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
2017-03-30 11:40:02	ga_ls8c_ard_3-0-0_113079_2017-03-30_final
2017-03-30 11:40:26	ga_ls8c_ard_3-0-0_113080_2017-03-30_final
2017-03-30 11:40:50	ga_ls8c_ard_3-0-0_113081_2017-03-30_final
2017-03-30 11:41:14	ga_ls8c_ard_3-0-0_113082_2017-03-30_final
2017-03-30 11:41:38	ga_ls8c_ard_3-0-0_113083_2017-03-30_final
2017-03-30 11:42:02	ga_ls8c_ard_3-0-0_113084_2017-03-30_final
2017-06-16 11:50:07	ga_ls8c_ard_3-0-0_115073_2017-06-16_final
2017-06-16 11:50:31	ga_ls8c_ard_3-0-0_115074_2017-06-16_final
2017-06-16 11:50:55	ga_ls8c_ard_3-0-0_115075_2017-06-16_final
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
2017-06-18 11:42:09	ga_ls8c_ard_3-0-0_113084_2017-06-18_final
2017-07-04 11:39:50	ga_ls8c_ard_3-0-0_113078_2017-07-04_final
2017-07-04 11:40:14	ga_ls8c_ard_3-0-0_113079_2017-07-04_final
2017-07-04 11:40:38	ga_ls8c_ard_3-0-0_113080_2017-07-04_final
2017-07-04 11:41:02	ga_ls8c_ard_3-0-0_113081_2017-07-04_final
2017-07-04 11:41:26	ga_ls8c_ard_3-0-0_113082_2017-07-04_final
2017-07-04 11:41:49	ga_ls8c_ard_3-0-0_113083_2017-07-04_final
2017-07-04 11:42:13	ga_ls8c_ard_3-0-0_113084_2017-07-04_final
2017-08-19 11:50:28	ga_ls8c_ard_3-0-0_115073_2017-08-19_final
2017-08-19 11:50:52	ga_ls8c_ard_3-0-0_115074_2017-08-19_final
2017-08-19 11:51:16	ga_ls8c_ard_3-0-0_115075_2017-08-19_final
2017-08-21 11:40:07	ga_ls8c_ard_3-0-0_113078_2017-08-21_final
2017-08-21 11:40:31	ga_ls8c_ard_3-0-0_113079_2017-08-21_final
2017-08-21 11:40:55	ga_ls8c_ard_3-0-0_113080_2017-08-21_final
2017-08-21 11:41:19	ga_ls8c_ard_3-0-0_113081_2017-08-21_final
2017-08-21 11:41:43	ga_ls8c_ard_3-0-0_113082_2017-08-21_final
2017-08-21 11:42:07	ga_ls8c_ard_3-0-0_113083_2017-08-21_final
2017-08-21 11:42:31	ga_ls8c_ard_3-0-0_113084_2017-08-21_final
2018-02-13 11:40:16	ga_ls8c_ard_3-0-0_113079_2018-02-13_final
2018-02-13 11:40:40	ga_ls8c_ard_3-0-0_113080_2018-02-13_final
2018-02-13 11:41:03	ga_ls8c_ard_3-0-0_113081_2018-02-13_final
2018-02-13 11:41:27	ga_ls8c_ard_3-0-0_113082_2018-02-13_final
2018-02-13 11:41:51	ga_ls8c_ard_3-0-0_113083_2018-02-13_final
2018-02-13 11:42:15	ga_ls8c_ard_3-0-0_113084_2018-02-13_final
2018-08-01 11:34:45	ga_ls8c_ard_3-0-0_112082_2018-08-01_final
2018-08-01 11:35:09	ga_ls8c_ard_3-0-0_112083_2018-08-01_final
2018-08-01 11:35:33	ga_ls8c_ard_3-0-0_112084_2018-08-01_final
2018-08-01 11:35:57	ga_ls8c_ard_3-0-0_112085_2018-08-01_final
2018-09-07 11:50:00	ga_ls8c_ard_3-0-0_115073_2018-09-07_final
2018-09-07 11:50:24	ga_ls8c_ard_3-0-0_115074_2018-09-07_final
2018-09-07 11:50:47	ga_ls8c_ard_3-0-0_115075_2018-09-07_final
2018-09-16 11:44:15	ga_ls8c_ard_3-0-0_114074_2018-09-16_final
2018-09-16 11:44:39	ga_ls8c_ard_3-0-0_114075_2018-09-16_final
2018-09-16 11:45:03	ga_ls8c_ard_3-0-0_114076_2018-09-16_final
