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
2014-08-01 09:40:00	ga_ls8c_ard_3-0-0_093087_2014-08-01_final
2014-08-01 09:40:24	ga_ls8c_ard_3-0-0_093088_2014-08-01_final
2014-09-18 09:40:09	ga_ls8c_ard_3-0-0_093087_2014-09-18_final
2014-09-18 09:40:33	ga_ls8c_ard_3-0-0_093088_2014-09-18_final
2014-10-02 09:52:33	ga_ls8c_ard_3-0-0_095087_2014-10-02_final
2014-10-04 09:40:13	ga_ls8c_ard_3-0-0_093087_2014-10-04_final
2014-10-04 09:40:37	ga_ls8c_ard_3-0-0_093088_2014-10-04_final
2014-11-05 09:40:39	ga_ls8c_ard_3-0-0_093088_2014-11-05_final
2014-11-19 09:52:34	ga_ls8c_ard_3-0-0_095087_2014-11-19_final
2017-08-02 09:33:49	ga_ls8c_ard_3-0-0_092087_2017-08-02_final
2017-08-02 09:34:13	ga_ls8c_ard_3-0-0_092088_2017-08-02_final
2017-08-04 09:21:28	ga_ls8c_ard_3-0-0_090087_2017-08-03_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 09:27:42	ga_ls8c_ard_3-0-0_091087_2017-08-10_final
2017-08-11 09:28:06	ga_ls8c_ard_3-0-0_091088_2017-08-10_final
2017-08-14 09:58:37	ga_ls8c_ard_3-0-0_096087_2017-08-14_final
2017-08-16 09:46:16	ga_ls8c_ard_3-0-0_094087_2017-08-16_final
2017-08-16 09:46:40	ga_ls8c_ard_3-0-0_094088_2017-08-16_final
2017-08-18 09:33:55	ga_ls8c_ard_3-0-0_092087_2017-08-18_final
2017-08-18 09:34:19	ga_ls8c_ard_3-0-0_092088_2017-08-18_final
2017-08-20 09:21:34	ga_ls8c_ard_3-0-0_090087_2017-08-19_final
2017-08-20 09:21:57	ga_ls8c_ard_3-0-0_090088_2017-08-19_final
2017-08-27 09:27:46	ga_ls8c_ard_3-0-0_091087_2017-08-26_final
2017-08-27 09:28:10	ga_ls8c_ard_3-0-0_091088_2017-08-26_final
2017-08-29 09:15:24	ga_ls8c_ard_3-0-0_089087_2017-08-28_final
2017-08-29 09:15:48	ga_ls8c_ard_3-0-0_089088_2017-08-28_final
2017-08-30 09:58:40	ga_ls8c_ard_3-0-0_096087_2017-08-30_final
2017-09-05 09:22:00	ga_ls8c_ard_3-0-0_090088_2017-09-04_final
2017-09-24 09:52:58	ga_ls8c_ard_3-0-0_095088_2017-09-24_final
2017-09-26 09:40:14	ga_ls8c_ard_3-0-0_093087_2017-09-26_final
2017-09-26 09:40:38	ga_ls8c_ard_3-0-0_093088_2017-09-26_final
2017-10-14 09:27:57	ga_ls8c_ard_3-0-0_091087_2017-10-13_final
2017-10-14 09:28:21	ga_ls8c_ard_3-0-0_091088_2017-10-13_final
2019-03-26 09:27:38	ga_ls8c_ard_3-1-0_091088_2019-03-25_final
2019-03-28 09:15:16	ga_ls8c_ard_3-1-0_089088_2019-03-27_final
2019-04-11 09:27:33	ga_ls8c_ard_3-1-0_091088_2019-04-10_final
2019-04-18 09:33:41	ga_ls8c_ard_3-1-0_092088_2019-04-18_final
2019-04-20 09:21:19	ga_ls8c_ard_3-0-0_090088_2019-04-19_final
2019-05-13 09:27:13	ga_ls8c_ard_3-0-0_091087_2019-05-12_final
2019-05-13 09:27:37	ga_ls8c_ard_3-0-0_091088_2019-05-12_final
2019-05-15 09:14:53	ga_ls8c_ard_3-0-0_089087_2019-05-14_final
2019-05-15 09:15:17	ga_ls8c_ard_3-0-0_089088_2019-05-14_final
2019-05-31 09:15:02	ga_ls8c_ard_3-0-0_089087_2019-05-30_final
2019-05-31 09:15:26	ga_ls8c_ard_3-0-0_089088_2019-05-30_final
2019-08-01 09:27:43	ga_ls8c_ard_3-1-0_091087_2019-07-31_final
2019-08-01 09:28:07	ga_ls8c_ard_3-1-0_091088_2019-07-31_final
