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
2018-10-25 11:50:18	ga_ls8c_ard_3-0-0_115073_2018-10-25_final
2018-10-25 11:50:42	ga_ls8c_ard_3-0-0_115074_2018-10-25_final
2018-10-25 11:51:06	ga_ls8c_ard_3-0-0_115075_2018-10-25_final
2018-11-28 11:40:22	ga_ls8c_ard_3-0-0_113079_2018-11-28_final
2018-11-28 11:40:46	ga_ls8c_ard_3-0-0_113080_2018-11-28_final
2018-11-28 11:41:10	ga_ls8c_ard_3-0-0_113081_2018-11-28_final
2018-11-28 11:41:34	ga_ls8c_ard_3-0-0_113082_2018-11-28_final
2018-11-28 11:41:58	ga_ls8c_ard_3-0-0_113083_2018-11-28_final
2018-11-28 11:42:22	ga_ls8c_ard_3-0-0_113084_2018-11-28_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
2018-12-12 11:51:05	ga_ls8c_ard_3-0-0_115075_2018-12-12_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
2018-12-21 11:46:54	ga_ls8c_ard_3-0-0_114080_2018-12-21_final
2019-01-06 11:44:53	ga_ls8c_ard_3-0-0_114075_2019-01-06_final
2019-01-06 11:45:17	ga_ls8c_ard_3-0-0_114076_2019-01-06_final
2019-01-06 11:45:41	ga_ls8c_ard_3-0-0_114077_2019-01-06_final
2019-01-06 11:46:05	ga_ls8c_ard_3-0-0_114078_2019-01-06_final
2019-01-06 11:46:29	ga_ls8c_ard_3-0-0_114079_2019-01-06_final
2019-01-06 11:46:53	ga_ls8c_ard_3-0-0_114080_2019-01-06_final
2022-03-03 11:45:02	ga_ls8c_ard_3-2-1_114075_2022-03-03_final
2022-03-03 11:45:26	ga_ls8c_ard_3-2-1_114076_2022-03-03_final
2022-03-03 11:46:38	ga_ls8c_ard_3-2-1_114079_2022-03-03_final
2022-03-03 11:47:02	ga_ls8c_ard_3-2-1_114080_2022-03-03_final
2022-03-10 11:50:47	ga_ls8c_ard_3-2-1_115074_2022-03-10_final
2022-03-10 11:51:11	ga_ls8c_ard_3-2-1_115075_2022-03-10_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-13 11:40:40	ga_ls8c_ard_3-2-1_113080_2022-04-13_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-13 11:41:52	ga_ls8c_ard_3-2-1_113083_2022-04-13_final
2022-04-13 11:42:16	ga_ls8c_ard_3-2-1_113084_2022-04-13_final
2022-04-20 11:44:27	ga_ls8c_ard_3-2-1_114074_2022-04-20_final
2022-04-20 11:44:51	ga_ls8c_ard_3-2-1_114075_2022-04-20_final
2022-04-20 11:45:15	ga_ls8c_ard_3-2-1_114076_2022-04-20_final
2022-04-20 11:45:39	ga_ls8c_ard_3-2-1_114077_2022-04-20_final
2022-04-20 11:46:03	ga_ls8c_ard_3-2-1_114078_2022-04-20_final
2022-04-20 11:46:27	ga_ls8c_ard_3-2-1_114079_2022-04-20_final
2022-04-20 11:46:51	ga_ls8c_ard_3-2-1_114080_2022-04-20_final
2022-04-22 11:35:40	ga_ls8c_ard_3-2-1_112083_2022-04-22_final
2022-04-22 11:36:04	ga_ls8c_ard_3-2-1_112084_2022-04-22_final
2022-04-27 11:50:34	ga_ls8c_ard_3-2-1_115074_2022-04-27_final
2022-04-27 11:50:58	ga_ls8c_ard_3-2-1_115075_2022-04-27_final
2022-04-29 11:40:12	ga_ls8c_ard_3-2-1_113079_2022-04-29_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_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
2022-05-13 11:51:07	ga_ls8c_ard_3-2-1_115075_2022-05-13_final
2022-05-15 11:40:22	ga_ls8c_ard_3-2-1_113079_2022-05-15_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-15 11:41:10	ga_ls8c_ard_3-2-1_113081_2022-05-15_final
2022-05-15 11:41:34	ga_ls8c_ard_3-2-1_113082_2022-05-15_final
2022-05-15 11:41:58	ga_ls8c_ard_3-2-1_113083_2022-05-15_final
2022-05-15 11:42:22	ga_ls8c_ard_3-2-1_113084_2022-05-15_final
2022-05-22 11:44:34	ga_ls8c_ard_3-2-1_114074_2022-05-22_final
2022-05-22 11:44:58	ga_ls8c_ard_3-2-1_114075_2022-05-22_final
2022-05-22 11:45:22	ga_ls8c_ard_3-2-1_114076_2022-05-22_final
2022-05-22 11:45:46	ga_ls8c_ard_3-2-1_114077_2022-05-22_final
2022-05-22 11:46:10	ga_ls8c_ard_3-2-1_114078_2022-05-22_final
2022-05-22 11:46:34	ga_ls8c_ard_3-2-1_114079_2022-05-22_final
2022-05-22 11:46:58	ga_ls8c_ard_3-2-1_114080_2022-05-22_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-24 11:36:12	ga_ls8c_ard_3-2-1_112084_2022-05-24_final
2022-05-29 11:50:45	ga_ls8c_ard_3-2-1_115074_2022-05-29_final
2022-05-29 11:51:09	ga_ls8c_ard_3-2-1_115075_2022-05-29_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-16 11:45:30	ga_ls8c_ard_3-2-1_114075_2022-12-16_final
2022-12-16 11:45:54	ga_ls8c_ard_3-2-1_114076_2022-12-16_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-16 11:47:06	ga_ls8c_ard_3-2-1_114079_2022-12-16_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-23 11:51:35	ga_ls8c_ard_3-2-1_115075_2022-12-23_final
2022-12-23 11:51:59	ga_ls8c_ard_3-2-1_115076_2022-12-23_final
2023-04-16 11:39:59	ga_ls8c_ard_3-2-1_113079_2023-04-16_final
2023-04-16 11:40:23	ga_ls8c_ard_3-2-1_113080_2023-04-16_final
2023-04-16 11:40:47	ga_ls8c_ard_3-2-1_113081_2023-04-16_final
2023-04-16 11:41:11	ga_ls8c_ard_3-2-1_113082_2023-04-16_final
2023-04-16 11:41:35	ga_ls8c_ard_3-2-1_113083_2023-04-16_final
2023-04-16 11:41:59	ga_ls8c_ard_3-2-1_113084_2023-04-16_final
2023-07-12 11:44:20	ga_ls8c_ard_3-2-1_114074_2023-07-12_final
2023-07-12 11:44:43	ga_ls8c_ard_3-2-1_114075_2023-07-12_final
2023-07-12 11:45:07	ga_ls8c_ard_3-2-1_114076_2023-07-12_final
2023-07-12 11:45:31	ga_ls8c_ard_3-2-1_114077_2023-07-12_final
2023-07-12 11:45:55	ga_ls8c_ard_3-2-1_114078_2023-07-12_final
2023-07-12 11:46:19	ga_ls8c_ard_3-2-1_114079_2023-07-12_final
2023-07-12 11:46:43	ga_ls8c_ard_3-2-1_114080_2023-07-12_final
2023-07-14 11:35:34	ga_ls8c_ard_3-2-1_112083_2023-07-14_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