2018-09-16 11:45:27	ga_ls8c_ard_3-0-0_114077_2018-09-16_final
2018-09-16 11:45:51	ga_ls8c_ard_3-0-0_114078_2018-09-16_final
2018-09-16 11:46:15	ga_ls8c_ard_3-0-0_114079_2018-09-16_final
2018-09-16 11:46:39	ga_ls8c_ard_3-0-0_114080_2018-09-16_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
2018-09-25 11:42:07	ga_ls8c_ard_3-0-0_113084_2018-09-25_final
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
2018-10-27 11:39:56	ga_ls8c_ard_3-0-0_113078_2018-10-27_final
2018-10-27 11:40:20	ga_ls8c_ard_3-0-0_113079_2018-10-27_final
2018-10-27 11:40:44	ga_ls8c_ard_3-0-0_113080_2018-10-27_final
2018-10-27 11:41:08	ga_ls8c_ard_3-0-0_113081_2018-10-27_final
2018-10-27 11:41:32	ga_ls8c_ard_3-0-0_113082_2018-10-27_final
2018-10-27 11:41:56	ga_ls8c_ard_3-0-0_113083_2018-10-27_final
2018-10-27 11:42:20	ga_ls8c_ard_3-0-0_113084_2018-10-27_final
2023-11-08 11:50:57	ga_ls8c_ard_3-2-1_115074_2023-11-08_final
2023-11-08 11:51:21	ga_ls8c_ard_3-2-1_115075_2023-11-08_final
2023-11-10 11:40:10	ga_ls8c_ard_3-2-1_113078_2023-11-10_final
2023-11-10 11:40:34	ga_ls8c_ard_3-2-1_113079_2023-11-10_final
2023-11-10 11:40:58	ga_ls8c_ard_3-2-1_113080_2023-11-10_final
2023-11-10 11:41:22	ga_ls8c_ard_3-2-1_113081_2023-11-10_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-10 11:42:09	ga_ls8c_ard_3-2-1_113083_2023-11-10_final
2023-11-10 11:42:33	ga_ls8c_ard_3-2-1_113084_2023-11-10_final
2023-12-19 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-12-19_final
2023-12-19 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-12-19_final
2023-12-19 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-12-19_final
2023-12-19 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-12-19_final
2023-12-19 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-12-19_final
2024-01-29 11:40:04	ga_ls8c_ard_3-2-1_113078_2024-01-29_final
2024-01-29 11:40:28	ga_ls8c_ard_3-2-1_113079_2024-01-29_final
2024-01-29 11:40:52	ga_ls8c_ard_3-2-1_113080_2024-01-29_final
2024-01-29 11:41:16	ga_ls8c_ard_3-2-1_113081_2024-01-29_final
2024-01-29 11:41:40	ga_ls8c_ard_3-2-1_113082_2024-01-29_final
2024-01-29 11:42:04	ga_ls8c_ard_3-2-1_113083_2024-01-29_final
2024-01-29 11:42:28	ga_ls8c_ard_3-2-1_113084_2024-01-29_final
2024-02-05 11:44:43	ga_ls8c_ard_3-2-1_114074_2024-02-05_final
2024-02-05 11:45:07	ga_ls8c_ard_3-2-1_114075_2024-02-05_final
2024-02-05 11:45:31	ga_ls8c_ard_3-2-1_114076_2024-02-05_final
2024-02-05 11:45:55	ga_ls8c_ard_3-2-1_114077_2024-02-05_final
2024-02-05 11:46:19	ga_ls8c_ard_3-2-1_114078_2024-02-05_final
2024-02-05 11:46:43	ga_ls8c_ard_3-2-1_114079_2024-02-05_final
2024-02-05 11:47:07	ga_ls8c_ard_3-2-1_114080_2024-02-05_final
2024-02-07 11:35:34	ga_ls8c_ard_3-2-1_112082_2024-02-07_final
2024-02-07 11:35:58	ga_ls8c_ard_3-2-1_112083_2024-02-07_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years