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
2018-02-28 09:21:12	ga_ls8c_ard_3-0-0_090087_2018-02-27_final
2018-03-05 09:39:18	ga_ls8c_ard_3-0-0_093086_2018-03-05_final
2018-03-05 09:39:42	ga_ls8c_ard_3-0-0_093087_2018-03-05_final
2018-03-07 09:27:19	ga_ls8c_ard_3-0-0_091087_2018-03-06_final
2018-03-09 09:14:56	ga_ls8c_ard_3-0-0_089087_2018-03-08_final
2018-03-10 09:58:11	ga_ls8c_ard_3-0-0_096087_2018-03-10_final
2018-03-25 09:14:49	ga_ls8c_ard_3-0-0_089087_2018-03-24_final
2018-03-26 09:58:04	ga_ls8c_ard_3-0-0_096087_2018-03-26_final
2018-04-06 09:39:26	ga_ls8c_ard_3-0-0_093087_2018-04-06_final
2018-04-08 09:27:03	ga_ls8c_ard_3-1-0_091087_2018-04-07_final
2018-04-10 09:14:41	ga_ls8c_ard_3-0-0_089087_2018-04-09_final
2018-04-11 09:57:56	ga_ls8c_ard_3-0-0_096087_2018-04-11_final
2018-04-20 09:51:39	ga_ls8c_ard_3-0-0_095087_2018-04-20_final
2018-04-22 09:39:16	ga_ls8c_ard_3-0-0_093087_2018-04-22_final
2018-04-24 09:26:54	ga_ls8c_ard_3-0-0_091087_2018-04-23_final
2018-05-10 09:26:45	ga_ls8c_ard_3-0-0_091087_2018-05-09_final
2018-05-12 09:14:22	ga_ls8c_ard_3-0-0_089087_2018-05-11_final
2018-05-13 09:57:13	ga_ls8c_ard_3-0-0_096086_2018-05-13_final
2018-05-13 09:57:37	ga_ls8c_ard_3-0-0_096087_2018-05-13_final
2018-05-19 09:20:27	ga_ls8c_ard_3-0-0_090087_2018-05-18_final
2018-05-22 09:51:19	ga_ls8c_ard_3-0-0_095087_2018-05-22_final
2018-05-24 09:38:56	ga_ls8c_ard_3-0-0_093087_2018-05-24_final
2018-05-26 09:26:32	ga_ls8c_ard_3-0-0_091087_2018-05-25_final
2018-05-28 09:14:09	ga_ls8c_ard_3-0-0_089087_2018-05-27_final
2018-05-29 09:57:24	ga_ls8c_ard_3-0-0_096087_2018-05-29_final
2018-06-04 09:19:52	ga_ls8c_ard_3-0-0_090086_2018-06-03_final
2018-06-04 09:20:16	ga_ls8c_ard_3-0-0_090087_2018-06-03_final
2018-06-05 10:03:08	ga_ls8c_ard_3-0-0_097086_2018-06-05_final
2018-06-09 09:38:27	ga_ls8c_ard_3-0-0_093086_2018-06-09_final
2018-06-09 09:38:51	ga_ls8c_ard_3-0-0_093087_2018-06-09_final
2018-06-11 09:26:07	ga_ls8c_ard_3-0-0_091086_2018-06-10_final
2018-06-11 09:26:31	ga_ls8c_ard_3-0-0_091087_2018-06-10_final
2018-06-14 09:57:27	ga_ls8c_ard_3-0-0_096087_2018-06-14_final
2018-06-20 09:20:02	ga_ls8c_ard_3-0-0_090086_2018-06-19_final
2018-06-20 09:20:26	ga_ls8c_ard_3-0-0_090087_2018-06-19_final
2018-06-21 10:03:18	ga_ls8c_ard_3-0-0_097086_2018-06-21_final
2018-06-28 10:09:33	ga_ls8c_ard_3-0-0_098086_2018-06-28_final
2018-06-29 09:13:57	ga_ls8c_ard_3-0-0_089086_2018-06-28_final
2018-06-29 09:14:21	ga_ls8c_ard_3-0-0_089087_2018-06-28_final
2018-06-30 09:57:13	ga_ls8c_ard_3-0-0_096086_2018-06-30_final
2018-06-30 09:57:37	ga_ls8c_ard_3-0-0_096087_2018-06-30_final
2018-07-11 09:38:46	ga_ls8c_ard_3-0-0_093086_2018-07-11_final
2018-07-11 09:39:10	ga_ls8c_ard_3-0-0_093087_2018-07-11_final
2018-07-13 09:26:25	ga_ls8c_ard_3-0-0_091086_2018-07-12_final
2018-07-13 09:26:49	ga_ls8c_ard_3-0-0_091087_2018-07-12_final
2018-07-16 09:57:45	ga_ls8c_ard_3-0-0_096087_2018-07-16_final
2018-07-20 09:32:39	ga_ls8c_ard_3-0-0_092086_2018-07-20_final
2018-07-20 09:33:03	ga_ls8c_ard_3-0-0_092087_2018-07-20_final
2018-07-22 09:20:18	ga_ls8c_ard_3-0-0_090086_2018-07-21_final
2018-07-22 09:20:42	ga_ls8c_ard_3-0-0_090087_2018-07-21_final
