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:

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First 100 results (query limit)

Time (local)	Label
2021-08-20 09:35:25	ga_ls8c_ard_3-2-0_093075_2021-08-20_final
2021-09-05 09:32:18	ga_ls8c_ard_3-2-0_093067_2021-09-05_final
2021-09-06 11:57:38	ga_ls8c_ard_3-2-0_116075_2021-09-06_final
2021-09-12 09:46:29	ga_ls8c_ard_3-2-0_094087_2021-09-12_final
2021-09-20 10:28:46	ga_ls8c_ard_3-2-0_102069_2021-09-20_final
2021-09-20 10:29:10	ga_ls8c_ard_3-2-0_102070_2021-09-20_final
2021-09-28 09:46:33	ga_ls8c_ard_3-2-0_094087_2021-09-28_final
2021-10-16 11:11:34	ga_ls8c_ard_3-2-0_108083_2021-10-16_final
2021-11-01 11:06:46	ga_ls8c_ard_3-2-0_108071_2021-11-01_final
2021-11-12 09:13:17	ga_ls8c_ard_3-2-0_089081_2021-11-11_final
2021-11-12 10:47:23	ga_ls8c_ard_3-2-0_105069_2021-11-12_final
2021-11-19 09:22:37	ga_ls8c_ard_3-2-0_090089_2021-11-18_final
2021-11-29 09:57:44	ga_ls8c_ard_3-2-0_096084_2021-11-29_final
2021-12-12 11:00:07	ga_ls8c_ard_3-2-1_107070_2021-12-12_final
2021-12-21 09:18:13	ga_ls8c_ard_3-2-1_090078_2021-12-20_final
2021-12-26 09:36:43	ga_ls8c_ard_3-2-1_093078_2021-12-26_final
2022-01-10 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-01-10_final
2022-01-16 09:58:23	ga_ls8c_ard_3-2-1_096086_2022-01-16_final
2022-01-19 10:23:41	ga_ls8c_ard_3-2-1_101072_2022-01-19_final
2022-01-20 09:33:15	ga_ls8c_ard_3-2-1_092085_2022-01-20_final
2022-02-05 11:06:29	ga_ls8c_ard_3-2-1_108071_2022-02-05_final
2022-02-05 11:06:53	ga_ls8c_ard_3-2-1_108072_2022-02-05_final
2022-02-14 11:05:26	ga_ls8c_ard_3-2-1_107084_2022-02-14_final
2022-02-17 09:52:38	ga_ls8c_ard_3-2-1_096072_2022-02-17_final
2022-03-02 10:59:47	ga_ls8c_ard_3-2-1_107070_2022-03-02_final
2022-03-12 09:57:32	ga_ls8c_ard_3-2-1_097069_2022-03-12_final
2022-03-24 10:25:18	ga_ls8c_ard_3-2-1_101077_2022-03-24_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-14 09:06:34	ga_ls8c_ard_3-2-1_088081_2022-04-13_final
2022-05-10 11:23:47	ga_ls8c_ard_3-2-1_110084_2022-05-10_final
2022-05-14 10:53:31	ga_ls8c_ard_3-2-1_106070_2022-05-14_final
2022-05-15 10:03:53	ga_ls8c_ard_3-2-1_097085_2022-05-15_final
2022-05-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2022-05-18_final
2022-05-31 11:42:01	ga_ls8c_ard_3-2-1_113083_2022-05-31_final
2022-06-02 09:49:36	ga_ls8c_ard_3-2-1_095080_2022-06-02_final
2022-06-03 10:31:41	ga_ls8c_ard_3-2-1_102077_2022-06-03_final
2022-06-23 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-06-23_final
2022-06-27 11:19:21	ga_ls8c_ard_3-2-1_110072_2022-06-27_final
2022-06-27 11:20:09	ga_ls8c_ard_3-2-1_110074_2022-06-27_final
2022-06-29 11:06:11	ga_ls8c_ard_3-2-1_108070_2022-06-29_final
2022-06-30 10:14:34	ga_ls8c_ard_3-2-1_099080_2022-06-30_final
2022-07-05 10:33:54	ga_ls8c_ard_3-2-1_102082_2022-07-05_final
2022-07-11 09:52:01	ga_ls8c_ard_3-2-1_096070_2022-07-11_final
2022-07-16 10:11:21	ga_ls8c_ard_3-2-1_099072_2022-07-16_final
2022-07-24 09:22:01	ga_ls8c_ard_3-2-1_091072_2022-07-23_final
2022-08-08 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-08-08_final
2022-08-09 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-08-08_final
2022-08-11 10:47:31	ga_ls8c_ard_3-2-1_105069_2022-08-11_final
2022-09-01 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-09-01_final
2022-09-20 10:03:00	ga_ls8c_ard_3-2-1_097081_2022-09-20_final
2022-10-01 09:40:28	ga_ls8c_ard_3-2-1_094071_2022-10-01_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-27 10:17:56	ga_ls8c_ard_3-2-1_100072_2022-10-27_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-14 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-14_final
2022-11-14 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-14_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-17 10:07:37	ga_ls8c_ard_3-2-1_098078_2023-01-17_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-07 09:16:06	ga_ls8c_ard_3-2-1_089089_2023-03-06_final
2023-03-18 10:28:24	ga_ls8c_ard_3-2-1_102069_2023-03-18_final
2023-03-22 11:44:53	ga_ls8c_ard_3-2-1_114075_2023-03-22_final
2023-03-26 09:45:14	ga_ls8c_ard_3-2-1_094085_2023-03-26_final
2023-03-28 11:10:57	ga_ls8c_ard_3-2-1_108083_2023-03-28_final
2023-04-08 10:46:38	ga_ls8c_ard_3-2-1_105069_2023-04-08_final
2023-04-11 11:23:27	ga_ls8c_ard_3-2-1_110084_2023-04-11_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-20 11:24:34	ga_ls8c_ard_3-2-1_111072_2023-05-20_final
2023-05-21 10:29:21	ga_ls8c_ard_3-2-1_102073_2023-05-21_final
2023-05-24 09:26:58	ga_ls8c_ard_3-2-1_091087_2023-05-23_final
2023-05-24 11:01:04	ga_ls8c_ard_3-2-1_107075_2023-05-24_final
2023-06-09 09:21:53	ga_ls8c_ard_3-2-1_091074_2023-06-08_final
2023-06-10 10:06:22	ga_ls8c_ard_3-2-1_098077_2023-06-10_final
2023-06-11 09:15:32	ga_ls8c_ard_3-2-1_089089_2023-06-10_final
2023-06-14 09:40:28	ga_ls8c_ard_3-2-1_094074_2023-06-14_final
2023-06-20 10:44:41	ga_ls8c_ard_3-2-1_104080_2023-06-20_final
2023-06-25 09:25:59	ga_ls8c_ard_3-2-1_091084_2023-06-24_final
2023-07-06 10:45:41	ga_ls8c_ard_3-2-1_104082_2023-07-06_final
2023-07-13 10:49:06	ga_ls8c_ard_3-2-1_105075_2023-07-13_final
2023-07-18 11:06:51	ga_ls8c_ard_3-2-1_108073_2023-07-18_final
2023-07-29 09:11:08	ga_ls8c_ard_3-2-1_089077_2023-07-28_final
2023-08-03 09:30:54	ga_ls8c_ard_3-2-1_092080_2023-08-03_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-21 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-08-20_final
2023-09-06 10:53:09	ga_ls8c_ard_3-2-1_106069_2023-09-06_final
2023-09-12 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-09-12_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