2019-09-02 09:27:52	ga_ls8c_ard_3-1-0_091087_2019-09-01_final
2019-09-02 09:28:16	ga_ls8c_ard_3-1-0_091088_2019-09-01_final
2019-09-09 09:34:29	ga_ls8c_ard_3-1-0_092088_2019-09-09_final
2019-09-11 09:21:44	ga_ls8c_ard_3-1-0_090087_2019-09-10_final
2019-09-11 09:22:08	ga_ls8c_ard_3-1-0_090088_2019-09-10_final
2019-10-20 09:28:28	ga_ls8c_ard_3-1-0_091088_2019-10-19_final
2022-08-07 09:40:54	ga_ls8c_ard_3-2-1_093088_2022-08-07_final
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-23 09:40:34	ga_ls8c_ard_3-2-1_093087_2022-08-23_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_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
2022-09-08 09:41:00	ga_ls8c_ard_3-2-1_093088_2022-09-08_final
2022-09-10 09:28:16	ga_ls8c_ard_3-2-1_091087_2022-09-09_final
2022-09-10 09:28:40	ga_ls8c_ard_3-2-1_091088_2022-09-09_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
2022-10-03 09:34:28	ga_ls8c_ard_3-2-1_092087_2022-10-03_final
2022-10-03 09:34:52	ga_ls8c_ard_3-2-1_092088_2022-10-03_final
2022-10-05 09:22:06	ga_ls8c_ard_3-2-1_090087_2022-10-04_final
2022-10-05 09:22:30	ga_ls8c_ard_3-2-1_090088_2022-10-04_final
2022-10-10 09:40:59	ga_ls8c_ard_3-2-1_093088_2022-10-10_final
2022-10-14 09:16:12	ga_ls8c_ard_3-2-1_089088_2022-10-13_final
2022-10-21 09:22:04	ga_ls8c_ard_3-2-1_090087_2022-10-20_final
2022-10-21 09:22:28	ga_ls8c_ard_3-2-1_090088_2022-10-20_final
2022-10-24 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-10-24_final
2022-10-26 09:41:03	ga_ls8c_ard_3-2-1_093088_2022-10-26_final
2022-10-28 09:28:42	ga_ls8c_ard_3-2-1_091088_2022-10-27_final
2022-10-30 09:16:21	ga_ls8c_ard_3-2-1_089088_2022-10-29_final
2022-11-04 09:34:54	ga_ls8c_ard_3-2-1_092088_2022-11-04_final
2022-11-06 09:22:08	ga_ls8c_ard_3-2-1_090087_2022-11-05_final
2022-11-06 09:22:31	ga_ls8c_ard_3-2-1_090088_2022-11-05_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-11 09:41:02	ga_ls8c_ard_3-2-1_093088_2022-11-11_final
2022-11-13 09:28:39	ga_ls8c_ard_3-2-1_091088_2022-11-12_final
2022-11-15 09:16:15	ga_ls8c_ard_3-2-1_089088_2022-11-14_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-20 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-11-20_final
2022-11-22 09:22:02	ga_ls8c_ard_3-2-1_090087_2022-11-21_final
2022-11-22 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-11-21_final
2022-11-27 09:40:59	ga_ls8c_ard_3-2-1_093088_2022-11-27_final
2022-11-29 09:28:38	ga_ls8c_ard_3-2-1_091088_2022-11-28_final
2022-12-01 09:16:16	ga_ls8c_ard_3-2-1_089088_2022-11-30_final
2022-12-08 09:22:02	ga_ls8c_ard_3-2-1_090087_2022-12-07_final
2022-12-08 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-12-07_final
2022-12-22 09:34:38	ga_ls8c_ard_3-2-1_092088_2022-12-22_final
2022-12-29 09:40:50	ga_ls8c_ard_3-2-1_093088_2022-12-29_final
2022-12-31 09:28:05	ga_ls8c_ard_3-2-1_091087_2022-12-30_final
2022-12-31 09:28:29	ga_ls8c_ard_3-2-1_091088_2022-12-30_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years