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
2018-02-08 11:22:57	ga_ls8c_ard_3-0-0_110082_2018-02-08_final
2018-08-19 11:22:34	ga_ls8c_ard_3-0-0_110082_2018-08-19_final
2018-11-07 11:23:02	ga_ls8c_ard_3-0-0_110082_2018-11-07_final
2019-04-16 11:22:33	ga_ls8c_ard_3-1-0_110082_2019-04-16_final
2019-06-19 11:22:57	ga_ls8c_ard_3-1-0_110082_2019-06-19_final
2019-08-22 11:23:16	ga_ls8c_ard_3-1-0_110082_2019-08-22_final
2019-12-28 11:23:20	ga_ls8c_ard_3-1-0_110082_2019-12-28_final
2020-01-13 11:23:17	ga_ls8c_ard_3-1-0_110082_2020-01-13_final
2020-01-29 11:23:12	ga_ls8c_ard_3-1-0_110082_2020-01-29_final
2020-02-14 11:23:08	ga_ls8c_ard_3-1-0_110082_2020-02-14_final
2020-03-01 11:23:03	ga_ls8c_ard_3-1-0_110082_2020-03-01_final
2020-03-17 11:22:56	ga_ls8c_ard_3-1-0_110082_2020-03-17_final
2020-04-02 11:22:47	ga_ls8c_ard_3-1-0_110082_2020-04-02_final
2020-04-18 11:22:40	ga_ls8c_ard_3-1-0_110082_2020-04-18_final
2020-05-04 11:22:32	ga_ls8c_ard_3-1-0_110082_2020-05-04_final
2020-05-20 11:22:32	ga_ls8c_ard_3-1-0_110082_2020-05-20_final
2020-06-05 11:22:38	ga_ls8c_ard_3-1-0_110082_2020-06-05_final
2020-06-21 11:22:48	ga_ls8c_ard_3-1-0_110082_2020-06-21_final
2020-07-07 11:22:55	ga_ls8c_ard_3-1-0_110082_2020-07-07_final
2020-07-23 11:23:01	ga_ls8c_ard_3-1-0_110082_2020-07-23_final
2020-08-08 11:23:04	ga_ls8c_ard_3-1-0_110082_2020-08-08_final
2020-08-24 11:23:11	ga_ls8c_ard_3-1-0_110082_2020-08-24_final
2020-09-09 11:23:18	ga_ls8c_ard_3-1-0_110082_2020-09-09_final
2020-09-25 11:23:23	ga_ls8c_ard_3-1-0_110082_2020-09-25_final
2020-10-11 11:23:26	ga_ls8c_ard_3-1-0_110082_2020-10-11_final
2020-10-27 11:23:26	ga_ls8c_ard_3-1-0_110082_2020-10-27_final
2020-11-12 11:23:22	ga_ls8c_ard_3-1-0_110082_2020-11-12_final
2020-11-28 11:23:26	ga_ls8c_ard_3-1-0_110082_2020-11-28_final
2020-12-14 11:23:27	ga_ls8c_ard_3-1-0_110082_2020-12-14_final
2021-03-04 11:23:03	ga_ls8c_ard_3-2-0_110082_2021-03-04_final
2021-03-20 11:22:55	ga_ls8c_ard_3-2-0_110082_2021-03-20_final
2021-04-05 11:22:51	ga_ls8c_ard_3-2-0_110082_2021-04-05_final
2021-04-21 11:22:44	ga_ls8c_ard_3-2-0_110082_2021-04-21_final
2021-05-07 11:22:35	ga_ls8c_ard_3-2-0_110082_2021-05-07_final
2021-05-23 11:22:46	ga_ls8c_ard_3-2-0_110082_2021-05-23_final
2021-06-08 11:22:53	ga_ls8c_ard_3-2-0_110082_2021-06-08_final
2021-06-24 11:22:58	ga_ls8c_ard_3-2-0_110082_2021-06-24_final
2021-07-10 11:23:00	ga_ls8c_ard_3-2-0_110082_2021-07-10_final
2021-07-26 11:23:06	ga_ls8c_ard_3-2-0_110082_2021-07-26_final
2021-08-11 11:23:13	ga_ls8c_ard_3-2-0_110082_2021-08-11_final
2021-08-27 11:23:18	ga_ls8c_ard_3-2-0_110082_2021-08-27_final
2021-09-12 11:23:22	ga_ls8c_ard_3-2-0_110082_2021-09-12_final
2021-09-28 11:23:26	ga_ls8c_ard_3-2-0_110082_2021-09-28_final
2021-10-14 11:23:31	ga_ls8c_ard_3-2-0_110082_2021-10-14_final
2021-10-30 11:23:32	ga_ls8c_ard_3-2-0_110082_2021-10-30_final
2021-11-15 11:23:27	ga_ls8c_ard_3-2-0_110082_2021-11-15_final
2021-12-01 11:23:28	ga_ls8c_ard_3-2-0_110082_2021-12-01_final
2021-12-17 11:23:26	ga_ls8c_ard_3-2-1_110082_2021-12-17_final
