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
2015-01-08 09:40:29	ga_ls8c_ard_3-0-0_093088_2015-01-08_final
2015-01-24 09:40:22	ga_ls8c_ard_3-0-0_093088_2015-01-24_final
2015-02-09 09:40:19	ga_ls8c_ard_3-0-0_093088_2015-02-09_final
2015-02-27 09:27:51	ga_ls8c_ard_3-0-0_091088_2015-02-26_final
2015-03-08 09:21:34	ga_ls8c_ard_3-0-0_090088_2015-03-07_final
2015-03-11 09:52:25	ga_ls8c_ard_3-0-0_095088_2015-03-11_final
2015-03-13 09:40:02	ga_ls8c_ard_3-0-0_093088_2015-03-13_final
2015-03-24 09:21:25	ga_ls8c_ard_3-0-0_090088_2015-03-23_final
2015-03-29 09:39:54	ga_ls8c_ard_3-0-0_093088_2015-03-29_final
2015-03-31 09:27:30	ga_ls8c_ard_3-0-0_091088_2015-03-30_final
2015-04-12 09:52:10	ga_ls8c_ard_3-0-0_095088_2015-04-12_final
2015-08-27 09:46:24	ga_ls8c_ard_3-0-0_094088_2015-08-27_final
2015-08-29 09:33:39	ga_ls8c_ard_3-0-0_092087_2015-08-29_final
2015-08-29 09:34:03	ga_ls8c_ard_3-0-0_092088_2015-08-29_final
2015-09-19 09:52:45	ga_ls8c_ard_3-0-0_095088_2015-09-19_final
2015-09-21 09:40:24	ga_ls8c_ard_3-0-0_093088_2015-09-21_final
2015-09-23 09:28:03	ga_ls8c_ard_3-0-0_091088_2015-09-22_final
2015-09-28 09:46:13	ga_ls8c_ard_3-0-0_094087_2015-09-28_final
2015-09-28 09:46:37	ga_ls8c_ard_3-0-0_094088_2015-09-28_final
2015-10-05 09:52:25	ga_ls8c_ard_3-0-0_095087_2015-10-05_final
2015-10-05 09:52:48	ga_ls8c_ard_3-0-0_095088_2015-10-05_final
2015-10-07 09:40:03	ga_ls8c_ard_3-0-0_093087_2015-10-07_final
2015-10-07 09:40:27	ga_ls8c_ard_3-0-0_093088_2015-10-07_final
2015-10-09 09:28:05	ga_ls8c_ard_3-0-0_091088_2015-10-08_final
2015-10-11 09:15:43	ga_ls8c_ard_3-0-0_089088_2015-10-10_final
2015-10-16 09:33:51	ga_ls8c_ard_3-0-0_092087_2015-10-16_final
2015-10-16 09:34:15	ga_ls8c_ard_3-0-0_092088_2015-10-16_final
2015-10-18 09:21:31	ga_ls8c_ard_3-0-0_090087_2015-10-17_final
2015-10-18 09:21:55	ga_ls8c_ard_3-0-0_090088_2015-10-17_final
2015-10-21 09:52:51	ga_ls8c_ard_3-0-0_095088_2015-10-21_final
2015-10-23 09:40:06	ga_ls8c_ard_3-0-0_093087_2015-10-23_final
2015-10-23 09:40:30	ga_ls8c_ard_3-0-0_093088_2015-10-23_final
2015-10-25 09:28:09	ga_ls8c_ard_3-0-0_091088_2015-10-24_final
2015-11-10 09:28:11	ga_ls8c_ard_3-0-0_091088_2015-11-09_final
2015-11-13 09:58:40	ga_ls8c_ard_3-0-0_096087_2015-11-13_final
2015-11-15 09:46:43	ga_ls8c_ard_3-0-0_094088_2015-11-15_final
2015-11-26 09:28:13	ga_ls8c_ard_3-0-0_091088_2015-11-25_final
2015-11-28 09:15:52	ga_ls8c_ard_3-0-0_089088_2015-11-27_final
2015-12-01 09:46:45	ga_ls8c_ard_3-0-0_094088_2015-12-01_final
2015-12-03 09:34:24	ga_ls8c_ard_3-0-0_092088_2015-12-03_final
2015-12-05 09:22:01	ga_ls8c_ard_3-0-0_090088_2015-12-04_final
2015-12-21 09:22:02	ga_ls8c_ard_3-0-0_090088_2015-12-20_final
2022-02-07 09:22:01	ga_ls8c_ard_3-2-1_090088_2022-02-06_final
2022-02-12 09:40:32	ga_ls8c_ard_3-2-1_093088_2022-02-12_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
2022-02-28 09:40:27	ga_ls8c_ard_3-2-1_093088_2022-02-28_final
2022-03-02 09:28:05	ga_ls8c_ard_3-2-1_091088_2022-03-01_final
2022-03-04 09:15:43	ga_ls8c_ard_3-2-1_089088_2022-03-03_final
2022-03-09 09:34:14	ga_ls8c_ard_3-2-1_092088_2022-03-09_final
2022-03-11 09:21:52	ga_ls8c_ard_3-2-1_090088_2022-03-10_final
2022-03-16 09:40:21	ga_ls8c_ard_3-2-1_093088_2022-03-16_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
2022-03-27 09:21:40	ga_ls8c_ard_3-2-1_090088_2022-03-26_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
2022-04-24 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-24_final
2022-04-28 09:21:39	ga_ls8c_ard_3-2-1_090088_2022-04-27_final
2022-05-01 09:52:10	ga_ls8c_ard_3-2-1_095087_2022-05-01_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-05 09:27:54	ga_ls8c_ard_3-2-1_091088_2022-05-04_final
2022-05-07 09:15:34	ga_ls8c_ard_3-2-1_089088_2022-05-06_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-12 09:34:09	ga_ls8c_ard_3-2-1_092088_2022-05-12_final
2022-05-14 09:21:49	ga_ls8c_ard_3-2-1_090088_2022-05-13_final
2022-05-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2022-05-17_final
2022-05-19 09:39:58	ga_ls8c_ard_3-2-1_093087_2022-05-19_final
2022-05-19 09:40:22	ga_ls8c_ard_3-2-1_093088_2022-05-19_final
2022-05-21 09:28:01	ga_ls8c_ard_3-2-1_091088_2022-05-20_final
2022-06-15 09:21:40	ga_ls8c_ard_3-2-1_090087_2022-06-14_final
2022-06-15 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-06-14_final
2022-07-15 09:34:28	ga_ls8c_ard_3-2-1_092088_2022-07-15_final
2022-07-17 09:22:07	ga_ls8c_ard_3-2-1_090088_2022-07-16_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
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_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
2022-08-11 09:16:13	ga_ls8c_ard_3-2-1_089088_2022-08-10_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
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_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 09:22:31	ga_ls8c_ard_3-2-1_090088_2022-11-05_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