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
2022-02-25 10:44:27	ga_ls8c_ard_3-2-1_104078_2022-02-25_final
2022-02-27 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-02-27_final
2022-03-07 09:44:37	ga_ls8c_ard_3-2-1_094083_2022-03-07_final
2022-03-07 11:22:42	ga_ls8c_ard_3-2-1_110081_2022-03-07_final
2022-03-12 11:39:12	ga_ls8c_ard_3-2-1_113076_2022-03-12_final
2022-03-16 09:36:46	ga_ls8c_ard_3-2-1_093079_2022-03-16_final
2022-03-21 09:54:27	ga_ls8c_ard_3-2-1_096077_2022-03-21_final
2022-03-21 11:33:20	ga_ls8c_ard_3-2-1_112077_2022-03-21_final
2022-03-23 11:20:56	ga_ls8c_ard_3-2-1_110077_2022-03-23_final
2022-03-25 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-03-25_final
2022-03-26 10:11:19	ga_ls8c_ard_3-2-1_099073_2022-03-26_final
2022-04-12 10:57:00	ga_ls8c_ard_3-2-1_106079_2022-04-12_final
2022-04-14 10:41:28	ga_ls8c_ard_3-2-1_104071_2022-04-14_final
2022-04-17 09:35:52	ga_ls8c_ard_3-2-1_093077_2022-04-17_final
2022-04-17 09:38:16	ga_ls8c_ard_3-2-1_093083_2022-04-17_final
2022-04-23 10:38:03	ga_ls8c_ard_3-2-1_103078_2022-04-23_final
2022-04-28 10:56:56	ga_ls8c_ard_3-2-1_106079_2022-04-28_final
2022-04-30 10:41:48	ga_ls8c_ard_3-2-1_104072_2022-04-30_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-06 10:06:23	ga_ls8c_ard_3-2-1_098076_2022-05-06_final
2022-05-17 11:28:49	ga_ls8c_ard_3-2-1_111081_2022-05-17_final
2022-05-24 09:56:07	ga_ls8c_ard_3-2-1_096081_2022-05-24_final
2022-05-30 10:58:20	ga_ls8c_ard_3-2-1_106082_2022-05-30_final
2022-06-08 10:48:42	ga_ls8c_ard_3-2-1_105073_2022-06-08_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-17 10:41:01	ga_ls8c_ard_3-2-1_104069_2022-06-17_final
2022-06-24 10:51:14	ga_ls8c_ard_3-2-1_105079_2022-06-24_final
2022-06-26 10:36:53	ga_ls8c_ard_3-2-1_103074_2022-06-26_final
2022-06-26 10:39:16	ga_ls8c_ard_3-2-1_103080_2022-06-26_final
2022-06-28 10:26:07	ga_ls8c_ard_3-2-1_101078_2022-06-28_final
2022-07-02 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-02_final
2022-07-02 11:39:53	ga_ls8c_ard_3-2-1_113077_2022-07-02_final
2022-07-04 11:27:32	ga_ls8c_ard_3-2-1_111077_2022-07-04_final
2022-07-10 10:48:50	ga_ls8c_ard_3-2-1_105073_2022-07-10_final
2022-07-11 09:55:13	ga_ls8c_ard_3-2-1_096078_2022-07-11_final
2022-07-18 11:39:54	ga_ls8c_ard_3-2-1_113077_2022-07-18_final
2022-07-20 11:27:34	ga_ls8c_ard_3-2-1_111077_2022-07-20_final
2022-07-26 10:52:57	ga_ls8c_ard_3-2-1_105083_2022-07-26_final
2022-08-07 11:13:24	ga_ls8c_ard_3-2-1_109072_2022-08-07_final
2022-08-12 09:54:17	ga_ls8c_ard_3-2-1_096075_2022-08-12_final
2022-08-12 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-08-12_final
2022-08-14 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-08-14_final
2022-08-18 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-08-17_final
2022-08-19 10:02:53	ga_ls8c_ard_3-2-1_097081_2022-08-19_final
2022-08-24 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-08-24_final
2022-08-25 11:01:06	ga_ls8c_ard_3-2-1_107072_2022-08-25_final
2022-08-25 11:03:54	ga_ls8c_ard_3-2-1_107079_2022-08-25_final
2022-08-27 10:49:08	ga_ls8c_ard_3-2-1_105073_2022-08-27_final
2022-09-05 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-09-05_final
