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
2019-03-10 09:26:06	ga_ls8c_ard_3-1-0_091084_2019-03-09_final
2019-03-22 09:47:35	ga_ls8c_ard_3-1-0_095076_2019-03-22_final
2019-03-22 09:49:34	ga_ls8c_ard_3-1-0_095081_2019-03-22_final
2019-04-07 09:47:07	ga_ls8c_ard_3-1-0_095075_2019-04-07_final
2019-04-07 09:48:43	ga_ls8c_ard_3-1-0_095079_2019-04-07_final
2019-07-12 09:47:56	ga_ls8c_ard_3-1-0_095076_2019-07-12_final
2019-07-12 09:49:32	ga_ls8c_ard_3-1-0_095080_2019-07-12_final
2019-07-12 09:49:56	ga_ls8c_ard_3-1-0_095081_2019-07-12_final
2019-08-13 09:48:07	ga_ls8c_ard_3-1-0_095076_2019-08-13_final
2019-08-13 09:48:31	ga_ls8c_ard_3-1-0_095077_2019-08-13_final
2019-08-13 09:50:55	ga_ls8c_ard_3-1-0_095083_2019-08-13_final
2019-08-29 09:47:23	ga_ls8c_ard_3-1-0_095074_2019-08-29_final
2019-08-29 09:49:47	ga_ls8c_ard_3-1-0_095080_2019-08-29_final
2019-09-14 09:48:16	ga_ls8c_ard_3-1-0_095076_2019-09-14_final
2019-09-14 09:48:40	ga_ls8c_ard_3-1-0_095077_2019-09-14_final
2019-09-18 09:24:46	ga_ls8c_ard_3-1-0_091079_2019-09-17_final
2019-09-18 09:26:22	ga_ls8c_ard_3-1-0_091083_2019-09-17_final
2019-09-30 09:47:57	ga_ls8c_ard_3-1-0_095075_2019-09-30_final
2019-09-30 09:51:09	ga_ls8c_ard_3-1-0_095083_2019-09-30_final
2019-10-04 09:24:50	ga_ls8c_ard_3-1-0_091079_2019-10-03_final
2019-10-16 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-10-16_final
2019-11-01 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-11-01_final
2019-11-01 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-11-01_final
2019-11-01 09:51:35	ga_ls8c_ard_3-1-0_095084_2019-11-01_final
2019-11-17 09:48:20	ga_ls8c_ard_3-1-0_095076_2019-11-17_final
2019-12-03 09:49:07	ga_ls8c_ard_3-1-0_095078_2019-12-03_final
2019-12-23 09:26:44	ga_ls8c_ard_3-1-0_091084_2019-12-22_final
2020-01-20 09:48:57	ga_ls8c_ard_3-1-0_095078_2020-01-20_final
2020-01-20 09:49:45	ga_ls8c_ard_3-1-0_095080_2020-01-20_final
2020-02-05 09:49:39	ga_ls8c_ard_3-1-0_095080_2020-02-05_final
2020-02-25 09:28:27	ga_ls8c_ard_3-1-0_091089_2020-02-24_final
2020-04-09 09:50:26	ga_ls8c_ard_3-1-0_095083_2020-04-09_final
2020-04-25 09:47:31	ga_ls8c_ard_3-1-0_095076_2020-04-25_final
2022-03-30 09:48:08	ga_ls8c_ard_3-2-1_095077_2022-03-30_final
2022-03-30 09:49:20	ga_ls8c_ard_3-2-1_095080_2022-03-30_final
2022-04-01 09:36:34	ga_ls8c_ard_3-2-1_093079_2022-04-01_final
2022-04-01 09:36:58	ga_ls8c_ard_3-2-1_093080_2022-04-01_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-07 10:36:50	ga_ls8c_ard_3-2-1_103075_2022-04-07_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-08 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-08_final
2022-04-08 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-08_final
2022-04-08 09:43:12	ga_ls8c_ard_3-2-1_094080_2022-04-08_final
2022-04-08 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-08_final
2022-04-10 09:30:28	ga_ls8c_ard_3-2-1_092079_2022-04-10_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-11 10:11:44	ga_ls8c_ard_3-2-1_099074_2022-04-11_final
2022-04-12 10:57:00	ga_ls8c_ard_3-2-1_106079_2022-04-12_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-15 09:51:02	ga_ls8c_ard_3-2-1_095084_2022-04-15_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-17 09:37:04	ga_ls8c_ard_3-2-1_093080_2022-04-17_final
2022-04-17 11:14:21	ga_ls8c_ard_3-2-1_109076_2022-04-17_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-22 11:33:16	ga_ls8c_ard_3-2-1_112077_2022-04-22_final
2022-04-23 10:36:27	ga_ls8c_ard_3-2-1_103074_2022-04-23_final
2022-04-23 10:36:51	ga_ls8c_ard_3-2-1_103075_2022-04-23_final
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-06 10:08:47	ga_ls8c_ard_3-2-1_098082_2022-05-06_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-08 11:33:20	ga_ls8c_ard_3-2-1_112077_2022-05-08_final
2022-05-08 11:33:44	ga_ls8c_ard_3-2-1_112078_2022-05-08_final
2022-05-09 10:36:31	ga_ls8c_ard_3-2-1_103074_2022-05-09_final
2022-05-09 10:36:55	ga_ls8c_ard_3-2-1_103075_2022-05-09_final
2022-05-09 10:38:07	ga_ls8c_ard_3-2-1_103078_2022-05-09_final
2022-05-09 10:38:31	ga_ls8c_ard_3-2-1_103079_2022-05-09_final
2022-05-10 11:21:00	ga_ls8c_ard_3-2-1_110077_2022-05-10_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-16 10:45:09	ga_ls8c_ard_3-2-1_104080_2022-05-16_final
2022-05-17 09:49:08	ga_ls8c_ard_3-2-1_095079_2022-05-17_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-24 09:54:55	ga_ls8c_ard_3-2-1_096078_2022-05-24_final
2022-05-24 09:56:31	ga_ls8c_ard_3-2-1_096082_2022-05-24_final
2022-05-24 11:32:36	ga_ls8c_ard_3-2-1_112075_2022-05-24_final
2022-05-24 11:33:00	ga_ls8c_ard_3-2-1_112076_2022-05-24_final
2022-05-24 11:33:24	ga_ls8c_ard_3-2-1_112077_2022-05-24_final
2022-05-24 11:34:36	ga_ls8c_ard_3-2-1_112080_2022-05-24_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-01 10:41:37	ga_ls8c_ard_3-2-1_104071_2022-06-01_final
2022-06-02 09:48:24	ga_ls8c_ard_3-2-1_095077_2022-06-02_final
2022-06-02 11:28:29	ga_ls8c_ard_3-2-1_111080_2022-06-02_final
2022-06-07 10:09:01	ga_ls8c_ard_3-2-1_098082_2022-06-07_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-06-13 11:10:05	ga_ls8c_ard_3-2-1_108080_2022-06-13_final
2022-06-16 10:00:56	ga_ls8c_ard_3-2-1_097077_2022-06-16_final
2022-06-16 10:02:56	ga_ls8c_ard_3-2-1_097082_2022-06-16_final
2022-06-17 10:41:49	ga_ls8c_ard_3-2-1_104071_2022-06-17_final
2022-06-17 10:45:24	ga_ls8c_ard_3-2-1_104080_2022-06-17_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