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
2017-06-18 11:39:46	ga_ls8c_ard_3-0-0_113078_2017-06-18_final
2017-06-18 11:40:10	ga_ls8c_ard_3-0-0_113079_2017-06-18_final
2017-06-18 11:40:34	ga_ls8c_ard_3-0-0_113080_2017-06-18_final
2017-06-18 11:40:58	ga_ls8c_ard_3-0-0_113081_2017-06-18_final
2017-06-18 11:41:22	ga_ls8c_ard_3-0-0_113082_2017-06-18_final
2017-06-18 11:41:46	ga_ls8c_ard_3-0-0_113083_2017-06-18_final
2017-06-20 11:30:12	ga_ls8c_ard_3-0-0_111085_2017-06-20_final
2017-07-06 11:30:16	ga_ls8c_ard_3-0-0_111085_2017-07-06_final
2018-11-10 11:50:20	ga_ls8c_ard_3-0-0_115073_2018-11-10_final
2018-11-10 11:50:44	ga_ls8c_ard_3-0-0_115074_2018-11-10_final
2019-01-13 11:50:15	ga_ls8c_ard_3-0-0_115073_2019-01-13_final
2019-01-13 11:50:39	ga_ls8c_ard_3-0-0_115074_2019-01-13_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
2022-02-06 11:50:56	ga_ls8c_ard_3-2-1_115074_2022-02-06_final
2022-02-17 11:35:31	ga_ls8c_ard_3-2-1_112082_2022-02-17_final
2022-02-17 11:35:55	ga_ls8c_ard_3-2-1_112083_2022-02-17_final
2022-02-17 11:36:19	ga_ls8c_ard_3-2-1_112084_2022-02-17_final
2022-05-06 11:44:29	ga_ls8c_ard_3-2-1_114074_2022-05-06_final
2022-05-06 11:44:53	ga_ls8c_ard_3-2-1_114075_2022-05-06_final
2022-05-06 11:45:16	ga_ls8c_ard_3-2-1_114076_2022-05-06_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-06 11:46:04	ga_ls8c_ard_3-2-1_114078_2022-05-06_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-08 11:35:20	ga_ls8c_ard_3-2-1_112082_2022-05-08_final
2022-05-08 11:35:44	ga_ls8c_ard_3-2-1_112083_2022-05-08_final
2022-05-08 11:36:08	ga_ls8c_ard_3-2-1_112084_2022-05-08_final
2022-05-13 11:50:43	ga_ls8c_ard_3-2-1_115074_2022-05-13_final
2022-06-07 11:44:42	ga_ls8c_ard_3-2-1_114074_2022-06-07_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-07 11:45:54	ga_ls8c_ard_3-2-1_114077_2022-06-07_final
2022-06-07 11:46:18	ga_ls8c_ard_3-2-1_114078_2022-06-07_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-09 11:35:34	ga_ls8c_ard_3-2-1_112082_2022-06-09_final
2022-06-09 11:35:58	ga_ls8c_ard_3-2-1_112083_2022-06-09_final
2022-06-09 11:36:22	ga_ls8c_ard_3-2-1_112084_2022-06-09_final
2022-06-23 11:44:51	ga_ls8c_ard_3-2-1_114074_2022-06-23_final
2022-06-23 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-06-23_final
2022-06-23 11:45:39	ga_ls8c_ard_3-2-1_114076_2022-06-23_final
2022-06-23 11:46:03	ga_ls8c_ard_3-2-1_114077_2022-06-23_final
2022-06-23 11:46:27	ga_ls8c_ard_3-2-1_114078_2022-06-23_final
2022-06-23 11:46:51	ga_ls8c_ard_3-2-1_114079_2022-06-23_final
2022-07-27 11:35:50	ga_ls8c_ard_3-2-1_112082_2022-07-27_final
2022-07-27 11:36:14	ga_ls8c_ard_3-2-1_112083_2022-07-27_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-08-03 11:40:29	ga_ls8c_ard_3-2-1_113078_2022-08-03_final