2022-01-02 11:23:21	ga_ls8c_ard_3-2-1_110082_2022-01-02_final
2022-01-18 11:23:18	ga_ls8c_ard_3-2-1_110082_2022-01-18_final
2022-02-03 11:23:14	ga_ls8c_ard_3-2-1_110082_2022-02-03_final
2022-02-19 11:23:08	ga_ls8c_ard_3-2-1_110082_2022-02-19_final
2022-03-07 11:23:06	ga_ls8c_ard_3-2-1_110082_2022-03-07_final
2022-03-23 11:22:56	ga_ls8c_ard_3-2-1_110082_2022-03-23_final
2022-04-08 11:22:53	ga_ls8c_ard_3-2-1_110082_2022-04-08_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-05-10 11:22:59	ga_ls8c_ard_3-2-1_110082_2022-05-10_final
2022-05-26 11:23:02	ga_ls8c_ard_3-2-1_110082_2022-05-26_final
2022-06-11 11:23:14	ga_ls8c_ard_3-2-1_110082_2022-06-11_final
2022-06-27 11:23:20	ga_ls8c_ard_3-2-1_110082_2022-06-27_final
2022-07-13 11:23:19	ga_ls8c_ard_3-2-1_110082_2022-07-13_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-08-14 11:23:37	ga_ls8c_ard_3-2-1_110082_2022-08-14_final
2022-08-30 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-08-30_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-09-15_final
2022-10-01 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-10-01_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-11-02 11:23:45	ga_ls8c_ard_3-2-1_110082_2022-11-02_final
2022-11-18 11:23:36	ga_ls8c_ard_3-2-1_110082_2022-11-18_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2023-01-05 11:23:31	ga_ls8c_ard_3-2-1_110082_2023-01-05_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-02-06 11:23:28	ga_ls8c_ard_3-2-1_110082_2023-02-06_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-03-26 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-03-26_final
2023-04-11 11:22:40	ga_ls8c_ard_3-2-1_110082_2023-04-11_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-05-13 11:22:23	ga_ls8c_ard_3-2-1_110082_2023-05-13_final
2023-05-29 11:22:25	ga_ls8c_ard_3-2-1_110082_2023-05-29_final
2023-06-14 11:22:33	ga_ls8c_ard_3-2-1_110082_2023-06-14_final
2023-06-30 11:22:41	ga_ls8c_ard_3-2-1_110082_2023-06-30_final
2023-07-16 11:22:48	ga_ls8c_ard_3-2-1_110082_2023-07-16_final
2023-08-01 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-08-01_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-09-02 11:23:05	ga_ls8c_ard_3-2-1_110082_2023-09-02_final
2023-09-18 11:23:10	ga_ls8c_ard_3-2-1_110082_2023-09-18_final
2023-10-04 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-10-04_final
2023-10-20 11:23:14	ga_ls8c_ard_3-2-1_110082_2023-10-20_final
2023-11-05 11:23:18	ga_ls8c_ard_3-2-1_110082_2023-11-05_final
2023-11-21 11:23:20	ga_ls8c_ard_3-2-1_110082_2023-11-21_final
2023-12-07 11:23:11	ga_ls8c_ard_3-2-1_110082_2023-12-07_final
2023-12-23 11:23:19	ga_ls8c_ard_3-2-1_110082_2023-12-23_final
2024-01-08 11:23:12	ga_ls8c_ard_3-2-1_110082_2024-01-08_final
2024-01-24 11:23:08	ga_ls8c_ard_3-2-1_110082_2024-01-24_final
2024-02-09 11:23:12	ga_ls8c_ard_3-2-1_110082_2024-02-09_final
2024-02-25 11:23:08	ga_ls8c_ard_3-2-1_110082_2024-02-25_final
2024-03-12 11:22:57	ga_ls8c_ard_3-2-1_110082_2024-03-12_nrt
2024-03-28 11:22:41	ga_ls8c_ard_3-2-1_110082_2024-03-28_nrt

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