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
2021-12-20 10:09:03	ga_ls8c_ard_3-2-1_099066_2021-12-20_final
2022-01-14 10:03:11	ga_ls8c_ard_3-2-1_098067_2022-01-14_final
2022-03-21 11:31:20	ga_ls8c_ard_3-2-1_112072_2022-03-21_final
2022-03-26 11:52:12	ga_ls8c_ard_3-2-1_115078_2022-03-26_final
2022-04-28 10:55:20	ga_ls8c_ard_3-2-1_106075_2022-04-28_final
2022-05-14 09:16:37	ga_ls8c_ard_3-2-1_090075_2022-05-13_final
2022-05-21 09:28:01	ga_ls8c_ard_3-2-1_091088_2022-05-20_final
2022-06-02 09:46:01	ga_ls8c_ard_3-2-1_095071_2022-06-02_final
2022-06-06 09:27:44	ga_ls8c_ard_3-2-1_091087_2022-06-05_final
2022-06-08 10:49:54	ga_ls8c_ard_3-2-1_105076_2022-06-08_final
2022-06-13 09:28:49	ga_ls8c_ard_3-2-1_092074_2022-06-12_final
2022-06-22 11:05:11	ga_ls8c_ard_3-2-1_107083_2022-06-22_final
2022-06-24 10:52:49	ga_ls8c_ard_3-2-1_105083_2022-06-24_final
2022-06-26 10:36:05	ga_ls8c_ard_3-2-1_103072_2022-06-26_final
2022-06-28 10:24:31	ga_ls8c_ard_3-2-1_101074_2022-06-28_final
2022-06-29 11:11:23	ga_ls8c_ard_3-2-1_108083_2022-06-29_final
2022-07-13 09:40:27	ga_ls8c_ard_3-2-1_094072_2022-07-13_final
2022-07-16 10:08:57	ga_ls8c_ard_3-2-1_099066_2022-07-16_final
2022-07-25 10:07:41	ga_ls8c_ard_3-2-1_098078_2022-07-25_final
2022-07-31 09:28:17	ga_ls8c_ard_3-2-1_092072_2022-07-30_final
2022-08-14 09:45:32	ga_ls8c_ard_3-2-1_094084_2022-08-14_final
2022-08-17 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-08-17_final
2022-08-26 10:05:29	ga_ls8c_ard_3-2-1_098072_2022-08-26_final
2022-08-28 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-08-28_final
2022-09-29 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-09-29_final
2022-09-29 11:32:54	ga_ls8c_ard_3-2-1_112074_2022-09-29_final
2022-10-02 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-10-02_final
2022-10-06 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-06_final
2022-10-07 09:07:43	ga_ls8c_ard_3-2-1_088082_2022-10-06_final
2022-10-12 09:28:11	ga_ls8c_ard_3-2-1_091087_2022-10-11_final
2022-11-09 11:26:18	ga_ls8c_ard_3-2-1_111073_2022-11-09_final
2022-11-29 09:22:15	ga_ls8c_ard_3-2-1_091072_2022-11-28_final
2022-11-29 11:00:44	ga_ls8c_ard_3-2-1_107071_2022-11-29_final
2022-12-04 09:40:23	ga_ls8c_ard_3-2-1_094071_2022-12-04_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-07 11:51:45	ga_ls8c_ard_3-2-1_115075_2022-12-07_final
2022-12-08 10:56:08	ga_ls8c_ard_3-2-1_106075_2022-12-08_final
2022-12-13 09:34:57	ga_ls8c_ard_3-2-1_093073_2022-12-13_final
2022-12-15 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-12-14_final
2022-12-17 09:14:34	ga_ls8c_ard_3-2-1_089084_2022-12-16_final
2022-12-20 11:19:31	ga_ls8c_ard_3-2-1_110072_2022-12-20_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-24 09:17:05	ga_ls8c_ard_3-2-1_090075_2022-12-23_final
2022-12-26 09:06:44	ga_ls8c_ard_3-2-1_088080_2022-12-25_final
2022-12-26 09:07:32	ga_ls8c_ard_3-2-1_088082_2022-12-25_final
2023-01-08 10:09:08	ga_ls8c_ard_3-2-1_099066_2023-01-08_final
2023-01-24 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-01-24_final
2023-02-01 11:00:33	ga_ls8c_ard_3-2-1_107071_2023-02-01_final
2023-02-24 09:28:44	ga_ls8c_ard_3-2-1_092074_2023-02-23_final
2023-03-01 09:46:28	ga_ls8c_ard_3-2-1_095072_2023-03-01_final
