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

86 results

Time (local)	Label
2020-10-13 11:05:05	ga_ls8c_ard_3-1-0_108067_2020-10-13_final
2020-10-13 11:05:53	ga_ls8c_ard_3-1-0_108069_2020-10-13_final
2020-10-13 11:06:41	ga_ls8c_ard_3-1-0_108071_2020-10-13_final
2020-10-13 11:07:05	ga_ls8c_ard_3-1-0_108072_2020-10-13_final
2020-10-13 11:08:17	ga_ls8c_ard_3-1-0_108075_2020-10-13_final
2020-10-13 11:09:52	ga_ls8c_ard_3-1-0_108079_2020-10-13_final
2020-10-13 11:11:04	ga_ls8c_ard_3-1-0_108082_2020-10-13_final
2020-10-14 10:09:52	ga_ls8c_ard_3-1-0_099068_2020-10-14_final
2020-10-14 10:10:16	ga_ls8c_ard_3-1-0_099069_2020-10-14_final
2020-10-14 10:11:04	ga_ls8c_ard_3-1-0_099071_2020-10-14_final
2020-10-14 10:13:03	ga_ls8c_ard_3-1-0_099076_2020-10-14_final
2020-10-14 10:13:27	ga_ls8c_ard_3-1-0_099077_2020-10-14_final
2020-10-14 10:14:15	ga_ls8c_ard_3-1-0_099079_2020-10-14_final
2020-10-14 10:14:39	ga_ls8c_ard_3-1-0_099080_2020-10-14_final
2020-10-14 10:15:03	ga_ls8c_ard_3-1-0_099081_2020-10-14_final
2020-10-14 10:15:51	ga_ls8c_ard_3-1-0_099083_2020-10-14_final
2020-10-15 10:53:55	ga_ls8c_ard_3-1-0_106070_2020-10-15_final
2020-10-15 10:54:19	ga_ls8c_ard_3-1-0_106071_2020-10-15_final
2020-10-15 10:55:07	ga_ls8c_ard_3-1-0_106073_2020-10-15_final
2020-10-15 10:56:19	ga_ls8c_ard_3-1-0_106076_2020-10-15_final
2020-10-15 10:56:43	ga_ls8c_ard_3-1-0_106077_2020-10-15_final
2020-10-15 10:57:31	ga_ls8c_ard_3-1-0_106079_2020-10-15_final
2020-10-15 10:57:55	ga_ls8c_ard_3-1-0_106080_2020-10-15_final
2020-10-16 10:01:54	ga_ls8c_ard_3-1-0_097079_2020-10-16_final
2020-10-16 10:02:17	ga_ls8c_ard_3-1-0_097080_2020-10-16_final
2020-10-16 10:02:41	ga_ls8c_ard_3-1-0_097081_2020-10-16_final
2020-10-16 10:04:41	ga_ls8c_ard_3-1-0_097086_2020-10-16_final
2020-10-16 11:38:47	ga_ls8c_ard_3-1-0_113074_2020-10-16_final
2020-10-16 11:39:35	ga_ls8c_ard_3-1-0_113076_2020-10-16_final
2020-10-16 11:40:47	ga_ls8c_ard_3-1-0_113079_2020-10-16_final
2020-10-16 11:41:11	ga_ls8c_ard_3-1-0_113080_2020-10-16_final
2020-10-17 10:40:22	ga_ls8c_ard_3-1-0_104067_2020-10-17_final
2020-10-17 10:41:34	ga_ls8c_ard_3-1-0_104070_2020-10-17_final
2020-10-17 10:41:58	ga_ls8c_ard_3-1-0_104071_2020-10-17_final
2020-10-17 10:43:10	ga_ls8c_ard_3-1-0_104074_2020-10-17_final
2020-10-17 10:43:33	ga_ls8c_ard_3-1-0_104075_2020-10-17_final
2020-10-17 10:43:57	ga_ls8c_ard_3-1-0_104076_2020-10-17_final
2020-10-17 10:44:45	ga_ls8c_ard_3-1-0_104078_2020-10-17_final
2020-10-17 10:45:09	ga_ls8c_ard_3-1-0_104079_2020-10-17_final
2020-10-17 10:45:33	ga_ls8c_ard_3-1-0_104080_2020-10-17_final
2020-10-17 10:46:21	ga_ls8c_ard_3-1-0_104082_2020-10-17_final
2020-10-18 11:23:38	ga_ls8c_ard_3-1-0_111067_2020-10-18_final
2020-10-18 11:24:02	ga_ls8c_ard_3-1-0_111068_2020-10-18_final
