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
2018-08-29 10:20:02	ga_ls8c_ard_3-0-0_100080_2018-08-29_final
2018-11-17 10:20:26	ga_ls8c_ard_3-0-0_100080_2018-11-17_final
2019-01-20 10:20:19	ga_ls8c_ard_3-0-0_100080_2019-01-20_final
2019-02-21 10:20:13	ga_ls8c_ard_3-0-0_100080_2019-02-21_final
2019-03-09 10:20:08	ga_ls8c_ard_3-1-0_100080_2019-03-09_final
2019-04-10 10:20:00	ga_ls8c_ard_3-1-0_100080_2019-04-10_final
2019-04-26 10:19:53	ga_ls8c_ard_3-0-0_100080_2019-04-26_final
2019-05-12 10:20:02	ga_ls8c_ard_3-0-0_100080_2019-05-12_final
2019-05-28 10:20:11	ga_ls8c_ard_3-0-0_100080_2019-05-28_final
2019-06-13 10:20:18	ga_ls8c_ard_3-1-0_100080_2019-06-13_final
2019-06-29 10:20:23	ga_ls8c_ard_3-1-0_100080_2019-06-29_final
2019-07-31 10:20:32	ga_ls8c_ard_3-1-0_100080_2019-07-31_final
2019-08-16 10:20:38	ga_ls8c_ard_3-1-0_100080_2019-08-16_final
2019-09-17 10:20:47	ga_ls8c_ard_3-1-0_100080_2019-09-17_final
2020-01-07 10:20:42	ga_ls8c_ard_3-1-0_100080_2020-01-07_final
2020-02-08 10:20:33	ga_ls8c_ard_3-1-0_100080_2020-02-08_final
2020-03-11 10:20:23	ga_ls8c_ard_3-1-0_100080_2020-03-11_final
2020-04-12 10:20:07	ga_ls8c_ard_3-1-0_100080_2020-04-12_final
2020-07-17 10:20:23	ga_ls8c_ard_3-1-0_100080_2020-07-17_final
2020-08-02 10:20:27	ga_ls8c_ard_3-1-0_100080_2020-08-02_final
2020-08-18 10:20:32	ga_ls8c_ard_3-1-0_100080_2020-08-18_final
2020-09-03 10:20:40	ga_ls8c_ard_3-1-0_100080_2020-09-03_final
2020-09-19 10:20:46	ga_ls8c_ard_3-1-0_100080_2020-09-19_final
2020-10-05 10:20:49	ga_ls8c_ard_3-1-0_100080_2020-10-05_final
2020-10-21 10:20:50	ga_ls8c_ard_3-1-0_100080_2020-10-21_final
2020-12-08 10:20:51	ga_ls8c_ard_3-1-0_100080_2020-12-08_final
2021-01-09 10:20:43	ga_ls8c_ard_3-2-0_100080_2021-01-09_final
2021-01-25 10:20:38	ga_ls8c_ard_3-2-0_100080_2021-01-25_final
2021-02-26 10:20:30	ga_ls8c_ard_3-2-0_100080_2021-02-26_final
2021-03-14 10:20:22	ga_ls8c_ard_3-2-0_100080_2021-03-14_final
2021-03-30 10:20:17	ga_ls8c_ard_3-2-0_100080_2021-03-30_final
2021-04-15 10:20:11	ga_ls8c_ard_3-2-0_100080_2021-04-15_final
2021-05-01 10:20:02	ga_ls8c_ard_3-2-0_100080_2021-05-01_final
2021-05-17 10:20:06	ga_ls8c_ard_3-2-0_100080_2021-05-17_final
2021-06-02 10:20:15	ga_ls8c_ard_3-2-0_100080_2021-06-02_final
2021-06-18 10:20:21	ga_ls8c_ard_3-2-0_100080_2021-06-18_final
2021-07-04 10:20:24	ga_ls8c_ard_3-2-0_100080_2021-07-04_final
2021-07-20 10:20:27	ga_ls8c_ard_3-2-0_100080_2021-07-20_final
2021-08-05 10:20:35	ga_ls8c_ard_3-2-0_100080_2021-08-05_final
2021-08-21 10:20:40	ga_ls8c_ard_3-2-0_100080_2021-08-21_final
2021-09-06 10:20:45	ga_ls8c_ard_3-2-0_100080_2021-09-06_final
2021-09-22 10:20:48	ga_ls8c_ard_3-2-0_100080_2021-09-22_final
2021-10-08 10:20:54	ga_ls8c_ard_3-2-0_100080_2021-10-08_final
2021-10-24 10:20:56	ga_ls8c_ard_3-2-0_100080_2021-10-24_final
2021-11-09 10:20:53	ga_ls8c_ard_3-2-0_100080_2021-11-09_final
2021-11-25 10:20:51	ga_ls8c_ard_3-2-0_100080_2021-11-25_final
2021-12-11 10:20:51	ga_ls8c_ard_3-2-1_100080_2021-12-11_final
2021-12-27 10:20:46	ga_ls8c_ard_3-2-1_100080_2021-12-27_final
2022-01-12 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-01-12_final
