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
2019-07-08 10:10:39	ga_ls8c_ard_3-1-0_099071_2019-07-08_final
2019-07-08 10:11:03	ga_ls8c_ard_3-1-0_099072_2019-07-08_final
2019-07-09 10:53:55	ga_ls8c_ard_3-1-0_106071_2019-07-09_final
2019-07-09 10:54:19	ga_ls8c_ard_3-1-0_106072_2019-07-09_final
2019-07-10 09:58:18	ga_ls8c_ard_3-1-0_097071_2019-07-10_final
2019-07-10 09:58:42	ga_ls8c_ard_3-1-0_097072_2019-07-10_final
2019-07-10 11:37:11	ga_ls8c_ard_3-1-0_113071_2019-07-10_final
2019-07-10 11:37:35	ga_ls8c_ard_3-1-0_113072_2019-07-10_final
2019-08-26 10:54:10	ga_ls8c_ard_3-1-0_106071_2019-08-26_final
2019-08-26 10:54:34	ga_ls8c_ard_3-1-0_106072_2019-08-26_final
2019-08-27 09:58:33	ga_ls8c_ard_3-1-0_097071_2019-08-27_final
2019-08-27 09:58:57	ga_ls8c_ard_3-1-0_097072_2019-08-27_final
2019-08-27 11:37:26	ga_ls8c_ard_3-1-0_113071_2019-08-27_final
2019-08-27 11:37:50	ga_ls8c_ard_3-1-0_113072_2019-08-27_final
2019-10-14 09:58:45	ga_ls8c_ard_3-1-0_097071_2019-10-14_final
2019-10-14 09:59:09	ga_ls8c_ard_3-1-0_097072_2019-10-14_final
2019-10-14 11:37:38	ga_ls8c_ard_3-1-0_113071_2019-10-14_final
2019-10-14 11:38:02	ga_ls8c_ard_3-1-0_113072_2019-10-14_final
2019-10-15 10:42:01	ga_ls8c_ard_3-1-0_104071_2019-10-15_final
2019-10-15 10:42:25	ga_ls8c_ard_3-1-0_104072_2019-10-15_final
2019-10-16 09:46:24	ga_ls8c_ard_3-1-0_095071_2019-10-16_final
2019-10-16 09:46:48	ga_ls8c_ard_3-1-0_095072_2019-10-16_final
2019-10-16 11:25:17	ga_ls8c_ard_3-1-0_111071_2019-10-16_final
2019-10-16 11:25:41	ga_ls8c_ard_3-1-0_111072_2019-10-16_final
2019-11-26 09:40:09	ga_ls8c_ard_3-1-0_094071_2019-11-26_final
2019-11-26 09:40:33	ga_ls8c_ard_3-1-0_094072_2019-11-26_final
2019-11-26 11:19:26	ga_ls8c_ard_3-1-0_110072_2019-11-26_final
2019-11-27 10:23:48	ga_ls8c_ard_3-1-0_101072_2019-11-27_final
2019-11-28 09:27:47	ga_ls8c_ard_3-1-0_092071_2019-11-27_final
2019-11-28 09:28:11	ga_ls8c_ard_3-1-0_092072_2019-11-27_final
2019-11-28 11:06:40	ga_ls8c_ard_3-1-0_108071_2019-11-28_final
2019-11-28 11:07:04	ga_ls8c_ard_3-1-0_108072_2019-11-28_final
2019-12-01 09:59:05	ga_ls8c_ard_3-1-0_097072_2019-12-01_final
2019-12-01 11:37:34	ga_ls8c_ard_3-1-0_113071_2019-12-01_final
2019-12-01 11:37:58	ga_ls8c_ard_3-1-0_113072_2019-12-01_final
2019-12-02 10:41:57	ga_ls8c_ard_3-1-0_104071_2019-12-02_final
2019-12-02 10:42:21	ga_ls8c_ard_3-1-0_104072_2019-12-02_final
2019-12-03 09:46:43	ga_ls8c_ard_3-1-0_095072_2019-12-03_final
2019-12-03 11:25:12	ga_ls8c_ard_3-1-0_111071_2019-12-03_final
2019-12-03 11:25:36	ga_ls8c_ard_3-1-0_111072_2019-12-03_final
2021-01-04 11:37:55	ga_ls8c_ard_3-2-0_113072_2021-01-04_final
2021-01-05 10:41:53	ga_ls8c_ard_3-2-0_104071_2021-01-05_final
2021-01-05 10:42:17	ga_ls8c_ard_3-2-0_104072_2021-01-05_final
2021-01-06 09:46:15	ga_ls8c_ard_3-2-0_095071_2021-01-06_final
2021-01-06 09:46:39	ga_ls8c_ard_3-2-0_095072_2021-01-06_final
2021-01-06 11:25:32	ga_ls8c_ard_3-2-0_111072_2021-01-06_final
