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
2022-06-24 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-06-24_final
2022-06-27 11:23:44	ga_ls8c_ard_3-2-1_110083_2022-06-27_final
2022-06-28 10:23:43	ga_ls8c_ard_3-2-1_101072_2022-06-28_final
2022-07-12 10:38:28	ga_ls8c_ard_3-2-1_103078_2022-07-12_final
2022-07-12 10:38:52	ga_ls8c_ard_3-2-1_103079_2022-07-12_final
2022-07-14 10:26:06	ga_ls8c_ard_3-2-1_101078_2022-07-14_final
2022-07-26 09:15:16	ga_ls8c_ard_3-2-1_089086_2022-07-25_final
2022-07-27 11:35:26	ga_ls8c_ard_3-2-1_112081_2022-07-27_final
2022-07-30 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-07-30_final
2022-08-02 09:21:31	ga_ls8c_ard_3-2-1_090086_2022-08-01_final
2022-08-02 10:58:49	ga_ls8c_ard_3-2-1_106082_2022-08-02_final
2022-08-04 10:46:28	ga_ls8c_ard_3-2-1_104082_2022-08-04_final
2022-08-06 10:30:08	ga_ls8c_ard_3-2-1_102072_2022-08-06_final
2022-08-07 09:37:43	ga_ls8c_ard_3-2-1_093080_2022-08-07_final
2022-08-07 11:13:48	ga_ls8c_ard_3-2-1_109073_2022-08-07_final
2022-08-08 10:19:23	ga_ls8c_ard_3-2-1_100076_2022-08-08_final
2022-08-11 09:13:01	ga_ls8c_ard_3-2-1_089080_2022-08-10_final
2022-08-12 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-08-12_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-25 09:24:13	ga_ls8c_ard_3-2-1_091077_2022-08-24_final
2022-09-01 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-09-01_final
2022-09-05 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-09-05_final
2022-09-12 10:52:49	ga_ls8c_ard_3-2-1_105082_2022-09-12_final
2022-09-17 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-09-17_final
2022-09-20 09:58:13	ga_ls8c_ard_3-2-1_097069_2022-09-20_final
2022-09-20 10:03:00	ga_ls8c_ard_3-2-1_097081_2022-09-20_final
2022-09-24 09:38:17	ga_ls8c_ard_3-2-1_093081_2022-09-24_final
2022-09-25 10:19:33	ga_ls8c_ard_3-2-1_100076_2022-09-25_final
2022-09-27 10:08:47	ga_ls8c_ard_3-2-1_098080_2022-09-27_final
2022-09-29 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-09-29_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-10-09 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-10-09_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2022-11-09 09:48:13	ga_ls8c_ard_3-2-1_095075_2022-11-09_final
2022-11-09 11:27:30	ga_ls8c_ard_3-2-1_111076_2022-11-09_final
2022-11-12 11:59:10	ga_ls8c_ard_3-2-1_116078_2022-11-12_final
2022-11-13 09:24:39	ga_ls8c_ard_3-2-1_091078_2022-11-12_final
2022-11-14 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-14_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-06 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-12-06_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-09 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-12-09_final
2022-12-10 10:41:22	ga_ls8c_ard_3-2-1_104069_2022-12-10_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-25 10:03:57	ga_ls8c_ard_3-2-1_097084_2022-12-25_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-10 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-10_final
2023-01-13 10:30:49	ga_ls8c_ard_3-2-1_102074_2023-01-13_final
2023-02-07 10:25:51	ga_ls8c_ard_3-2-1_101077_2023-02-07_final
2023-02-08 09:29:25	ga_ls8c_ard_3-2-1_092075_2023-02-07_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-08 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-02-08_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-24 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-02-24_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-22 10:06:00	ga_ls8c_ard_3-2-1_098075_2023-03-22_final
2023-03-23 09:13:57	ga_ls8c_ard_3-2-1_089084_2023-03-22_final
2023-03-24 09:52:49	ga_ls8c_ard_3-2-1_096073_2023-03-24_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-03-27 10:24:30	ga_ls8c_ard_3-2-1_101075_2023-03-27_final
2023-03-28 09:30:28	ga_ls8c_ard_3-2-1_092079_2023-03-28_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-11 09:40:11	ga_ls8c_ard_3-2-1_094073_2023-04-11_final
2023-04-11 09:44:34	ga_ls8c_ard_3-2-1_094084_2023-04-11_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-13 09:32:37	ga_ls8c_ard_3-2-1_092085_2023-04-13_final
2023-04-13 09:33:01	ga_ls8c_ard_3-2-1_092086_2023-04-13_final
2023-04-13 11:06:18	ga_ls8c_ard_3-2-1_108072_2023-04-13_final
2023-04-20 11:12:50	ga_ls8c_ard_3-2-1_109073_2023-04-20_final
2023-04-21 10:18:25	ga_ls8c_ard_3-2-1_100076_2023-04-21_final
2023-04-24 10:51:19	ga_ls8c_ard_3-2-1_105081_2023-04-24_final
2023-05-05 10:33:05	ga_ls8c_ard_3-2-1_102082_2023-05-05_final
2023-05-08 09:25:27	ga_ls8c_ard_3-2-1_091083_2023-05-07_final
2023-05-08 10:59:33	ga_ls8c_ard_3-2-1_107071_2023-05-08_final
2023-05-09 10:04:18	ga_ls8c_ard_3-2-1_098072_2023-05-09_final
2023-05-10 09:12:39	ga_ls8c_ard_3-2-1_089082_2023-05-09_final
2023-05-10 10:46:21	ga_ls8c_ard_3-2-1_105069_2023-05-10_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