2022-01-28 10:20:38	ga_ls8c_ard_3-2-1_100080_2022-01-28_final
2022-02-13 10:20:35	ga_ls8c_ard_3-2-1_100080_2022-02-13_final
2022-03-01 10:20:31	ga_ls8c_ard_3-2-1_100080_2022-03-01_final
2022-03-17 10:20:25	ga_ls8c_ard_3-2-1_100080_2022-03-17_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-05-04 10:20:19	ga_ls8c_ard_3-2-1_100080_2022-05-04_final
2022-05-20 10:20:26	ga_ls8c_ard_3-2-1_100080_2022-05-20_final
2022-06-05 10:20:33	ga_ls8c_ard_3-2-1_100080_2022-06-05_final
2022-06-21 10:20:43	ga_ls8c_ard_3-2-1_100080_2022-06-21_final
2022-07-07 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-07-07_final
2022-07-23 10:20:49	ga_ls8c_ard_3-2-1_100080_2022-07-23_final
2022-08-08 10:20:59	ga_ls8c_ard_3-2-1_100080_2022-08-08_final
2022-08-24 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-08-24_final
2022-09-09 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-09-09_final
2022-09-25 10:21:09	ga_ls8c_ard_3-2-1_100080_2022-09-25_final
2022-10-11 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-10-11_final
2022-10-27 10:21:07	ga_ls8c_ard_3-2-1_100080_2022-10-27_final
2022-11-12 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-11-12_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-30 10:20:55	ga_ls8c_ard_3-2-1_100080_2022-12-30_final
2023-01-15 10:20:49	ga_ls8c_ard_3-2-1_100080_2023-01-15_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-16 10:20:45	ga_ls8c_ard_3-2-1_100080_2023-02-16_final
2023-03-04 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-03-04_final
2023-03-20 10:20:24	ga_ls8c_ard_3-2-1_100080_2023-03-20_final
2023-04-05 10:20:12	ga_ls8c_ard_3-2-1_100080_2023-04-05_final
2023-04-21 10:20:00	ga_ls8c_ard_3-2-1_100080_2023-04-21_final
2023-05-07 10:19:53	ga_ls8c_ard_3-2-1_100080_2023-05-07_final
2023-05-23 10:19:48	ga_ls8c_ard_3-2-1_100080_2023-05-23_final
2023-06-08 10:19:54	ga_ls8c_ard_3-2-1_100080_2023-06-08_final
2023-06-24 10:19:59	ga_ls8c_ard_3-2-1_100080_2023-06-24_final
2023-07-10 10:20:11	ga_ls8c_ard_3-2-1_100080_2023-07-10_final
2023-07-26 10:20:17	ga_ls8c_ard_3-2-1_100080_2023-07-26_final
2023-08-11 10:20:21	ga_ls8c_ard_3-2-1_100080_2023-08-11_final
2023-08-27 10:20:30	ga_ls8c_ard_3-2-1_100080_2023-08-27_final
2023-09-12 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-09-12_final
2023-09-28 10:20:37	ga_ls8c_ard_3-2-1_100080_2023-09-28_final
2023-10-14 10:20:40	ga_ls8c_ard_3-2-1_100080_2023-10-14_final
2023-10-30 10:20:43	ga_ls8c_ard_3-2-1_100080_2023-10-30_final
2023-11-15 10:20:41	ga_ls8c_ard_3-2-1_100080_2023-11-15_final
2023-12-01 10:20:42	ga_ls8c_ard_3-2-1_100080_2023-12-01_final
2023-12-17 10:20:42	ga_ls8c_ard_3-2-1_100080_2023-12-17_final
2024-01-02 10:20:37	ga_ls8c_ard_3-2-1_100080_2024-01-02_final
2024-01-18 10:20:37	ga_ls8c_ard_3-2-1_100080_2024-01-18_final
2024-02-03 10:20:35	ga_ls8c_ard_3-2-1_100080_2024-02-03_final
2024-02-19 10:20:34	ga_ls8c_ard_3-2-1_100080_2024-02-19_final
2024-03-06 10:20:23	ga_ls8c_ard_3-2-1_100080_2024-03-06_final
2024-03-22 10:20:14	ga_ls8c_ard_3-2-1_100080_2024-03-22_final
2024-04-07 10:20:06	ga_ls8c_ard_3-2-1_100080_2024-04-07_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years