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
2022-02-01 11:36:24	ga_ls8c_ard_3-2-1_112084_2022-02-01_final
2022-02-07 09:22:01	ga_ls8c_ard_3-2-1_090088_2022-02-06_final
2022-02-16 09:14:35	ga_ls8c_ard_3-2-1_089085_2022-02-15_final
2022-02-16 10:46:41	ga_ls8c_ard_3-2-1_105068_2022-02-16_final
2022-02-18 10:34:18	ga_ls8c_ard_3-2-1_103068_2022-02-18_final
2022-02-24 11:38:28	ga_ls8c_ard_3-2-1_113074_2022-02-24_final
2022-02-26 11:24:55	ga_ls8c_ard_3-2-1_111071_2022-02-26_final
2022-03-03 11:47:02	ga_ls8c_ard_3-2-1_114080_2022-03-03_final
2022-03-05 11:31:28	ga_ls8c_ard_3-2-1_112072_2022-03-05_final
2022-03-08 10:23:05	ga_ls8c_ard_3-2-1_101071_2022-03-08_final
2022-03-16 11:15:15	ga_ls8c_ard_3-2-1_109078_2022-03-16_final
2022-03-18 09:23:11	ga_ls8c_ard_3-2-1_091076_2022-03-17_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-05 09:11:05	ga_ls8c_ard_3-2-1_089077_2022-04-04_final
2022-04-07 10:35:38	ga_ls8c_ard_3-2-1_103072_2022-04-07_final
2022-04-09 10:22:53	ga_ls8c_ard_3-2-1_101071_2022-04-09_final
2022-04-17 11:12:22	ga_ls8c_ard_3-2-1_109071_2022-04-17_final
2022-04-17 11:16:45	ga_ls8c_ard_3-2-1_109082_2022-04-17_final
2022-04-27 11:52:10	ga_ls8c_ard_3-2-1_115078_2022-04-27_final
2022-04-28 09:22:27	ga_ls8c_ard_3-2-1_090090_2022-04-27_final
2022-05-05 11:03:36	ga_ls8c_ard_3-2-1_107080_2022-05-05_final
2022-05-09 10:34:08	ga_ls8c_ard_3-2-1_103068_2022-05-09_final
2022-05-21 09:25:37	ga_ls8c_ard_3-2-1_091082_2022-05-20_final
2022-05-23 09:16:03	ga_ls8c_ard_3-2-1_089089_2022-05-22_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-06-11 11:19:14	ga_ls8c_ard_3-2-1_110072_2022-06-11_final
2022-06-15 09:17:16	ga_ls8c_ard_3-2-1_090076_2022-06-14_final
2022-06-18 11:28:41	ga_ls8c_ard_3-2-1_111080_2022-06-18_final
2022-06-18 11:29:52	ga_ls8c_ard_3-2-1_111083_2022-06-18_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_final
2022-06-20 11:14:20	ga_ls8c_ard_3-2-1_109075_2022-06-20_final
2022-06-24 09:11:57	ga_ls8c_ard_3-2-1_089078_2022-06-23_final
2022-06-27 09:46:27	ga_ls8c_ard_3-2-1_094087_2022-06-27_final
2022-07-07 10:22:20	ga_ls8c_ard_3-2-1_100084_2022-07-07_final
2022-07-25 10:10:05	ga_ls8c_ard_3-2-1_098084_2022-07-25_final
2022-08-07 09:40:30	ga_ls8c_ard_3-2-1_093087_2022-08-07_final
2022-08-10 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-08-10_final
2022-08-11 10:47:07	ga_ls8c_ard_3-2-1_105068_2022-08-11_final
2022-08-18 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-08-17_final
2022-08-21 11:26:13	ga_ls8c_ard_3-2-1_111073_2022-08-21_final
2022-08-23 09:34:59	ga_ls8c_ard_3-2-1_093073_2022-08-23_final
2022-09-02 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-09-02_final
2022-09-03 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-09-03_final
2022-09-06 11:26:15	ga_ls8c_ard_3-2-1_111073_2022-09-06_final
2022-09-10 11:00:22	ga_ls8c_ard_3-2-1_107070_2022-09-10_final
2022-09-18 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-09-18_final
2022-09-22 09:46:39	ga_ls8c_ard_3-2-1_095071_2022-09-22_final
2022-09-27 10:07:59	ga_ls8c_ard_3-2-1_098078_2022-09-27_final
