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 09:13:43	ga_ls8c_ard_3-2-1_089083_2022-03-03_final
2022-03-04 09:14:07	ga_ls8c_ard_3-2-1_089084_2022-03-03_final
2022-03-04 09:16:07	ga_ls8c_ard_3-2-1_089089_2022-03-03_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_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 09:52:59	ga_ls8c_ard_3-2-1_096073_2022-03-05_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 09:55:47	ga_ls8c_ard_3-2-1_096080_2022-03-05_final
2022-03-05 09:56:59	ga_ls8c_ard_3-2-1_096083_2022-03-05_final
2022-03-05 09:57:23	ga_ls8c_ard_3-2-1_096084_2022-03-05_final
2022-03-05 11:32:40	ga_ls8c_ard_3-2-1_112075_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
2022-03-06 10:35:51	ga_ls8c_ard_3-2-1_103072_2022-03-06_final
2022-03-06 10:37:27	ga_ls8c_ard_3-2-1_103076_2022-03-06_final
2022-03-06 10:38:14	ga_ls8c_ard_3-2-1_103078_2022-03-06_final
2022-03-06 10:39:26	ga_ls8c_ard_3-2-1_103081_2022-03-06_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 11:22:18	ga_ls8c_ard_3-2-1_110080_2022-03-07_final
2022-03-08 10:25:28	ga_ls8c_ard_3-2-1_101077_2022-03-08_final
2022-03-08 10:26:16	ga_ls8c_ard_3-2-1_101079_2022-03-08_final
2022-03-09 09:27:27	ga_ls8c_ard_3-2-1_092071_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 09:31:26	ga_ls8c_ard_3-2-1_092081_2022-03-09_final
2022-03-09 09:33:26	ga_ls8c_ard_3-2-1_092086_2022-03-09_final
2022-03-09 11:05:56	ga_ls8c_ard_3-2-1_108070_2022-03-09_final
2022-03-09 11:07:08	ga_ls8c_ard_3-2-1_108073_2022-03-09_final
2022-03-09 11:08:44	ga_ls8c_ard_3-2-1_108077_2022-03-09_final
2022-03-09 11:09:55	ga_ls8c_ard_3-2-1_108080_2022-03-09_final
2022-03-09 11:11:31	ga_ls8c_ard_3-2-1_108084_2022-03-09_final
2022-03-10 10:10:18	ga_ls8c_ard_3-2-1_099070_2022-03-10_final
2022-03-10 10:14:18	ga_ls8c_ard_3-2-1_099080_2022-03-10_final
2022-03-10 11:51:35	ga_ls8c_ard_3-2-1_115076_2022-03-10_final
2022-03-11 09:16:16	ga_ls8c_ard_3-2-1_090074_2022-03-10_final
2022-03-11 09:18:40	ga_ls8c_ard_3-2-1_090080_2022-03-10_final
2022-03-11 09:21:28	ga_ls8c_ard_3-2-1_090087_2022-03-10_final
2022-03-11 09:22:16	ga_ls8c_ard_3-2-1_090089_2022-03-10_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 09:57:32	ga_ls8c_ard_3-2-1_097069_2022-03-12_final
2022-03-12 10:00:43	ga_ls8c_ard_3-2-1_097077_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
2022-03-13 09:06:17	ga_ls8c_ard_3-2-1_088080_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
2022-03-13 10:41:59	ga_ls8c_ard_3-2-1_104072_2022-03-13_final
2022-03-13 10:43:35	ga_ls8c_ard_3-2-1_104076_2022-03-13_final
2022-03-13 10:44:22	ga_ls8c_ard_3-2-1_104078_2022-03-13_final
2022-03-13 10:45:34	ga_ls8c_ard_3-2-1_104081_2022-03-13_final
2022-03-14 09:45:57	ga_ls8c_ard_3-2-1_095071_2022-03-14_final
2022-03-14 09:47:57	ga_ls8c_ard_3-2-1_095076_2022-03-14_final
2022-03-14 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-03-14_final
2022-03-14 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-03-14_final
2022-03-14 11:25:38	ga_ls8c_ard_3-2-1_111073_2022-03-14_final
2022-03-14 11:28:02	ga_ls8c_ard_3-2-1_111079_2022-03-14_final
2022-03-14 11:28:25	ga_ls8c_ard_3-2-1_111080_2022-03-14_final
2022-03-14 11:30:01	ga_ls8c_ard_3-2-1_111084_2022-03-14_final
2022-03-15 10:28:00	ga_ls8c_ard_3-2-1_102068_2022-03-15_final
2022-03-15 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-03-15_final
2022-03-16 09:33:58	ga_ls8c_ard_3-2-1_093072_2022-03-16_final
2022-03-16 09:35:10	ga_ls8c_ard_3-2-1_093075_2022-03-16_final
2022-03-16 09:35:34	ga_ls8c_ard_3-2-1_093076_2022-03-16_final
2022-03-16 09:37:58	ga_ls8c_ard_3-2-1_093082_2022-03-16_final
2022-03-16 09:39:09	ga_ls8c_ard_3-2-1_093085_2022-03-16_final
2022-03-16 11:11:39	ga_ls8c_ard_3-2-1_109069_2022-03-16_final
2022-03-16 11:15:39	ga_ls8c_ard_3-2-1_109079_2022-03-16_final
2022-03-17 10:18:01	ga_ls8c_ard_3-2-1_100074_2022-03-17_final
2022-03-17 10:20:01	ga_ls8c_ard_3-2-1_100079_2022-03-17_final
2022-03-17 10:21:36	ga_ls8c_ard_3-2-1_100083_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 09:26:22	ga_ls8c_ard_3-2-1_091084_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 11:01:16	ga_ls8c_ard_3-2-1_107074_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 10:04:02	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 10:09:13	ga_ls8c_ard_3-2-1_098083_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years