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
2016-05-28 11:50:03	ga_ls8c_ard_3-0-0_115073_2016-05-28_final
2016-05-28 11:50:27	ga_ls8c_ard_3-0-0_115074_2016-05-28_final
2016-05-30 11:39:18	ga_ls8c_ard_3-0-0_113077_2016-05-30_final
2016-05-30 11:39:42	ga_ls8c_ard_3-0-0_113078_2016-05-30_final
2016-05-30 11:40:06	ga_ls8c_ard_3-0-0_113079_2016-05-30_final
2016-05-30 11:40:30	ga_ls8c_ard_3-0-0_113080_2016-05-30_final
2016-05-30 11:40:54	ga_ls8c_ard_3-0-0_113081_2016-05-30_final
2016-05-30 11:41:17	ga_ls8c_ard_3-0-0_113082_2016-05-30_final
2016-05-30 11:41:41	ga_ls8c_ard_3-0-0_113083_2016-05-30_final
2018-09-23 11:50:04	ga_ls8c_ard_3-0-0_115073_2018-09-23_final
2018-09-23 11:50:28	ga_ls8c_ard_3-0-0_115074_2018-09-23_final
2018-09-25 11:39:44	ga_ls8c_ard_3-0-0_113078_2018-09-25_final
2018-09-25 11:40:07	ga_ls8c_ard_3-0-0_113079_2018-09-25_final
2018-09-25 11:40:31	ga_ls8c_ard_3-0-0_113080_2018-09-25_final
2018-09-25 11:40:55	ga_ls8c_ard_3-0-0_113081_2018-09-25_final
2018-09-25 11:41:19	ga_ls8c_ard_3-0-0_113082_2018-09-25_final
2018-09-25 11:41:43	ga_ls8c_ard_3-0-0_113083_2018-09-25_final
2018-10-02 11:44:22	ga_ls8c_ard_3-0-0_114074_2018-10-02_final
2018-10-02 11:44:46	ga_ls8c_ard_3-0-0_114075_2018-10-02_final
2018-10-02 11:45:10	ga_ls8c_ard_3-0-0_114076_2018-10-02_final
2018-10-02 11:45:34	ga_ls8c_ard_3-0-0_114077_2018-10-02_final
2018-10-02 11:45:58	ga_ls8c_ard_3-0-0_114078_2018-10-02_final
2018-10-02 11:46:22	ga_ls8c_ard_3-0-0_114079_2018-10-02_final
2018-10-18 11:44:29	ga_ls8c_ard_3-0-0_114074_2018-10-18_final
2018-10-18 11:44:53	ga_ls8c_ard_3-0-0_114075_2018-10-18_final
2018-10-18 11:45:17	ga_ls8c_ard_3-0-0_114076_2018-10-18_final
2018-10-18 11:45:41	ga_ls8c_ard_3-0-0_114077_2018-10-18_final
2018-10-18 11:46:05	ga_ls8c_ard_3-0-0_114078_2018-10-18_final
2018-10-18 11:46:29	ga_ls8c_ard_3-0-0_114079_2018-10-18_final
2018-12-05 11:44:32	ga_ls8c_ard_3-0-0_114074_2018-12-05_final
2018-12-05 11:44:56	ga_ls8c_ard_3-0-0_114075_2018-12-05_final
2018-12-05 11:45:20	ga_ls8c_ard_3-0-0_114076_2018-12-05_final
2018-12-05 11:45:44	ga_ls8c_ard_3-0-0_114077_2018-12-05_final
2018-12-05 11:46:07	ga_ls8c_ard_3-0-0_114078_2018-12-05_final
2018-12-05 11:46:31	ga_ls8c_ard_3-0-0_114079_2018-12-05_final
2018-12-12 11:50:17	ga_ls8c_ard_3-0-0_115073_2018-12-12_final
2018-12-12 11:50:41	ga_ls8c_ard_3-0-0_115074_2018-12-12_final
2018-12-14 11:39:54	ga_ls8c_ard_3-0-0_113078_2018-12-14_final
2018-12-14 11:40:18	ga_ls8c_ard_3-0-0_113079_2018-12-14_final
2018-12-14 11:40:42	ga_ls8c_ard_3-0-0_113080_2018-12-14_final
2018-12-14 11:41:06	ga_ls8c_ard_3-0-0_113081_2018-12-14_final
2018-12-14 11:41:30	ga_ls8c_ard_3-0-0_113082_2018-12-14_final
2018-12-14 11:41:54	ga_ls8c_ard_3-0-0_113083_2018-12-14_final
2018-12-21 11:44:30	ga_ls8c_ard_3-0-0_114074_2018-12-21_final
2018-12-21 11:44:54	ga_ls8c_ard_3-0-0_114075_2018-12-21_final
2018-12-21 11:45:18	ga_ls8c_ard_3-0-0_114076_2018-12-21_final
2018-12-21 11:45:42	ga_ls8c_ard_3-0-0_114077_2018-12-21_final
2018-12-21 11:46:06	ga_ls8c_ard_3-0-0_114078_2018-12-21_final
2018-12-21 11:46:30	ga_ls8c_ard_3-0-0_114079_2018-12-21_final
2019-01-15 11:39:53	ga_ls8c_ard_3-0-0_113078_2019-01-15_final
