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
2022-01-13 11:02:23	ga_ls8c_ard_3-2-1_107076_2022-01-13_final
2022-01-20 09:34:27	ga_ls8c_ard_3-2-1_092088_2022-01-20_final
2022-02-15 10:03:01	ga_ls8c_ard_3-2-1_098067_2022-02-15_final
2022-03-02 09:28:05	ga_ls8c_ard_3-2-1_091088_2022-03-01_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_2022-03-03_final
2022-03-19 10:02:50	ga_ls8c_ard_3-2-1_098067_2022-03-19_final
2022-03-25 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-03-25_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-08 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-08_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-04-19 09:22:18	ga_ls8c_ard_3-2-1_091074_2022-04-18_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-05-01 11:24:40	ga_ls8c_ard_3-2-1_111071_2022-05-01_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-19 11:17:40	ga_ls8c_ard_3-2-1_109084_2022-05-19_final
2022-05-21 11:04:54	ga_ls8c_ard_3-2-1_107083_2022-05-21_final
2022-05-25 10:34:11	ga_ls8c_ard_3-2-1_103068_2022-05-25_final
2022-05-31 09:57:56	ga_ls8c_ard_3-2-1_097070_2022-05-31_final
2022-06-02 09:49:36	ga_ls8c_ard_3-2-1_095080_2022-06-02_final
2022-06-27 11:19:45	ga_ls8c_ard_3-2-1_110073_2022-06-27_final
2022-07-02 11:42:41	ga_ls8c_ard_3-2-1_113084_2022-07-02_final
2022-07-04 11:23:56	ga_ls8c_ard_3-2-1_111068_2022-07-04_final
2022-07-08 09:28:43	ga_ls8c_ard_3-2-1_091089_2022-07-07_final
2022-08-02 09:21:55	ga_ls8c_ard_3-2-1_090087_2022-08-01_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-25 09:22:13	ga_ls8c_ard_3-2-1_091072_2022-08-24_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-09-03 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-09-02_final
2022-09-04 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-09-04_final
2022-09-04 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-09-04_final
2022-09-19 09:22:56	ga_ls8c_ard_3-2-1_090089_2022-09-18_final
2022-09-21 10:46:40	ga_ls8c_ard_3-2-1_104082_2022-09-21_final
2022-09-22 11:24:21	ga_ls8c_ard_3-2-1_111068_2022-09-22_final
2022-10-22 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-22_final
2022-10-24 11:26:18	ga_ls8c_ard_3-2-1_111073_2022-10-24_final
2022-11-02 11:20:57	ga_ls8c_ard_3-2-1_110075_2022-11-02_final
2022-11-06 10:53:49	ga_ls8c_ard_3-2-1_106069_2022-11-06_final
2022-11-13 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-13_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-25 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-11-25_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-18 09:57:49	ga_ls8c_ard_3-2-1_096084_2022-12-18_final
2022-12-22 11:09:55	ga_ls8c_ard_3-2-1_108079_2022-12-22_final
2023-02-03 10:49:23	ga_ls8c_ard_3-2-1_105074_2023-02-03_final
2023-03-01 09:46:28	ga_ls8c_ard_3-2-1_095072_2023-03-01_final
2023-03-01 11:26:08	ga_ls8c_ard_3-2-1_111074_2023-03-01_final
2023-03-08 09:51:46	ga_ls8c_ard_3-2-1_096070_2023-03-08_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-22 10:04:48	ga_ls8c_ard_3-2-1_098072_2023-03-22_final
