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
2018-11-26 11:50:20	ga_ls8c_ard_3-0-0_115073_2018-11-26_final
2018-11-26 11:50:44	ga_ls8c_ard_3-0-0_115074_2018-11-26_final
2018-11-26 11:51:08	ga_ls8c_ard_3-0-0_115075_2018-11-26_final
2018-11-26 11:51:32	ga_ls8c_ard_3-0-0_115076_2018-11-26_final
2018-11-26 11:51:56	ga_ls8c_ard_3-0-0_115077_2018-11-26_final
2018-11-26 11:52:20	ga_ls8c_ard_3-0-0_115078_2018-11-26_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
2018-12-07 11:36:09	ga_ls8c_ard_3-0-0_112084_2018-12-07_final
2018-12-07 11:36:33	ga_ls8c_ard_3-0-0_112085_2018-12-07_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
2018-12-12 11:51:29	ga_ls8c_ard_3-0-0_115076_2018-12-12_final
2018-12-12 11:51:53	ga_ls8c_ard_3-0-0_115077_2018-12-12_final
2018-12-12 11:52:17	ga_ls8c_ard_3-0-0_115078_2018-12-12_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
2018-12-14 11:42:18	ga_ls8c_ard_3-0-0_113084_2018-12-14_final
2018-12-30 11:41:07	ga_ls8c_ard_3-0-0_113081_2018-12-30_final
2018-12-30 11:41:31	ga_ls8c_ard_3-0-0_113082_2018-12-30_final
2018-12-30 11:41:55	ga_ls8c_ard_3-0-0_113083_2018-12-30_final
2018-12-30 11:42:19	ga_ls8c_ard_3-0-0_113084_2018-12-30_final
2019-01-08 11:36:31	ga_ls8c_ard_3-0-0_112085_2019-01-08_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
2019-01-13 11:51:03	ga_ls8c_ard_3-0-0_115075_2019-01-13_final
2019-01-13 11:51:27	ga_ls8c_ard_3-0-0_115076_2019-01-13_final
2019-01-13 11:51:51	ga_ls8c_ard_3-0-0_115077_2019-01-13_final
2019-01-13 11:52:15	ga_ls8c_ard_3-0-0_115078_2019-01-13_final
2019-07-08 11:50:20	ga_ls8c_ard_3-1-0_115073_2019-07-08_final
2019-07-08 11:50:44	ga_ls8c_ard_3-1-0_115074_2019-07-08_final
2019-07-08 11:51:08	ga_ls8c_ard_3-1-0_115075_2019-07-08_final
2019-07-08 11:51:32	ga_ls8c_ard_3-1-0_115076_2019-07-08_final
2019-07-08 11:51:56	ga_ls8c_ard_3-1-0_115077_2019-07-08_final
2019-07-08 11:52:20	ga_ls8c_ard_3-1-0_115078_2019-07-08_final
2019-07-10 11:41:10	ga_ls8c_ard_3-1-0_113081_2019-07-10_final
2019-07-10 11:41:34	ga_ls8c_ard_3-1-0_113082_2019-07-10_final
2019-07-10 11:41:58	ga_ls8c_ard_3-1-0_113083_2019-07-10_final
2019-07-10 11:42:22	ga_ls8c_ard_3-1-0_113084_2019-07-10_final
2019-07-24 11:50:24	ga_ls8c_ard_3-1-0_115073_2019-07-24_final
2019-07-24 11:50:48	ga_ls8c_ard_3-1-0_115074_2019-07-24_final
2019-07-24 11:51:12	ga_ls8c_ard_3-1-0_115075_2019-07-24_final
2019-07-24 11:51:36	ga_ls8c_ard_3-1-0_115076_2019-07-24_final
2019-07-24 11:52:00	ga_ls8c_ard_3-1-0_115077_2019-07-24_final
2019-07-24 11:52:24	ga_ls8c_ard_3-1-0_115078_2019-07-24_final
2019-07-26 11:41:15	ga_ls8c_ard_3-1-0_113081_2019-07-26_final
2019-07-26 11:41:39	ga_ls8c_ard_3-1-0_113082_2019-07-26_final
2019-07-26 11:42:03	ga_ls8c_ard_3-1-0_113083_2019-07-26_final
2019-07-26 11:42:27	ga_ls8c_ard_3-1-0_113084_2019-07-26_final
2019-08-02 11:45:53	ga_ls8c_ard_3-1-0_114077_2019-08-02_final
2019-08-02 11:46:17	ga_ls8c_ard_3-1-0_114078_2019-08-02_final
2019-08-02 11:46:41	ga_ls8c_ard_3-1-0_114079_2019-08-02_final
