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
2022-10-24 11:26:42	ga_ls8c_ard_3-2-1_111074_2022-10-24_final
2022-11-02 11:21:21	ga_ls8c_ard_3-2-1_110076_2022-11-02_final
2022-11-04 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-11-04_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-11 11:14:43	ga_ls8c_ard_3-2-1_109075_2022-11-11_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-11 11:15:31	ga_ls8c_ard_3-2-1_109077_2022-11-11_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-27 11:14:17	ga_ls8c_ard_3-2-1_109074_2022-11-27_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-06 11:09:18	ga_ls8c_ard_3-2-1_108077_2022-12-06_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-14 10:20:36	ga_ls8c_ard_3-2-1_100079_2022-12-14_final
2022-12-18 09:55:25	ga_ls8c_ard_3-2-1_096078_2022-12-18_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-22 09:31:02	ga_ls8c_ard_3-2-1_092079_2022-12-22_final
2022-12-30 10:18:07	ga_ls8c_ard_3-2-1_100073_2022-12-30_final
2023-01-02 10:52:13	ga_ls8c_ard_3-2-1_105081_2023-01-02_final
2023-01-03 09:55:24	ga_ls8c_ard_3-2-1_096078_2023-01-03_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-09 10:53:59	ga_ls8c_ard_3-2-1_106070_2023-01-09_final
2023-01-12 09:49:09	ga_ls8c_ard_3-2-1_095078_2023-01-12_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-16 11:03:16	ga_ls8c_ard_3-2-1_107078_2023-01-16_final
2023-02-03 10:50:35	ga_ls8c_ard_3-2-1_105077_2023-02-03_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-22 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-02-22_final
2023-02-24 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-02-24_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_final
2023-03-03 11:13:46	ga_ls8c_ard_3-2-1_109074_2023-03-03_final
2023-03-03 11:14:10	ga_ls8c_ard_3-2-1_109075_2023-03-03_final
2023-03-10 11:20:41	ga_ls8c_ard_3-2-1_110076_2023-03-10_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-03-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2023-03-17_final
2023-03-21 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-03-21_final
2023-03-23 10:46:51	ga_ls8c_ard_3-2-1_105069_2023-03-23_final
2023-04-01 10:45:23	ga_ls8c_ard_3-2-1_104081_2023-04-01_final
2023-04-01 10:45:47	ga_ls8c_ard_3-2-1_104082_2023-04-01_final
2023-04-13 11:09:54	ga_ls8c_ard_3-2-1_108081_2023-04-13_final
2023-04-14 11:50:22	ga_ls8c_ard_3-2-1_115074_2023-04-14_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-04-18 09:48:19	ga_ls8c_ard_3-2-1_095078_2023-04-18_final
2023-04-18 11:25:13	ga_ls8c_ard_3-2-1_111073_2023-04-18_final
2023-04-21 10:19:36	ga_ls8c_ard_3-2-1_100079_2023-04-21_final
2023-04-29 11:09:50	ga_ls8c_ard_3-2-1_108081_2023-04-29_final
2023-04-30 11:50:17	ga_ls8c_ard_3-2-1_115074_2023-04-30_final
2023-05-01 10:58:15	ga_ls8c_ard_3-2-1_106083_2023-05-01_final
2023-05-03 10:45:04	ga_ls8c_ard_3-2-1_104081_2023-05-03_final
2023-05-11 09:54:18	ga_ls8c_ard_3-2-1_096078_2023-05-11_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-15 11:07:13	ga_ls8c_ard_3-2-1_108075_2023-05-15_final
