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
2022-01-14 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-01-14_final
2022-09-18 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-09-18_final
2022-09-19 10:55:50	ga_ls8c_ard_3-2-1_106074_2022-09-19_final
2022-09-20 09:57:25	ga_ls8c_ard_3-2-1_097067_2022-09-20_final
2022-09-20 10:00:13	ga_ls8c_ard_3-2-1_097074_2022-09-20_final
2022-09-23 10:30:43	ga_ls8c_ard_3-2-1_102073_2022-09-23_final
2022-10-05 09:18:54	ga_ls8c_ard_3-2-1_090079_2022-10-04_final
2022-10-07 10:41:49	ga_ls8c_ard_3-2-1_104070_2022-10-07_final
2022-10-10 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-10-10_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-11 10:17:26	ga_ls8c_ard_3-2-1_100071_2022-10-11_final
2022-10-13 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-10-13_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-14 09:15:00	ga_ls8c_ard_3-2-1_089085_2022-10-13_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-15 09:53:53	ga_ls8c_ard_3-2-1_096074_2022-10-15_final
2022-10-18 10:24:02	ga_ls8c_ard_3-2-1_101072_2022-10-18_final
2022-10-25 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-10-25_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-26 11:15:09	ga_ls8c_ard_3-2-1_109076_2022-10-26_final
2022-10-26 11:17:56	ga_ls8c_ard_3-2-1_109083_2022-10-26_final
2022-10-29 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-10-29_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-11-01 10:36:29	ga_ls8c_ard_3-2-1_103072_2022-11-01_final
2022-11-02 11:19:45	ga_ls8c_ard_3-2-1_110072_2022-11-02_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-13 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-12_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-14 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-14_final
2022-11-15 09:13:52	ga_ls8c_ard_3-2-1_089082_2022-11-14_final
2022-11-18 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-11-18_final
2022-11-22 09:18:02	ga_ls8c_ard_3-2-1_090077_2022-11-21_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-04 09:46:46	ga_ls8c_ard_3-2-1_094087_2022-12-04_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-07 10:13:40	ga_ls8c_ard_3-2-1_099077_2022-12-07_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-15 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-12-14_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-16 10:10:12	ga_ls8c_ard_3-2-1_098084_2022-12-16_final
2022-12-17 09:13:46	ga_ls8c_ard_3-2-1_089082_2022-12-16_final
2022-12-17 10:49:04	ga_ls8c_ard_3-2-1_105073_2022-12-17_final
2022-12-18 09:55:02	ga_ls8c_ard_3-2-1_096077_2022-12-18_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-26 10:45:37	ga_ls8c_ard_3-2-1_104080_2022-12-26_final
2022-12-29 09:40:26	ga_ls8c_ard_3-2-1_093087_2022-12-29_final
2022-12-29 11:14:08	ga_ls8c_ard_3-2-1_109074_2022-12-29_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-07 09:29:28	ga_ls8c_ard_3-2-1_092075_2023-01-06_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-09 10:54:47	ga_ls8c_ard_3-2-1_106072_2023-01-09_final
2023-01-09 10:59:10	ga_ls8c_ard_3-2-1_106083_2023-01-09_final
2023-01-10 10:04:20	ga_ls8c_ard_3-2-1_097085_2023-01-10_final
2023-01-12 11:29:14	ga_ls8c_ard_3-2-1_111081_2023-01-12_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-08 09:29:49	ga_ls8c_ard_3-2-1_092076_2023-02-07_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-14 10:30:21	ga_ls8c_ard_3-2-1_102073_2023-02-14_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-24 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-02-24_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-03-01 11:30:08	ga_ls8c_ard_3-2-1_111084_2023-03-01_final
2023-03-03 09:38:05	ga_ls8c_ard_3-2-1_093082_2023-03-03_final
2023-03-05 11:00:36	ga_ls8c_ard_3-2-1_107072_2023-03-05_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-12 09:30:38	ga_ls8c_ard_3-2-1_092079_2023-03-12_final
2023-03-12 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-03-12_final
2023-03-13 10:12:42	ga_ls8c_ard_3-2-1_099076_2023-03-13_final
2023-03-13 11:51:35	ga_ls8c_ard_3-2-1_115076_2023-03-13_final
2023-03-14 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-03-14_final
2023-03-24 09:52:49	ga_ls8c_ard_3-2-1_096073_2023-03-24_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-04 11:11:51	ga_ls8c_ard_3-2-1_109070_2023-04-04_final
2023-04-10 10:35:02	ga_ls8c_ard_3-2-1_103071_2023-04-10_final
2023-04-15 10:54:20	ga_ls8c_ard_3-2-1_106073_2023-04-15_final
2023-04-16 09:58:42	ga_ls8c_ard_3-2-1_097073_2023-04-16_final
2023-04-17 10:40:22	ga_ls8c_ard_3-2-1_104069_2023-04-17_final
2023-04-20 11:13:38	ga_ls8c_ard_3-2-1_109075_2023-04-20_final
2023-04-24 10:47:43	ga_ls8c_ard_3-2-1_105072_2023-04-24_final
2023-05-02 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-05-02_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-08 09:25:51	ga_ls8c_ard_3-2-1_091084_2023-05-07_final
2023-05-09 11:45:35	ga_ls8c_ard_3-2-1_114078_2023-05-09_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-13 09:40:19	ga_ls8c_ard_3-2-1_094074_2023-05-13_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-15 11:10:49	ga_ls8c_ard_3-2-1_108084_2023-05-15_final
2023-05-16 10:13:11	ga_ls8c_ard_3-2-1_099079_2023-05-16_final
2023-05-26 09:13:49	ga_ls8c_ard_3-2-1_089085_2023-05-25_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