2022-09-10 09:24:40	ga_ls8c_ard_3-2-1_091078_2022-09-09_final
2022-09-11 11:46:02	ga_ls8c_ard_3-2-1_114076_2022-09-11_final
2022-09-12 10:50:49	ga_ls8c_ard_3-2-1_105077_2022-09-12_final
2022-09-18 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-09-18_final
2022-09-26 11:03:13	ga_ls8c_ard_3-2-1_107077_2022-09-26_final
2022-09-27 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-09-27_final
2022-10-01 09:42:27	ga_ls8c_ard_3-2-1_094076_2022-10-01_final
2022-10-01 09:45:15	ga_ls8c_ard_3-2-1_094083_2022-10-01_final
2022-10-10 11:16:16	ga_ls8c_ard_3-2-1_109079_2022-10-10_final
2022-10-15 11:33:10	ga_ls8c_ard_3-2-1_112075_2022-10-15_final
2022-10-17 09:41:57	ga_ls8c_ard_3-2-1_094075_2022-10-17_final
2022-10-31 09:56:25	ga_ls8c_ard_3-2-1_096080_2022-10-31_final
2022-11-03 10:24:56	ga_ls8c_ard_3-2-1_101074_2022-11-03_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-10 10:33:04	ga_ls8c_ard_3-2-1_102079_2022-11-10_final
2022-11-11 11:16:19	ga_ls8c_ard_3-2-1_109079_2022-11-11_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-16 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-11-16_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-11-19 10:24:48	ga_ls8c_ard_3-2-1_101074_2022-11-19_final
2022-11-21 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-11-21_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-12-02 09:55:32	ga_ls8c_ard_3-2-1_096078_2022-12-02_final
2022-12-02 11:35:37	ga_ls8c_ard_3-2-1_112081_2022-12-02_final
2022-12-04 11:22:52	ga_ls8c_ard_3-2-1_110080_2022-12-04_final
2022-12-05 10:27:14	ga_ls8c_ard_3-2-1_101080_2022-12-05_final
2022-12-06 09:35:36	ga_ls8c_ard_3-2-1_092090_2022-12-06_final
2022-12-09 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-12-09_final
2022-12-12 10:32:59	ga_ls8c_ard_3-2-1_102079_2022-12-12_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-22 09:31:02	ga_ls8c_ard_3-2-1_092079_2022-12-22_final
2022-12-24 10:58:22	ga_ls8c_ard_3-2-1_106081_2022-12-24_final
2022-12-25 10:03:33	ga_ls8c_ard_3-2-1_097083_2022-12-25_final
2023-01-14 11:16:27	ga_ls8c_ard_3-2-1_109080_2023-01-14_final
2023-01-15 10:20:49	ga_ls8c_ard_3-2-1_100080_2023-01-15_final
2023-01-17 10:09:13	ga_ls8c_ard_3-2-1_098082_2023-01-17_final
2023-01-19 09:54:52	ga_ls8c_ard_3-2-1_096077_2023-01-19_final
2023-01-23 09:30:12	ga_ls8c_ard_3-2-1_092077_2023-01-23_final
2023-01-23 09:31:00	ga_ls8c_ard_3-2-1_092079_2023-01-23_final
2023-01-26 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-26_final
2023-01-26 10:01:08	ga_ls8c_ard_3-2-1_097077_2023-01-26_final
2023-01-30 11:16:30	ga_ls8c_ard_3-2-1_109080_2023-01-30_final
2023-01-30 11:16:54	ga_ls8c_ard_3-2-1_109081_2023-01-30_final
2023-02-06 09:41:47	ga_ls8c_ard_3-2-1_094075_2023-02-06_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-15 11:16:47	ga_ls8c_ard_3-2-1_109081_2023-02-15_final
2023-02-20 11:34:26	ga_ls8c_ard_3-2-1_112079_2023-02-20_final
2023-02-27 10:00:01	ga_ls8c_ard_3-2-1_097075_2023-02-27_final
2023-03-04 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-03-04_final
2023-03-08 11:35:02	ga_ls8c_ard_3-2-1_112081_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