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
2022-03-04 09:10:08	ga_ls8c_ard_3-2-1_089074_2022-03-03_final
2022-03-04 09:12:08	ga_ls8c_ard_3-2-1_089079_2022-03-03_final
2022-03-04 09:14:07	ga_ls8c_ard_3-2-1_089084_2022-03-03_final
2022-03-04 10:48:13	ga_ls8c_ard_3-2-1_105072_2022-03-04_final
2022-03-04 10:49:25	ga_ls8c_ard_3-2-1_105075_2022-03-04_final
2022-03-04 10:50:37	ga_ls8c_ard_3-2-1_105078_2022-03-04_final
2022-03-04 10:52:12	ga_ls8c_ard_3-2-1_105082_2022-03-04_final
2022-03-05 09:53:23	ga_ls8c_ard_3-2-1_096074_2022-03-05_final
2022-03-05 09:55:23	ga_ls8c_ard_3-2-1_096079_2022-03-05_final
2022-03-05 09:56:59	ga_ls8c_ard_3-2-1_096083_2022-03-05_final
2022-03-05 11:33:04	ga_ls8c_ard_3-2-1_112076_2022-03-05_final
2022-03-05 11:35:04	ga_ls8c_ard_3-2-1_112081_2022-03-05_final
2022-03-06 10:34:15	ga_ls8c_ard_3-2-1_103068_2022-03-06_final
2022-03-06 10:35:27	ga_ls8c_ard_3-2-1_103071_2022-03-06_final
2022-03-07 09:40:13	ga_ls8c_ard_3-2-1_094072_2022-03-07_final
2022-03-07 09:41:25	ga_ls8c_ard_3-2-1_094075_2022-03-07_final
2022-03-07 09:42:37	ga_ls8c_ard_3-2-1_094078_2022-03-07_final
2022-03-07 09:44:13	ga_ls8c_ard_3-2-1_094082_2022-03-07_final
2022-03-07 09:45:24	ga_ls8c_ard_3-2-1_094085_2022-03-07_final
2022-03-07 11:17:54	ga_ls8c_ard_3-2-1_110069_2022-03-07_final
2022-03-07 11:21:06	ga_ls8c_ard_3-2-1_110077_2022-03-07_final
2022-03-08 10:22:41	ga_ls8c_ard_3-2-1_101070_2022-03-08_final
2022-03-08 10:25:28	ga_ls8c_ard_3-2-1_101077_2022-03-08_final
2022-03-08 10:26:40	ga_ls8c_ard_3-2-1_101080_2022-03-08_final
2022-03-09 09:29:03	ga_ls8c_ard_3-2-1_092075_2022-03-08_final
2022-03-09 09:29:27	ga_ls8c_ard_3-2-1_092076_2022-03-08_final
2022-03-09 09:33:26	ga_ls8c_ard_3-2-1_092086_2022-03-09_final
2022-03-09 11:05:32	ga_ls8c_ard_3-2-1_108069_2022-03-09_final
2022-03-09 11:05:56	ga_ls8c_ard_3-2-1_108070_2022-03-09_final
2022-03-09 11:09:55	ga_ls8c_ard_3-2-1_108080_2022-03-09_final
2022-03-10 10:13:06	ga_ls8c_ard_3-2-1_099077_2022-03-10_final
2022-03-10 11:51:35	ga_ls8c_ard_3-2-1_115076_2022-03-10_final
2022-03-11 09:17:28	ga_ls8c_ard_3-2-1_090077_2022-03-10_final
2022-03-11 09:18:40	ga_ls8c_ard_3-2-1_090080_2022-03-10_final
2022-03-11 10:53:10	ga_ls8c_ard_3-2-1_106069_2022-03-11_final
2022-03-11 10:53:34	ga_ls8c_ard_3-2-1_106070_2022-03-11_final
2022-03-11 10:57:33	ga_ls8c_ard_3-2-1_106080_2022-03-11_final
2022-03-12 09:57:56	ga_ls8c_ard_3-2-1_097070_2022-03-12_final
2022-03-12 10:00:43	ga_ls8c_ard_3-2-1_097077_2022-03-12_final
2022-03-12 10:01:55	ga_ls8c_ard_3-2-1_097080_2022-03-12_final
2022-03-12 11:37:37	ga_ls8c_ard_3-2-1_113072_2022-03-12_final
2022-03-12 11:38:48	ga_ls8c_ard_3-2-1_113075_2022-03-12_final
2022-03-12 11:40:00	ga_ls8c_ard_3-2-1_113078_2022-03-12_final
2022-03-12 11:41:36	ga_ls8c_ard_3-2-1_113082_2022-03-12_final
2022-03-13 10:40:23	ga_ls8c_ard_3-2-1_104068_2022-03-13_final
2022-03-13 10:41:35	ga_ls8c_ard_3-2-1_104071_2022-03-13_final
2022-03-14 09:47:57	ga_ls8c_ard_3-2-1_095076_2022-03-14_final
2022-03-14 11:25:38	ga_ls8c_ard_3-2-1_111073_2022-03-14_final
2022-03-14 11:26:02	ga_ls8c_ard_3-2-1_111074_2022-03-14_final
2022-03-14 11:28:02	ga_ls8c_ard_3-2-1_111079_2022-03-14_final
