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
2022-07-24 11:04:06	ga_ls8c_ard_3-2-1_107080_2022-07-24_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-07-31 11:08:21	ga_ls8c_ard_3-2-1_108075_2022-07-31_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-08-24 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-08-24_final
2022-08-25 09:27:01	ga_ls8c_ard_3-2-1_091084_2022-08-24_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-08-30 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-08-30_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-17 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-09-17_final
2022-09-17 11:08:35	ga_ls8c_ard_3-2-1_108075_2022-09-17_final
2022-09-20 11:41:29	ga_ls8c_ard_3-2-1_113080_2022-09-20_final
2022-09-26 11:03:37	ga_ls8c_ard_3-2-1_107078_2022-09-26_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-10-02 10:27:18	ga_ls8c_ard_3-2-1_101080_2022-10-02_final
2022-10-05 10:58:59	ga_ls8c_ard_3-2-1_106082_2022-10-05_final
2022-10-10 09:37:23	ga_ls8c_ard_3-2-1_093079_2022-10-10_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-21 10:56:34	ga_ls8c_ard_3-2-1_106076_2022-10-21_final
2022-10-22 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-22_final
2022-10-26 11:15:33	ga_ls8c_ard_3-2-1_109077_2022-10-26_final
2022-10-28 11:03:12	ga_ls8c_ard_3-2-1_107077_2022-10-28_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-02 11:21:21	ga_ls8c_ard_3-2-1_110076_2022-11-02_final
2022-11-03 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-11-03_final
2022-11-04 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-11-04_final
2022-11-06 10:56:37	ga_ls8c_ard_3-2-1_106076_2022-11-06_final
2022-11-10 10:34:16	ga_ls8c_ard_3-2-1_102082_2022-11-10_final
2022-11-12 10:18:17	ga_ls8c_ard_3-2-1_100073_2022-11-12_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-22 10:53:44	ga_ls8c_ard_3-2-1_106069_2022-11-22_final
2022-11-23 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-11-23_final
2022-11-27 11:14:41	ga_ls8c_ard_3-2-1_109075_2022-11-27_final
2022-12-01 10:51:34	ga_ls8c_ard_3-2-1_105079_2022-12-01_final
2022-12-04 09:40:47	ga_ls8c_ard_3-2-1_094072_2022-12-04_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-15 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-12-15_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2022-12-17 10:50:40	ga_ls8c_ard_3-2-1_105077_2022-12-17_final
2022-12-19 10:34:41	ga_ls8c_ard_3-2-1_103068_2022-12-19_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2022-12-29 09:38:03	ga_ls8c_ard_3-2-1_093081_2022-12-29_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-09 10:54:23	ga_ls8c_ard_3-2-1_106071_2023-01-09_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-18 09:14:47	ga_ls8c_ard_3-2-1_089085_2023-01-17_final
2023-01-21 11:20:14	ga_ls8c_ard_3-2-1_110074_2023-01-21_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-26 09:58:44	ga_ls8c_ard_3-2-1_097071_2023-01-26_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-01-30 11:12:07	ga_ls8c_ard_3-2-1_109069_2023-01-30_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-02-06 09:44:11	ga_ls8c_ard_3-2-1_094081_2023-02-06_final
2023-02-08 09:31:01	ga_ls8c_ard_3-2-1_092079_2023-02-08_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-22 11:18:26	ga_ls8c_ard_3-2-1_110070_2023-02-22_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_final
2023-03-03 09:34:05	ga_ls8c_ard_3-2-1_093072_2023-03-03_final
2023-03-03 09:37:41	ga_ls8c_ard_3-2-1_093081_2023-03-03_final
2023-03-04 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-03-04_final
2023-03-07 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-03-07_final
2023-03-10 11:18:17	ga_ls8c_ard_3-2-1_110070_2023-03-10_final
2023-03-12 09:33:50	ga_ls8c_ard_3-2-1_092087_2023-03-12_final
2023-03-14 09:21:51	ga_ls8c_ard_3-2-1_090088_2023-03-13_final
2023-03-15 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-03-15_final
2023-03-26 09:41:15	ga_ls8c_ard_3-2-1_094075_2023-03-26_final
2023-03-29 11:52:37	ga_ls8c_ard_3-2-1_115079_2023-03-29_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-04-02 11:27:50	ga_ls8c_ard_3-2-1_111079_2023-04-02_final
2023-04-04 09:37:21	ga_ls8c_ard_3-2-1_093081_2023-04-04_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-15 10:57:08	ga_ls8c_ard_3-2-1_106080_2023-04-15_final
2023-04-16 09:56:43	ga_ls8c_ard_3-2-1_097068_2023-04-16_final
2023-04-18 09:51:55	ga_ls8c_ard_3-2-1_095087_2023-04-18_final
2023-04-20 11:13:38	ga_ls8c_ard_3-2-1_109075_2023-04-20_final
2023-04-30 10:15:48	ga_ls8c_ard_3-2-1_099085_2023-04-30_final
2023-05-01 09:16:58	ga_ls8c_ard_3-2-1_090077_2023-04-30_final
2023-05-01 10:57:03	ga_ls8c_ard_3-2-1_106080_2023-05-01_final
2023-05-08 11:04:20	ga_ls8c_ard_3-2-1_107083_2023-05-08_final
2023-05-09 10:09:05	ga_ls8c_ard_3-2-1_098084_2023-05-09_final
2023-05-10 10:49:32	ga_ls8c_ard_3-2-1_105077_2023-05-10_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