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
2019-08-22 11:18:04	ga_ls8c_ard_3-1-0_110069_2019-08-22_final
2019-09-23 11:18:14	ga_ls8c_ard_3-1-0_110069_2019-09-23_final
2019-10-09 11:18:17	ga_ls8c_ard_3-1-0_110069_2019-10-09_final
2019-10-25 11:18:18	ga_ls8c_ard_3-1-0_110069_2019-10-25_final
2019-11-10 11:18:17	ga_ls8c_ard_3-1-0_110069_2019-11-10_final
2019-12-12 11:18:13	ga_ls8c_ard_3-1-0_110069_2019-12-12_final
2019-12-28 11:18:09	ga_ls8c_ard_3-1-0_110069_2019-12-28_final
2020-02-14 11:17:57	ga_ls8c_ard_3-1-0_110069_2020-02-14_final
2020-03-01 11:17:52	ga_ls8c_ard_3-1-0_110069_2020-03-01_final
2020-03-17 11:17:45	ga_ls8c_ard_3-1-0_110069_2020-03-17_final
2020-04-02 11:17:36	ga_ls8c_ard_3-1-0_110069_2020-04-02_final
2020-05-04 11:17:21	ga_ls8c_ard_3-1-0_110069_2020-05-04_final
2020-05-20 11:17:21	ga_ls8c_ard_3-1-0_110069_2020-05-20_final
2020-06-05 11:17:27	ga_ls8c_ard_3-1-0_110069_2020-06-05_final
2020-07-07 11:17:44	ga_ls8c_ard_3-1-0_110069_2020-07-07_final
2020-07-23 11:17:49	ga_ls8c_ard_3-1-0_110069_2020-07-23_final
2020-08-08 11:17:53	ga_ls8c_ard_3-1-0_110069_2020-08-08_final
2020-08-24 11:18:00	ga_ls8c_ard_3-1-0_110069_2020-08-24_final
2020-09-09 11:18:07	ga_ls8c_ard_3-1-0_110069_2020-09-09_final
2020-09-25 11:18:12	ga_ls8c_ard_3-1-0_110069_2020-09-25_final
2020-10-11 11:18:15	ga_ls8c_ard_3-1-0_110069_2020-10-11_final
2020-10-27 11:18:14	ga_ls8c_ard_3-1-0_110069_2020-10-27_final
2020-11-12 11:18:11	ga_ls8c_ard_3-1-0_110069_2020-11-12_final
2020-11-28 11:18:15	ga_ls8c_ard_3-1-0_110069_2020-11-28_final
2020-12-14 11:18:16	ga_ls8c_ard_3-1-0_110069_2020-12-14_final
2020-12-30 11:18:12	ga_ls8c_ard_3-2-0_110069_2020-12-30_final
2021-01-15 11:18:05	ga_ls8c_ard_3-2-0_110069_2021-01-15_final
2021-01-31 11:18:03	ga_ls8c_ard_3-2-0_110069_2021-01-31_final
2021-02-16 11:17:59	ga_ls8c_ard_3-2-0_110069_2021-02-16_final
2021-03-04 11:17:52	ga_ls8c_ard_3-2-0_110069_2021-03-04_final
2021-03-20 11:17:44	ga_ls8c_ard_3-2-0_110069_2021-03-20_final
2021-04-05 11:17:40	ga_ls8c_ard_3-2-0_110069_2021-04-05_final
2021-04-21 11:17:33	ga_ls8c_ard_3-2-0_110069_2021-04-21_final
2021-05-07 11:17:24	ga_ls8c_ard_3-2-0_110069_2021-05-07_final
2021-05-23 11:17:35	ga_ls8c_ard_3-2-0_110069_2021-05-23_final
2021-06-08 11:17:42	ga_ls8c_ard_3-2-0_110069_2021-06-08_final
2021-06-24 11:17:47	ga_ls8c_ard_3-2-0_110069_2021-06-24_final
2021-07-10 11:17:49	ga_ls8c_ard_3-2-0_110069_2021-07-10_final
2021-07-26 11:17:55	ga_ls8c_ard_3-2-0_110069_2021-07-26_final
2021-08-11 11:18:02	ga_ls8c_ard_3-2-0_110069_2021-08-11_final
2021-08-27 11:18:06	ga_ls8c_ard_3-2-0_110069_2021-08-27_final
2021-09-12 11:18:11	ga_ls8c_ard_3-2-0_110069_2021-09-12_final
2021-09-28 11:18:15	ga_ls8c_ard_3-2-0_110069_2021-09-28_final
2021-10-14 11:18:20	ga_ls8c_ard_3-2-0_110069_2021-10-14_final
2021-10-30 11:18:20	ga_ls8c_ard_3-2-0_110069_2021-10-30_final
2021-11-15 11:18:16	ga_ls8c_ard_3-2-0_110069_2021-11-15_final
2021-12-01 11:18:16	ga_ls8c_ard_3-2-0_110069_2021-12-01_final
2021-12-17 11:18:15	ga_ls8c_ard_3-2-1_110069_2021-12-17_final
2022-01-02 11:18:09	ga_ls8c_ard_3-2-1_110069_2022-01-02_final
2022-01-18 11:18:07	ga_ls8c_ard_3-2-1_110069_2022-01-18_final