2022-08-03 11:40:53	ga_ls8c_ard_3-2-1_113079_2022-08-03_final
2022-08-03 11:41:17	ga_ls8c_ard_3-2-1_113080_2022-08-03_final
2022-08-03 11:41:41	ga_ls8c_ard_3-2-1_113081_2022-08-03_final
2022-08-03 11:42:05	ga_ls8c_ard_3-2-1_113082_2022-08-03_final
2022-08-03 11:42:29	ga_ls8c_ard_3-2-1_113083_2022-08-03_final
2023-02-02 11:45:01	ga_ls8c_ard_3-2-1_114074_2023-02-02_final
2023-02-02 11:45:24	ga_ls8c_ard_3-2-1_114075_2023-02-02_final
2023-02-02 11:45:48	ga_ls8c_ard_3-2-1_114076_2023-02-02_final
2023-02-02 11:46:12	ga_ls8c_ard_3-2-1_114077_2023-02-02_final
2023-02-02 11:46:36	ga_ls8c_ard_3-2-1_114078_2023-02-02_final
2023-02-02 11:47:00	ga_ls8c_ard_3-2-1_114079_2023-02-02_final
2023-02-04 11:35:50	ga_ls8c_ard_3-2-1_112082_2023-02-04_final
2023-02-04 11:36:14	ga_ls8c_ard_3-2-1_112083_2023-02-04_final
2023-02-04 11:36:38	ga_ls8c_ard_3-2-1_112084_2023-02-04_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-20 11:36:26	ga_ls8c_ard_3-2-1_112084_2023-02-20_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-02-27 11:40:54	ga_ls8c_ard_3-2-1_113080_2023-02-27_final
2023-02-27 11:41:18	ga_ls8c_ard_3-2-1_113081_2023-02-27_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-06 11:44:38	ga_ls8c_ard_3-2-1_114074_2023-03-06_final
2023-03-06 11:45:02	ga_ls8c_ard_3-2-1_114075_2023-03-06_final
2023-03-06 11:45:26	ga_ls8c_ard_3-2-1_114076_2023-03-06_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-06 11:46:38	ga_ls8c_ard_3-2-1_114079_2023-03-06_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-03-31 11:40:14	ga_ls8c_ard_3-2-1_113079_2023-03-31_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-03-31 11:41:02	ga_ls8c_ard_3-2-1_113081_2023-03-31_final
2023-03-31 11:41:26	ga_ls8c_ard_3-2-1_113082_2023-03-31_final
2023-03-31 11:41:50	ga_ls8c_ard_3-2-1_113083_2023-03-31_final
2023-06-10 11:44:03	ga_ls8c_ard_3-2-1_114074_2023-06-10_final
2023-06-10 11:44:27	ga_ls8c_ard_3-2-1_114075_2023-06-10_final
2023-06-10 11:44:51	ga_ls8c_ard_3-2-1_114076_2023-06-10_final
2023-06-10 11:45:15	ga_ls8c_ard_3-2-1_114077_2023-06-10_final
2023-06-10 11:45:39	ga_ls8c_ard_3-2-1_114078_2023-06-10_final
2023-06-10 11:46:03	ga_ls8c_ard_3-2-1_114079_2023-06-10_final
2023-06-12 11:34:54	ga_ls8c_ard_3-2-1_112082_2023-06-12_final
2023-06-12 11:35:18	ga_ls8c_ard_3-2-1_112083_2023-06-12_final
2023-06-12 11:35:42	ga_ls8c_ard_3-2-1_112084_2023-06-12_final
2023-06-17 11:50:16	ga_ls8c_ard_3-2-1_115074_2023-06-17_final
2023-06-19 11:39:31	ga_ls8c_ard_3-2-1_113078_2023-06-19_final
2023-06-19 11:39:55	ga_ls8c_ard_3-2-1_113079_2023-06-19_final
2023-06-19 11:40:19	ga_ls8c_ard_3-2-1_113080_2023-06-19_final
2023-06-19 11:40:43	ga_ls8c_ard_3-2-1_113081_2023-06-19_final
2023-06-19 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-06-19_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