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
2023-02-01 11:03:45	ga_ls8c_ard_3-2-1_107079_2023-02-01_final
2023-02-02 10:08:55	ga_ls8c_ard_3-2-1_098081_2023-02-02_final
2023-03-15 09:59:55	ga_ls8c_ard_3-2-1_097075_2023-03-15_final
2023-03-19 09:35:57	ga_ls8c_ard_3-2-1_093077_2023-03-19_final
2023-03-19 09:37:09	ga_ls8c_ard_3-2-1_093080_2023-03-19_final
2023-03-21 11:03:14	ga_ls8c_ard_3-2-1_107079_2023-03-21_final
2023-07-04 10:56:01	ga_ls8c_ard_3-2-1_106077_2023-07-04_final
2023-07-07 09:46:52	ga_ls8c_ard_3-2-1_095074_2023-07-07_final
2023-07-09 11:15:00	ga_ls8c_ard_3-2-1_109078_2023-07-09_final
2023-07-12 10:05:03	ga_ls8c_ard_3-2-1_098073_2023-07-12_final
2023-07-12 10:05:26	ga_ls8c_ard_3-2-1_098074_2023-07-12_final
2023-07-13 10:47:07	ga_ls8c_ard_3-2-1_105070_2023-07-13_final
2023-07-13 10:47:31	ga_ls8c_ard_3-2-1_105071_2023-07-13_final
2023-07-14 09:54:41	ga_ls8c_ard_3-2-1_096078_2023-07-14_final
2023-07-15 10:36:45	ga_ls8c_ard_3-2-1_103075_2023-07-15_final
2023-07-16 11:22:24	ga_ls8c_ard_3-2-1_110081_2023-07-16_final
2023-07-19 10:16:01	ga_ls8c_ard_3-2-1_099085_2023-07-19_final
2023-07-21 09:59:40	ga_ls8c_ard_3-2-1_097075_2023-07-21_final
2023-07-21 11:40:08	ga_ls8c_ard_3-2-1_113079_2023-07-21_final
2023-07-22 10:43:44	ga_ls8c_ard_3-2-1_104077_2023-07-22_final
2023-07-23 09:46:56	ga_ls8c_ard_3-2-1_095074_2023-07-23_final
2023-07-23 11:27:01	ga_ls8c_ard_3-2-1_111077_2023-07-23_final
2023-07-24 10:29:25	ga_ls8c_ard_3-2-1_102072_2023-07-24_final
2023-07-25 09:35:48	ga_ls8c_ard_3-2-1_093077_2023-07-25_final
2023-07-25 11:15:05	ga_ls8c_ard_3-2-1_109078_2023-07-25_final
2023-07-26 11:57:58	ga_ls8c_ard_3-2-1_116077_2023-07-26_final
2023-07-27 09:23:52	ga_ls8c_ard_3-2-1_091078_2023-07-26_final
2023-07-27 11:03:09	ga_ls8c_ard_3-2-1_107079_2023-07-27_final
2023-07-28 10:05:09	ga_ls8c_ard_3-2-1_098073_2023-07-28_final
2023-07-28 10:05:33	ga_ls8c_ard_3-2-1_098074_2023-07-28_final
2023-07-28 11:46:02	ga_ls8c_ard_3-2-1_114078_2023-07-28_final
2023-07-29 10:47:37	ga_ls8c_ard_3-2-1_105071_2023-07-29_final
2023-07-29 10:50:25	ga_ls8c_ard_3-2-1_105078_2023-07-29_final
2023-07-30 09:52:24	ga_ls8c_ard_3-2-1_096072_2023-07-30_final
2023-07-30 09:54:48	ga_ls8c_ard_3-2-1_096078_2023-07-30_final
2023-07-30 09:56:24	ga_ls8c_ard_3-2-1_096082_2023-07-30_final
2023-07-31 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-07-31_final
2023-07-31 10:38:28	ga_ls8c_ard_3-2-1_103079_2023-07-31_final
2023-08-01 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-08-01_final
2023-08-01 09:43:39	ga_ls8c_ard_3-2-1_094081_2023-08-01_final
2023-08-01 09:44:27	ga_ls8c_ard_3-2-1_094083_2023-08-01_final
2023-08-01 11:20:57	ga_ls8c_ard_3-2-1_110077_2023-08-01_final
2023-08-03 09:29:43	ga_ls8c_ard_3-2-1_092077_2023-08-02_final
2023-08-03 09:32:06	ga_ls8c_ard_3-2-1_092083_2023-08-03_final
2023-08-03 11:06:36	ga_ls8c_ard_3-2-1_108072_2023-08-03_final
2023-08-04 10:12:11	ga_ls8c_ard_3-2-1_099075_2023-08-04_final
2023-08-04 11:50:40	ga_ls8c_ard_3-2-1_115074_2023-08-04_final
2023-08-07 10:43:53	ga_ls8c_ard_3-2-1_104077_2023-08-07_final
2023-08-07 10:44:41	ga_ls8c_ard_3-2-1_104079_2023-08-07_final
2023-08-09 10:31:07	ga_ls8c_ard_3-2-1_102076_2023-08-09_final
