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
2015-02-08 10:29:58	ga_ls8c_ard_3-1-0_102073_2015-02-08_final
2016-03-21 10:38:25	ga_ls8c_ard_3-1-0_103079_2016-03-21_final
2016-08-09 10:08:58	ga_ls8c_ard_3-1-0_098082_2016-08-09_final
2019-03-22 09:48:22	ga_ls8c_ard_3-1-0_095078_2019-03-22_final
2019-03-23 10:32:26	ga_ls8c_ard_3-1-0_102080_2019-03-23_final
2019-03-29 09:53:20	ga_ls8c_ard_3-1-0_096075_2019-03-29_final
2019-03-29 11:32:37	ga_ls8c_ard_3-1-0_112076_2019-03-29_final
2019-03-30 10:36:35	ga_ls8c_ard_3-1-0_103075_2019-03-30_final
2019-04-01 10:25:49	ga_ls8c_ard_3-1-0_101079_2019-04-01_final
2019-04-01 10:26:13	ga_ls8c_ard_3-1-0_101080_2019-04-01_final
2019-04-05 10:02:17	ga_ls8c_ard_3-1-0_097082_2019-04-05_final
2019-04-07 09:48:19	ga_ls8c_ard_3-1-0_095078_2019-04-07_final
2019-04-07 11:27:36	ga_ls8c_ard_3-1-0_111079_2019-04-07_final
2019-04-14 11:32:56	ga_ls8c_ard_3-1-0_112077_2019-04-14_final
2019-04-15 10:36:30	ga_ls8c_ard_3-1-0_103075_2019-04-15_final
2019-04-17 10:25:44	ga_ls8c_ard_3-1-0_101079_2019-04-17_final
2019-04-18 11:08:11	ga_ls8c_ard_3-1-0_108077_2019-04-18_final
2019-06-17 11:34:06	ga_ls8c_ard_3-1-0_112079_2019-06-17_final
2019-06-17 11:36:06	ga_ls8c_ard_3-1-0_112084_2019-06-17_final
2019-06-23 10:58:15	ga_ls8c_ard_3-1-0_106082_2019-06-23_final
2019-06-26 09:48:17	ga_ls8c_ard_3-1-0_095077_2019-06-26_final
2019-06-26 09:48:41	ga_ls8c_ard_3-1-0_095078_2019-06-26_final
2019-06-26 11:27:34	ga_ls8c_ard_3-1-0_111078_2019-06-26_final
2019-06-26 11:27:58	ga_ls8c_ard_3-1-0_111079_2019-06-26_final
2019-06-27 10:31:09	ga_ls8c_ard_3-1-0_102076_2019-06-27_final
2019-07-03 09:54:05	ga_ls8c_ard_3-1-0_096076_2019-07-03_final
2019-07-03 11:32:58	ga_ls8c_ard_3-1-0_112076_2019-07-03_final
2019-07-03 11:33:46	ga_ls8c_ard_3-1-0_112078_2019-07-03_final
2019-07-03 11:34:10	ga_ls8c_ard_3-1-0_112079_2019-07-03_final
2019-07-06 10:26:12	ga_ls8c_ard_3-1-0_101079_2019-07-06_final
2019-07-09 09:18:37	ga_ls8c_ard_3-1-0_090080_2019-07-08_final
2019-07-12 09:48:20	ga_ls8c_ard_3-1-0_095077_2019-07-12_final
2019-07-12 09:48:44	ga_ls8c_ard_3-1-0_095078_2019-07-12_final
2019-07-12 11:28:01	ga_ls8c_ard_3-1-0_111079_2019-07-12_final
2019-07-19 09:54:08	ga_ls8c_ard_3-1-0_096076_2019-07-19_final
2019-07-19 09:54:32	ga_ls8c_ard_3-1-0_096077_2019-07-19_final
2019-07-19 11:33:49	ga_ls8c_ard_3-1-0_112078_2019-07-19_final
2019-07-19 11:34:13	ga_ls8c_ard_3-1-0_112079_2019-07-19_final
2019-07-22 10:26:15	ga_ls8c_ard_3-1-0_101079_2019-07-22_final
2019-07-28 09:48:25	ga_ls8c_ard_3-1-0_095077_2019-07-28_final
2019-07-28 09:48:49	ga_ls8c_ard_3-1-0_095078_2019-07-28_final
2019-07-28 11:28:06	ga_ls8c_ard_3-1-0_111079_2019-07-28_final
2019-07-29 10:33:41	ga_ls8c_ard_3-1-0_102082_2019-07-29_final
2019-08-04 09:54:15	ga_ls8c_ard_3-1-0_096076_2019-08-04_final
2019-08-04 09:54:39	ga_ls8c_ard_3-1-0_096077_2019-08-04_final
2019-08-04 11:33:56	ga_ls8c_ard_3-1-0_112078_2019-08-04_final
2019-08-04 11:34:20	ga_ls8c_ard_3-1-0_112079_2019-08-04_final
2019-08-13 09:48:31	ga_ls8c_ard_3-1-0_095077_2019-08-13_final
2019-08-13 09:48:55	ga_ls8c_ard_3-1-0_095078_2019-08-13_final
2019-08-13 11:27:48	ga_ls8c_ard_3-1-0_111078_2019-08-13_final
