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
2014-12-21 09:46:56	ga_ls8c_ard_3-0-0_095073_2014-12-21_final
2015-02-23 09:45:25	ga_ls8c_ard_3-0-0_095070_2015-02-23_final
2015-07-17 09:51:33	ga_ls8c_ard_3-0-0_095086_2015-07-17_final
2015-11-06 09:46:07	ga_ls8c_ard_3-0-0_095071_2015-11-06_final
2017-02-12 09:52:20	ga_ls8c_ard_3-0-0_095087_2017-02-12_final
2017-04-17 09:45:50	ga_ls8c_ard_3-0-0_095072_2017-04-17_final
2017-09-08 09:50:54	ga_ls8c_ard_3-0-0_095083_2017-09-08_final
2018-10-13 09:44:14	ga_ls8c_ard_3-0-0_095067_2018-10-13_final
2019-02-02 09:47:46	ga_ls8c_ard_3-0-0_095076_2019-02-02_final
2019-02-18 09:44:08	ga_ls8c_ard_3-0-0_095067_2019-02-18_final
2019-04-23 09:46:12	ga_ls8c_ard_3-0-0_095073_2019-04-23_final
2019-06-10 09:51:47	ga_ls8c_ard_3-0-0_095086_2019-06-10_final
2021-03-13 09:34:19	ga_ls8c_ard_3-2-0_093073_2021-03-13_final
2021-03-15 11:00:01	ga_ls8c_ard_3-2-0_107071_2021-03-15_final
2021-03-23 10:09:20	ga_ls8c_ard_3-2-0_099068_2021-03-23_final
2021-03-24 10:52:36	ga_ls8c_ard_3-2-0_106068_2021-03-24_final
2021-04-05 09:41:10	ga_ls8c_ard_3-2-0_094075_2021-04-05_final
2021-04-11 10:45:44	ga_ls8c_ard_3-2-0_104082_2021-04-11_final
2021-04-16 09:21:46	ga_ls8c_ard_3-2-0_091073_2021-04-15_final
2021-04-24 10:09:09	ga_ls8c_ard_3-2-0_099068_2021-04-24_final
2021-05-25 09:33:08	ga_ls8c_ard_3-2-0_092086_2021-05-25_final
2021-05-26 10:10:49	ga_ls8c_ard_3-2-0_099072_2021-05-26_final
2021-06-19 09:27:31	ga_ls8c_ard_3-2-0_091087_2021-06-18_final
2021-06-24 09:46:05	ga_ls8c_ard_3-2-0_094087_2021-06-24_final
2021-07-14 10:55:53	ga_ls8c_ard_3-2-0_106076_2021-07-14_final
2021-07-19 09:34:23	ga_ls8c_ard_3-2-0_093073_2021-07-19_final
2021-08-16 09:57:19	ga_ls8c_ard_3-2-0_097068_2021-08-16_final
2021-08-22 09:23:03	ga_ls8c_ard_3-2-0_091075_2021-08-21_final
2021-09-26 09:50:55	ga_ls8c_ard_3-2-0_096067_2021-09-26_final
2021-09-28 11:18:15	ga_ls8c_ard_3-2-0_110069_2021-09-28_final
2021-10-07 09:34:02	ga_ls8c_ard_3-2-0_093071_2021-10-07_final
2021-10-21 09:44:50	ga_ls8c_ard_3-2-0_095067_2021-10-21_final
2021-11-17 09:34:59	ga_ls8c_ard_3-2-0_092089_2021-11-17_final
2021-11-20 11:37:59	ga_ls8c_ard_3-2-0_113072_2021-11-20_final
2021-12-21 09:17:49	ga_ls8c_ard_3-2-1_090077_2021-12-20_final
2022-01-06 10:54:14	ga_ls8c_ard_3-2-1_106071_2022-01-06_final
2022-01-15 10:51:13	ga_ls8c_ard_3-2-1_105079_2022-01-15_final
2022-01-22 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-01-22_final
2022-01-27 11:12:16	ga_ls8c_ard_3-2-1_109070_2022-01-27_final
2022-02-23 09:21:31	ga_ls8c_ard_3-2-1_090087_2022-02-22_final
2022-02-27 10:33:41	ga_ls8c_ard_3-2-1_102082_2022-02-27_final
2022-03-03 10:07:21	ga_ls8c_ard_3-2-1_098078_2022-03-03_final
2022-03-15 10:28:48	ga_ls8c_ard_3-2-1_102070_2022-03-15_final
2022-03-21 11:31:44	ga_ls8c_ard_3-2-1_112073_2022-03-21_final
2022-03-23 09:40:04	ga_ls8c_ard_3-2-1_094072_2022-03-23_final
2022-03-30 09:45:44	ga_ls8c_ard_3-2-1_095071_2022-03-30_final
2022-04-05 10:51:57	ga_ls8c_ard_3-2-1_105082_2022-04-05_final
2022-04-11 10:08:57	ga_ls8c_ard_3-2-1_099067_2022-04-11_final
2022-04-14 09:06:10	ga_ls8c_ard_3-2-1_088080_2022-04-13_final
