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
2015-12-01 09:46:45	ga_ls8c_ard_3-0-0_094088_2015-12-01_final
2016-01-06 09:21:58	ga_ls8c_ard_3-0-0_090088_2016-01-05_final
2016-01-18 09:46:42	ga_ls8c_ard_3-0-0_094088_2016-01-18_final
2016-04-27 09:21:26	ga_ls8c_ard_3-0-0_090088_2016-04-26_final
2016-04-30 09:52:23	ga_ls8c_ard_3-0-0_095088_2016-04-30_final
2016-05-09 09:46:11	ga_ls8c_ard_3-0-0_094088_2016-05-09_final
2017-03-25 09:46:14	ga_ls8c_ard_3-0-0_094088_2017-03-25_final
2017-03-27 09:33:51	ga_ls8c_ard_3-0-0_092088_2017-03-27_final
2017-03-29 09:21:29	ga_ls8c_ard_3-0-0_090088_2017-03-28_final
2017-05-16 09:20:56	ga_ls8c_ard_3-0-0_090087_2017-05-15_final
2017-05-16 09:21:20	ga_ls8c_ard_3-0-0_090088_2017-05-15_final
2017-06-20 09:52:07	ga_ls8c_ard_3-0-0_095087_2017-06-20_final
2017-06-20 09:52:31	ga_ls8c_ard_3-0-0_095088_2017-06-20_final
2017-08-04 09:21:52	ga_ls8c_ard_3-0-0_090088_2017-08-03_final
2017-08-07 09:52:48	ga_ls8c_ard_3-0-0_095088_2017-08-07_final
2017-08-09 09:40:03	ga_ls8c_ard_3-0-0_093087_2017-08-09_final
2017-08-09 09:40:27	ga_ls8c_ard_3-0-0_093088_2017-08-09_final
2017-08-11 09:28:06	ga_ls8c_ard_3-0-0_091088_2017-08-10_final
2018-02-15 09:52:36	ga_ls8c_ard_3-0-0_095088_2018-02-15_final
2018-05-08 09:39:31	ga_ls8c_ard_3-0-0_093088_2018-05-08_final
2018-05-10 09:27:09	ga_ls8c_ard_3-0-0_091088_2018-05-09_final
2018-05-24 09:39:20	ga_ls8c_ard_3-0-0_093088_2018-05-24_final
2018-05-26 09:26:56	ga_ls8c_ard_3-0-0_091088_2018-05-25_final
2018-11-07 09:46:32	ga_ls8c_ard_3-0-0_094088_2018-11-07_final
2018-11-14 09:52:44	ga_ls8c_ard_3-0-0_095088_2018-11-14_final
2018-11-23 09:46:32	ga_ls8c_ard_3-0-0_094088_2018-11-23_final
2018-11-25 09:33:47	ga_ls8c_ard_3-0-0_092087_2018-11-25_final
2018-11-25 09:34:11	ga_ls8c_ard_3-0-0_092088_2018-11-25_final
2018-11-27 09:21:49	ga_ls8c_ard_3-0-0_090088_2018-11-26_final
2018-12-09 09:46:30	ga_ls8c_ard_3-0-0_094088_2018-12-09_final
2018-12-11 09:33:44	ga_ls8c_ard_3-0-0_092087_2018-12-11_final
2018-12-11 09:34:08	ga_ls8c_ard_3-0-0_092088_2018-12-11_final
2018-12-16 09:52:39	ga_ls8c_ard_3-0-0_095088_2018-12-16_final
2018-12-18 09:39:54	ga_ls8c_ard_3-0-0_093087_2018-12-18_final
2018-12-18 09:40:18	ga_ls8c_ard_3-0-0_093088_2018-12-18_final
2018-12-20 09:27:57	ga_ls8c_ard_3-0-0_091088_2018-12-19_final
2018-12-29 09:21:46	ga_ls8c_ard_3-0-0_090088_2018-12-28_final
2019-01-07 09:15:34	ga_ls8c_ard_3-0-0_089088_2019-01-06_final
2019-01-10 09:46:28	ga_ls8c_ard_3-0-0_094088_2019-01-10_final
2019-01-12 09:33:42	ga_ls8c_ard_3-0-0_092087_2019-01-12_final
2019-01-12 09:34:06	ga_ls8c_ard_3-0-0_092088_2019-01-12_final
2019-01-14 09:21:44	ga_ls8c_ard_3-0-0_090088_2019-01-13_final
2019-01-17 09:52:37	ga_ls8c_ard_3-0-0_095088_2019-01-17_final
2019-01-26 09:46:24	ga_ls8c_ard_3-0-0_094088_2019-01-26_final
2019-01-28 09:33:38	ga_ls8c_ard_3-0-0_092087_2019-01-28_final
2019-01-28 09:34:02	ga_ls8c_ard_3-0-0_092088_2019-01-28_final
2019-01-30 09:21:40	ga_ls8c_ard_3-0-0_090088_2019-01-29_final
2022-02-14 09:28:09	ga_ls8c_ard_3-2-1_091088_2022-02-13_final
2022-02-16 09:15:46	ga_ls8c_ard_3-2-1_089088_2022-02-15_final
