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
2019-08-03 10:46:17	ga_ls8c_ard_3-1-0_105067_2019-08-03_final
2019-08-19 10:46:22	ga_ls8c_ard_3-1-0_105067_2019-08-19_final
2019-09-20 10:46:31	ga_ls8c_ard_3-1-0_105067_2019-09-20_final
2019-10-06 10:46:35	ga_ls8c_ard_3-1-0_105067_2019-10-06_final
2019-10-22 10:46:36	ga_ls8c_ard_3-1-0_105067_2019-10-22_final
2019-11-07 10:46:35	ga_ls8c_ard_3-1-0_105067_2019-11-07_final
2019-11-23 10:46:32	ga_ls8c_ard_3-1-0_105067_2019-11-23_final
2019-12-09 10:46:31	ga_ls8c_ard_3-1-0_105067_2019-12-09_final
2019-12-25 10:46:28	ga_ls8c_ard_3-1-0_105067_2019-12-25_final
2020-01-26 10:46:20	ga_ls8c_ard_3-1-0_105067_2020-01-26_final
2020-02-11 10:46:15	ga_ls8c_ard_3-1-0_105067_2020-02-11_final
2020-02-27 10:46:11	ga_ls8c_ard_3-1-0_105067_2020-02-27_final
2020-03-14 10:46:05	ga_ls8c_ard_3-1-0_105067_2020-03-14_final
2020-04-15 10:45:49	ga_ls8c_ard_3-1-0_105067_2020-04-15_final
2020-05-01 10:45:41	ga_ls8c_ard_3-1-0_105067_2020-05-01_final
2020-06-18 10:45:53	ga_ls8c_ard_3-1-0_105067_2020-06-18_final
2020-07-04 10:46:01	ga_ls8c_ard_3-1-0_105067_2020-07-04_final
2020-07-20 10:46:06	ga_ls8c_ard_3-1-0_105067_2020-07-20_final
2020-08-05 10:46:10	ga_ls8c_ard_3-1-0_105067_2020-08-05_final
2020-08-21 10:46:17	ga_ls8c_ard_3-1-0_105067_2020-08-21_final
2020-09-06 10:46:24	ga_ls8c_ard_3-1-0_105067_2020-09-06_final
2020-09-22 10:46:29	ga_ls8c_ard_3-1-0_105067_2020-09-22_final
2020-10-08 10:46:32	ga_ls8c_ard_3-1-0_105067_2020-10-08_final
2020-10-24 10:46:33	ga_ls8c_ard_3-1-0_105067_2020-10-24_final
2020-11-25 10:46:33	ga_ls8c_ard_3-1-0_105067_2020-11-25_final
2020-12-11 10:46:34	ga_ls8c_ard_3-1-0_105067_2020-12-11_final
2020-12-27 10:46:31	ga_ls8c_ard_3-2-0_105067_2020-12-27_final
2021-01-12 10:46:25	ga_ls8c_ard_3-2-0_105067_2021-01-12_final
2021-01-28 10:46:21	ga_ls8c_ard_3-2-0_105067_2021-01-28_final
2021-02-13 10:46:18	ga_ls8c_ard_3-2-0_105067_2021-02-13_final
2021-03-01 10:46:12	ga_ls8c_ard_3-2-0_105067_2021-03-01_final
2021-03-17 10:46:02	ga_ls8c_ard_3-2-0_105067_2021-03-17_final
2021-04-02 10:45:59	ga_ls8c_ard_3-2-0_105067_2021-04-02_final
2021-04-18 10:45:53	ga_ls8c_ard_3-2-0_105067_2021-04-18_final
2021-05-04 10:45:43	ga_ls8c_ard_3-2-0_105067_2021-05-04_final
2021-05-20 10:45:51	ga_ls8c_ard_3-2-0_105067_2021-05-20_final
2021-06-05 10:45:59	ga_ls8c_ard_3-2-0_105067_2021-06-05_final
2021-06-21 10:46:04	ga_ls8c_ard_3-2-0_105067_2021-06-21_final
2021-07-07 10:46:07	ga_ls8c_ard_3-2-0_105067_2021-07-07_final
2021-07-23 10:46:11	ga_ls8c_ard_3-2-0_105067_2021-07-23_final
2021-08-08 10:46:19	ga_ls8c_ard_3-2-0_105067_2021-08-08_final
2021-08-24 10:46:24	ga_ls8c_ard_3-2-0_105067_2021-08-24_final
2021-09-09 10:46:29	ga_ls8c_ard_3-2-0_105067_2021-09-09_final
2021-09-25 10:46:31	ga_ls8c_ard_3-2-0_105067_2021-09-25_final
2021-10-11 10:46:37	ga_ls8c_ard_3-2-0_105067_2021-10-11_final
2021-10-27 10:46:39	ga_ls8c_ard_3-2-0_105067_2021-10-27_final
2021-11-12 10:46:35	ga_ls8c_ard_3-2-0_105067_2021-11-12_final
2021-11-28 10:46:34	ga_ls8c_ard_3-2-0_105067_2021-11-28_final
