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
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-05-17_final
2022-05-19 09:39:10	ga_ls8c_ard_3-2-1_093085_2022-05-19_final
2022-05-22 11:46:58	ga_ls8c_ard_3-2-1_114080_2022-05-22_final
2022-05-24 09:54:31	ga_ls8c_ard_3-2-1_096077_2022-05-24_final
2022-05-25 10:37:22	ga_ls8c_ard_3-2-1_103076_2022-05-25_final
2022-05-26 11:18:14	ga_ls8c_ard_3-2-1_110070_2022-05-26_final
2022-05-28 11:08:40	ga_ls8c_ard_3-2-1_108077_2022-05-28_final
2022-05-30 09:21:03	ga_ls8c_ard_3-2-1_090086_2022-05-29_final
2022-06-16 10:00:56	ga_ls8c_ard_3-2-1_097077_2022-06-16_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-06-21_final
2022-06-25 09:56:24	ga_ls8c_ard_3-2-1_096081_2022-06-25_final
2022-06-29 09:30:30	ga_ls8c_ard_3-2-1_092078_2022-06-29_final
2022-07-03 10:45:04	ga_ls8c_ard_3-2-1_104079_2022-07-03_final
2022-07-04 09:50:14	ga_ls8c_ard_3-2-1_095081_2022-07-04_final
2022-07-14 10:25:18	ga_ls8c_ard_3-2-1_101076_2022-07-14_final
2022-07-16 11:51:02	ga_ls8c_ard_3-2-1_115074_2022-07-16_final
2022-07-26 09:13:40	ga_ls8c_ard_3-2-1_089082_2022-07-25_final
2022-07-29 09:45:00	ga_ls8c_ard_3-2-1_094083_2022-07-29_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-08-07 11:12:36	ga_ls8c_ard_3-2-1_109070_2022-08-07_final
2022-08-08 10:20:59	ga_ls8c_ard_3-2-1_100080_2022-08-08_final
2022-08-09 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-08-09_final
2022-08-18 09:20:01	ga_ls8c_ard_3-2-1_090082_2022-08-17_final
2022-08-21 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-08-21_final
2022-08-31 10:24:49	ga_ls8c_ard_3-2-1_101074_2022-08-31_final
2022-09-03 10:58:30	ga_ls8c_ard_3-2-1_106081_2022-09-03_final
2022-09-19 09:20:32	ga_ls8c_ard_3-2-1_090083_2022-09-18_final
2022-10-03 09:32:05	ga_ls8c_ard_3-2-1_092081_2022-10-03_final
2022-10-13 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-10-13_final
2022-11-02 11:23:21	ga_ls8c_ard_3-2-1_110081_2022-11-02_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-09 09:50:37	ga_ls8c_ard_3-2-1_095081_2022-11-09_final
2022-11-14 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-14_final
2022-11-14 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-14_final
2022-11-17 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-11-17_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-08 09:18:51	ga_ls8c_ard_3-2-1_090079_2022-12-07_final
2022-12-11 11:27:48	ga_ls8c_ard_3-2-1_111077_2022-12-11_final
2022-12-14 10:20:36	ga_ls8c_ard_3-2-1_100079_2022-12-14_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final
2022-12-31 09:26:05	ga_ls8c_ard_3-2-1_091082_2022-12-30_final
2023-01-02 10:51:25	ga_ls8c_ard_3-2-1_105079_2023-01-02_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-19 09:52:52	ga_ls8c_ard_3-2-1_096072_2023-01-19_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-02-13 09:48:17	ga_ls8c_ard_3-2-1_095076_2023-02-13_final
2023-02-15 09:36:42	ga_ls8c_ard_3-2-1_093078_2023-02-15_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-24 09:32:20	ga_ls8c_ard_3-2-1_092083_2023-02-24_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-06 11:46:38	ga_ls8c_ard_3-2-1_114079_2023-03-06_final
2023-03-09 10:38:13	ga_ls8c_ard_3-2-1_103078_2023-03-09_final
2023-03-10 11:21:05	ga_ls8c_ard_3-2-1_110077_2023-03-10_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-28 11:09:45	ga_ls8c_ard_3-2-1_108080_2023-03-28_final
2023-04-09 09:52:35	ga_ls8c_ard_3-2-1_096073_2023-04-09_final
2023-04-09 09:55:47	ga_ls8c_ard_3-2-1_096081_2023-04-09_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-04-29 09:29:45	ga_ls8c_ard_3-2-1_092078_2023-04-28_final
2023-05-01 09:17:46	ga_ls8c_ard_3-2-1_090079_2023-04-30_final
2023-05-08 11:02:20	ga_ls8c_ard_3-2-1_107078_2023-05-08_final
2023-05-09 10:04:42	ga_ls8c_ard_3-2-1_098073_2023-05-09_final
2023-05-09 10:05:54	ga_ls8c_ard_3-2-1_098076_2023-05-09_final
2023-05-10 09:09:27	ga_ls8c_ard_3-2-1_089074_2023-05-09_final
2023-05-12 10:37:56	ga_ls8c_ard_3-2-1_103079_2023-05-12_final
2023-05-15 09:30:20	ga_ls8c_ard_3-2-1_092080_2023-05-15_final
2023-05-22 11:14:37	ga_ls8c_ard_3-2-1_109078_2023-05-22_final
2023-05-31 09:29:58	ga_ls8c_ard_3-2-1_092079_2023-05-30_final
2023-06-07 11:15:30	ga_ls8c_ard_3-2-1_109080_2023-06-07_final
2023-06-10 11:45:15	ga_ls8c_ard_3-2-1_114077_2023-06-10_final
2023-06-12 09:54:49	ga_ls8c_ard_3-2-1_096079_2023-06-12_final
2023-06-16 11:06:13	ga_ls8c_ard_3-2-1_108072_2023-06-16_final
2023-06-17 10:11:47	ga_ls8c_ard_3-2-1_099075_2023-06-17_final
2023-06-19 11:39:55	ga_ls8c_ard_3-2-1_113079_2023-06-19_final
2023-07-09 09:37:43	ga_ls8c_ard_3-2-1_093082_2023-07-09_final
2023-07-09 09:38:31	ga_ls8c_ard_3-2-1_093084_2023-07-09_final
2023-07-16 09:43:31	ga_ls8c_ard_3-2-1_094081_2023-07-16_final
2023-07-27 11:02:45	ga_ls8c_ard_3-2-1_107078_2023-07-27_final
2023-08-02 10:23:44	ga_ls8c_ard_3-2-1_101073_2023-08-02_final
2023-08-04 11:50:40	ga_ls8c_ard_3-2-1_115074_2023-08-04_final
2023-08-05 10:54:15	ga_ls8c_ard_3-2-1_106072_2023-08-05_final
2023-08-08 11:23:33	ga_ls8c_ard_3-2-1_111068_2023-08-08_final
2023-08-14 10:48:06	ga_ls8c_ard_3-2-1_105072_2023-08-14_final
2023-08-14 10:51:18	ga_ls8c_ard_3-2-1_105080_2023-08-14_final
2023-08-21 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-08-20_final
2023-08-24 09:48:00	ga_ls8c_ard_3-2-1_095076_2023-08-24_final
2023-09-09 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-09-09_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