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
2018-10-20 11:33:44	ga_ls8c_ard_3-0-0_112078_2018-10-20_final
2018-11-05 11:33:47	ga_ls8c_ard_3-0-0_112078_2018-11-05_final
2018-11-21 11:33:48	ga_ls8c_ard_3-0-0_112078_2018-11-21_final
2018-12-07 11:33:45	ga_ls8c_ard_3-0-0_112078_2018-12-07_final
2019-01-08 11:33:43	ga_ls8c_ard_3-0-0_112078_2019-01-08_final
2019-02-25 11:33:34	ga_ls8c_ard_3-0-0_112078_2019-02-25_final
2019-03-29 11:33:25	ga_ls8c_ard_3-1-0_112078_2019-03-29_final
2019-04-30 11:33:17	ga_ls8c_ard_3-0-0_112078_2019-04-30_final
2019-05-16 11:33:27	ga_ls8c_ard_3-0-0_112078_2019-05-16_final
2019-06-01 11:33:35	ga_ls8c_ard_3-0-0_112078_2019-06-01_final
2019-07-03 11:33:46	ga_ls8c_ard_3-1-0_112078_2019-07-03_final
2019-07-19 11:33:49	ga_ls8c_ard_3-1-0_112078_2019-07-19_final
2019-11-08 11:34:14	ga_ls8c_ard_3-1-0_112078_2019-11-08_final
2019-11-24 11:34:11	ga_ls8c_ard_3-1-0_112078_2019-11-24_final
2019-12-10 11:34:10	ga_ls8c_ard_3-1-0_112078_2019-12-10_final
2019-12-26 11:34:07	ga_ls8c_ard_3-1-0_112078_2019-12-26_final
2020-01-27 11:33:59	ga_ls8c_ard_3-1-0_112078_2020-01-27_final
2020-03-15 11:33:43	ga_ls8c_ard_3-1-0_112078_2020-03-15_final
2020-03-31 11:33:34	ga_ls8c_ard_3-1-0_112078_2020-03-31_final
2020-04-16 11:33:27	ga_ls8c_ard_3-1-0_112078_2020-04-16_final
2020-05-02 11:33:19	ga_ls8c_ard_3-1-0_112078_2020-05-02_final
2020-05-18 11:33:17	ga_ls8c_ard_3-1-0_112078_2020-05-18_final
2020-06-19 11:33:33	ga_ls8c_ard_3-1-0_112078_2020-06-19_final
2020-07-21 11:33:46	ga_ls8c_ard_3-1-0_112078_2020-07-21_final
2020-08-06 11:33:49	ga_ls8c_ard_3-1-0_112078_2020-08-06_final
2020-08-22 11:33:56	ga_ls8c_ard_3-1-0_112078_2020-08-22_final
2020-10-09 11:34:11	ga_ls8c_ard_3-1-0_112078_2020-10-09_final
2020-10-25 11:34:12	ga_ls8c_ard_3-1-0_112078_2020-10-25_final
2020-11-10 11:34:09	ga_ls8c_ard_3-1-0_112078_2020-11-10_final
2020-11-26 11:34:12	ga_ls8c_ard_3-1-0_112078_2020-11-26_final
2020-12-12 11:34:13	ga_ls8c_ard_3-1-0_112078_2020-12-12_final
2021-03-18 11:33:41	ga_ls8c_ard_3-2-0_112078_2021-03-18_final
2021-04-03 11:33:38	ga_ls8c_ard_3-2-0_112078_2021-04-03_final
2021-04-19 11:33:31	ga_ls8c_ard_3-2-0_112078_2021-04-19_final
2021-05-05 11:33:22	ga_ls8c_ard_3-2-0_112078_2021-05-05_final
2021-05-21 11:33:31	ga_ls8c_ard_3-2-0_112078_2021-05-21_final
2021-06-06 11:33:39	ga_ls8c_ard_3-2-0_112078_2021-06-06_final
2021-06-22 11:33:44	ga_ls8c_ard_3-2-0_112078_2021-06-22_final
2021-07-08 11:33:46	ga_ls8c_ard_3-2-0_112078_2021-07-08_final
2021-07-24 11:33:51	ga_ls8c_ard_3-2-0_112078_2021-07-24_final
2021-08-09 11:33:58	ga_ls8c_ard_3-2-0_112078_2021-08-09_final
2021-08-25 11:34:03	ga_ls8c_ard_3-2-0_112078_2021-08-25_final
2021-09-10 11:34:08	ga_ls8c_ard_3-2-0_112078_2021-09-10_final
2021-09-26 11:34:11	ga_ls8c_ard_3-2-0_112078_2021-09-26_final
2021-10-12 11:34:16	ga_ls8c_ard_3-2-0_112078_2021-10-12_final
2021-10-28 11:34:18	ga_ls8c_ard_3-2-0_112078_2021-10-28_final
2021-11-13 11:34:14	ga_ls8c_ard_3-2-0_112078_2021-11-13_final
2021-11-29 11:34:13	ga_ls8c_ard_3-2-0_112078_2021-11-29_final
2021-12-15 11:34:12	ga_ls8c_ard_3-2-1_112078_2021-12-15_final
2021-12-31 11:34:06	ga_ls8c_ard_3-2-1_112078_2021-12-31_final