2022-04-17 09:34:17	ga_ls8c_ard_3-2-1_093073_2022-04-17_final
2022-05-13 10:09:51	ga_ls8c_ard_3-2-1_099069_2022-05-13_final
2022-05-21 09:27:37	ga_ls8c_ard_3-2-1_091087_2022-05-20_final
2022-05-25 10:39:22	ga_ls8c_ard_3-2-1_103081_2022-05-25_final
2022-06-13 11:06:06	ga_ls8c_ard_3-2-1_108070_2022-06-13_final
2022-06-15 10:55:45	ga_ls8c_ard_3-2-1_106075_2022-06-15_final
2022-06-22 09:22:42	ga_ls8c_ard_3-2-1_091074_2022-06-21_final
2022-06-24 10:50:02	ga_ls8c_ard_3-2-1_105076_2022-06-24_final
2022-07-23 11:58:31	ga_ls8c_ard_3-2-1_116077_2022-07-23_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-09 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-08-08_final
2022-08-12 11:31:59	ga_ls8c_ard_3-2-1_112072_2022-08-12_final
2022-08-17 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-08-17_final
2022-08-21 11:24:38	ga_ls8c_ard_3-2-1_111069_2022-08-21_final
2022-08-27 09:14:15	ga_ls8c_ard_3-2-1_089083_2022-08-26_final
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-09 10:17:54	ga_ls8c_ard_3-2-1_100072_2022-09-09_final
2022-09-10 09:27:52	ga_ls8c_ard_3-2-1_091086_2022-09-09_final
2022-09-18 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-09-18_final
2022-09-24 09:34:42	ga_ls8c_ard_3-2-1_093072_2022-09-24_final
2022-10-08 09:50:58	ga_ls8c_ard_3-2-1_095082_2022-10-08_final
2022-10-13 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-10-13_final
2022-10-20 10:14:29	ga_ls8c_ard_3-2-1_099079_2022-10-20_final
2022-10-20 11:52:58	ga_ls8c_ard_3-2-1_115078_2022-10-20_final
2022-10-28 09:23:07	ga_ls8c_ard_3-2-1_091074_2022-10-27_final
2022-11-15 09:11:04	ga_ls8c_ard_3-2-1_089075_2022-11-14_final
2022-11-15 10:50:21	ga_ls8c_ard_3-2-1_105076_2022-11-15_final
2022-11-25 11:24:39	ga_ls8c_ard_3-2-1_111069_2022-11-25_final
2022-12-08 09:17:39	ga_ls8c_ard_3-2-1_090076_2022-12-07_final
2022-12-22 09:32:14	ga_ls8c_ard_3-2-1_092082_2022-12-22_final
2023-01-13 10:29:37	ga_ls8c_ard_3-2-1_102071_2023-01-13_final
2023-01-24 10:11:29	ga_ls8c_ard_3-2-1_099072_2023-01-24_final
2023-02-06 09:41:00	ga_ls8c_ard_3-2-1_094073_2023-02-06_final
2023-02-09 10:09:52	ga_ls8c_ard_3-2-1_099068_2023-02-09_final
2023-02-12 10:46:19	ga_ls8c_ard_3-2-1_104082_2023-02-12_final
2023-02-14 10:33:32	ga_ls8c_ard_3-2-1_102081_2023-02-14_final
2023-02-18 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-02-18_final
2023-02-25 10:11:11	ga_ls8c_ard_3-2-1_099072_2023-02-25_final
2023-03-01 11:25:45	ga_ls8c_ard_3-2-1_111073_2023-03-01_final
2023-03-06 10:09:21	ga_ls8c_ard_3-2-1_098083_2023-03-06_final
2023-03-08 09:51:46	ga_ls8c_ard_3-2-1_096070_2023-03-08_final
2023-03-09 10:35:49	ga_ls8c_ard_3-2-1_103072_2023-03-09_final
2023-03-15 09:57:08	ga_ls8c_ard_3-2-1_097068_2023-03-15_final
2023-03-16 09:06:41	ga_ls8c_ard_3-2-1_088081_2023-03-15_final
2023-03-29 10:13:44	ga_ls8c_ard_3-2-1_099079_2023-03-29_final
2023-03-29 11:53:01	ga_ls8c_ard_3-2-1_115080_2023-03-29_final
2023-03-30 10:52:59	ga_ls8c_ard_3-2-1_106069_2023-03-30_final
2023-04-02 09:46:34	ga_ls8c_ard_3-2-1_095073_2023-04-02_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