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
2016-08-26 10:51:09	ga_ls8c_ard_3-1-0_105079_2016-08-26_final
2019-03-07 10:30:54	ga_ls8c_ard_3-1-0_102076_2019-03-07_final
2019-03-09 11:57:49	ga_ls8c_ard_3-1-0_116077_2019-03-09_final
2019-03-22 09:48:46	ga_ls8c_ard_3-1-0_095079_2019-03-22_final
2019-04-01 10:26:13	ga_ls8c_ard_3-1-0_101080_2019-04-01_final
2019-04-02 11:08:41	ga_ls8c_ard_3-1-0_108078_2019-04-02_final
2019-04-07 11:27:36	ga_ls8c_ard_3-1-0_111079_2019-04-07_final
2019-04-07 11:27:59	ga_ls8c_ard_3-1-0_111080_2019-04-07_final
2019-06-17 11:32:54	ga_ls8c_ard_3-1-0_112076_2019-06-17_final
2019-06-26 09:48:41	ga_ls8c_ard_3-1-0_095078_2019-06-26_final
2019-06-26 11:27:34	ga_ls8c_ard_3-1-0_111078_2019-06-26_final
2019-07-03 09:53:41	ga_ls8c_ard_3-1-0_096075_2019-07-03_final
2019-07-18 10:50:33	ga_ls8c_ard_3-1-0_105078_2019-07-18_final
2019-07-19 09:53:44	ga_ls8c_ard_3-1-0_096075_2019-07-19_final
2019-08-03 10:50:40	ga_ls8c_ard_3-1-0_105078_2019-08-03_final
2019-08-04 09:53:51	ga_ls8c_ard_3-1-0_096075_2019-08-04_final
2019-08-04 11:33:32	ga_ls8c_ard_3-1-0_112077_2019-08-04_final
2019-08-14 10:31:23	ga_ls8c_ard_3-1-0_102076_2019-08-14_final
2019-08-20 09:53:08	ga_ls8c_ard_3-1-0_096073_2019-08-20_final
2019-08-23 10:26:51	ga_ls8c_ard_3-1-0_101080_2019-08-23_final
2019-08-30 10:31:27	ga_ls8c_ard_3-1-0_102076_2019-08-30_final
2019-09-05 09:53:59	ga_ls8c_ard_3-1-0_096075_2019-09-05_final
2019-09-05 11:34:04	ga_ls8c_ard_3-1-0_112078_2019-09-05_final
2019-09-08 10:26:54	ga_ls8c_ard_3-1-0_101080_2019-09-08_final
2019-09-14 11:27:33	ga_ls8c_ard_3-1-0_111077_2019-09-14_final
2019-09-21 09:54:05	ga_ls8c_ard_3-1-0_096075_2019-09-21_final
2019-09-21 11:34:10	ga_ls8c_ard_3-1-0_112078_2019-09-21_final
2019-09-21 11:34:34	ga_ls8c_ard_3-1-0_112079_2019-09-21_final
2019-09-25 11:09:28	ga_ls8c_ard_3-1-0_108078_2019-09-25_final
2019-09-30 11:27:38	ga_ls8c_ard_3-1-0_111077_2019-09-30_final
2019-10-01 10:31:37	ga_ls8c_ard_3-1-0_102076_2019-10-01_final
2019-10-07 09:54:09	ga_ls8c_ard_3-1-0_096075_2019-10-07_final
2019-10-07 11:32:14	ga_ls8c_ard_3-1-0_112073_2019-10-07_final
2019-10-07 11:33:26	ga_ls8c_ard_3-1-0_112076_2019-10-07_final
2019-10-07 11:34:14	ga_ls8c_ard_3-1-0_112078_2019-10-07_final
2019-10-07 11:34:38	ga_ls8c_ard_3-1-0_112079_2019-10-07_final
2019-10-16 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-10-16_final
2019-10-16 11:27:40	ga_ls8c_ard_3-1-0_111077_2019-10-16_final
2019-10-16 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-10-16_final
2019-10-17 10:32:27	ga_ls8c_ard_3-1-0_102078_2019-10-17_final
2019-10-27 11:09:32	ga_ls8c_ard_3-1-0_108078_2019-10-27_final
2019-11-08 09:54:57	ga_ls8c_ard_3-1-0_096077_2019-11-08_final
2019-11-08 11:32:14	ga_ls8c_ard_3-1-0_112073_2019-11-08_final
2019-11-17 09:49:32	ga_ls8c_ard_3-1-0_095079_2019-11-17_final
2019-11-24 11:32:11	ga_ls8c_ard_3-1-0_112073_2019-11-24_final
2019-12-03 09:49:31	ga_ls8c_ard_3-1-0_095079_2019-12-03_final