2022-03-14 11:29:37	ga_ls8c_ard_3-2-1_111083_2022-03-14_final
2022-03-15 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-03-15_final
2022-03-15 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-03-15_final
2022-03-15 10:32:00	ga_ls8c_ard_3-2-1_102078_2022-03-15_final
2022-03-16 09:35:10	ga_ls8c_ard_3-2-1_093075_2022-03-16_final
2022-03-16 09:36:22	ga_ls8c_ard_3-2-1_093078_2022-03-16_final
2022-03-16 09:37:58	ga_ls8c_ard_3-2-1_093082_2022-03-16_final
2022-03-16 09:40:21	ga_ls8c_ard_3-2-1_093088_2022-03-16_final
2022-03-16 11:13:15	ga_ls8c_ard_3-2-1_109073_2022-03-16_final
2022-03-16 11:13:39	ga_ls8c_ard_3-2-1_109074_2022-03-16_final
2022-03-16 11:15:39	ga_ls8c_ard_3-2-1_109079_2022-03-16_final
2022-03-16 11:17:38	ga_ls8c_ard_3-2-1_109084_2022-03-16_final
2022-03-17 10:17:37	ga_ls8c_ard_3-2-1_100073_2022-03-17_final
2022-03-17 10:20:01	ga_ls8c_ard_3-2-1_100079_2022-03-17_final
2022-03-17 10:22:00	ga_ls8c_ard_3-2-1_100084_2022-03-17_final
2022-03-18 09:21:59	ga_ls8c_ard_3-2-1_091073_2022-03-17_final
2022-03-18 09:22:23	ga_ls8c_ard_3-2-1_091074_2022-03-17_final
2022-03-18 09:24:23	ga_ls8c_ard_3-2-1_091079_2022-03-17_final
2022-03-18 09:25:58	ga_ls8c_ard_3-2-1_091083_2022-03-17_final
2022-03-18 09:28:22	ga_ls8c_ard_3-2-1_091089_2022-03-17_final
2022-03-18 09:28:46	ga_ls8c_ard_3-2-1_091090_2022-03-17_final
2022-03-18 11:00:52	ga_ls8c_ard_3-2-1_107073_2022-03-18_final
2022-03-18 11:04:51	ga_ls8c_ard_3-2-1_107083_2022-03-18_final
2022-03-18 11:05:15	ga_ls8c_ard_3-2-1_107084_2022-03-18_final
2022-03-19 10:02:50	ga_ls8c_ard_3-2-1_098067_2022-03-19_final
2022-03-19 10:03:14	ga_ls8c_ard_3-2-1_098068_2022-03-19_final
2022-03-19 10:03:38	ga_ls8c_ard_3-2-1_098069_2022-03-19_final
2022-03-19 10:04:02	ga_ls8c_ard_3-2-1_098070_2022-03-19_final
2022-03-19 10:04:26	ga_ls8c_ard_3-2-1_098071_2022-03-19_final
2022-03-19 10:04:50	ga_ls8c_ard_3-2-1_098072_2022-03-19_final
2022-03-19 10:05:14	ga_ls8c_ard_3-2-1_098073_2022-03-19_final
2022-03-19 10:05:38	ga_ls8c_ard_3-2-1_098074_2022-03-19_final
2022-03-19 10:06:02	ga_ls8c_ard_3-2-1_098075_2022-03-19_final
2022-03-19 10:06:26	ga_ls8c_ard_3-2-1_098076_2022-03-19_final
2022-03-19 10:06:50	ga_ls8c_ard_3-2-1_098077_2022-03-19_final
2022-03-19 10:07:14	ga_ls8c_ard_3-2-1_098078_2022-03-19_final
2022-03-19 10:07:38	ga_ls8c_ard_3-2-1_098079_2022-03-19_final
2022-03-19 10:08:02	ga_ls8c_ard_3-2-1_098080_2022-03-19_final
2022-03-19 10:08:26	ga_ls8c_ard_3-2-1_098081_2022-03-19_final
2022-03-19 10:08:49	ga_ls8c_ard_3-2-1_098082_2022-03-19_final
2022-03-19 10:09:13	ga_ls8c_ard_3-2-1_098083_2022-03-19_final
2022-03-19 10:09:37	ga_ls8c_ard_3-2-1_098084_2022-03-19_final
2022-03-19 10:10:01	ga_ls8c_ard_3-2-1_098085_2022-03-19_final
2022-03-19 11:44:31	ga_ls8c_ard_3-2-1_114074_2022-03-19_final
2022-03-19 11:44:55	ga_ls8c_ard_3-2-1_114075_2022-03-19_final
2022-03-19 11:45:19	ga_ls8c_ard_3-2-1_114076_2022-03-19_final
2022-03-19 11:45:43	ga_ls8c_ard_3-2-1_114077_2022-03-19_final
2022-03-19 11:46:07	ga_ls8c_ard_3-2-1_114078_2022-03-19_final
2022-03-19 11:46:31	ga_ls8c_ard_3-2-1_114079_2022-03-19_final
2022-03-19 11:46:55	ga_ls8c_ard_3-2-1_114080_2022-03-19_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years