2020-10-18 11:24:26	ga_ls8c_ard_3-1-0_111069_2020-10-18_final
2020-10-18 11:25:37	ga_ls8c_ard_3-1-0_111072_2020-10-18_final
2020-10-18 11:26:49	ga_ls8c_ard_3-1-0_111075_2020-10-18_final
2020-10-18 11:27:13	ga_ls8c_ard_3-1-0_111076_2020-10-18_final
2020-10-18 11:28:25	ga_ls8c_ard_3-1-0_111079_2020-10-18_final
2020-10-18 11:28:49	ga_ls8c_ard_3-1-0_111080_2020-10-18_final
2020-10-18 11:30:01	ga_ls8c_ard_3-1-0_111083_2020-10-18_final
2020-10-18 11:30:49	ga_ls8c_ard_3-1-0_111085_2020-10-18_final
2020-10-19 10:28:00	ga_ls8c_ard_3-1-0_102067_2020-10-19_final
2020-10-19 10:28:48	ga_ls8c_ard_3-1-0_102069_2020-10-19_final
2020-10-19 10:29:12	ga_ls8c_ard_3-1-0_102070_2020-10-19_final
2020-10-19 10:30:00	ga_ls8c_ard_3-1-0_102072_2020-10-19_final
2020-10-19 10:30:48	ga_ls8c_ard_3-1-0_102074_2020-10-19_final
2020-10-19 10:31:12	ga_ls8c_ard_3-1-0_102075_2020-10-19_final
2020-10-19 10:32:00	ga_ls8c_ard_3-1-0_102077_2020-10-19_final
2020-10-19 10:33:36	ga_ls8c_ard_3-1-0_102081_2020-10-19_final
2020-10-19 10:33:59	ga_ls8c_ard_3-1-0_102082_2020-10-19_final
2020-10-19 10:34:23	ga_ls8c_ard_3-1-0_102083_2020-10-19_final
2020-10-20 11:12:04	ga_ls8c_ard_3-1-0_109069_2020-10-20_final
2020-10-20 11:13:40	ga_ls8c_ard_3-1-0_109073_2020-10-20_final
2020-10-20 11:16:03	ga_ls8c_ard_3-1-0_109079_2020-10-20_final
2020-10-20 11:16:27	ga_ls8c_ard_3-1-0_109080_2020-10-20_final
2020-10-20 11:17:39	ga_ls8c_ard_3-1-0_109083_2020-10-20_final
2020-10-20 11:18:03	ga_ls8c_ard_3-1-0_109084_2020-10-20_final
2020-10-20 11:18:27	ga_ls8c_ard_3-1-0_109085_2020-10-20_final
2020-10-21 10:15:39	ga_ls8c_ard_3-1-0_100067_2020-10-21_final
2020-10-21 10:16:27	ga_ls8c_ard_3-1-0_100069_2020-10-21_final
2020-10-21 10:18:50	ga_ls8c_ard_3-1-0_100075_2020-10-21_final
2020-10-21 10:19:14	ga_ls8c_ard_3-1-0_100076_2020-10-21_final
2020-10-21 10:19:38	ga_ls8c_ard_3-1-0_100077_2020-10-21_final
2020-10-21 10:20:02	ga_ls8c_ard_3-1-0_100078_2020-10-21_final
2020-10-21 10:20:26	ga_ls8c_ard_3-1-0_100079_2020-10-21_final
2020-10-21 10:20:50	ga_ls8c_ard_3-1-0_100080_2020-10-21_final
2020-10-21 10:21:14	ga_ls8c_ard_3-1-0_100081_2020-10-21_final
2020-10-21 10:21:38	ga_ls8c_ard_3-1-0_100082_2020-10-21_final
2020-10-21 10:22:02	ga_ls8c_ard_3-1-0_100083_2020-10-21_final
2020-10-21 10:22:26	ga_ls8c_ard_3-1-0_100084_2020-10-21_final
2020-10-21 10:22:50	ga_ls8c_ard_3-1-0_100085_2020-10-21_final
2020-10-22 10:58:54	ga_ls8c_ard_3-1-0_107067_2020-10-22_final
2020-10-22 10:59:18	ga_ls8c_ard_3-1-0_107068_2020-10-22_final
2020-10-22 11:04:06	ga_ls8c_ard_3-1-0_107080_2020-10-22_final
2020-10-22 11:04:53	ga_ls8c_ard_3-1-0_107082_2020-10-22_final
2020-10-22 11:05:41	ga_ls8c_ard_3-1-0_107084_2020-10-22_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