2022-02-21 09:34:17	ga_ls8c_ard_3-2-1_092088_2022-02-21_final
2022-02-23 09:21:55	ga_ls8c_ard_3-2-1_090088_2022-02-22_final
2022-03-18 09:27:58	ga_ls8c_ard_3-2-1_091088_2022-03-17_final
2022-03-20 09:15:35	ga_ls8c_ard_3-2-1_089088_2022-03-19_final
2022-03-25 09:34:04	ga_ls8c_ard_3-2-1_092088_2022-03-25_final
2022-04-01 09:40:10	ga_ls8c_ard_3-2-1_093088_2022-04-01_final
2022-04-03 09:27:48	ga_ls8c_ard_3-2-1_091088_2022-04-02_final
2022-04-05 09:15:28	ga_ls8c_ard_3-2-1_089088_2022-04-04_final
2022-04-10 09:34:04	ga_ls8c_ard_3-2-1_092088_2022-04-10_final
2022-04-12 09:21:43	ga_ls8c_ard_3-2-1_090088_2022-04-11_final
2022-04-15 09:52:14	ga_ls8c_ard_3-2-1_095087_2022-04-15_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-17 09:40:16	ga_ls8c_ard_3-2-1_093088_2022-04-17_final
2022-04-19 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-04-18_final
2022-04-19 09:27:54	ga_ls8c_ard_3-2-1_091088_2022-04-18_final
2022-04-21 09:15:32	ga_ls8c_ard_3-2-1_089088_2022-04-20_final
2022-05-07 09:15:34	ga_ls8c_ard_3-2-1_089088_2022-05-06_final
2022-06-22 09:28:17	ga_ls8c_ard_3-2-1_091088_2022-06-21_final
2022-06-24 09:15:56	ga_ls8c_ard_3-2-1_089088_2022-06-23_final
2022-06-27 09:46:27	ga_ls8c_ard_3-2-1_094087_2022-06-27_final
2022-06-29 09:34:29	ga_ls8c_ard_3-2-1_092088_2022-06-29_final
2022-07-01 09:21:44	ga_ls8c_ard_3-2-1_090087_2022-06-30_final
2022-07-01 09:22:08	ga_ls8c_ard_3-2-1_090088_2022-06-30_final
2022-07-06 09:40:40	ga_ls8c_ard_3-2-1_093088_2022-07-06_final
2022-07-08 09:27:55	ga_ls8c_ard_3-2-1_091087_2022-07-07_final
2022-07-08 09:28:19	ga_ls8c_ard_3-2-1_091088_2022-07-07_final
2022-07-10 09:15:57	ga_ls8c_ard_3-2-1_089088_2022-07-09_final
2022-07-22 09:40:44	ga_ls8c_ard_3-2-1_093088_2022-07-22_final
2022-07-24 09:28:24	ga_ls8c_ard_3-2-1_091088_2022-07-23_final
2022-07-26 09:16:04	ga_ls8c_ard_3-2-1_089088_2022-07-25_final
2022-07-31 09:34:16	ga_ls8c_ard_3-2-1_092087_2022-07-31_final
2022-07-31 09:34:40	ga_ls8c_ard_3-2-1_092088_2022-07-31_final
2022-08-07 09:40:54	ga_ls8c_ard_3-2-1_093088_2022-08-07_final
2022-08-09 09:28:34	ga_ls8c_ard_3-2-1_091088_2022-08-08_final
2022-08-14 09:46:44	ga_ls8c_ard_3-2-1_094087_2022-08-14_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-25 09:28:12	ga_ls8c_ard_3-2-1_091087_2022-08-24_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-27 09:16:15	ga_ls8c_ard_3-2-1_089088_2022-08-26_final
2022-09-01 09:34:47	ga_ls8c_ard_3-2-1_092088_2022-09-01_final
2022-09-03 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-09-02_final
2022-09-08 09:41:00	ga_ls8c_ard_3-2-1_093088_2022-09-08_final
2022-09-12 09:16:19	ga_ls8c_ard_3-2-1_089088_2022-09-11_final
2022-09-17 09:34:53	ga_ls8c_ard_3-2-1_092088_2022-09-17_final
2022-09-19 09:22:32	ga_ls8c_ard_3-2-1_090088_2022-09-18_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-09-24 09:41:05	ga_ls8c_ard_3-2-1_093088_2022-09-24_final
2022-10-03 09:34:52	ga_ls8c_ard_3-2-1_092088_2022-10-03_final
2022-10-05 09:22:30	ga_ls8c_ard_3-2-1_090088_2022-10-04_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_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