2019-08-02 11:47:05	ga_ls8c_ard_3-1-0_114080_2019-08-02_final
2019-08-02 11:47:29	ga_ls8c_ard_3-1-0_114081_2019-08-02_final
2019-08-04 11:36:20	ga_ls8c_ard_3-1-0_112084_2019-08-04_final
2019-08-04 11:36:44	ga_ls8c_ard_3-1-0_112085_2019-08-04_final
2019-08-09 11:50:31	ga_ls8c_ard_3-1-0_115073_2019-08-09_final
2019-08-09 11:50:54	ga_ls8c_ard_3-1-0_115074_2019-08-09_final
2019-08-09 11:51:18	ga_ls8c_ard_3-1-0_115075_2019-08-09_final
2019-08-09 11:51:42	ga_ls8c_ard_3-1-0_115076_2019-08-09_final
2019-08-09 11:52:06	ga_ls8c_ard_3-1-0_115077_2019-08-09_final
2019-08-09 11:52:30	ga_ls8c_ard_3-1-0_115078_2019-08-09_final
2019-08-11 11:41:21	ga_ls8c_ard_3-1-0_113081_2019-08-11_final
2019-08-11 11:41:45	ga_ls8c_ard_3-1-0_113082_2019-08-11_final
2019-08-11 11:42:09	ga_ls8c_ard_3-1-0_113083_2019-08-11_final
2019-08-11 11:42:33	ga_ls8c_ard_3-1-0_113084_2019-08-11_final
2019-09-10 11:50:39	ga_ls8c_ard_3-1-0_115073_2019-09-10_final
2019-09-10 11:51:03	ga_ls8c_ard_3-1-0_115074_2019-09-10_final
2019-09-10 11:51:27	ga_ls8c_ard_3-1-0_115075_2019-09-10_final
2019-09-10 11:51:51	ga_ls8c_ard_3-1-0_115076_2019-09-10_final
2019-09-10 11:52:15	ga_ls8c_ard_3-1-0_115077_2019-09-10_final
2019-09-10 11:52:39	ga_ls8c_ard_3-1-0_115078_2019-09-10_final
2019-09-12 11:41:30	ga_ls8c_ard_3-1-0_113081_2019-09-12_final
2019-09-12 11:41:54	ga_ls8c_ard_3-1-0_113082_2019-09-12_final
2019-09-12 11:42:18	ga_ls8c_ard_3-1-0_113083_2019-09-12_final
2019-09-12 11:42:42	ga_ls8c_ard_3-1-0_113084_2019-09-12_final
2022-01-05 11:51:03	ga_ls8c_ard_3-2-1_115074_2022-01-05_final
2022-01-05 11:51:27	ga_ls8c_ard_3-2-1_115075_2022-01-05_final
2022-01-05 11:51:51	ga_ls8c_ard_3-2-1_115076_2022-01-05_final
2022-01-05 11:52:15	ga_ls8c_ard_3-2-1_115077_2022-01-05_final
2022-01-05 11:52:39	ga_ls8c_ard_3-2-1_115078_2022-01-05_final
2022-01-07 11:41:29	ga_ls8c_ard_3-2-1_113081_2022-01-07_final
2022-01-07 11:41:53	ga_ls8c_ard_3-2-1_113082_2022-01-07_final
2022-01-07 11:42:17	ga_ls8c_ard_3-2-1_113083_2022-01-07_final
2022-01-07 11:42:41	ga_ls8c_ard_3-2-1_113084_2022-01-07_final
2022-01-21 11:51:00	ga_ls8c_ard_3-2-1_115074_2022-01-21_final
2022-01-21 11:51:24	ga_ls8c_ard_3-2-1_115075_2022-01-21_final
2022-01-21 11:51:48	ga_ls8c_ard_3-2-1_115076_2022-01-21_final
2022-01-21 11:52:12	ga_ls8c_ard_3-2-1_115077_2022-01-21_final
2022-01-21 11:52:35	ga_ls8c_ard_3-2-1_115078_2022-01-21_final
2022-01-23 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-01-23_final
2022-01-23 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-01-23_final
2022-01-23 11:42:13	ga_ls8c_ard_3-2-1_113083_2022-01-23_final
2022-01-23 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-01-23_final
2022-01-30 11:45:58	ga_ls8c_ard_3-2-1_114077_2022-01-30_final
2022-01-30 11:46:22	ga_ls8c_ard_3-2-1_114078_2022-01-30_final
2022-01-30 11:46:46	ga_ls8c_ard_3-2-1_114079_2022-01-30_final
2022-01-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2022-01-30_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