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
2015-02-12 10:02:47	ga_ls8c_ard_3-0-0_098067_2015-02-12_final
2015-02-12 11:41:40	ga_ls8c_ard_3-0-0_114067_2015-02-12_final
2015-02-14 11:29:16	ga_ls8c_ard_3-0-0_112067_2015-02-14_final
2015-02-16 09:38:02	ga_ls8c_ard_3-0-0_094067_2015-02-16_final
2015-02-25 11:10:44	ga_ls8c_ard_3-0-0_109067_2015-02-25_final
2015-02-26 10:15:06	ga_ls8c_ard_3-0-0_100067_2015-02-26_final
2015-02-27 10:58:21	ga_ls8c_ard_3-0-0_107067_2015-02-27_final
2015-05-19 10:01:59	ga_ls8c_ard_3-0-0_098067_2015-05-19_final
2015-05-19 11:40:52	ga_ls8c_ard_3-0-0_114067_2015-05-19_final
2015-05-20 10:45:15	ga_ls8c_ard_3-0-0_105067_2015-05-20_final
2015-05-21 09:49:38	ga_ls8c_ard_3-0-0_096067_2015-05-21_final
2015-05-21 11:28:31	ga_ls8c_ard_3-0-0_112067_2015-05-21_final
2015-06-04 10:02:07	ga_ls8c_ard_3-0-0_098067_2015-06-04_final
2015-06-04 11:41:00	ga_ls8c_ard_3-0-0_114067_2015-06-04_final
2015-06-05 10:45:23	ga_ls8c_ard_3-0-0_105067_2015-06-05_final
2015-06-06 09:49:47	ga_ls8c_ard_3-0-0_096067_2015-06-06_final
2015-06-06 11:28:40	ga_ls8c_ard_3-0-0_112067_2015-06-06_final
2018-02-13 09:56:35	ga_ls8c_ard_3-0-0_097067_2018-02-13_final
2018-02-13 11:35:28	ga_ls8c_ard_3-0-0_113067_2018-02-13_final
2018-02-14 10:39:51	ga_ls8c_ard_3-0-0_104067_2018-02-14_final
2018-02-15 09:44:13	ga_ls8c_ard_3-0-0_095067_2018-02-15_final
2018-02-15 11:23:06	ga_ls8c_ard_3-0-0_111067_2018-02-15_final
2018-02-16 10:27:28	ga_ls8c_ard_3-0-0_102067_2018-02-16_final
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-17 11:10:44	ga_ls8c_ard_3-0-0_109067_2018-02-17_final
2018-02-18 10:15:06	ga_ls8c_ard_3-0-0_100067_2018-02-18_final
2018-04-16 10:08:26	ga_ls8c_ard_3-0-0_099067_2018-04-16_final
2018-04-17 10:51:41	ga_ls8c_ard_3-0-0_106067_2018-04-17_final
2018-04-18 09:56:03	ga_ls8c_ard_3-0-0_097067_2018-04-18_final
2018-04-18 11:34:56	ga_ls8c_ard_3-0-0_113067_2018-04-18_final
2018-06-03 10:07:55	ga_ls8c_ard_3-0-0_099067_2018-06-03_final
2018-06-04 10:51:10	ga_ls8c_ard_3-0-0_106067_2018-06-04_final
2018-06-05 09:55:33	ga_ls8c_ard_3-0-0_097067_2018-06-05_final
2018-06-05 11:34:26	ga_ls8c_ard_3-0-0_113067_2018-06-05_final
2018-07-23 09:55:59	ga_ls8c_ard_3-0-0_097067_2018-07-23_final
2018-07-23 11:34:52	ga_ls8c_ard_3-0-0_113067_2018-07-23_final
2018-07-24 10:39:15	ga_ls8c_ard_3-0-0_104067_2018-07-24_final
2018-07-25 09:43:38	ga_ls8c_ard_3-0-0_095067_2018-07-25_final
2018-07-25 11:22:31	ga_ls8c_ard_3-0-0_111067_2018-07-25_final
2018-07-26 10:26:54	ga_ls8c_ard_3-0-0_102067_2018-07-26_final
2018-07-27 09:31:17	ga_ls8c_ard_3-0-0_093067_2018-07-27_final
2018-07-27 11:10:10	ga_ls8c_ard_3-0-0_109067_2018-07-27_final
2018-07-28 10:14:34	ga_ls8c_ard_3-0-0_100067_2018-07-28_final
2018-07-29 10:57:50	ga_ls8c_ard_3-0-0_107067_2018-07-29_final
2018-07-30 10:02:13	ga_ls8c_ard_3-0-0_098067_2018-07-30_final
2018-07-30 11:41:07	ga_ls8c_ard_3-0-0_114067_2018-07-30_final
2018-07-31 10:45:30	ga_ls8c_ard_3-0-0_105067_2018-07-31_final
2018-08-01 09:49:53	ga_ls8c_ard_3-0-0_096067_2018-08-01_final
2018-08-01 11:28:46	ga_ls8c_ard_3-0-0_112067_2018-08-01_final
2018-08-15 10:02:23	ga_ls8c_ard_3-0-0_098067_2018-08-15_final