2021-01-07 10:29:54	ga_ls8c_ard_3-2-0_102072_2021-01-07_final
2021-01-31 11:18:50	ga_ls8c_ard_3-2-0_110071_2021-01-31_final
2021-01-31 11:19:14	ga_ls8c_ard_3-2-0_110072_2021-01-31_final
2021-02-01 10:23:37	ga_ls8c_ard_3-2-0_101072_2021-02-01_final
2021-02-02 09:27:35	ga_ls8c_ard_3-2-0_092071_2021-02-01_final
2021-02-02 09:27:59	ga_ls8c_ard_3-2-0_092072_2021-02-01_final
2021-02-02 11:06:52	ga_ls8c_ard_3-2-0_108072_2021-02-02_final
2021-02-03 10:11:15	ga_ls8c_ard_3-2-0_099072_2021-02-03_final
2021-04-07 09:27:36	ga_ls8c_ard_3-2-0_092072_2021-04-06_final
2021-04-07 11:06:29	ga_ls8c_ard_3-2-0_108072_2021-04-07_final
2021-04-08 10:10:52	ga_ls8c_ard_3-2-0_099072_2021-04-08_final
2021-04-09 10:54:07	ga_ls8c_ard_3-2-0_106072_2021-04-09_final
2021-04-10 09:58:29	ga_ls8c_ard_3-2-0_097072_2021-04-10_final
2021-08-28 10:23:17	ga_ls8c_ard_3-2-0_101071_2021-08-28_final
2021-08-28 10:23:41	ga_ls8c_ard_3-2-0_101072_2021-08-28_final
2021-08-29 09:27:40	ga_ls8c_ard_3-2-0_092071_2021-08-28_final
2021-08-29 09:28:04	ga_ls8c_ard_3-2-0_092072_2021-08-28_final
2021-08-29 11:06:57	ga_ls8c_ard_3-2-0_108072_2021-08-29_final
2021-08-30 10:11:20	ga_ls8c_ard_3-2-0_099072_2021-08-30_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-11 09:58:41	ga_ls8c_ard_3-2-1_097071_2023-02-11_final
2023-02-11 09:59:05	ga_ls8c_ard_3-2-1_097072_2023-02-11_final
2023-02-11 11:37:58	ga_ls8c_ard_3-2-1_113072_2023-02-11_final
2023-02-12 10:41:56	ga_ls8c_ard_3-2-1_104071_2023-02-12_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-13 09:46:42	ga_ls8c_ard_3-2-1_095072_2023-02-13_final
2023-02-13 11:25:11	ga_ls8c_ard_3-2-1_111071_2023-02-13_final
2023-02-13 11:25:35	ga_ls8c_ard_3-2-1_111072_2023-02-13_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-15 09:33:55	ga_ls8c_ard_3-2-1_093071_2023-02-15_final
2023-02-15 09:34:19	ga_ls8c_ard_3-2-1_093072_2023-02-15_final
2023-02-15 11:13:12	ga_ls8c_ard_3-2-1_109072_2023-02-15_final
2023-02-16 10:17:09	ga_ls8c_ard_3-2-1_100071_2023-02-16_final
2023-02-16 10:17:33	ga_ls8c_ard_3-2-1_100072_2023-02-16_final
2023-02-17 09:21:55	ga_ls8c_ard_3-2-1_091072_2023-02-16_final
2023-02-17 11:00:48	ga_ls8c_ard_3-2-1_107072_2023-02-17_final
2023-02-18 10:04:46	ga_ls8c_ard_3-2-1_098071_2023-02-18_final
2023-02-18 10:05:10	ga_ls8c_ard_3-2-1_098072_2023-02-18_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-02-20 09:52:45	ga_ls8c_ard_3-2-1_096072_2023-02-20_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 09:34:05	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
2023-03-05 09:21:43	ga_ls8c_ard_3-2-1_091072_2023-03-04_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-05 11:00:36	ga_ls8c_ard_3-2-1_107072_2023-03-05_final
2023-03-06 10:04:58	ga_ls8c_ard_3-2-1_098072_2023-03-06_final
2023-03-07 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-03-07_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_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