2022-01-16 11:34:05	ga_ls8c_ard_3-2-1_112078_2022-01-16_final
2022-02-01 11:34:00	ga_ls8c_ard_3-2-1_112078_2022-02-01_final
2022-02-17 11:33:55	ga_ls8c_ard_3-2-1_112078_2022-02-17_final
2022-03-05 11:33:52	ga_ls8c_ard_3-2-1_112078_2022-03-05_final
2022-03-21 11:33:44	ga_ls8c_ard_3-2-1_112078_2022-03-21_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-22 11:33:40	ga_ls8c_ard_3-2-1_112078_2022-04-22_final
2022-05-08 11:33:44	ga_ls8c_ard_3-2-1_112078_2022-05-08_final
2022-05-24 11:33:48	ga_ls8c_ard_3-2-1_112078_2022-05-24_final
2022-06-09 11:33:58	ga_ls8c_ard_3-2-1_112078_2022-06-09_final
2022-06-25 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-06-25_final
2022-07-11 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-07-11_final
2022-07-27 11:34:14	ga_ls8c_ard_3-2-1_112078_2022-07-27_final
2022-08-12 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-08-12_final
2022-08-28 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-08-28_final
2022-09-13 11:34:29	ga_ls8c_ard_3-2-1_112078_2022-09-13_final
2022-09-29 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-09-29_final
2022-10-15 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-10-15_final
2022-10-31 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-10-31_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-12-02 11:34:25	ga_ls8c_ard_3-2-1_112078_2022-12-02_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2023-01-03 11:34:17	ga_ls8c_ard_3-2-1_112078_2023-01-03_final
2023-01-19 11:34:09	ga_ls8c_ard_3-2-1_112078_2023-01-19_final
2023-02-04 11:34:14	ga_ls8c_ard_3-2-1_112078_2023-02-04_final
2023-02-20 11:34:02	ga_ls8c_ard_3-2-1_112078_2023-02-20_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-24 11:33:42	ga_ls8c_ard_3-2-1_112078_2023-03-24_final
2023-04-09 11:33:28	ga_ls8c_ard_3-2-1_112078_2023-04-09_final
2023-04-25 11:33:23	ga_ls8c_ard_3-2-1_112078_2023-04-25_final
2023-05-11 11:33:11	ga_ls8c_ard_3-2-1_112078_2023-05-11_final
2023-05-27 11:33:10	ga_ls8c_ard_3-2-1_112078_2023-05-27_final
2023-06-12 11:33:18	ga_ls8c_ard_3-2-1_112078_2023-06-12_final
2023-06-28 11:33:26	ga_ls8c_ard_3-2-1_112078_2023-06-28_final
2023-07-14 11:33:34	ga_ls8c_ard_3-2-1_112078_2023-07-14_final
2023-07-30 11:33:41	ga_ls8c_ard_3-2-1_112078_2023-07-30_final
2023-08-15 11:33:47	ga_ls8c_ard_3-2-1_112078_2023-08-15_final
2023-08-31 11:33:52	ga_ls8c_ard_3-2-1_112078_2023-08-31_final
2023-09-16 11:33:55	ga_ls8c_ard_3-2-1_112078_2023-09-16_final
2023-10-02 11:33:59	ga_ls8c_ard_3-2-1_112078_2023-10-02_final
2023-11-03 11:34:04	ga_ls8c_ard_3-2-1_112078_2023-11-03_final
2023-11-19 11:34:05	ga_ls8c_ard_3-2-1_112078_2023-11-19_final
2023-12-05 11:33:59	ga_ls8c_ard_3-2-1_112078_2023-12-05_final
2023-12-21 11:34:05	ga_ls8c_ard_3-2-1_112078_2023-12-21_final
2024-01-06 11:33:56	ga_ls8c_ard_3-2-1_112078_2024-01-06_final
2024-01-22 11:33:56	ga_ls8c_ard_3-2-1_112078_2024-01-22_final
2024-02-07 11:33:58	ga_ls8c_ard_3-2-1_112078_2024-02-07_final
2024-02-23 11:33:55	ga_ls8c_ard_3-2-1_112078_2024-02-23_final
2024-03-10 11:33:43	ga_ls8c_ard_3-2-1_112078_2024-03-10_final
2024-03-26 11:33:30	ga_ls8c_ard_3-2-1_112078_2024-03-26_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