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
2015-06-03 09:28:25	ga_ls8c_ard_3-0-0_091091_2015-06-02_final
2015-06-19 09:28:34	ga_ls8c_ard_3-0-0_091091_2015-06-18_final
2016-05-20 09:28:51	ga_ls8c_ard_3-0-0_091091_2016-05-19_final
2016-05-29 09:22:44	ga_ls8c_ard_3-0-0_090091_2016-05-28_final
2016-06-05 09:28:57	ga_ls8c_ard_3-0-0_091091_2016-06-04_final
2016-06-14 09:22:47	ga_ls8c_ard_3-0-0_090091_2016-06-13_final
2016-06-21 09:29:01	ga_ls8c_ard_3-0-0_091091_2016-06-20_final
2016-07-16 09:23:03	ga_ls8c_ard_3-0-0_090091_2016-07-15_final
2016-07-23 09:29:15	ga_ls8c_ard_3-0-0_091091_2016-07-22_final
2016-08-01 09:23:06	ga_ls8c_ard_3-0-0_090091_2016-07-31_final
2016-08-08 09:29:18	ga_ls8c_ard_3-0-0_091091_2016-08-07_final
2016-08-17 09:23:10	ga_ls8c_ard_3-0-0_090091_2016-08-16_final
2016-09-02 09:23:17	ga_ls8c_ard_3-0-0_090091_2016-09-01_final
2016-09-09 09:29:29	ga_ls8c_ard_3-0-0_091091_2016-09-08_final
2016-09-25 09:29:30	ga_ls8c_ard_3-0-0_091091_2016-09-24_final
2016-10-04 09:23:21	ga_ls8c_ard_3-0-0_090091_2016-10-03_final
2016-10-11 09:29:34	ga_ls8c_ard_3-0-0_091091_2016-10-10_final
2016-10-27 09:29:37	ga_ls8c_ard_3-0-0_091091_2016-10-26_final
2016-12-30 09:29:30	ga_ls8c_ard_3-0-0_091091_2016-12-29_final
2017-04-30 09:22:23	ga_ls8c_ard_3-0-0_090091_2017-04-29_final
2017-05-07 09:28:36	ga_ls8c_ard_3-0-0_091091_2017-05-06_final
2017-05-16 09:22:32	ga_ls8c_ard_3-0-0_090091_2017-05-15_final
2017-05-23 09:28:47	ga_ls8c_ard_3-0-0_091091_2017-05-22_final
2017-06-01 09:22:41	ga_ls8c_ard_3-0-0_090091_2017-05-31_final
2017-06-08 09:28:55	ga_ls8c_ard_3-0-0_091091_2017-06-07_final
2017-06-17 09:22:48	ga_ls8c_ard_3-0-0_090091_2017-06-16_final
2017-06-24 09:29:01	ga_ls8c_ard_3-0-0_091091_2017-06-23_final
2017-07-03 09:22:52	ga_ls8c_ard_3-0-0_090091_2017-07-02_final
2017-07-10 09:29:04	ga_ls8c_ard_3-0-0_091091_2017-07-09_final
2017-07-19 09:22:57	ga_ls8c_ard_3-0-0_090091_2017-07-18_final
2017-07-26 09:29:11	ga_ls8c_ard_3-0-0_091091_2017-07-25_final
2017-08-04 09:23:04	ga_ls8c_ard_3-0-0_090091_2017-08-03_final
2017-08-11 09:29:18	ga_ls8c_ard_3-0-0_091091_2017-08-10_final
2017-08-27 09:29:22	ga_ls8c_ard_3-0-0_091091_2017-08-26_final
2018-06-04 09:21:52	ga_ls8c_ard_3-0-0_090091_2018-06-03_final
2018-06-11 09:28:06	ga_ls8c_ard_3-0-0_091091_2018-06-10_final
2018-06-20 09:22:02	ga_ls8c_ard_3-0-0_090091_2018-06-19_final
2018-06-27 09:28:17	ga_ls8c_ard_3-0-0_091091_2018-06-26_final
2018-07-06 09:22:11	ga_ls8c_ard_3-0-0_090091_2018-07-05_final
2018-07-13 09:28:25	ga_ls8c_ard_3-0-0_091091_2018-07-12_final
2018-07-22 09:22:18	ga_ls8c_ard_3-0-0_090091_2018-07-21_final
2018-08-07 09:22:27	ga_ls8c_ard_3-0-0_090091_2018-08-06_final
2018-08-14 09:28:41	ga_ls8c_ard_3-0-0_091091_2018-08-13_final
2018-08-23 09:22:35	ga_ls8c_ard_3-0-0_090091_2018-08-22_final
2018-08-30 09:28:48	ga_ls8c_ard_3-0-0_091091_2018-08-29_final
2018-10-10 09:22:54	ga_ls8c_ard_3-0-0_090091_2018-10-09_final
2018-10-17 09:29:07	ga_ls8c_ard_3-0-0_091091_2018-10-16_final
2018-12-13 09:22:57	ga_ls8c_ard_3-0-0_090091_2018-12-12_final
2018-12-29 09:22:58	ga_ls8c_ard_3-0-0_090091_2018-12-28_final
2019-01-14 09:22:56	ga_ls8c_ard_3-0-0_090091_2019-01-13_final
