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
2022-01-14 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-01-14_final
2022-01-14 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-01-14_final
2022-11-26 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-11-26_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-02 09:53:57	ga_ls8c_ard_3-2-1_096074_2022-12-02_final
2022-12-02 09:58:44	ga_ls8c_ard_3-2-1_096086_2022-12-02_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-07 10:13:16	ga_ls8c_ard_3-2-1_099076_2022-12-07_final
2022-12-09 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-12-09_final
2022-12-09 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-12-09_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 10:03:49	ga_ls8c_ard_3-2-1_098068_2022-12-16_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-16 11:45:30	ga_ls8c_ard_3-2-1_114075_2022-12-16_final
2022-12-18 09:53:26	ga_ls8c_ard_3-2-1_096073_2022-12-18_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-26 10:44:49	ga_ls8c_ard_3-2-1_104078_2022-12-26_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-31 09:28:05	ga_ls8c_ard_3-2-1_091087_2022-12-30_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-08 10:13:31	ga_ls8c_ard_3-2-1_099077_2023-01-08_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-12 09:50:21	ga_ls8c_ard_3-2-1_095081_2023-01-12_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-17 10:07:37	ga_ls8c_ard_3-2-1_098078_2023-01-17_final
2023-01-17 10:08:25	ga_ls8c_ard_3-2-1_098080_2023-01-17_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-21 09:40:33	ga_ls8c_ard_3-2-1_094072_2023-01-21_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-26 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-26_final
2023-01-31 10:17:17	ga_ls8c_ard_3-2-1_100071_2023-01-31_final
2023-02-05 10:39:01	ga_ls8c_ard_3-2-1_103079_2023-02-05_final
2023-02-06 11:23:52	ga_ls8c_ard_3-2-1_110083_2023-02-06_final
2023-02-08 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-02-08_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-23 10:23:11	ga_ls8c_ard_3-2-1_101071_2023-02-23_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-24 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-02-24_final
2023-02-26 10:55:38	ga_ls8c_ard_3-2-1_106075_2023-02-26_final
2023-02-27 11:39:18	ga_ls8c_ard_3-2-1_113076_2023-02-27_final
2023-03-02 10:31:19	ga_ls8c_ard_3-2-1_102076_2023-03-02_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-05 09:24:30	ga_ls8c_ard_3-2-1_091079_2023-03-04_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_final
2023-03-10 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-03-10_final
2023-03-10 11:23:28	ga_ls8c_ard_3-2-1_110083_2023-03-10_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-13 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-03-13_final
2023-03-14 09:21:27	ga_ls8c_ard_3-2-1_090087_2023-03-13_final
2023-03-23 09:15:57	ga_ls8c_ard_3-2-1_089089_2023-03-22_final
2023-03-27 10:26:06	ga_ls8c_ard_3-2-1_101079_2023-03-27_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-03-29 10:12:32	ga_ls8c_ard_3-2-1_099076_2023-03-29_final
2023-03-29 11:53:01	ga_ls8c_ard_3-2-1_115080_2023-03-29_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-04-01 10:43:00	ga_ls8c_ard_3-2-1_104075_2023-04-01_final
2023-04-02 11:27:26	ga_ls8c_ard_3-2-1_111078_2023-04-02_final
2023-04-04 09:33:22	ga_ls8c_ard_3-2-1_093071_2023-04-04_final
2023-04-06 11:00:15	ga_ls8c_ard_3-2-1_107072_2023-04-06_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-11 11:22:16	ga_ls8c_ard_3-2-1_110081_2023-04-11_final
2023-04-13 09:28:37	ga_ls8c_ard_3-2-1_092075_2023-04-12_final
2023-04-14 10:09:05	ga_ls8c_ard_3-2-1_099068_2023-04-14_final
2023-04-15 09:17:51	ga_ls8c_ard_3-2-1_090079_2023-04-14_final
2023-04-15 10:53:56	ga_ls8c_ard_3-2-1_106072_2023-04-15_final
2023-04-16 11:39:35	ga_ls8c_ard_3-2-1_113078_2023-04-16_final
2023-04-20 09:39:08	ga_ls8c_ard_3-2-1_093086_2023-04-20_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-04-21 10:16:25	ga_ls8c_ard_3-2-1_100071_2023-04-21_final
2023-04-24 09:14:02	ga_ls8c_ard_3-2-1_089085_2023-04-23_final
2023-04-24 09:14:26	ga_ls8c_ard_3-2-1_089086_2023-04-23_final
2023-04-25 09:56:29	ga_ls8c_ard_3-2-1_096083_2023-04-25_final
2023-04-30 10:13:24	ga_ls8c_ard_3-2-1_099079_2023-04-30_final
2023-05-02 11:39:06	ga_ls8c_ard_3-2-1_113077_2023-05-02_final
2023-05-05 10:29:05	ga_ls8c_ard_3-2-1_102072_2023-05-05_final
2023-05-06 11:11:08	ga_ls8c_ard_3-2-1_109069_2023-05-06_final
2023-05-07 10:18:18	ga_ls8c_ard_3-2-1_100076_2023-05-07_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-08 09:23:51	ga_ls8c_ard_3-2-1_091079_2023-05-07_final
2023-05-08 11:00:44	ga_ls8c_ard_3-2-1_107074_2023-05-08_final
2023-05-10 09:12:39	ga_ls8c_ard_3-2-1_089082_2023-05-09_final
2023-05-10 09:13:27	ga_ls8c_ard_3-2-1_089084_2023-05-09_final
2023-05-10 09:13:51	ga_ls8c_ard_3-2-1_089085_2023-05-09_final
2023-05-11 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-11_final
2023-05-13 11:22:23	ga_ls8c_ard_3-2-1_110082_2023-05-13_final
2023-05-15 11:05:37	ga_ls8c_ard_3-2-1_108071_2023-05-15_final
2023-05-16 10:13:11	ga_ls8c_ard_3-2-1_099079_2023-05-16_final
2023-05-16 10:13:35	ga_ls8c_ard_3-2-1_099080_2023-05-16_final
2023-05-17 10:54:26	ga_ls8c_ard_3-2-1_106074_2023-05-17_final
2023-05-18 11:40:54	ga_ls8c_ard_3-2-1_113082_2023-05-18_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_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