2019-12-06 11:57:42	ga_ls8c_ard_3-1-0_116075_2019-12-06_final
2019-12-06 11:58:06	ga_ls8c_ard_3-1-0_116076_2019-12-06_final
2019-12-10 11:34:10	ga_ls8c_ard_3-1-0_112078_2019-12-10_final
2019-12-22 11:58:03	ga_ls8c_ard_3-1-0_116076_2019-12-22_final
2020-01-07 11:57:59	ga_ls8c_ard_3-1-0_116076_2020-01-07_final
2020-01-23 11:57:55	ga_ls8c_ard_3-1-0_116076_2020-01-23_final
2020-02-06 10:32:07	ga_ls8c_ard_3-1-0_102078_2020-02-06_final
2020-02-09 09:24:08	ga_ls8c_ard_3-1-0_091078_2020-02-08_final
2020-02-11 10:50:39	ga_ls8c_ard_3-1-0_105078_2020-02-11_final
2020-02-12 11:33:06	ga_ls8c_ard_3-1-0_112076_2020-02-12_final
2020-02-21 11:27:17	ga_ls8c_ard_3-1-0_111077_2020-02-21_final
2020-02-28 09:54:57	ga_ls8c_ard_3-1-0_096078_2020-02-28_final
2020-03-08 09:48:43	ga_ls8c_ard_3-1-0_095078_2020-03-08_final
2020-03-09 10:31:58	ga_ls8c_ard_3-1-0_102078_2020-03-09_final
2020-03-15 09:54:02	ga_ls8c_ard_3-1-0_096076_2020-03-15_final
2020-03-15 09:54:26	ga_ls8c_ard_3-1-0_096077_2020-03-15_final
2020-03-19 11:08:34	ga_ls8c_ard_3-1-0_108077_2020-03-19_final
2020-03-25 10:31:50	ga_ls8c_ard_3-1-0_102078_2020-03-25_final
2020-03-30 10:52:19	ga_ls8c_ard_3-1-0_105083_2020-03-30_final
2020-03-31 09:54:17	ga_ls8c_ard_3-1-0_096077_2020-03-31_final
2020-03-31 11:32:46	ga_ls8c_ard_3-1-0_112076_2020-03-31_final
2020-03-31 11:33:58	ga_ls8c_ard_3-1-0_112079_2020-03-31_final
2020-04-04 11:08:48	ga_ls8c_ard_3-1-0_108078_2020-04-04_final
2020-04-10 10:30:54	ga_ls8c_ard_3-1-0_102076_2020-04-10_final
2020-04-16 11:32:39	ga_ls8c_ard_3-1-0_112076_2020-04-16_final
2020-04-16 11:33:03	ga_ls8c_ard_3-1-0_112077_2020-04-16_final
2020-05-02 09:51:38	ga_ls8c_ard_3-1-0_096071_2020-05-02_final
2020-05-02 09:54:26	ga_ls8c_ard_3-1-0_096078_2020-05-02_final
2020-05-05 10:25:42	ga_ls8c_ard_3-1-0_101079_2020-05-05_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_final
2022-04-06 11:32:50	ga_ls8c_ard_3-2-1_112076_2022-04-06_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-08 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-08_final
2022-04-09 10:26:29	ga_ls8c_ard_3-2-1_101080_2022-04-09_final
2022-04-13 11:39:28	ga_ls8c_ard_3-2-1_113077_2022-04-13_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-22 09:54:47	ga_ls8c_ard_3-2-1_096078_2022-04-22_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
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-06 11:45:16	ga_ls8c_ard_3-2-1_114076_2022-05-06_final
2022-05-09 10:38:31	ga_ls8c_ard_3-2-1_103079_2022-05-09_final
2022-05-12 11:09:03	ga_ls8c_ard_3-2-1_108078_2022-05-12_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-15 11:39:34	ga_ls8c_ard_3-2-1_113077_2022-05-15_final
2022-05-16 10:44:45	ga_ls8c_ard_3-2-1_104079_2022-05-16_final
2022-05-24 09:52:31	ga_ls8c_ard_3-2-1_096072_2022-05-24_final
2022-05-26 09:42:33	ga_ls8c_ard_3-2-1_094078_2022-05-26_final
2022-06-02 09:48:24	ga_ls8c_ard_3-2-1_095077_2022-06-02_final
2022-06-02 11:28:05	ga_ls8c_ard_3-2-1_111079_2022-06-02_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