2021-12-14 10:46:33	ga_ls8c_ard_3-2-1_105067_2021-12-14_final
2021-12-30 10:46:28	ga_ls8c_ard_3-2-1_105067_2021-12-30_final
2022-01-15 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-01-15_final
2022-01-31 10:46:21	ga_ls8c_ard_3-2-1_105067_2022-01-31_final
2022-02-16 10:46:17	ga_ls8c_ard_3-2-1_105067_2022-02-16_final
2022-03-04 10:46:13	ga_ls8c_ard_3-2-1_105067_2022-03-04_final
2022-03-20 10:46:05	ga_ls8c_ard_3-2-1_105067_2022-03-20_final
2022-04-05 10:45:58	ga_ls8c_ard_3-2-1_105067_2022-04-05_final
2022-04-21 10:46:02	ga_ls8c_ard_3-2-1_105067_2022-04-21_final
2022-05-07 10:46:04	ga_ls8c_ard_3-2-1_105067_2022-05-07_final
2022-05-23 10:46:09	ga_ls8c_ard_3-2-1_105067_2022-05-23_final
2022-06-08 10:46:18	ga_ls8c_ard_3-2-1_105067_2022-06-08_final
2022-06-24 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-06-24_final
2022-07-10 10:46:27	ga_ls8c_ard_3-2-1_105067_2022-07-10_final
2022-07-26 10:46:34	ga_ls8c_ard_3-2-1_105067_2022-07-26_final
2022-08-11 10:46:43	ga_ls8c_ard_3-2-1_105067_2022-08-11_final
2022-08-27 10:46:45	ga_ls8c_ard_3-2-1_105067_2022-08-27_final
2022-09-12 10:46:49	ga_ls8c_ard_3-2-1_105067_2022-09-12_final
2022-09-28 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-09-28_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-17 10:46:40	ga_ls8c_ard_3-2-1_105067_2022-12-17_final
2023-01-02 10:46:38	ga_ls8c_ard_3-2-1_105067_2023-01-02_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-02-03 10:46:36	ga_ls8c_ard_3-2-1_105067_2023-02-03_final
2023-02-19 10:46:24	ga_ls8c_ard_3-2-1_105067_2023-02-19_final
2023-03-07 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-03-07_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-04-08 10:45:51	ga_ls8c_ard_3-2-1_105067_2023-04-08_final
2023-04-24 10:45:44	ga_ls8c_ard_3-2-1_105067_2023-04-24_final
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-26 10:45:31	ga_ls8c_ard_3-2-1_105067_2023-05-26_final
2023-06-11 10:45:38	ga_ls8c_ard_3-2-1_105067_2023-06-11_final
2023-06-27 10:45:45	ga_ls8c_ard_3-2-1_105067_2023-06-27_final
2023-07-13 10:45:55	ga_ls8c_ard_3-2-1_105067_2023-07-13_final
2023-07-29 10:46:02	ga_ls8c_ard_3-2-1_105067_2023-07-29_final
2023-08-14 10:46:07	ga_ls8c_ard_3-2-1_105067_2023-08-14_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-09-15 10:46:16	ga_ls8c_ard_3-2-1_105067_2023-09-15_final
2023-10-01 10:46:20	ga_ls8c_ard_3-2-1_105067_2023-10-01_final
2023-10-17 10:46:22	ga_ls8c_ard_3-2-1_105067_2023-10-17_final
2023-11-02 10:46:25	ga_ls8c_ard_3-2-1_105067_2023-11-02_final
2023-11-18 10:46:26	ga_ls8c_ard_3-2-1_105067_2023-11-18_final
2023-12-04 10:46:21	ga_ls8c_ard_3-2-1_105067_2023-12-04_final
2023-12-20 10:46:26	ga_ls8c_ard_3-2-1_105067_2023-12-20_final
2024-01-05 10:46:17	ga_ls8c_ard_3-2-1_105067_2024-01-05_final
2024-01-21 10:46:18	ga_ls8c_ard_3-2-1_105067_2024-01-21_final
2024-01-21 10:46:18	ga_ls8c_ard_3-2-1_105067_2024-01-21_nrt
2024-02-06 10:46:19	ga_ls8c_ard_3-2-1_105067_2024-02-06_final
2024-02-22 10:46:16	ga_ls8c_ard_3-2-1_105067_2024-02-22_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