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
2018-07-23 11:40:27	ga_ls8c_ard_3-0-0_113081_2018-07-23_final
2018-08-24 11:40:44	ga_ls8c_ard_3-0-0_113081_2018-08-24_final
2018-10-11 11:41:03	ga_ls8c_ard_3-0-0_113081_2018-10-11_final
2018-10-27 11:41:08	ga_ls8c_ard_3-0-0_113081_2018-10-27_final
2019-03-20 11:40:49	ga_ls8c_ard_3-1-0_113081_2019-03-20_final
2019-05-23 11:40:53	ga_ls8c_ard_3-0-0_113081_2019-05-23_final
2019-06-24 11:41:07	ga_ls8c_ard_3-1-0_113081_2019-06-24_final
2019-08-11 11:41:21	ga_ls8c_ard_3-1-0_113081_2019-08-11_final
2019-09-12 11:41:30	ga_ls8c_ard_3-1-0_113081_2019-09-12_final
2019-09-28 11:41:35	ga_ls8c_ard_3-1-0_113081_2019-09-28_final
2019-10-30 11:41:38	ga_ls8c_ard_3-1-0_113081_2019-10-30_final
2019-12-17 11:41:32	ga_ls8c_ard_3-2-0_113081_2019-12-17_final
2020-02-03 11:41:19	ga_ls8c_ard_3-1-0_113081_2020-02-03_final
2020-04-07 11:40:53	ga_ls8c_ard_3-1-0_113081_2020-04-07_final
2020-06-10 11:40:50	ga_ls8c_ard_3-1-0_113081_2020-06-10_final
2020-06-26 11:40:59	ga_ls8c_ard_3-1-0_113081_2020-06-26_final
2020-07-12 11:41:06	ga_ls8c_ard_3-1-0_113081_2020-07-12_final
2020-07-28 11:41:10	ga_ls8c_ard_3-1-0_113081_2020-07-28_final
2020-08-13 11:41:14	ga_ls8c_ard_3-1-0_113081_2020-08-13_final
2020-08-29 11:41:22	ga_ls8c_ard_3-1-0_113081_2020-08-29_final
2020-09-14 11:41:29	ga_ls8c_ard_3-1-0_113081_2020-09-14_final
2020-09-30 11:41:33	ga_ls8c_ard_3-1-0_113081_2020-09-30_final
2020-10-16 11:41:35	ga_ls8c_ard_3-1-0_113081_2020-10-16_final
2020-11-01 11:41:33	ga_ls8c_ard_3-1-0_113081_2020-11-01_final
2020-11-17 11:41:32	ga_ls8c_ard_3-1-0_113081_2020-11-17_final
2020-12-03 11:41:35	ga_ls8c_ard_3-1-0_113081_2020-12-03_final
2020-12-19 11:41:35	ga_ls8c_ard_3-2-0_113081_2020-12-19_final
2021-01-04 11:41:30	ga_ls8c_ard_3-2-0_113081_2021-01-04_final
2021-01-20 11:41:23	ga_ls8c_ard_3-2-0_113081_2021-01-20_final
2021-02-05 11:41:21	ga_ls8c_ard_3-2-0_113081_2021-02-05_final
2021-02-21 11:41:17	ga_ls8c_ard_3-2-0_113081_2021-02-21_final
2021-03-09 11:41:09	ga_ls8c_ard_3-2-0_113081_2021-03-09_final
2021-03-25 11:41:03	ga_ls8c_ard_3-2-0_113081_2021-03-25_final
2021-04-10 11:40:58	ga_ls8c_ard_3-2-0_113081_2021-04-10_final
2021-04-26 11:40:50	ga_ls8c_ard_3-2-0_113081_2021-04-26_final
2021-05-12 11:40:47	ga_ls8c_ard_3-2-0_113081_2021-05-12_final
2021-05-28 11:40:57	ga_ls8c_ard_3-2-0_113081_2021-05-28_final
2021-06-13 11:41:04	ga_ls8c_ard_3-2-0_113081_2021-06-13_final
2021-06-29 11:41:08	ga_ls8c_ard_3-2-0_113081_2021-06-29_final
2021-07-15 11:41:09	ga_ls8c_ard_3-2-0_113081_2021-07-15_final
2021-07-31 11:41:17	ga_ls8c_ard_3-2-0_113081_2021-07-31_final
2021-08-16 11:41:23	ga_ls8c_ard_3-2-0_113081_2021-08-16_final
2021-09-01 11:41:28	ga_ls8c_ard_3-2-0_113081_2021-09-01_final
2021-09-17 11:41:32	ga_ls8c_ard_3-2-0_113081_2021-09-17_final
2021-10-03 11:41:37	ga_ls8c_ard_3-2-0_113081_2021-10-03_final
2021-10-19 11:41:40	ga_ls8c_ard_3-2-0_113081_2021-10-19_final
2021-11-04 11:41:39	ga_ls8c_ard_3-2-0_113081_2021-11-04_final
2021-11-20 11:41:34	ga_ls8c_ard_3-2-0_113081_2021-11-20_final
2021-12-06 11:41:36	ga_ls8c_ard_3-2-1_113081_2021-12-06_final
2021-12-22 11:41:33	ga_ls8c_ard_3-2-1_113081_2021-12-22_final