2019-08-13 11:28:12	ga_ls8c_ard_3-1-0_111079_2019-08-13_final
2019-08-20 09:54:20	ga_ls8c_ard_3-1-0_096076_2019-08-20_final
2019-08-20 09:54:44	ga_ls8c_ard_3-1-0_096077_2019-08-20_final
2019-08-20 11:34:01	ga_ls8c_ard_3-1-0_112078_2019-08-20_final
2019-08-20 11:34:25	ga_ls8c_ard_3-1-0_112079_2019-08-20_final
2019-08-24 11:08:55	ga_ls8c_ard_3-1-0_108077_2019-08-24_final
2019-08-27 10:00:09	ga_ls8c_ard_3-1-0_097075_2019-08-27_final
2019-08-29 09:48:59	ga_ls8c_ard_3-1-0_095078_2019-08-29_final
2019-08-29 11:27:52	ga_ls8c_ard_3-1-0_111078_2019-08-29_final
2019-08-30 10:31:27	ga_ls8c_ard_3-1-0_102076_2019-08-30_final
2019-09-03 10:09:08	ga_ls8c_ard_3-1-0_098082_2019-09-03_final
2019-09-05 09:54:23	ga_ls8c_ard_3-1-0_096076_2019-09-05_final
2019-09-05 11:33:16	ga_ls8c_ard_3-1-0_112076_2019-09-05_final
2019-09-12 10:00:13	ga_ls8c_ard_3-1-0_097075_2019-09-12_final
2019-09-14 09:49:04	ga_ls8c_ard_3-1-0_095078_2019-09-14_final
2019-09-14 11:27:57	ga_ls8c_ard_3-1-0_111078_2019-09-14_final
2019-09-15 10:32:20	ga_ls8c_ard_3-1-0_102078_2019-09-15_final
2019-09-21 09:54:29	ga_ls8c_ard_3-1-0_096076_2019-09-21_final
2019-09-28 10:00:18	ga_ls8c_ard_3-1-0_097075_2019-09-28_final
2019-10-01 10:33:13	ga_ls8c_ard_3-1-0_102080_2019-10-01_final
2019-10-07 09:54:33	ga_ls8c_ard_3-1-0_096076_2019-10-07_final
2019-10-10 10:27:03	ga_ls8c_ard_3-1-0_101080_2019-10-10_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2019-10-27 11:09:08	ga_ls8c_ard_3-1-0_108077_2019-10-27_final
2019-10-29 09:23:29	ga_ls8c_ard_3-1-0_090091_2019-10-28_final
2019-11-12 11:09:06	ga_ls8c_ard_3-1-0_108077_2019-11-12_final
2019-11-14 10:58:20	ga_ls8c_ard_3-1-0_106081_2019-11-14_final
2019-11-28 11:09:04	ga_ls8c_ard_3-1-0_108077_2019-11-28_final
2019-12-30 11:08:58	ga_ls8c_ard_3-1-0_108077_2019-12-30_final
2020-01-27 09:52:18	ga_ls8c_ard_3-1-0_096071_2020-01-27_final
2020-03-15 11:33:19	ga_ls8c_ard_3-1-0_112077_2020-03-15_final
2020-03-19 11:08:34	ga_ls8c_ard_3-1-0_108077_2020-03-19_final
2020-03-24 09:48:35	ga_ls8c_ard_3-1-0_095078_2020-03-24_final
2020-03-31 09:53:53	ga_ls8c_ard_3-1-0_096076_2020-03-31_final
2020-04-10 10:30:54	ga_ls8c_ard_3-1-0_102076_2020-04-10_final
2020-04-16 09:53:46	ga_ls8c_ard_3-1-0_096076_2020-04-16_final
2020-04-16 11:32:39	ga_ls8c_ard_3-1-0_112076_2020-04-16_final
2020-04-25 09:47:55	ga_ls8c_ard_3-1-0_095077_2020-04-25_final
2020-04-25 09:48:19	ga_ls8c_ard_3-1-0_095078_2020-04-25_final
2020-05-02 11:32:31	ga_ls8c_ard_3-1-0_112076_2020-05-02_final
2020-05-05 10:25:42	ga_ls8c_ard_3-1-0_101079_2020-05-05_final
2020-05-06 11:08:09	ga_ls8c_ard_3-1-0_108077_2020-05-06_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 11:32:50	ga_ls8c_ard_3-2-1_112076_2022-04-06_final
2022-04-10 11:08:33	ga_ls8c_ard_3-2-1_108077_2022-04-10_final
2022-04-25 10:23:16	ga_ls8c_ard_3-2-1_101072_2022-04-25_final
2022-05-05 11:04:00	ga_ls8c_ard_3-2-1_107081_2022-05-05_final
2022-05-24 11:33:24	ga_ls8c_ard_3-2-1_112077_2022-05-24_final
2022-06-13 11:09:17	ga_ls8c_ard_3-2-1_108078_2022-06-13_final
2022-06-18 09:48:36	ga_ls8c_ard_3-2-1_095077_2022-06-18_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