2023-04-04 09:35:22	ga_ls8c_ard_3-2-1_093076_2023-04-04_final
2023-04-06 09:21:46	ga_ls8c_ard_3-2-1_091073_2023-04-05_final
2023-04-07 10:02:36	ga_ls8c_ard_3-2-1_098067_2023-04-07_final
2023-04-07 10:09:47	ga_ls8c_ard_3-2-1_098085_2023-04-07_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-04-16 09:57:07	ga_ls8c_ard_3-2-1_097069_2023-04-16_final
2023-04-17 10:39:58	ga_ls8c_ard_3-2-1_104068_2023-04-17_final
2023-04-24 09:12:02	ga_ls8c_ard_3-2-1_089080_2023-04-23_final
2023-04-24 10:51:19	ga_ls8c_ard_3-2-1_105081_2023-04-24_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-16 10:08:24	ga_ls8c_ard_3-2-1_099067_2023-05-16_final
2023-06-24 10:21:11	ga_ls8c_ard_3-2-1_100083_2023-06-24_final
2023-07-01 10:27:05	ga_ls8c_ard_3-2-1_101082_2023-07-01_final
2023-07-06 10:45:41	ga_ls8c_ard_3-2-1_104082_2023-07-06_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-07-27 11:04:45	ga_ls8c_ard_3-2-1_107083_2023-07-27_final
2023-08-04 10:13:46	ga_ls8c_ard_3-2-1_099079_2023-08-04_final
2023-08-20 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-08-20_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-05 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-09-05_final
2023-09-18 09:45:53	ga_ls8c_ard_3-2-1_094086_2023-09-18_final
2023-09-21 10:10:00	ga_ls8c_ard_3-2-1_099069_2023-09-21_final
2023-09-22 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-09-22_final
2023-09-24 10:42:30	ga_ls8c_ard_3-2-1_104073_2023-09-24_final
2023-10-19 10:34:23	ga_ls8c_ard_3-2-1_103068_2023-10-19_final
2023-10-31 11:01:59	ga_ls8c_ard_3-2-1_107075_2023-10-31_final
2023-11-06 10:23:16	ga_ls8c_ard_3-2-1_101071_2023-11-06_final
2023-11-09 10:52:55	ga_ls8c_ard_3-2-1_106068_2023-11-09_final
2023-11-10 09:58:05	ga_ls8c_ard_3-2-1_097070_2023-11-10_final
2023-11-10 11:42:33	ga_ls8c_ard_3-2-1_113084_2023-11-10_final
2023-11-11 09:07:16	ga_ls8c_ard_3-2-1_088082_2023-11-10_final
2023-11-18 10:49:13	ga_ls8c_ard_3-2-1_105074_2023-11-18_final
2023-11-18 10:50:01	ga_ls8c_ard_3-2-1_105076_2023-11-18_final
2023-11-28 09:48:14	ga_ls8c_ard_3-2-1_095076_2023-11-28_final
2023-12-03 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-12-03_final
2023-12-10 10:09:39	ga_ls8c_ard_3-2-1_099068_2023-12-10_final
2023-12-13 09:06:30	ga_ls8c_ard_3-2-1_088080_2023-12-12_final
2023-12-18 09:27:29	ga_ls8c_ard_3-2-1_091086_2023-12-17_final
2023-12-20 09:11:56	ga_ls8c_ard_3-2-1_089078_2023-12-19_final
2023-12-23 09:44:26	ga_ls8c_ard_3-2-1_094082_2023-12-23_final
2024-01-04 10:03:02	ga_ls8c_ard_3-2-1_098067_2024-01-04_final
2024-01-08 09:43:31	ga_ls8c_ard_3-2-1_094080_2024-01-08_final
2024-01-27 10:13:55	ga_ls8c_ard_3-2-1_099079_2024-01-27_final
2024-02-03 10:22:10	ga_ls8c_ard_3-2-1_100084_2024-02-03_final
2024-02-13 09:21:59	ga_ls8c_ard_3-2-1_090088_2024-02-12_final
2024-02-16 09:52:03	ga_ls8c_ard_3-2-1_095086_2024-02-16_final
2024-02-20 09:27:44	ga_ls8c_ard_3-2-1_091087_2024-02-19_final
2024-02-25 11:20:20	ga_ls8c_ard_3-2-1_110075_2024-02-25_final
2024-02-28 10:10:44	ga_ls8c_ard_3-2-1_099071_2024-02-28_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