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
2022-01-14 10:09:34	ga_ls8c_ard_3-2-1_098083_2022-01-14_final
2022-12-06 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-12-06_final
2022-12-06 11:06:06	ga_ls8c_ard_3-2-1_108069_2022-12-06_final
2022-12-06 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-12-06_final
2022-12-12 10:30:59	ga_ls8c_ard_3-2-1_102074_2022-12-12_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-12 10:34:10	ga_ls8c_ard_3-2-1_102082_2022-12-12_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-22 11:11:07	ga_ls8c_ard_3-2-1_108082_2022-12-22_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-30 10:21:43	ga_ls8c_ard_3-2-1_100082_2022-12-30_final
2022-12-31 09:27:41	ga_ls8c_ard_3-2-1_091086_2022-12-30_final
2023-01-03 09:57:47	ga_ls8c_ard_3-2-1_096084_2023-01-03_final
2023-01-05 09:45:25	ga_ls8c_ard_3-2-1_094084_2023-01-05_final
2023-01-05 11:20:43	ga_ls8c_ard_3-2-1_110075_2023-01-05_final
2023-01-06 10:25:29	ga_ls8c_ard_3-2-1_101076_2023-01-06_final
2023-01-07 09:31:51	ga_ls8c_ard_3-2-1_092081_2023-01-07_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-09 09:19:05	ga_ls8c_ard_3-2-1_090080_2023-01-08_final
2023-01-10 11:39:14	ga_ls8c_ard_3-2-1_113075_2023-01-10_final
2023-01-10 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-10_final
2023-01-12 11:29:14	ga_ls8c_ard_3-2-1_111081_2023-01-12_final
2023-01-12 11:30:02	ga_ls8c_ard_3-2-1_111083_2023-01-12_final
2023-01-13 10:32:24	ga_ls8c_ard_3-2-1_102078_2023-01-13_final
2023-01-16 09:25:34	ga_ls8c_ard_3-2-1_091081_2023-01-15_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-22 10:24:37	ga_ls8c_ard_3-2-1_101074_2023-01-22_final
2023-01-23 09:31:00	ga_ls8c_ard_3-2-1_092079_2023-01-23_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-01-26 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-26_final
2023-01-30 09:36:49	ga_ls8c_ard_3-2-1_093078_2023-01-30_final
2023-01-30 11:15:18	ga_ls8c_ard_3-2-1_109077_2023-01-30_final
2023-01-30 11:17:18	ga_ls8c_ard_3-2-1_109082_2023-01-30_final
2023-02-01 09:27:39	ga_ls8c_ard_3-2-1_091086_2023-01-31_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-06 11:23:28	ga_ls8c_ard_3-2-1_110082_2023-02-06_final
2023-02-06 11:23:52	ga_ls8c_ard_3-2-1_110083_2023-02-06_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-13 11:26:46	ga_ls8c_ard_3-2-1_111075_2023-02-13_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-26 09:19:09	ga_ls8c_ard_3-2-1_090081_2023-02-25_final
2023-02-27 10:00:25	ga_ls8c_ard_3-2-1_097076_2023-02-27_final
2023-03-02 10:31:43	ga_ls8c_ard_3-2-1_102077_2023-03-02_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-05 09:23:42	ga_ls8c_ard_3-2-1_091077_2023-03-04_final
2023-03-05 09:27:42	ga_ls8c_ard_3-2-1_091087_2023-03-04_final
2023-03-05 11:01:47	ga_ls8c_ard_3-2-1_107075_2023-03-05_final
2023-03-07 09:13:43	ga_ls8c_ard_3-2-1_089083_2023-03-06_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-03-11 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-03-11_final
2023-03-12 11:06:20	ga_ls8c_ard_3-2-1_108071_2023-03-12_final
2023-03-12 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-03-12_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-15 11:41:12	ga_ls8c_ard_3-2-1_113081_2023-03-15_final
2023-03-17 11:29:13	ga_ls8c_ard_3-2-1_111082_2023-03-17_final
2023-03-21 11:05:14	ga_ls8c_ard_3-2-1_107084_2023-03-21_final
2023-03-24 09:53:13	ga_ls8c_ard_3-2-1_096074_2023-03-24_final
2023-03-27 10:23:42	ga_ls8c_ard_3-2-1_101073_2023-03-27_final
2023-03-27 10:24:30	ga_ls8c_ard_3-2-1_101075_2023-03-27_final
2023-03-28 11:10:09	ga_ls8c_ard_3-2-1_108081_2023-03-28_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-05 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-04-05_final
2023-04-11 09:44:58	ga_ls8c_ard_3-2-1_094085_2023-04-11_final
2023-04-11 11:23:03	ga_ls8c_ard_3-2-1_110083_2023-04-11_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-12 10:23:27	ga_ls8c_ard_3-2-1_101073_2023-04-12_final
2023-04-14 11:51:10	ga_ls8c_ard_3-2-1_115076_2023-04-14_final
2023-04-16 10:00:18	ga_ls8c_ard_3-2-1_097077_2023-04-16_final
2023-04-16 10:01:54	ga_ls8c_ard_3-2-1_097081_2023-04-16_final
2023-04-17 10:40:22	ga_ls8c_ard_3-2-1_104069_2023-04-17_final
2023-04-20 11:12:50	ga_ls8c_ard_3-2-1_109073_2023-04-20_final
2023-04-27 09:40:08	ga_ls8c_ard_3-2-1_094073_2023-04-27_final
2023-05-01 10:54:16	ga_ls8c_ard_3-2-1_106073_2023-05-01_final
2023-05-01 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-05-01_final
2023-05-03 10:43:04	ga_ls8c_ard_3-2-1_104076_2023-05-03_final
2023-05-04 09:51:02	ga_ls8c_ard_3-2-1_095085_2023-05-04_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-05 10:30:17	ga_ls8c_ard_3-2-1_102075_2023-05-05_final
2023-05-05 10:32:17	ga_ls8c_ard_3-2-1_102080_2023-05-05_final
2023-05-08 10:59:33	ga_ls8c_ard_3-2-1_107071_2023-05-08_final
2023-05-09 10:05:06	ga_ls8c_ard_3-2-1_098074_2023-05-09_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-09 11:45:11	ga_ls8c_ard_3-2-1_114077_2023-05-09_final
2023-05-09 11:45:35	ga_ls8c_ard_3-2-1_114078_2023-05-09_final
2023-05-10 09:12:15	ga_ls8c_ard_3-2-1_089081_2023-05-09_final
2023-05-10 09:13:51	ga_ls8c_ard_3-2-1_089085_2023-05-09_final
2023-05-13 09:43:30	ga_ls8c_ard_3-2-1_094082_2023-05-13_final
2023-05-13 09:44:18	ga_ls8c_ard_3-2-1_094084_2023-05-13_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-14 10:22:22	ga_ls8c_ard_3-2-1_101071_2023-05-14_final
2023-05-18 09:58:49	ga_ls8c_ard_3-2-1_097074_2023-05-18_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_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