2023-08-10 09:36:17	ga_ls8c_ard_3-2-1_093078_2023-08-10_final
2023-08-12 09:23:57	ga_ls8c_ard_3-2-1_091078_2023-08-11_final
2023-08-12 09:24:21	ga_ls8c_ard_3-2-1_091079_2023-08-11_final
2023-08-12 09:25:32	ga_ls8c_ard_3-2-1_091082_2023-08-11_final
2023-08-13 10:05:14	ga_ls8c_ard_3-2-1_098073_2023-08-13_final
2023-08-14 10:47:18	ga_ls8c_ard_3-2-1_105070_2023-08-14_final
2023-08-14 10:47:42	ga_ls8c_ard_3-2-1_105071_2023-08-14_final
2023-08-15 09:52:30	ga_ls8c_ard_3-2-1_096072_2023-08-15_final
2023-08-15 09:52:54	ga_ls8c_ard_3-2-1_096073_2023-08-15_final
2023-08-15 09:53:18	ga_ls8c_ard_3-2-1_096074_2023-08-15_final
2023-08-15 09:56:29	ga_ls8c_ard_3-2-1_096082_2023-08-15_final
2023-08-16 10:36:58	ga_ls8c_ard_3-2-1_103075_2023-08-16_final
2023-08-17 11:22:14	ga_ls8c_ard_3-2-1_110080_2023-08-17_final
2023-08-18 10:26:14	ga_ls8c_ard_3-2-1_101079_2023-08-18_final
2023-08-19 09:29:49	ga_ls8c_ard_3-2-1_092077_2023-08-18_final
2023-08-19 09:30:13	ga_ls8c_ard_3-2-1_092078_2023-08-19_final
2023-08-20 10:11:53	ga_ls8c_ard_3-2-1_099074_2023-08-20_final
2023-08-21 09:18:40	ga_ls8c_ard_3-2-1_090080_2023-08-20_final
2023-08-21 09:19:52	ga_ls8c_ard_3-2-1_090083_2023-08-20_final
2023-08-23 10:44:01	ga_ls8c_ard_3-2-1_104077_2023-08-23_final
2023-08-23 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-08-23_final
2023-08-24 09:48:00	ga_ls8c_ard_3-2-1_095076_2023-08-24_final
2023-08-24 11:27:17	ga_ls8c_ard_3-2-1_111077_2023-08-24_final
2023-08-24 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-08-24_final
2023-08-26 09:36:26	ga_ls8c_ard_3-2-1_093078_2023-08-26_final
2023-08-26 11:12:32	ga_ls8c_ard_3-2-1_109071_2023-08-26_final
2023-08-26 11:15:19	ga_ls8c_ard_3-2-1_109078_2023-08-26_final
2023-08-28 09:24:29	ga_ls8c_ard_3-2-1_091079_2023-08-27_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-29 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-08-29_final
2023-08-29 11:47:25	ga_ls8c_ard_3-2-1_114081_2023-08-29_final
2023-08-30 10:47:24	ga_ls8c_ard_3-2-1_105070_2023-08-30_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-30 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-08-30_final
2023-09-02 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-09-02_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-06 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-09-05_final
2023-09-06 09:18:39	ga_ls8c_ard_3-2-1_090080_2023-09-05_final
2023-09-06 10:57:56	ga_ls8c_ard_3-2-1_106081_2023-09-06_final
2023-09-07 11:38:49	ga_ls8c_ard_3-2-1_113075_2023-09-07_final
2023-09-07 11:40:24	ga_ls8c_ard_3-2-1_113079_2023-09-07_final
2023-09-08 10:42:00	ga_ls8c_ard_3-2-1_104072_2023-09-08_final
2023-09-08 10:44:00	ga_ls8c_ard_3-2-1_104077_2023-09-08_final
2023-09-08 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-09-08_final
2023-09-09 11:27:40	ga_ls8c_ard_3-2-1_111078_2023-09-09_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 09:36:27	ga_ls8c_ard_3-2-1_093078_2023-09-11_final
2023-09-11 11:15:20	ga_ls8c_ard_3-2-1_109078_2023-09-11_final
2023-09-13 09:24:31	ga_ls8c_ard_3-2-1_091079_2023-09-12_final
2023-09-13 09:25:43	ga_ls8c_ard_3-2-1_091082_2023-09-12_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