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
2014-07-27 09:22:35	ga_ls8c_ard_3-0-0_090090_2014-07-26_final
2014-10-06 09:29:04	ga_ls8c_ard_3-0-0_091090_2014-10-05_final
2014-10-22 09:29:06	ga_ls8c_ard_3-0-0_091090_2014-10-21_final
2015-01-03 09:22:43	ga_ls8c_ard_3-0-0_090090_2015-01-02_final
2017-09-03 09:35:09	ga_ls8c_ard_3-0-0_092090_2017-09-03_final
2017-10-07 09:22:57	ga_ls8c_ard_3-0-0_090090_2017-10-06_final
2017-10-07 09:23:21	ga_ls8c_ard_3-0-0_090091_2017-10-06_final
2017-10-14 09:29:09	ga_ls8c_ard_3-0-0_091090_2017-10-13_final
2017-10-14 09:29:33	ga_ls8c_ard_3-0-0_091091_2017-10-13_final
2017-11-06 09:35:20	ga_ls8c_ard_3-0-0_092090_2017-11-06_final
2017-11-22 09:35:15	ga_ls8c_ard_3-0-0_092090_2017-11-22_final
2018-01-11 09:22:46	ga_ls8c_ard_3-0-0_090090_2018-01-10_final
2018-01-11 09:23:10	ga_ls8c_ard_3-0-0_090091_2018-01-10_final
2018-01-27 09:22:37	ga_ls8c_ard_3-0-0_090090_2018-01-26_final
2018-01-27 09:23:01	ga_ls8c_ard_3-0-0_090091_2018-01-26_final
2018-03-07 09:28:55	ga_ls8c_ard_3-0-0_091091_2018-03-06_final
2018-03-23 09:28:23	ga_ls8c_ard_3-0-0_091090_2018-03-22_final
2018-03-23 09:28:47	ga_ls8c_ard_3-0-0_091091_2018-03-22_final
2018-03-25 09:16:00	ga_ls8c_ard_3-0-0_089090_2018-03-24_final
2018-04-08 09:28:39	ga_ls8c_ard_3-0-0_091091_2018-04-07_final
2018-04-17 09:22:23	ga_ls8c_ard_3-0-0_090091_2018-04-16_final
2018-04-24 09:28:06	ga_ls8c_ard_3-0-0_091090_2018-04-23_final
2018-04-24 09:28:30	ga_ls8c_ard_3-0-0_091091_2018-04-23_final
2018-05-10 09:27:56	ga_ls8c_ard_3-0-0_091090_2018-05-09_final
2018-05-10 09:28:20	ga_ls8c_ard_3-0-0_091091_2018-05-09_final
2018-05-12 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-05-11_final
2018-05-26 09:28:08	ga_ls8c_ard_3-0-0_091091_2018-05-25_final
2018-06-04 09:21:28	ga_ls8c_ard_3-0-0_090090_2018-06-03_final
2018-06-04 09:21:52	ga_ls8c_ard_3-0-0_090091_2018-06-03_final
2018-06-11 09:27:42	ga_ls8c_ard_3-0-0_091090_2018-06-10_final
2018-06-11 09:28:06	ga_ls8c_ard_3-0-0_091091_2018-06-10_final
2018-06-13 09:15:22	ga_ls8c_ard_3-0-0_089090_2018-06-12_final
2018-06-27 09:27:53	ga_ls8c_ard_3-0-0_091090_2018-06-26_final
2018-06-27 09:28:17	ga_ls8c_ard_3-0-0_091091_2018-06-26_final
2018-06-29 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-06-28_final
2018-07-13 09:28:01	ga_ls8c_ard_3-0-0_091090_2018-07-12_final
2018-07-13 09:28:25	ga_ls8c_ard_3-0-0_091091_2018-07-12_final
2018-07-15 09:15:40	ga_ls8c_ard_3-0-0_089090_2018-07-14_final
2018-07-20 09:34:15	ga_ls8c_ard_3-0-0_092090_2018-07-20_final
2018-07-22 09:21:54	ga_ls8c_ard_3-0-0_090090_2018-07-21_final
2018-07-22 09:22:18	ga_ls8c_ard_3-0-0_090091_2018-07-21_final
2020-03-03 09:35:00	ga_ls8c_ard_3-1-0_092090_2020-03-03_final
2020-04-22 09:22:14	ga_ls8c_ard_3-1-0_090090_2020-04-21_final
2020-04-22 09:22:38	ga_ls8c_ard_3-1-0_090091_2020-04-21_final
2021-10-16 09:35:28	ga_ls8c_ard_3-2-0_092090_2021-10-16_final
2022-05-12 09:34:57	ga_ls8c_ard_3-2-1_092090_2022-05-12_final
2022-05-14 09:22:37	ga_ls8c_ard_3-2-1_090090_2022-05-13_final
2022-05-14 09:23:00	ga_ls8c_ard_3-2-1_090091_2022-05-13_final
2022-05-21 09:28:49	ga_ls8c_ard_3-2-1_091090_2022-05-20_final