2023-05-15 11:08:25	ga_ls8c_ard_3-2-1_108078_2023-05-15_final
2023-05-16 11:50:04	ga_ls8c_ard_3-2-1_115074_2023-05-16_final
2023-05-20 09:48:04	ga_ls8c_ard_3-2-1_095078_2023-05-20_final
2023-05-20 11:24:58	ga_ls8c_ard_3-2-1_111073_2023-05-20_final
2023-05-23 11:57:53	ga_ls8c_ard_3-2-1_116078_2023-05-23_final
2023-05-27 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-27_final
2023-06-01 11:50:07	ga_ls8c_ard_3-2-1_115074_2023-06-01_final
2023-06-03 10:03:17	ga_ls8c_ard_3-2-1_097085_2023-06-03_final
2023-06-05 11:25:51	ga_ls8c_ard_3-2-1_111075_2023-06-05_final
2023-06-09 11:02:22	ga_ls8c_ard_3-2-1_107078_2023-06-09_final
2023-06-11 10:49:38	ga_ls8c_ard_3-2-1_105077_2023-06-11_final
2023-06-14 11:19:21	ga_ls8c_ard_3-2-1_110074_2023-06-14_final
2023-06-16 11:09:24	ga_ls8c_ard_3-2-1_108080_2023-06-16_final
2023-06-18 10:58:15	ga_ls8c_ard_3-2-1_106083_2023-06-18_final
2023-06-23 11:14:24	ga_ls8c_ard_3-2-1_109077_2023-06-23_final
2023-06-24 10:19:35	ga_ls8c_ard_3-2-1_100079_2023-06-24_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-07-02 09:30:16	ga_ls8c_ard_3-2-1_092079_2023-07-02_final
2023-07-05 10:03:36	ga_ls8c_ard_3-2-1_097085_2023-07-05_final
2023-07-07 09:48:28	ga_ls8c_ard_3-2-1_095078_2023-07-07_final
2023-07-09 11:15:00	ga_ls8c_ard_3-2-1_109078_2023-07-09_final
2023-07-16 09:42:19	ga_ls8c_ard_3-2-1_094078_2023-07-16_final
2023-07-16 11:20:01	ga_ls8c_ard_3-2-1_110075_2023-07-16_final
2023-07-18 11:08:03	ga_ls8c_ard_3-2-1_108076_2023-07-18_final
2023-07-21 10:03:39	ga_ls8c_ard_3-2-1_097085_2023-07-21_final
2023-08-11 10:19:57	ga_ls8c_ard_3-2-1_100079_2023-08-11_final
2023-08-11 11:58:02	ga_ls8c_ard_3-2-1_116077_2023-08-11_final
2023-08-15 09:55:41	ga_ls8c_ard_3-2-1_096080_2023-08-15_final
2023-08-15 11:32:11	ga_ls8c_ard_3-2-1_112074_2023-08-15_final
2023-08-17 11:20:39	ga_ls8c_ard_3-2-1_110076_2023-08-17_final
2023-09-02 11:19:54	ga_ls8c_ard_3-2-1_110074_2023-09-02_final
2023-09-13 11:03:00	ga_ls8c_ard_3-2-1_107078_2023-09-13_final
2023-09-20 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-09-20_final
2023-09-20 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-09-20_final
2023-09-23 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-09-23_final
2023-09-25 11:25:23	ga_ls8c_ard_3-2-1_111072_2023-09-25_final
2023-10-04 11:20:01	ga_ls8c_ard_3-2-1_110074_2023-10-04_final
2023-10-07 11:50:56	ga_ls8c_ard_3-2-1_115074_2023-10-07_final
2023-10-09 10:04:06	ga_ls8c_ard_3-2-1_097085_2023-10-09_final
2023-10-10 10:46:10	ga_ls8c_ard_3-2-1_104082_2023-10-10_final
2023-10-17 10:50:21	ga_ls8c_ard_3-2-1_105077_2023-10-17_final
2023-10-22 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-10-22_final
2023-10-29 11:15:08	ga_ls8c_ard_3-2-1_109077_2023-10-29_final
2023-11-02 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-02_final
2023-11-05 11:20:54	ga_ls8c_ard_3-2-1_110076_2023-11-05_final
2023-11-07 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-11-07_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