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
2022-08-24 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-08-24_final
2022-08-27 10:50:44	ga_ls8c_ard_3-2-1_105077_2022-08-27_final
2022-08-29 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-08-29_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
2022-09-06 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-09-06_final
2022-09-11 10:06:21	ga_ls8c_ard_3-2-1_098074_2022-09-11_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 11:34:05	ga_ls8c_ard_3-2-1_112077_2022-09-13_final
2022-09-15 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-09-15_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
2022-09-18 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-09-18_final
2022-09-20 10:03:24	ga_ls8c_ard_3-2-1_097082_2022-09-20_final
2022-09-20 11:39:53	ga_ls8c_ard_3-2-1_113076_2022-09-20_final
2022-09-20 11:40:41	ga_ls8c_ard_3-2-1_113078_2022-09-20_final
2022-09-21 10:45:04	ga_ls8c_ard_3-2-1_104078_2022-09-21_final
2022-09-22 11:27:56	ga_ls8c_ard_3-2-1_111077_2022-09-22_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
2022-09-29 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-09-29_final
2022-09-29 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-09-29_final
2022-09-30 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-09-30_final
2022-10-02 10:26:30	ga_ls8c_ard_3-2-1_101078_2022-10-02_final
2022-10-04 10:12:56	ga_ls8c_ard_3-2-1_099075_2022-10-04_final
2022-10-09 10:31:49	ga_ls8c_ard_3-2-1_102076_2022-10-09_final
2022-10-09 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-10-09_final
2022-10-10 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-10-10_final
2022-10-15 09:54:41	ga_ls8c_ard_3-2-1_096076_2022-10-15_final
2022-10-18 10:27:13	ga_ls8c_ard_3-2-1_101080_2022-10-18_final
2022-10-22 11:40:14	ga_ls8c_ard_3-2-1_113077_2022-10-22_final
2022-10-22 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-22_final
2022-10-22 11:41:02	ga_ls8c_ard_3-2-1_113079_2022-10-22_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-10-24 09:49:00	ga_ls8c_ard_3-2-1_095077_2022-10-24_final
2022-10-27 11:58:49	ga_ls8c_ard_3-2-1_116077_2022-10-27_final
2022-11-01 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-11-01_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-15 10:51:09	ga_ls8c_ard_3-2-1_105078_2022-11-15_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-25 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-11-25_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-11-28 11:58:45	ga_ls8c_ard_3-2-1_116077_2022-11-28_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
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-09 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-12-09_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-12 10:33:22	ga_ls8c_ard_3-2-1_102080_2022-12-12_final
2022-12-13 09:38:32	ga_ls8c_ard_3-2-1_093082_2022-12-13_final
2022-12-14 10:19:24	ga_ls8c_ard_3-2-1_100076_2022-12-14_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-19 10:37:28	ga_ls8c_ard_3-2-1_103075_2022-12-19_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-27 09:49:12	ga_ls8c_ard_3-2-1_095078_2022-12-27_final
2022-12-27 11:28:29	ga_ls8c_ard_3-2-1_111079_2022-12-27_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-02 10:51:01	ga_ls8c_ard_3-2-1_105078_2023-01-02_final
2023-01-05 11:21:55	ga_ls8c_ard_3-2-1_110078_2023-01-05_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-06 10:27:29	ga_ls8c_ard_3-2-1_101081_2023-01-06_final
2023-01-10 10:00:21	ga_ls8c_ard_3-2-1_097075_2023-01-10_final
2023-01-12 09:49:33	ga_ls8c_ard_3-2-1_095079_2023-01-12_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_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
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-11 10:00:17	ga_ls8c_ard_3-2-1_097075_2023-02-11_final
2023-02-11 10:03:04	ga_ls8c_ard_3-2-1_097082_2023-02-11_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-13 11:28:22	ga_ls8c_ard_3-2-1_111079_2023-02-13_final
2023-02-16 10:21:09	ga_ls8c_ard_3-2-1_100081_2023-02-16_final
2023-02-20 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_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
2023-02-20 09:56:21	ga_ls8c_ard_3-2-1_096081_2023-02-20_final
2023-02-22 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-02-22_final
2023-02-22 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-02-22_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-02-24 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-02-24_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-01 09:49:39	ga_ls8c_ard_3-2-1_095080_2023-03-01_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-02 10:32:54	ga_ls8c_ard_3-2-1_102080_2023-03-02_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
2023-03-08 09:56:09	ga_ls8c_ard_3-2-1_096081_2023-03-08_final
2023-03-10 09:41:24	ga_ls8c_ard_3-2-1_094075_2023-03-10_final
2023-03-10 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-03-10_final
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-11 10:26:15	ga_ls8c_ard_3-2-1_101079_2023-03-11_final
2023-03-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2023-03-17_final
2023-03-17 11:27:13	ga_ls8c_ard_3-2-1_111077_2023-03-17_final
2023-03-17 11:27:37	ga_ls8c_ard_3-2-1_111078_2023-03-17_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