2022-02-03 11:18:03	ga_ls8c_ard_3-2-1_110069_2022-02-03_final
2022-02-19 11:17:57	ga_ls8c_ard_3-2-1_110069_2022-02-19_final
2022-03-07 11:17:54	ga_ls8c_ard_3-2-1_110069_2022-03-07_final
2022-03-23 11:17:45	ga_ls8c_ard_3-2-1_110069_2022-03-23_final
2022-04-08 11:17:42	ga_ls8c_ard_3-2-1_110069_2022-04-08_final
2022-04-24 11:17:42	ga_ls8c_ard_3-2-1_110069_2022-04-24_final
2022-05-10 11:17:48	ga_ls8c_ard_3-2-1_110069_2022-05-10_final
2022-05-26 11:17:50	ga_ls8c_ard_3-2-1_110069_2022-05-26_final
2022-06-11 11:18:02	ga_ls8c_ard_3-2-1_110069_2022-06-11_final
2022-06-27 11:18:09	ga_ls8c_ard_3-2-1_110069_2022-06-27_final
2022-07-13 11:18:08	ga_ls8c_ard_3-2-1_110069_2022-07-13_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-08-14 11:18:26	ga_ls8c_ard_3-2-1_110069_2022-08-14_final
2022-08-30 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-08-30_final
2022-09-15 11:18:32	ga_ls8c_ard_3-2-1_110069_2022-09-15_final
2022-10-01 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-10-01_final
2022-10-17 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-10-17_final
2022-11-02 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-11-02_final
2022-11-18 11:18:25	ga_ls8c_ard_3-2-1_110069_2022-11-18_final
2022-12-04 11:18:28	ga_ls8c_ard_3-2-1_110069_2022-12-04_final
2022-12-20 11:18:20	ga_ls8c_ard_3-2-1_110069_2022-12-20_final
2023-01-05 11:18:19	ga_ls8c_ard_3-2-1_110069_2023-01-05_final
2023-01-21 11:18:14	ga_ls8c_ard_3-2-1_110069_2023-01-21_final
2023-02-06 11:18:17	ga_ls8c_ard_3-2-1_110069_2023-02-06_final
2023-02-22 11:18:02	ga_ls8c_ard_3-2-1_110069_2023-02-22_final
2023-03-10 11:17:53	ga_ls8c_ard_3-2-1_110069_2023-03-10_final
2023-03-26 11:17:44	ga_ls8c_ard_3-2-1_110069_2023-03-26_final
2023-04-11 11:17:28	ga_ls8c_ard_3-2-1_110069_2023-04-11_final
2023-04-27 11:17:25	ga_ls8c_ard_3-2-1_110069_2023-04-27_final
2023-05-13 11:17:12	ga_ls8c_ard_3-2-1_110069_2023-05-13_final
2023-05-29 11:17:13	ga_ls8c_ard_3-2-1_110069_2023-05-29_final
2023-06-14 11:17:22	ga_ls8c_ard_3-2-1_110069_2023-06-14_final
2023-06-30 11:17:30	ga_ls8c_ard_3-2-1_110069_2023-06-30_final
2023-07-16 11:17:37	ga_ls8c_ard_3-2-1_110069_2023-07-16_final
2023-08-01 11:17:45	ga_ls8c_ard_3-2-1_110069_2023-08-01_final
2023-08-17 11:17:51	ga_ls8c_ard_3-2-1_110069_2023-08-17_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-18 11:17:59	ga_ls8c_ard_3-2-1_110069_2023-09-18_final
2023-10-04 11:18:02	ga_ls8c_ard_3-2-1_110069_2023-10-04_final
2023-10-20 11:18:03	ga_ls8c_ard_3-2-1_110069_2023-10-20_final
2023-11-05 11:18:06	ga_ls8c_ard_3-2-1_110069_2023-11-05_final
2023-11-21 11:18:09	ga_ls8c_ard_3-2-1_110069_2023-11-21_final
2023-12-07 11:18:00	ga_ls8c_ard_3-2-1_110069_2023-12-07_final
2023-12-23 11:18:08	ga_ls8c_ard_3-2-1_110069_2023-12-23_final
2024-01-08 11:18:00	ga_ls8c_ard_3-2-1_110069_2024-01-08_final
2024-01-24 11:17:57	ga_ls8c_ard_3-2-1_110069_2024-01-24_final
2024-01-24 11:17:57	ga_ls8c_ard_3-2-1_110069_2024-01-24_nrt
2024-02-09 11:18:01	ga_ls8c_ard_3-2-1_110069_2024-02-09_final
2024-02-25 11:17:57	ga_ls8c_ard_3-2-1_110069_2024-02-25_final
2024-03-12 11:17:45	ga_ls8c_ard_3-2-1_110069_2024-03-12_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