2023-03-01 11:24:09	ga_ls8c_ard_3-2-1_111069_2023-03-01_final
2023-03-05 09:22:54	ga_ls8c_ard_3-2-1_091075_2023-03-04_final
2023-03-10 09:41:00	ga_ls8c_ard_3-2-1_094074_2023-03-10_final
2023-03-14 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-03-13_final
2023-03-15 09:57:32	ga_ls8c_ard_3-2-1_097069_2023-03-15_final
2023-03-20 10:20:48	ga_ls8c_ard_3-2-1_100081_2023-03-20_final
2023-03-21 09:23:10	ga_ls8c_ard_3-2-1_091076_2023-03-20_final
2023-03-31 11:42:13	ga_ls8c_ard_3-2-1_113084_2023-03-31_final
2023-04-15 10:54:20	ga_ls8c_ard_3-2-1_106073_2023-04-15_final
2023-05-02 10:03:01	ga_ls8c_ard_3-2-1_097084_2023-05-02_final
2023-05-07 10:16:18	ga_ls8c_ard_3-2-1_100071_2023-05-07_final
2023-05-08 09:22:15	ga_ls8c_ard_3-2-1_091075_2023-05-07_final
2023-05-11 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-11_final
2023-05-16 11:50:52	ga_ls8c_ard_3-2-1_115076_2023-05-16_final
2023-05-17 10:52:03	ga_ls8c_ard_3-2-1_106068_2023-05-17_final
2023-06-01 10:09:14	ga_ls8c_ard_3-2-1_099069_2023-06-01_final
2023-06-02 10:52:06	ga_ls8c_ard_3-2-1_106068_2023-06-02_final
2023-06-05 11:25:03	ga_ls8c_ard_3-2-1_111073_2023-06-05_final
2023-06-11 09:09:33	ga_ls8c_ard_3-2-1_089074_2023-06-10_final
2023-06-20 09:05:48	ga_ls8c_ard_3-2-1_088080_2023-06-19_final
2023-07-03 10:09:33	ga_ls8c_ard_3-2-1_099069_2023-07-03_final
2023-07-11 09:22:11	ga_ls8c_ard_3-2-1_091074_2023-07-10_final
2023-08-05 09:21:45	ga_ls8c_ard_3-2-1_090088_2023-08-04_final
2023-08-10 11:13:59	ga_ls8c_ard_3-2-1_109075_2023-08-10_final
2023-08-14 09:10:25	ga_ls8c_ard_3-2-1_089075_2023-08-13_final
2023-08-20 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-08-20_final
2023-08-21 09:22:16	ga_ls8c_ard_3-2-1_090089_2023-08-20_final
2023-09-04 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-09-04_final
2023-09-06 09:22:15	ga_ls8c_ard_3-2-1_090089_2023-09-05_final
2023-09-23 11:38:31	ga_ls8c_ard_3-2-1_113074_2023-09-23_final
2023-10-08 09:16:50	ga_ls8c_ard_3-2-1_090075_2023-10-07_final
2023-10-09 10:03:42	ga_ls8c_ard_3-2-1_097084_2023-10-09_final
2023-10-22 09:34:49	ga_ls8c_ard_3-2-1_092089_2023-10-22_final
2023-10-24 09:22:52	ga_ls8c_ard_3-2-1_090090_2023-10-23_final
2023-11-08 11:52:57	ga_ls8c_ard_3-2-1_115079_2023-11-08_final
2023-11-12 11:25:50	ga_ls8c_ard_3-2-1_111073_2023-11-12_final
2023-11-17 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-11-17_final
2023-12-02 09:21:52	ga_ls8c_ard_3-2-1_091072_2023-12-01_final
2023-12-13 09:07:18	ga_ls8c_ard_3-2-1_088082_2023-12-12_final
2023-12-19 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-12-19_final
2023-12-21 11:32:29	ga_ls8c_ard_3-2-1_112074_2023-12-21_final
2023-12-30 09:52:33	ga_ls8c_ard_3-2-1_095087_2023-12-30_final
2024-01-03 09:21:47	ga_ls8c_ard_3-2-1_091072_2024-01-02_final
2024-01-06 09:58:15	ga_ls8c_ard_3-2-1_096086_2024-01-06_final
2024-01-09 10:27:35	ga_ls8c_ard_3-2-1_101082_2024-01-09_final
2024-01-28 09:21:54	ga_ls8c_ard_3-2-1_090088_2024-01-27_final
2024-01-28 10:54:24	ga_ls8c_ard_3-2-1_106072_2024-01-28_final
2024-02-12 11:52:30	ga_ls8c_ard_3-2-1_115078_2024-02-12_final
2024-02-12 11:52:54	ga_ls8c_ard_3-2-1_115079_2024-02-12_final
2024-02-15 10:41:42	ga_ls8c_ard_3-2-1_104071_2024-02-15_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