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
2022-11-05 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-11-05_final
2022-11-05 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-11-05_final
2022-11-05 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-11-05_final
2022-11-05 11:53:50	ga_ls8c_ard_3-2-1_115080_2022-11-05_final
2022-11-07 10:03:23	ga_ls8c_ard_3-2-1_097082_2022-11-07_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-21 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-11-21_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-12-02 11:34:25	ga_ls8c_ard_3-2-1_112078_2022-12-02_final
2022-12-03 10:38:00	ga_ls8c_ard_3-2-1_103076_2022-12-03_final
2022-12-06 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-12-06_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-16 10:09:25	ga_ls8c_ard_3-2-1_098082_2022-12-16_final
2022-12-18 09:55:25	ga_ls8c_ard_3-2-1_096078_2022-12-18_final
2022-12-19 10:37:04	ga_ls8c_ard_3-2-1_103074_2022-12-19_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-27 09:49:36	ga_ls8c_ard_3-2-1_095079_2022-12-27_final
2022-12-28 10:30:04	ga_ls8c_ard_3-2-1_102072_2022-12-28_final
2022-12-28 10:32:28	ga_ls8c_ard_3-2-1_102078_2022-12-28_final
2022-12-28 10:32:52	ga_ls8c_ard_3-2-1_102079_2022-12-28_final
2022-12-30 10:21:19	ga_ls8c_ard_3-2-1_100081_2022-12-30_final
2023-01-01 10:06:57	ga_ls8c_ard_3-2-1_098076_2023-01-01_final
2023-01-01 10:09:21	ga_ls8c_ard_3-2-1_098082_2023-01-01_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-03 09:55:24	ga_ls8c_ard_3-2-1_096078_2023-01-03_final
2023-01-03 09:56:35	ga_ls8c_ard_3-2-1_096081_2023-01-03_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-09 10:57:10	ga_ls8c_ard_3-2-1_106078_2023-01-09_final
2023-01-09 10:57:34	ga_ls8c_ard_3-2-1_106079_2023-01-09_final
2023-01-10 11:39:38	ga_ls8c_ard_3-2-1_113076_2023-01-10_final
2023-01-12 11:27:39	ga_ls8c_ard_3-2-1_111077_2023-01-12_final
2023-01-12 11:28:02	ga_ls8c_ard_3-2-1_111078_2023-01-12_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-16 11:03:16	ga_ls8c_ard_3-2-1_107078_2023-01-16_final
2023-01-17 10:09:13	ga_ls8c_ard_3-2-1_098082_2023-01-17_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-19 09:54:04	ga_ls8c_ard_3-2-1_096075_2023-01-19_final
2023-01-21 11:22:13	ga_ls8c_ard_3-2-1_110079_2023-01-21_final
2023-01-26 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-26_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-06 09:43:23	ga_ls8c_ard_3-2-1_094079_2023-02-06_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-06 11:23:04	ga_ls8c_ard_3-2-1_110081_2023-02-06_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-11 10:00:41	ga_ls8c_ard_3-2-1_097076_2023-02-11_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-16 10:20:45	ga_ls8c_ard_3-2-1_100080_2023-02-16_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-18 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-02-18_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-19 10:51:12	ga_ls8c_ard_3-2-1_105079_2023-02-19_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-20 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-25 10:12:46	ga_ls8c_ard_3-2-1_099076_2023-02-25_final
2023-02-26 10:56:26	ga_ls8c_ard_3-2-1_106077_2023-02-26_final
2023-02-27 10:00:49	ga_ls8c_ard_3-2-1_097077_2023-02-27_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-03-01 09:50:03	ga_ls8c_ard_3-2-1_095081_2023-03-01_final
2023-03-01 11:27:20	ga_ls8c_ard_3-2-1_111077_2023-03-01_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-01 11:28:08	ga_ls8c_ard_3-2-1_111079_2023-03-01_final
2023-03-03 09:36:29	ga_ls8c_ard_3-2-1_093078_2023-03-03_final
2023-03-03 09:38:29	ga_ls8c_ard_3-2-1_093083_2023-03-03_final
2023-03-03 11:16:10	ga_ls8c_ard_3-2-1_109080_2023-03-03_final
2023-03-04 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-03-04_final
2023-03-04 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-03-04_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_final
2023-03-08 09:56:33	ga_ls8c_ard_3-2-1_096082_2023-03-08_final
2023-03-09 10:37:01	ga_ls8c_ard_3-2-1_103075_2023-03-09_final
2023-03-09 10:37:25	ga_ls8c_ard_3-2-1_103076_2023-03-09_final
2023-03-10 09:41:24	ga_ls8c_ard_3-2-1_094075_2023-03-10_final
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-13 10:12:42	ga_ls8c_ard_3-2-1_099076_2023-03-13_final
2023-03-15 09:59:08	ga_ls8c_ard_3-2-1_097073_2023-03-15_final
2023-03-15 11:39:36	ga_ls8c_ard_3-2-1_113077_2023-03-15_final
2023-03-16 10:43:34	ga_ls8c_ard_3-2-1_104076_2023-03-16_final
2023-03-16 10:43:58	ga_ls8c_ard_3-2-1_104077_2023-03-16_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