2022-10-01 09:40:51	ga_ls8c_ard_3-2-1_094072_2022-10-01_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-06 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-06_final
2022-10-06 10:01:21	ga_ls8c_ard_3-2-1_097077_2022-10-06_final
2022-10-09 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-10-09_final
2022-10-14 10:49:30	ga_ls8c_ard_3-2-1_105074_2022-10-14_final
2022-10-22 09:58:09	ga_ls8c_ard_3-2-1_097069_2022-10-22_final
2022-10-22 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-22_final
2022-10-26 11:14:45	ga_ls8c_ard_3-2-1_109075_2022-10-26_final
2022-10-27 10:19:32	ga_ls8c_ard_3-2-1_100076_2022-10-27_final
2022-10-30 09:11:57	ga_ls8c_ard_3-2-1_089077_2022-10-29_final
2022-11-02 09:44:52	ga_ls8c_ard_3-2-1_094082_2022-11-02_final
2022-11-02 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-11-02_final
2022-11-04 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-11-03_final
2022-11-09 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-11-09_final
2022-12-01 10:49:34	ga_ls8c_ard_3-2-1_105074_2022-12-01_final
2022-12-02 11:36:49	ga_ls8c_ard_3-2-1_112084_2022-12-02_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-17 09:13:22	ga_ls8c_ard_3-2-1_089081_2022-12-16_final
2022-12-21 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-12-21_final
2022-12-23 10:09:54	ga_ls8c_ard_3-2-1_099068_2022-12-23_final
2023-01-02 09:10:32	ga_ls8c_ard_3-2-1_089074_2023-01-01_final
2023-01-05 09:41:02	ga_ls8c_ard_3-2-1_094073_2023-01-05_final
2023-01-05 11:19:07	ga_ls8c_ard_3-2-1_110071_2023-01-05_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-14 11:12:52	ga_ls8c_ard_3-2-1_109071_2023-01-14_final
2023-01-16 09:27:10	ga_ls8c_ard_3-2-1_091085_2023-01-15_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-01-25 09:21:03	ga_ls8c_ard_3-2-1_090085_2023-01-24_final
2023-01-26 11:38:01	ga_ls8c_ard_3-2-1_113072_2023-01-26_final
2023-01-26 11:38:49	ga_ls8c_ard_3-2-1_113074_2023-01-26_final
2023-01-30 09:35:37	ga_ls8c_ard_3-2-1_093075_2023-01-30_final
2023-02-06 11:24:40	ga_ls8c_ard_3-2-1_110085_2023-02-06_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-02-18 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-02-18_final
2023-02-27 11:38:30	ga_ls8c_ard_3-2-1_113074_2023-02-27_final
2023-03-06 10:03:22	ga_ls8c_ard_3-2-1_098068_2023-03-06_final
2023-03-10 09:39:48	ga_ls8c_ard_3-2-1_094071_2023-03-10_final
2023-03-14 09:16:40	ga_ls8c_ard_3-2-1_090075_2023-03-13_final
2023-03-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2023-03-17_final
2023-03-25 10:35:41	ga_ls8c_ard_3-2-1_103072_2023-03-25_final
2023-03-28 09:33:40	ga_ls8c_ard_3-2-1_092087_2023-03-28_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-04-02 11:24:15	ga_ls8c_ard_3-2-1_111070_2023-04-02_final
2023-04-05 10:18:36	ga_ls8c_ard_3-2-1_100076_2023-04-05_final
2023-04-28 10:27:22	ga_ls8c_ard_3-2-1_101083_2023-04-28_final
2023-05-09 10:06:42	ga_ls8c_ard_3-2-1_098078_2023-05-09_final
2023-05-15 09:28:20	ga_ls8c_ard_3-2-1_092075_2023-05-14_final
2023-05-16 10:09:36	ga_ls8c_ard_3-2-1_099070_2023-05-16_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