2019-01-15 11:40:17	ga_ls8c_ard_3-0-0_113079_2019-01-15_final
2019-01-15 11:40:41	ga_ls8c_ard_3-0-0_113080_2019-01-15_final
2019-01-15 11:41:05	ga_ls8c_ard_3-0-0_113081_2019-01-15_final
2019-01-15 11:41:28	ga_ls8c_ard_3-0-0_113082_2019-01-15_final
2019-01-15 11:41:52	ga_ls8c_ard_3-0-0_113083_2019-01-15_final
2019-12-08 11:44:32	ga_ls8c_ard_3-1-0_114073_2019-12-08_final
2019-12-08 11:44:56	ga_ls8c_ard_3-1-0_114074_2019-12-08_final
2019-12-08 11:45:20	ga_ls8c_ard_3-1-0_114075_2019-12-08_final
2019-12-08 11:45:44	ga_ls8c_ard_3-1-0_114076_2019-12-08_final
2019-12-08 11:46:08	ga_ls8c_ard_3-1-0_114077_2019-12-08_final
2019-12-08 11:46:32	ga_ls8c_ard_3-1-0_114078_2019-12-08_final
2019-12-08 11:46:56	ga_ls8c_ard_3-1-0_114079_2019-12-08_final
2019-12-10 11:35:46	ga_ls8c_ard_3-1-0_112082_2019-12-10_final
2019-12-10 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-12-10_final
2019-12-10 11:36:34	ga_ls8c_ard_3-1-0_112084_2019-12-10_final
2019-12-10 11:36:58	ga_ls8c_ard_3-1-0_112085_2019-12-10_final
2019-12-31 11:50:38	ga_ls8c_ard_3-1-0_115073_2019-12-31_final
2019-12-31 11:51:02	ga_ls8c_ard_3-1-0_115074_2019-12-31_final
2020-01-02 11:40:15	ga_ls8c_ard_3-1-0_113078_2020-01-02_final
2020-01-02 11:40:39	ga_ls8c_ard_3-1-0_113079_2020-01-02_final
2020-01-02 11:41:03	ga_ls8c_ard_3-1-0_113080_2020-01-02_final
2020-01-02 11:41:27	ga_ls8c_ard_3-1-0_113081_2020-01-02_final
2020-01-02 11:41:51	ga_ls8c_ard_3-1-0_113082_2020-01-02_final
2020-01-02 11:42:15	ga_ls8c_ard_3-1-0_113083_2020-01-02_final
2020-02-10 11:44:17	ga_ls8c_ard_3-1-0_114073_2020-02-10_final
2020-02-10 11:44:40	ga_ls8c_ard_3-1-0_114074_2020-02-10_final
2020-02-10 11:45:04	ga_ls8c_ard_3-1-0_114075_2020-02-10_final
2020-02-10 11:45:28	ga_ls8c_ard_3-1-0_114076_2020-02-10_final
2020-02-10 11:45:52	ga_ls8c_ard_3-1-0_114077_2020-02-10_final
2020-02-10 11:46:16	ga_ls8c_ard_3-1-0_114078_2020-02-10_final
2020-02-10 11:46:40	ga_ls8c_ard_3-1-0_114079_2020-02-10_final
2020-02-12 11:35:30	ga_ls8c_ard_3-1-0_112082_2020-02-12_final
2020-02-12 11:35:54	ga_ls8c_ard_3-1-0_112083_2020-02-12_final
2020-02-12 11:36:18	ga_ls8c_ard_3-1-0_112084_2020-02-12_final
2020-02-12 11:36:42	ga_ls8c_ard_3-1-0_112085_2020-02-12_final
2020-02-17 11:50:26	ga_ls8c_ard_3-1-0_115073_2020-02-17_final
2020-02-17 11:50:50	ga_ls8c_ard_3-1-0_115074_2020-02-17_final
2020-06-28 11:30:14	ga_ls8c_ard_3-1-0_111085_2020-06-28_final
2020-07-10 11:50:15	ga_ls8c_ard_3-1-0_115073_2020-07-10_final
2020-07-10 11:50:39	ga_ls8c_ard_3-1-0_115074_2020-07-10_final
2020-07-26 11:50:20	ga_ls8c_ard_3-1-0_115073_2020-07-26_final
2020-07-26 11:50:44	ga_ls8c_ard_3-1-0_115074_2020-07-26_final
2020-07-28 11:39:58	ga_ls8c_ard_3-1-0_113078_2020-07-28_final
2020-07-28 11:40:22	ga_ls8c_ard_3-1-0_113079_2020-07-28_final
2020-07-28 11:40:46	ga_ls8c_ard_3-1-0_113080_2020-07-28_final
2020-07-28 11:41:10	ga_ls8c_ard_3-1-0_113081_2020-07-28_final
2020-07-28 11:41:34	ga_ls8c_ard_3-1-0_113082_2020-07-28_final
2020-07-28 11:41:58	ga_ls8c_ard_3-1-0_113083_2020-07-28_final
2020-07-30 11:30:25	ga_ls8c_ard_3-1-0_111085_2020-07-30_final
2020-09-12 11:50:38	ga_ls8c_ard_3-1-0_115073_2020-09-12_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