2022-05-23 09:16:27	ga_ls8c_ard_3-2-1_089090_2022-05-22_final
2022-05-28 09:34:58	ga_ls8c_ard_3-2-1_092090_2022-05-28_final
2022-05-30 09:22:39	ga_ls8c_ard_3-2-1_090090_2022-05-29_final
2022-05-30 09:23:03	ga_ls8c_ard_3-2-1_090091_2022-05-29_final
2022-06-06 09:28:56	ga_ls8c_ard_3-2-1_091090_2022-06-05_final
2022-06-08 09:16:36	ga_ls8c_ard_3-2-1_089090_2022-06-07_final
2022-06-13 09:35:12	ga_ls8c_ard_3-2-1_092090_2022-06-13_final
2022-09-26 09:29:31	ga_ls8c_ard_3-2-1_091090_2022-09-25_final
2022-09-28 09:17:09	ga_ls8c_ard_3-2-1_089090_2022-09-27_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-05 09:23:42	ga_ls8c_ard_3-2-1_090091_2022-10-04_final
2022-10-12 09:29:23	ga_ls8c_ard_3-2-1_091090_2022-10-11_final
2022-10-28 09:29:30	ga_ls8c_ard_3-2-1_091090_2022-10-27_final
2023-02-01 09:29:15	ga_ls8c_ard_3-2-1_091090_2023-01-31_final
2023-02-03 09:16:53	ga_ls8c_ard_3-2-1_089090_2023-02-02_final
2023-02-08 09:35:24	ga_ls8c_ard_3-2-1_092090_2023-02-08_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-10 09:23:25	ga_ls8c_ard_3-2-1_090091_2023-02-09_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-19 09:16:42	ga_ls8c_ard_3-2-1_089090_2023-02-18_final
2023-02-24 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-02-24_final
2023-02-26 09:22:44	ga_ls8c_ard_3-2-1_090090_2023-02-25_final
2023-02-26 09:23:08	ga_ls8c_ard_3-2-1_090091_2023-02-25_final
2023-03-05 09:28:54	ga_ls8c_ard_3-2-1_091090_2023-03-04_final
2023-03-14 09:23:03	ga_ls8c_ard_3-2-1_090091_2023-03-13_final
2023-03-23 09:16:21	ga_ls8c_ard_3-2-1_089090_2023-03-22_final
2023-03-28 09:34:52	ga_ls8c_ard_3-2-1_092090_2023-03-28_final
2023-03-30 09:22:53	ga_ls8c_ard_3-2-1_090091_2023-03-29_final
2023-04-15 09:22:14	ga_ls8c_ard_3-2-1_090090_2023-04-14_final
2023-04-15 09:22:38	ga_ls8c_ard_3-2-1_090091_2023-04-14_final
2023-05-31 09:34:21	ga_ls8c_ard_3-2-1_092090_2023-05-31_final
2023-06-02 09:22:00	ga_ls8c_ard_3-2-1_090090_2023-06-01_final
2023-06-02 09:22:24	ga_ls8c_ard_3-2-1_090091_2023-06-01_final
2023-06-09 09:28:17	ga_ls8c_ard_3-2-1_091090_2023-06-08_final
2023-06-11 09:15:56	ga_ls8c_ard_3-2-1_089090_2023-06-10_final
2023-06-16 09:34:31	ga_ls8c_ard_3-2-1_092090_2023-06-16_final
2023-06-18 09:22:09	ga_ls8c_ard_3-2-1_090090_2023-06-17_final
2023-06-18 09:22:33	ga_ls8c_ard_3-2-1_090091_2023-06-17_final
2023-06-25 09:28:23	ga_ls8c_ard_3-2-1_091090_2023-06-24_final
2023-06-27 09:16:03	ga_ls8c_ard_3-2-1_089090_2023-06-26_final
2023-07-02 09:34:40	ga_ls8c_ard_3-2-1_092090_2023-07-02_final
2023-07-04 09:22:20	ga_ls8c_ard_3-2-1_090090_2023-07-03_final
2023-07-04 09:22:44	ga_ls8c_ard_3-2-1_090091_2023-07-03_final
2023-07-11 09:28:34	ga_ls8c_ard_3-2-1_091090_2023-07-10_final
2023-07-13 09:16:13	ga_ls8c_ard_3-2-1_089090_2023-07-12_final
2023-07-18 09:34:45	ga_ls8c_ard_3-2-1_092090_2023-07-18_final
2023-07-20 09:22:23	ga_ls8c_ard_3-2-1_090090_2023-07-19_final
2023-07-20 09:22:47	ga_ls8c_ard_3-2-1_090091_2023-07-19_final
2023-07-29 09:16:19	ga_ls8c_ard_3-2-1_089090_2023-07-28_final
2023-08-03 09:34:54	ga_ls8c_ard_3-2-1_092090_2023-08-03_final
2023-08-05 09:22:33	ga_ls8c_ard_3-2-1_090090_2023-08-04_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