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
2022-02-16 10:50:40	ga_ls8c_ard_3-2-1_105078_2022-02-16_final
2022-02-19 09:43:03	ga_ls8c_ard_3-2-1_094079_2022-02-19_final
2022-02-24 11:39:40	ga_ls8c_ard_3-2-1_113077_2022-02-24_final
2022-02-25 10:45:39	ga_ls8c_ard_3-2-1_104081_2022-02-25_final
2022-02-26 09:48:25	ga_ls8c_ard_3-2-1_095077_2022-02-26_final
2022-02-27 10:32:05	ga_ls8c_ard_3-2-1_102078_2022-02-27_final
2022-03-03 10:08:33	ga_ls8c_ard_3-2-1_098081_2022-03-03_final
2022-03-07 09:42:13	ga_ls8c_ard_3-2-1_094077_2022-03-07_final
2022-03-07 11:21:54	ga_ls8c_ard_3-2-1_110079_2022-03-07_final
2022-03-09 11:09:07	ga_ls8c_ard_3-2-1_108078_2022-03-09_final
2022-03-12 11:40:00	ga_ls8c_ard_3-2-1_113078_2022-03-12_final
2022-03-15 10:32:24	ga_ls8c_ard_3-2-1_102079_2022-03-15_final
2022-03-18 09:27:10	ga_ls8c_ard_3-2-1_091086_2022-03-17_final
2022-03-26 10:14:31	ga_ls8c_ard_3-2-1_099081_2022-03-26_final
2022-03-28 11:39:24	ga_ls8c_ard_3-2-1_113077_2022-03-28_final
2022-03-28 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-03-28_final
2022-03-30 09:48:56	ga_ls8c_ard_3-2-1_095079_2022-03-30_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-07 10:38:01	ga_ls8c_ard_3-2-1_103078_2022-04-07_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-21 10:47:37	ga_ls8c_ard_3-2-1_105071_2022-04-21_final
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-22 09:55:35	ga_ls8c_ard_3-2-1_096080_2022-04-22_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-26 11:06:31	ga_ls8c_ard_3-2-1_108072_2022-04-26_final
2022-05-05 11:02:48	ga_ls8c_ard_3-2-1_107078_2022-05-05_final
2022-05-16 10:44:45	ga_ls8c_ard_3-2-1_104079_2022-05-16_final
2022-05-19 11:15:40	ga_ls8c_ard_3-2-1_109079_2022-05-19_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-26 09:42:33	ga_ls8c_ard_3-2-1_094078_2022-05-26_final
2022-05-29 10:12:16	ga_ls8c_ard_3-2-1_099075_2022-05-29_final
2022-05-31 11:40:01	ga_ls8c_ard_3-2-1_113078_2022-05-31_final
2022-06-02 09:48:24	ga_ls8c_ard_3-2-1_095077_2022-06-02_final
2022-06-09 09:54:17	ga_ls8c_ard_3-2-1_096076_2022-06-09_final
2022-06-09 09:54:41	ga_ls8c_ard_3-2-1_096077_2022-06-09_final
2022-06-09 09:56:41	ga_ls8c_ard_3-2-1_096082_2022-06-09_final
2022-06-09 11:33:34	ga_ls8c_ard_3-2-1_112077_2022-06-09_final
2022-06-11 09:42:45	ga_ls8c_ard_3-2-1_094078_2022-06-11_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-19 10:31:28	ga_ls8c_ard_3-2-1_102076_2022-06-19_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_final
2022-07-04 09:49:03	ga_ls8c_ard_3-2-1_095078_2022-07-04_final
2022-07-06 11:15:58	ga_ls8c_ard_3-2-1_109079_2022-07-06_final
2022-07-10 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-07-10_final
2022-07-13 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-07-13_final
2022-07-14 10:26:30	ga_ls8c_ard_3-2-1_101079_2022-07-14_final
2022-07-18 11:40:18	ga_ls8c_ard_3-2-1_113078_2022-07-18_final
2022-07-20 09:47:53	ga_ls8c_ard_3-2-1_095075_2022-07-20_final
2022-07-26 10:50:34	ga_ls8c_ard_3-2-1_105077_2022-07-26_final
2022-08-01 10:12:45	ga_ls8c_ard_3-2-1_099075_2022-08-01_final
2022-08-09 11:05:03	ga_ls8c_ard_3-2-1_107082_2022-08-09_final
2022-08-27 10:50:44	ga_ls8c_ard_3-2-1_105077_2022-08-27_final
2022-08-28 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-08-28_final
2022-08-28 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-08-28_final
2022-08-28 11:33:12	ga_ls8c_ard_3-2-1_112075_2022-08-28_final
2022-08-30 11:22:50	ga_ls8c_ard_3-2-1_110080_2022-08-30_final
2022-09-05 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-09-05_final
2022-09-11 10:06:21	ga_ls8c_ard_3-2-1_098074_2022-09-11_final
2022-09-13 09:54:24	ga_ls8c_ard_3-2-1_096075_2022-09-13_final
2022-09-13 09:55:12	ga_ls8c_ard_3-2-1_096077_2022-09-13_final
2022-09-13 09:56:24	ga_ls8c_ard_3-2-1_096080_2022-09-13_final
2022-09-13 11:33:41	ga_ls8c_ard_3-2-1_112076_2022-09-13_final
2022-09-15 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-09-15_final
2022-09-15 11:22:32	ga_ls8c_ard_3-2-1_110079_2022-09-15_final
2022-09-20 10:03:24	ga_ls8c_ard_3-2-1_097082_2022-09-20_final
2022-09-21 10:45:04	ga_ls8c_ard_3-2-1_104078_2022-09-21_final
2022-09-22 11:28:20	ga_ls8c_ard_3-2-1_111078_2022-09-22_final
2022-10-04 10:12:56	ga_ls8c_ard_3-2-1_099075_2022-10-04_final
2022-10-09 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-10-09_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-11-07 11:41:04	ga_ls8c_ard_3-2-1_113079_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-15 10:51:09	ga_ls8c_ard_3-2-1_105078_2022-11-15_final
2022-11-16 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-11-16_final
2022-11-19 10:23:12	ga_ls8c_ard_3-2-1_101070_2022-11-19_final
2022-11-23 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-11-23_final
2022-11-25 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-11-25_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-12-02 09:54:21	ga_ls8c_ard_3-2-1_096075_2022-12-02_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-27 09:48:48	ga_ls8c_ard_3-2-1_095077_2022-12-27_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-15 11:58:30	ga_ls8c_ard_3-2-1_116077_2023-01-15_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-02-13 11:27:34	ga_ls8c_ard_3-2-1_111077_2023-02-13_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-20 09:54:21	ga_ls8c_ard_3-2-1_096076_2023-02-20_final
2023-02-20 09:55:57	ga_ls8c_ard_3-2-1_096080_2023-02-20_final
2023-02-22 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-02-22_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-06 10:08:57	ga_ls8c_ard_3-2-1_098082_2023-03-06_final
2023-03-08 09:55:45	ga_ls8c_ard_3-2-1_096080_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years