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
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-29 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-09-29_final
2022-09-30 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-09-30_final
2022-10-02 10:24:07	ga_ls8c_ard_3-2-1_101072_2022-10-02_final
2022-10-07 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-07_final
2022-10-10 09:36:59	ga_ls8c_ard_3-2-1_093078_2022-10-10_final
2022-10-10 11:16:16	ga_ls8c_ard_3-2-1_109079_2022-10-10_final
2022-10-18 10:26:49	ga_ls8c_ard_3-2-1_101079_2022-10-18_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-23 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-23_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-10-24 11:27:05	ga_ls8c_ard_3-2-1_111075_2022-10-24_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-11-02 11:22:33	ga_ls8c_ard_3-2-1_110079_2022-11-02_final
2022-11-05 11:53:50	ga_ls8c_ard_3-2-1_115080_2022-11-05_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-09 11:27:06	ga_ls8c_ard_3-2-1_111075_2022-11-09_final
2022-11-10 10:32:40	ga_ls8c_ard_3-2-1_102078_2022-11-10_final
2022-11-11 09:38:38	ga_ls8c_ard_3-2-1_093082_2022-11-11_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-18 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-11-18_final
2022-11-19 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-11-19_final
2022-11-20 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-11-19_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-12-04 11:22:52	ga_ls8c_ard_3-2-1_110080_2022-12-04_final
2022-12-07 10:12:28	ga_ls8c_ard_3-2-1_099074_2022-12-07_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-11 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-12-11_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-16 11:47:54	ga_ls8c_ard_3-2-1_114081_2022-12-16_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-22 09:30:38	ga_ls8c_ard_3-2-1_092078_2022-12-22_final
2022-12-27 11:27:41	ga_ls8c_ard_3-2-1_111077_2022-12-27_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2023-01-01 10:06:57	ga_ls8c_ard_3-2-1_098076_2023-01-01_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-09 10:57:34	ga_ls8c_ard_3-2-1_106079_2023-01-09_final
2023-01-12 11:28:02	ga_ls8c_ard_3-2-1_111078_2023-01-12_final
2023-01-15 10:20:49	ga_ls8c_ard_3-2-1_100080_2023-01-15_final
2023-01-16 09:25:58	ga_ls8c_ard_3-2-1_091082_2023-01-15_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-19 09:54:52	ga_ls8c_ard_3-2-1_096077_2023-01-19_final
2023-01-19 09:56:28	ga_ls8c_ard_3-2-1_096081_2023-01-19_final
2023-01-21 09:42:32	ga_ls8c_ard_3-2-1_094077_2023-01-21_final
2023-01-30 09:36:25	ga_ls8c_ard_3-2-1_093077_2023-01-30_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-05 10:37:25	ga_ls8c_ard_3-2-1_103075_2023-02-05_final
2023-02-06 11:23:04	ga_ls8c_ard_3-2-1_110081_2023-02-06_final
2023-02-10 10:56:43	ga_ls8c_ard_3-2-1_106077_2023-02-10_final
2023-02-15 09:36:42	ga_ls8c_ard_3-2-1_093078_2023-02-15_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-20 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_final
2023-02-20 11:34:26	ga_ls8c_ard_3-2-1_112079_2023-02-20_final
2023-02-21 10:37:12	ga_ls8c_ard_3-2-1_103075_2023-02-21_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-02-28 10:44:05	ga_ls8c_ard_3-2-1_104077_2023-02-28_final
2023-03-02 10:32:54	ga_ls8c_ard_3-2-1_102080_2023-03-02_final
2023-03-05 09:25:42	ga_ls8c_ard_3-2-1_091082_2023-03-04_final
2023-03-12 09:30:14	ga_ls8c_ard_3-2-1_092078_2023-03-12_final
2023-03-16 10:43:58	ga_ls8c_ard_3-2-1_104077_2023-03-16_final
2023-03-18 10:30:23	ga_ls8c_ard_3-2-1_102074_2023-03-18_final
2023-03-24 11:33:42	ga_ls8c_ard_3-2-1_112078_2023-03-24_final
2023-03-28 11:11:21	ga_ls8c_ard_3-2-1_108084_2023-03-28_final
2023-03-31 10:00:09	ga_ls8c_ard_3-2-1_097076_2023-03-31_final
2023-03-31 11:38:38	ga_ls8c_ard_3-2-1_113075_2023-03-31_final
2023-04-02 11:29:26	ga_ls8c_ard_3-2-1_111083_2023-04-02_final
2023-04-05 10:17:24	ga_ls8c_ard_3-2-1_100073_2023-04-05_final
2023-04-06 11:03:26	ga_ls8c_ard_3-2-1_107080_2023-04-06_final
2023-04-08 10:50:38	ga_ls8c_ard_3-2-1_105079_2023-04-08_final
2023-04-19 10:29:11	ga_ls8c_ard_3-2-1_102072_2023-04-19_final
2023-04-20 09:38:20	ga_ls8c_ard_3-2-1_093084_2023-04-20_final
2023-04-20 11:15:37	ga_ls8c_ard_3-2-1_109080_2023-04-20_final
2023-04-24 10:52:07	ga_ls8c_ard_3-2-1_105083_2023-04-24_final
2023-04-25 11:32:11	ga_ls8c_ard_3-2-1_112075_2023-04-25_final
2023-04-26 10:34:57	ga_ls8c_ard_3-2-1_103071_2023-04-26_final
2023-04-30 10:11:48	ga_ls8c_ard_3-2-1_099075_2023-04-30_final
2023-05-01 10:57:27	ga_ls8c_ard_3-2-1_106081_2023-05-01_final
2023-05-03 10:43:28	ga_ls8c_ard_3-2-1_104077_2023-05-03_final
2023-05-08 11:02:44	ga_ls8c_ard_3-2-1_107079_2023-05-08_final
2023-05-09 10:08:18	ga_ls8c_ard_3-2-1_098082_2023-05-09_final
2023-05-10 09:09:27	ga_ls8c_ard_3-2-1_089074_2023-05-09_final
2023-05-10 10:51:56	ga_ls8c_ard_3-2-1_105083_2023-05-10_final
2023-05-11 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-11_final
2023-05-15 09:31:32	ga_ls8c_ard_3-2-1_092083_2023-05-15_final
2023-05-17 10:56:02	ga_ls8c_ard_3-2-1_106078_2023-05-17_final
2023-05-17 10:57:14	ga_ls8c_ard_3-2-1_106081_2023-05-17_final
2023-05-19 10:40:30	ga_ls8c_ard_3-2-1_104070_2023-05-19_final
2023-05-19 10:44:53	ga_ls8c_ard_3-2-1_104081_2023-05-19_final
2023-05-20 11:26:34	ga_ls8c_ard_3-2-1_111077_2023-05-20_final
2023-05-22 11:11:49	ga_ls8c_ard_3-2-1_109071_2023-05-22_final
2023-05-24 09:24:58	ga_ls8c_ard_3-2-1_091082_2023-05-23_final
2023-05-25 10:07:50	ga_ls8c_ard_3-2-1_098081_2023-05-25_final
2023-05-26 10:47:07	ga_ls8c_ard_3-2-1_105071_2023-05-26_final
2023-05-26 10:51:54	ga_ls8c_ard_3-2-1_105083_2023-05-26_final
2023-05-27 09:54:17	ga_ls8c_ard_3-2-1_096078_2023-05-27_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