2018-08-15 11:41:16	ga_ls8c_ard_3-0-0_114067_2018-08-15_final
2018-08-16 10:45:39	ga_ls8c_ard_3-0-0_105067_2018-08-16_final
2018-08-17 09:50:02	ga_ls8c_ard_3-0-0_096067_2018-08-17_final
2018-08-17 11:28:55	ga_ls8c_ard_3-0-0_112067_2018-08-17_final
2018-08-18 10:33:18	ga_ls8c_ard_3-0-0_103067_2018-08-18_final
2018-08-19 09:37:41	ga_ls8c_ard_3-0-0_094067_2018-08-19_final
2018-09-09 09:56:22	ga_ls8c_ard_3-0-0_097067_2018-09-09_final
2018-09-09 11:35:15	ga_ls8c_ard_3-0-0_113067_2018-09-09_final
2018-09-10 10:39:38	ga_ls8c_ard_3-0-0_104067_2018-09-10_final
2018-09-11 09:44:01	ga_ls8c_ard_3-0-0_095067_2018-09-11_final
2018-09-11 11:22:54	ga_ls8c_ard_3-0-0_111067_2018-09-11_final
2018-09-12 10:27:17	ga_ls8c_ard_3-0-0_102067_2018-09-12_final
2018-09-13 09:31:40	ga_ls8c_ard_3-0-0_093067_2018-09-13_final
2018-09-17 10:45:50	ga_ls8c_ard_3-0-0_105067_2018-09-17_final
2018-09-18 09:50:13	ga_ls8c_ard_3-0-0_096067_2018-09-18_final
2018-09-18 11:29:06	ga_ls8c_ard_3-0-0_112067_2018-09-18_final
2018-09-23 10:08:24	ga_ls8c_ard_3-2-1_099066_2018-09-23_final
2018-09-23 10:08:48	ga_ls8c_ard_3-0-0_099067_2018-09-23_final
2018-09-24 10:52:04	ga_ls8c_ard_3-0-0_106067_2018-09-24_final
2018-09-24 12:30:57	ga_ls8c_ard_3-2-1_122067_2018-09-24_final
2018-09-25 09:56:27	ga_ls8c_ard_3-0-0_097067_2018-09-25_final
2018-09-25 11:35:20	ga_ls8c_ard_3-0-0_113067_2018-09-25_final
2018-11-30 11:23:13	ga_ls8c_ard_3-0-0_111067_2018-11-30_final
2018-12-01 10:27:35	ga_ls8c_ard_3-0-0_102067_2018-12-01_final
2018-12-02 09:31:58	ga_ls8c_ard_3-0-0_093067_2018-12-02_final
2018-12-17 10:27:32	ga_ls8c_ard_3-0-0_102067_2018-12-17_final
2018-12-18 09:31:55	ga_ls8c_ard_3-0-0_093067_2018-12-18_final
2018-12-18 11:10:48	ga_ls8c_ard_3-0-0_109067_2018-12-18_final
2018-12-19 10:15:11	ga_ls8c_ard_3-0-0_100067_2018-12-19_final
2018-12-20 10:58:27	ga_ls8c_ard_3-0-0_107067_2018-12-20_final
2018-12-20 12:37:20	ga_ls8c_ard_3-2-1_123067_2018-12-20_final
2018-12-28 10:09:00	ga_ls8c_ard_3-0-0_099067_2018-12-28_final
2018-12-29 10:52:16	ga_ls8c_ard_3-0-0_106067_2018-12-29_final
2018-12-29 12:31:09	ga_ls8c_ard_3-2-1_122067_2018-12-29_final
2018-12-30 09:56:39	ga_ls8c_ard_3-0-0_097067_2018-12-30_final
2018-12-30 11:35:32	ga_ls8c_ard_3-0-0_113067_2018-12-30_final
2018-12-31 10:39:54	ga_ls8c_ard_3-0-0_104067_2018-12-31_final
2019-01-01 09:44:17	ga_ls8c_ard_3-0-0_095067_2019-01-01_final
2019-01-01 11:23:10	ga_ls8c_ard_3-0-0_111067_2019-01-01_final
2019-01-02 10:27:32	ga_ls8c_ard_3-0-0_102067_2019-01-02_final
2019-01-03 09:31:55	ga_ls8c_ard_3-0-0_093067_2019-01-03_final
2019-01-13 10:08:58	ga_ls8c_ard_3-0-0_099067_2019-01-13_final
2019-01-14 10:52:14	ga_ls8c_ard_3-0-0_106067_2019-01-14_final
2019-01-15 09:56:36	ga_ls8c_ard_3-0-0_097067_2019-01-15_final
2019-01-15 11:35:29	ga_ls8c_ard_3-0-0_113067_2019-01-15_final
2019-01-26 11:16:54	ga_ls8c_ard_3-0-0_110067_2019-01-26_final
2019-01-27 10:21:17	ga_ls8c_ard_3-0-0_101067_2019-01-27_final
2019-01-28 09:25:39	ga_ls8c_ard_3-0-0_092067_2019-01-27_final
2019-01-28 11:04:32	ga_ls8c_ard_3-0-0_108067_2019-01-28_final
2019-01-29 10:08:54	ga_ls8c_ard_3-0-0_099067_2019-01-29_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