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 10:04:22	ga_ls8c_ard_3-2-1_098070_2022-01-14_final
2022-01-14 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-01-14_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_final
2022-07-04 11:28:20	ga_ls8c_ard_3-2-1_111079_2022-07-04_final
2022-07-05 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-07-05_final
2022-07-07 11:58:26	ga_ls8c_ard_3-2-1_116077_2022-07-07_final
2022-07-09 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-07-09_final
2022-07-12 10:37:16	ga_ls8c_ard_3-2-1_103075_2022-07-12_final
2022-07-12 10:37:40	ga_ls8c_ard_3-2-1_103076_2022-07-12_final
2022-07-13 09:43:14	ga_ls8c_ard_3-2-1_094079_2022-07-13_final
2022-07-16 10:14:56	ga_ls8c_ard_3-2-1_099081_2022-07-16_final
2022-07-20 09:47:53	ga_ls8c_ard_3-2-1_095075_2022-07-20_final
2022-07-21 10:32:21	ga_ls8c_ard_3-2-1_102078_2022-07-21_final
2022-07-27 09:54:09	ga_ls8c_ard_3-2-1_096075_2022-07-27_final
2022-07-28 10:39:01	ga_ls8c_ard_3-2-1_103079_2022-07-28_final
2022-08-03 10:00:24	ga_ls8c_ard_3-2-1_097075_2022-08-03_final
2022-08-03 10:03:12	ga_ls8c_ard_3-2-1_097082_2022-08-03_final
2022-08-12 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-08-12_final
2022-08-13 10:37:33	ga_ls8c_ard_3-2-1_103075_2022-08-13_final
2022-08-13 10:39:09	ga_ls8c_ard_3-2-1_103079_2022-08-13_final
2022-08-15 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-15_final
2022-08-22 10:33:00	ga_ls8c_ard_3-2-1_102079_2022-08-22_final
2022-08-23 11:16:15	ga_ls8c_ard_3-2-1_109079_2022-08-23_final
2022-08-26 10:09:04	ga_ls8c_ard_3-2-1_098081_2022-08-26_final
2022-08-27 10:51:08	ga_ls8c_ard_3-2-1_105078_2022-08-27_final
2022-08-28 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-08-28_final
2022-09-01 09:30:23	ga_ls8c_ard_3-2-1_092077_2022-09-01_final
2022-09-04 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-09-04_final
2022-09-07 10:32:38	ga_ls8c_ard_3-2-1_102078_2022-09-07_final
2022-09-07 10:33:02	ga_ls8c_ard_3-2-1_102079_2022-09-07_final
2022-09-11 10:06:21	ga_ls8c_ard_3-2-1_098074_2022-09-11_final
2022-09-13 09:54:48	ga_ls8c_ard_3-2-1_096076_2022-09-13_final
2022-09-15 11:22:32	ga_ls8c_ard_3-2-1_110079_2022-09-15_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_final
2022-09-24 11:12:23	ga_ls8c_ard_3-2-1_109069_2022-09-24_final
2022-09-27 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-09-27_final
2022-09-28 10:51:15	ga_ls8c_ard_3-2-1_105078_2022-09-28_final
2022-09-30 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-09-30_final
2022-10-06 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-06_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-13 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-10-13_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-15 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-10-15_final
2022-10-24 09:49:24	ga_ls8c_ard_3-2-1_095078_2022-10-24_final
2022-10-29 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-10-29_final
2022-10-31 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-10-31_final
2022-11-02 11:22:09	ga_ls8c_ard_3-2-1_110078_2022-11-02_final
2022-11-07 11:41:04	ga_ls8c_ard_3-2-1_113079_2022-11-07_final
2022-11-15 10:51:09	ga_ls8c_ard_3-2-1_105078_2022-11-15_final
2022-11-18 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-11-18_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-30 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-30_final
2022-12-01 10:51:10	ga_ls8c_ard_3-2-1_105078_2022-12-01_final
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-09 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-12-09_final
2022-12-14 10:19:24	ga_ls8c_ard_3-2-1_100076_2022-12-14_final
2022-12-18 11:34:42	ga_ls8c_ard_3-2-1_112079_2022-12-18_final
2022-12-19 10:37:28	ga_ls8c_ard_3-2-1_103075_2022-12-19_final
2022-12-19 10:39:04	ga_ls8c_ard_3-2-1_103079_2022-12-19_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-27 11:28:29	ga_ls8c_ard_3-2-1_111079_2022-12-27_final
2023-01-01 10:08:57	ga_ls8c_ard_3-2-1_098081_2023-01-01_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-05 11:21:55	ga_ls8c_ard_3-2-1_110078_2023-01-05_final
2023-01-12 09:50:21	ga_ls8c_ard_3-2-1_095081_2023-01-12_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-13 10:32:48	ga_ls8c_ard_3-2-1_102079_2023-01-13_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-19 09:54:28	ga_ls8c_ard_3-2-1_096076_2023-01-19_final
2023-01-21 11:21:49	ga_ls8c_ard_3-2-1_110078_2023-01-21_final
2023-02-06 11:21:52	ga_ls8c_ard_3-2-1_110078_2023-02-06_final
2023-02-11 10:03:04	ga_ls8c_ard_3-2-1_097082_2023-02-11_final
2023-02-13 11:28:22	ga_ls8c_ard_3-2-1_111079_2023-02-13_final
2023-02-13 11:28:46	ga_ls8c_ard_3-2-1_111080_2023-02-13_final
2023-02-14 10:32:44	ga_ls8c_ard_3-2-1_102079_2023-02-14_final
2023-02-15 09:38:18	ga_ls8c_ard_3-2-1_093082_2023-02-15_final
2023-02-20 11:33:14	ga_ls8c_ard_3-2-1_112076_2023-02-20_final
2023-02-22 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-02-22_final
2023-02-22 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-02-22_final
2023-03-10 11:21:29	ga_ls8c_ard_3-2-1_110078_2023-03-10_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-17 11:27:13	ga_ls8c_ard_3-2-1_111077_2023-03-17_final
2023-03-17 11:28:01	ga_ls8c_ard_3-2-1_111079_2023-03-17_final
2023-03-18 10:32:23	ga_ls8c_ard_3-2-1_102079_2023-03-18_final
2023-03-20 10:17:36	ga_ls8c_ard_3-2-1_100073_2023-03-20_final
2023-03-26 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-03-26_final
2023-03-27 10:26:30	ga_ls8c_ard_3-2-1_101080_2023-03-27_final
2023-04-01 10:41:00	ga_ls8c_ard_3-2-1_104070_2023-04-01_final
2023-04-01 10:45:23	ga_ls8c_ard_3-2-1_104081_2023-04-01_final
2023-04-04 09:37:45	ga_ls8c_ard_3-2-1_093082_2023-04-04_final
2023-04-09 11:32:40	ga_ls8c_ard_3-2-1_112076_2023-04-09_final
2023-04-19 10:31:58	ga_ls8c_ard_3-2-1_102079_2023-04-19_final
2023-04-28 10:26:11	ga_ls8c_ard_3-2-1_101080_2023-04-28_final
2023-04-29 11:08:14	ga_ls8c_ard_3-2-1_108077_2023-04-29_final
2023-04-30 10:14:12	ga_ls8c_ard_3-2-1_099081_2023-04-30_final
2023-05-04 11:26:43	ga_ls8c_ard_3-2-1_111077_2023-05-04_final
2023-05-05 10:31:53	ga_ls8c_ard_3-2-1_102079_2023-05-05_final
2023-05-13 09:40:43	ga_ls8c_ard_3-2-1_094075_2023-05-13_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