2019-01-21 09:29:05	ga_ls8c_ard_3-0-0_091091_2019-01-20_final
2019-01-30 09:22:52	ga_ls8c_ard_3-0-0_090091_2019-01-29_final
2019-12-16 09:23:23	ga_ls8c_ard_3-2-0_090091_2019-12-15_final
2020-01-01 09:23:18	ga_ls8c_ard_3-1-0_090091_2019-12-31_final
2020-05-15 09:28:41	ga_ls8c_ard_3-1-0_091091_2020-05-14_final
2020-05-24 09:22:32	ga_ls8c_ard_3-1-0_090091_2020-05-23_final
2020-05-31 09:28:45	ga_ls8c_ard_3-1-0_091091_2020-05-30_final
2020-06-09 09:22:40	ga_ls8c_ard_3-1-0_090091_2020-06-08_final
2020-06-16 09:28:55	ga_ls8c_ard_3-1-0_091091_2020-06-15_final
2020-06-25 09:22:49	ga_ls8c_ard_3-1-0_090091_2020-06-24_final
2020-07-02 09:29:03	ga_ls8c_ard_3-1-0_091091_2020-07-01_final
2020-07-11 09:22:56	ga_ls8c_ard_3-1-0_090091_2020-07-10_final
2020-07-18 09:29:09	ga_ls8c_ard_3-1-0_091091_2020-07-17_final
2020-08-03 09:29:13	ga_ls8c_ard_3-1-0_091091_2020-08-02_final
2020-08-12 09:23:04	ga_ls8c_ard_3-1-0_090091_2020-08-11_final
2020-08-19 09:29:19	ga_ls8c_ard_3-1-0_091091_2020-08-18_final
2020-08-28 09:23:13	ga_ls8c_ard_3-1-0_090091_2020-08-27_final
2020-09-04 09:29:27	ga_ls8c_ard_3-1-0_091091_2020-09-03_final
2020-09-29 09:23:24	ga_ls8c_ard_3-1-0_090091_2020-09-28_final
2020-10-22 09:29:36	ga_ls8c_ard_3-1-0_091091_2020-10-21_final
2020-12-02 09:23:26	ga_ls8c_ard_3-1-0_090091_2020-12-01_final
2020-12-09 09:29:37	ga_ls8c_ard_3-1-0_091091_2020-12-08_final
2021-05-11 09:22:37	ga_ls8c_ard_3-2-0_090091_2021-05-10_final
2021-07-21 09:29:14	ga_ls8c_ard_3-2-0_091091_2021-07-20_final
2021-07-30 09:23:08	ga_ls8c_ard_3-2-0_090091_2021-07-29_final
2021-08-06 09:29:22	ga_ls8c_ard_3-2-0_091091_2021-08-05_final
2021-08-15 09:23:14	ga_ls8c_ard_3-2-0_090091_2021-08-14_final
2021-08-22 09:29:27	ga_ls8c_ard_3-2-0_091091_2021-08-21_final
2021-08-31 09:23:18	ga_ls8c_ard_3-2-0_090091_2021-08-30_final
2021-09-16 09:23:22	ga_ls8c_ard_3-2-0_090091_2021-09-15_final
2021-10-02 09:23:27	ga_ls8c_ard_3-2-0_090091_2021-10-01_final
2021-10-09 09:29:40	ga_ls8c_ard_3-2-0_091091_2021-10-08_final
2022-04-28 09:22:51	ga_ls8c_ard_3-2-1_090091_2022-04-27_final
2022-05-14 09:23:00	ga_ls8c_ard_3-2-1_090091_2022-05-13_final
2022-05-30 09:23:03	ga_ls8c_ard_3-2-1_090091_2022-05-29_final
2022-06-15 09:23:15	ga_ls8c_ard_3-2-1_090091_2022-06-14_final
2022-07-01 09:23:20	ga_ls8c_ard_3-2-1_090091_2022-06-30_final
2022-07-17 09:23:19	ga_ls8c_ard_3-2-1_090091_2022-07-16_final
2022-08-18 09:23:37	ga_ls8c_ard_3-2-1_090091_2022-08-17_final
2022-10-05 09:23:42	ga_ls8c_ard_3-2-1_090091_2022-10-04_final
2023-06-02 09:22:24	ga_ls8c_ard_3-2-1_090091_2023-06-01_final
2023-06-18 09:22:33	ga_ls8c_ard_3-2-1_090091_2023-06-17_final
2023-07-04 09:22:44	ga_ls8c_ard_3-2-1_090091_2023-07-03_final
2023-07-20 09:22:47	ga_ls8c_ard_3-2-1_090091_2023-07-19_final
2023-08-05 09:22:57	ga_ls8c_ard_3-2-1_090091_2023-08-04_final
2023-08-21 09:23:04	ga_ls8c_ard_3-2-1_090091_2023-08-20_final
2023-09-06 09:23:03	ga_ls8c_ard_3-2-1_090091_2023-09-05_final
2023-09-22 09:23:09	ga_ls8c_ard_3-2-1_090091_2023-09-21_final
2023-10-24 09:23:16	ga_ls8c_ard_3-2-1_090091_2023-10-23_final
2023-11-25 09:23:20	ga_ls8c_ard_3-2-1_090091_2023-11-24_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