-01-07 10:48:04	ga_ls8c_ard_3-0-0_105072_2019-01-07_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-19 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-08-19_final
2022-08-21 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-08-21_final
2022-08-21 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-08-21_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-22 10:29:48	ga_ls8c_ard_3-2-1_102071_2022-08-22_final
2022-08-22 10:30:12	ga_ls8c_ard_3-2-1_102072_2022-08-22_final
2022-08-23 09:34:11	ga_ls8c_ard_3-2-1_093071_2022-08-23_final
2022-10-30 10:48:27	ga_ls8c_ard_3-2-1_105071_2022-10-30_final
2022-10-30 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-10-30_final
2022-10-31 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-10-31_final
2022-10-31 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-10-31_final
2022-11-01 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-11-01_final
2022-11-01 10:36:29	ga_ls8c_ard_3-2-1_103072_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
2022-11-03 10:24:08	ga_ls8c_ard_3-2-1_101072_2022-11-03_final
2022-11-04 09:28:06	ga_ls8c_ard_3-2-1_092071_2022-11-03_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-04 11:07:23	ga_ls8c_ard_3-2-1_108072_2022-11-04_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-07 09:59:00	ga_ls8c_ard_3-2-1_097071_2022-11-07_final
2022-11-07 11:38:17	ga_ls8c_ard_3-2-1_113072_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2023-09-02 09:39:49	ga_ls8c_ard_3-2-1_094071_2023-09-02_final
2023-09-02 09:40:13	ga_ls8c_ard_3-2-1_094072_2023-09-02_final
2023-09-02 11:18:42	ga_ls8c_ard_3-2-1_110071_2023-09-02_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