2022-01-07 11:41:29	ga_ls8c_ard_3-2-1_113081_2022-01-07_final
2022-01-23 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-01-23_final
2022-02-08 11:41:21	ga_ls8c_ard_3-2-1_113081_2022-02-08_final
2022-02-24 11:41:16	ga_ls8c_ard_3-2-1_113081_2022-02-24_final
2022-03-12 11:41:12	ga_ls8c_ard_3-2-1_113081_2022-03-12_final
2022-03-28 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-03-28_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-05-15 11:41:10	ga_ls8c_ard_3-2-1_113081_2022-05-15_final
2022-05-31 11:41:13	ga_ls8c_ard_3-2-1_113081_2022-05-31_final
2022-06-16 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-06-16_final
2022-07-02 11:41:29	ga_ls8c_ard_3-2-1_113081_2022-07-02_final
2022-07-18 11:41:30	ga_ls8c_ard_3-2-1_113081_2022-07-18_final
2022-08-03 11:41:41	ga_ls8c_ard_3-2-1_113081_2022-08-03_final
2022-08-19 11:41:46	ga_ls8c_ard_3-2-1_113081_2022-08-19_final
2022-09-04 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-09-04_final
2022-09-20 11:41:53	ga_ls8c_ard_3-2-1_113081_2022-09-20_final
2022-10-06 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-06_final
2022-10-22 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-22_final
2022-11-07 11:41:52	ga_ls8c_ard_3-2-1_113081_2022-11-07_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-12-09 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-12-09_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2023-01-10 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-10_final
2023-01-26 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-26_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-27 11:41:18	ga_ls8c_ard_3-2-1_113081_2023-02-27_final
2023-03-15 11:41:12	ga_ls8c_ard_3-2-1_113081_2023-03-15_final
2023-03-31 11:41:02	ga_ls8c_ard_3-2-1_113081_2023-03-31_final
2023-04-16 11:40:47	ga_ls8c_ard_3-2-1_113081_2023-04-16_final
2023-05-02 11:40:42	ga_ls8c_ard_3-2-1_113081_2023-05-02_final
2023-05-18 11:40:30	ga_ls8c_ard_3-2-1_113081_2023-05-18_final
2023-06-03 11:40:34	ga_ls8c_ard_3-2-1_113081_2023-06-03_final
2023-06-19 11:40:43	ga_ls8c_ard_3-2-1_113081_2023-06-19_final
2023-07-05 11:40:54	ga_ls8c_ard_3-2-1_113081_2023-07-05_final
2023-07-21 11:40:56	ga_ls8c_ard_3-2-1_113081_2023-07-21_final
2023-08-06 11:41:06	ga_ls8c_ard_3-2-1_113081_2023-08-06_final
2023-08-22 11:41:13	ga_ls8c_ard_3-2-1_113081_2023-08-22_final
2023-09-07 11:41:12	ga_ls8c_ard_3-2-1_113081_2023-09-07_final
2023-09-23 11:41:19	ga_ls8c_ard_3-2-1_113081_2023-09-23_final
2023-10-09 11:41:23	ga_ls8c_ard_3-2-1_113081_2023-10-09_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-11-10 11:41:22	ga_ls8c_ard_3-2-1_113081_2023-11-10_final
2023-11-26 11:41:29	ga_ls8c_ard_3-2-1_113081_2023-11-26_final
2023-12-12 11:41:24	ga_ls8c_ard_3-2-1_113081_2023-12-12_final
2023-12-28 11:41:25	ga_ls8c_ard_3-2-1_113081_2023-12-28_final
2024-01-13 11:41:22	ga_ls8c_ard_3-2-1_113081_2024-01-13_final
2024-01-29 11:41:16	ga_ls8c_ard_3-2-1_113081_2024-01-29_final
2024-02-14 11:41:19	ga_ls8c_ard_3-2-1_113081_2024-02-14_final
2024-03-01 11:41:13	ga_ls8c_ard_3-2-1_113081_2024-03-01_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