2019-10-18 09:40:01	ga_ls8c_ard_3-1-0_093086_2019-10-18_final
2019-10-18 09:40:25	ga_ls8c_ard_3-1-0_093087_2019-10-18_final
2021-04-28 09:51:58	ga_ls8c_ard_3-2-0_095087_2021-04-28_final
2021-04-30 09:39:35	ga_ls8c_ard_3-2-0_093087_2021-04-30_final
2021-05-07 09:45:42	ga_ls8c_ard_3-2-0_094087_2021-05-07_final
2021-05-09 09:32:58	ga_ls8c_ard_3-2-0_092086_2021-05-09_final
2021-05-09 09:33:22	ga_ls8c_ard_3-2-0_092087_2021-05-09_final
2021-05-11 09:20:38	ga_ls8c_ard_3-2-0_090086_2021-05-10_final
2021-05-11 09:21:02	ga_ls8c_ard_3-2-0_090087_2021-05-10_final
2021-05-12 10:03:54	ga_ls8c_ard_3-2-0_097086_2021-05-12_final
2021-07-17 09:51:55	ga_ls8c_ard_3-2-0_095086_2021-07-17_final
2021-07-17 09:52:19	ga_ls8c_ard_3-2-0_095087_2021-07-17_final
2021-07-19 09:39:34	ga_ls8c_ard_3-2-0_093086_2021-07-19_final
2021-07-19 09:39:58	ga_ls8c_ard_3-2-0_093087_2021-07-19_final
2021-07-21 09:27:38	ga_ls8c_ard_3-2-0_091087_2021-07-20_final
2021-07-22 10:10:30	ga_ls8c_ard_3-2-0_098086_2021-07-22_final
2021-07-23 09:15:17	ga_ls8c_ard_3-2-0_089087_2021-07-22_final
2021-07-24 09:58:10	ga_ls8c_ard_3-2-0_096086_2021-07-24_final
2021-07-24 09:58:34	ga_ls8c_ard_3-2-0_096087_2021-07-24_final
2021-07-26 09:45:49	ga_ls8c_ard_3-2-0_094086_2021-07-26_final
2021-07-26 09:46:13	ga_ls8c_ard_3-2-0_094087_2021-07-26_final
2021-07-28 09:33:52	ga_ls8c_ard_3-2-0_092087_2021-07-28_final
2021-07-30 09:21:32	ga_ls8c_ard_3-2-0_090087_2021-07-29_final
2021-08-02 09:52:27	ga_ls8c_ard_3-2-0_095087_2021-08-02_final
2021-08-04 09:39:42	ga_ls8c_ard_3-2-0_093086_2021-08-04_final
2021-08-04 09:40:06	ga_ls8c_ard_3-2-0_093087_2021-08-04_final
2021-08-07 10:10:38	ga_ls8c_ard_3-2-0_098086_2021-08-07_final
2021-08-08 09:15:01	ga_ls8c_ard_3-2-0_089086_2021-08-07_final
2021-08-08 09:15:25	ga_ls8c_ard_3-2-0_089087_2021-08-07_final
2021-08-09 09:58:41	ga_ls8c_ard_3-2-0_096087_2021-08-09_final
2021-08-11 09:45:56	ga_ls8c_ard_3-2-0_094086_2021-08-11_final
2021-08-11 09:46:20	ga_ls8c_ard_3-2-0_094087_2021-08-11_final
2021-08-13 09:33:35	ga_ls8c_ard_3-2-0_092086_2021-08-13_final
2021-08-13 09:33:59	ga_ls8c_ard_3-2-0_092087_2021-08-13_final
2021-08-15 09:21:38	ga_ls8c_ard_3-2-0_090087_2021-08-14_final
2021-09-08 10:10:48	ga_ls8c_ard_3-2-0_098086_2021-09-08_final
2021-09-09 09:15:34	ga_ls8c_ard_3-2-0_089087_2021-09-08_final
2021-09-10 09:58:26	ga_ls8c_ard_3-2-0_096086_2021-09-10_final
2021-09-10 09:58:50	ga_ls8c_ard_3-2-0_096087_2021-09-10_final
2021-09-12 09:46:05	ga_ls8c_ard_3-2-0_094086_2021-09-12_final
2021-09-12 09:46:29	ga_ls8c_ard_3-2-0_094087_2021-09-12_final
2021-09-14 09:34:08	ga_ls8c_ard_3-2-0_092087_2021-09-14_final
2021-10-09 09:27:40	ga_ls8c_ard_3-2-0_091086_2021-10-08_final
2021-10-09 09:28:04	ga_ls8c_ard_3-2-0_091087_2021-10-08_final
2021-10-10 10:10:56	ga_ls8c_ard_3-2-0_098086_2021-10-10_final
2021-10-11 09:15:19	ga_ls8c_ard_3-2-0_089086_2021-10-10_final
2021-10-11 09:15:43	ga_ls8c_ard_3-2-0_089087_2021-10-10_final
2021-10-12 09:58:59	ga_ls8c_ard_3-2-0_096087_2021-10-12_final
2021-10-14 09:46:14	ga_ls8c_ard_3-2-0_094086_2021-10-14_final
2021-10-14 09:46:38	ga_ls8c_ard_3-2-0_094087_2021-10-14_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