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
2014-05-21 10:22:59	ga_ls8c_ard_3-1-0_101072_2014-05-21_final
2016-07-08 10:08:50	ga_ls8c_ard_3-1-0_098082_2016-07-08_final
2016-08-26 10:51:09	ga_ls8c_ard_3-1-0_105079_2016-08-26_final
2018-07-14 10:05:18	ga_ls8c_ard_3-1-0_098075_2018-07-14_final
2019-03-10 09:24:06	ga_ls8c_ard_3-1-0_091079_2019-03-09_final
2019-03-12 10:50:13	ga_ls8c_ard_3-1-0_105078_2019-03-12_final
2019-03-27 10:08:30	ga_ls8c_ard_3-1-0_098082_2019-03-27_final
2019-03-28 10:50:09	ga_ls8c_ard_3-1-0_105078_2019-03-28_final
2019-04-02 11:08:41	ga_ls8c_ard_3-1-0_108078_2019-04-02_final
2019-04-08 10:32:22	ga_ls8c_ard_3-1-0_102080_2019-04-08_final
2019-04-14 11:32:32	ga_ls8c_ard_3-1-0_112076_2019-04-14_final
2019-04-18 11:08:35	ga_ls8c_ard_3-1-0_108078_2019-04-18_final
2019-06-17 09:54:01	ga_ls8c_ard_3-1-0_096076_2019-06-17_final
2019-06-17 11:33:18	ga_ls8c_ard_3-1-0_112077_2019-06-17_final
2019-06-27 10:31:57	ga_ls8c_ard_3-1-0_102078_2019-06-27_final
2019-06-29 11:58:05	ga_ls8c_ard_3-1-0_116077_2019-06-29_final
2019-07-03 11:33:22	ga_ls8c_ard_3-1-0_112077_2019-07-03_final
2019-07-09 10:58:42	ga_ls8c_ard_3-1-0_106083_2019-07-09_final
2019-07-12 11:27:13	ga_ls8c_ard_3-1-0_111077_2019-07-12_final
2019-07-13 10:31:12	ga_ls8c_ard_3-1-0_102076_2019-07-13_final
2019-07-19 11:33:49	ga_ls8c_ard_3-1-0_112078_2019-07-19_final
2019-07-23 11:08:44	ga_ls8c_ard_3-1-0_108077_2019-07-23_final
2019-07-23 11:09:08	ga_ls8c_ard_3-1-0_108078_2019-07-23_final
2019-07-28 11:27:18	ga_ls8c_ard_3-1-0_111077_2019-07-28_final
2019-07-28 11:27:42	ga_ls8c_ard_3-1-0_111078_2019-07-28_final
2019-07-29 10:32:05	ga_ls8c_ard_3-1-0_102078_2019-07-29_final
2019-07-31 11:58:14	ga_ls8c_ard_3-1-0_116077_2019-07-31_final
2019-08-02 10:06:12	ga_ls8c_ard_3-1-0_098075_2019-08-02_final
2019-08-07 10:27:10	ga_ls8c_ard_3-1-0_101081_2019-08-07_final
2019-08-13 09:48:31	ga_ls8c_ard_3-1-0_095077_2019-08-13_final
2019-08-13 11:27:48	ga_ls8c_ard_3-1-0_111078_2019-08-13_final
2019-08-14 10:31:23	ga_ls8c_ard_3-1-0_102076_2019-08-14_final
2019-08-14 10:32:59	ga_ls8c_ard_3-1-0_102080_2019-08-14_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
2019-08-24 11:08:55	ga_ls8c_ard_3-1-0_108077_2019-08-24_final
2019-08-29 09:49:23	ga_ls8c_ard_3-1-0_095079_2019-08-29_final
2019-08-29 11:27:28	ga_ls8c_ard_3-1-0_111077_2019-08-29_final
2019-08-29 11:27:52	ga_ls8c_ard_3-1-0_111078_2019-08-29_final
2019-08-30 10:33:03	ga_ls8c_ard_3-1-0_102080_2019-08-30_final
2019-09-01 11:58:23	ga_ls8c_ard_3-1-0_116077_2019-09-01_final
2019-09-04 10:50:48	ga_ls8c_ard_3-1-0_105078_2019-09-04_final
2019-09-05 09:54:23	ga_ls8c_ard_3-1-0_096076_2019-09-05_final
2019-09-05 09:54:47	ga_ls8c_ard_3-1-0_096077_2019-09-05_final
2019-09-05 11:34:52	ga_ls8c_ard_3-1-0_112080_2019-09-05_final
2019-09-25 09:30:35	ga_ls8c_ard_3-1-0_092078_2019-09-25_final
2019-09-25 09:30:59	ga_ls8c_ard_3-1-0_092079_2019-09-25_final
2019-09-25 11:05:53	ga_ls8c_ard_3-1-0_108069_2019-09-25_final
2019-09-25 11:09:04	ga_ls8c_ard_3-1-0_108077_2019-09-25_final
2019-09-30 11:28:26	ga_ls8c_ard_3-1-0_111079_2019-09-30_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
2019-10-16 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-10-16_final
2019-10-17 10:33:15	ga_ls8c_ard_3-1-0_102080_2019-10-17_final
2019-10-22 10:51:00	ga_ls8c_ard_3-1-0_105078_2019-10-22_final
2019-10-23 09:54:35	ga_ls8c_ard_3-1-0_096076_2019-10-23_final
2019-11-01 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-11-01_final
2019-11-07 10:50:58	ga_ls8c_ard_3-1-0_105078_2019-11-07_final
2019-11-08 09:54:33	ga_ls8c_ard_3-1-0_096076_2019-11-08_final
2019-11-17 09:49:08	ga_ls8c_ard_3-1-0_095078_2019-11-17_final
2019-11-17 09:49:32	ga_ls8c_ard_3-1-0_095079_2019-11-17_final
2019-11-28 11:09:04	ga_ls8c_ard_3-1-0_108077_2019-11-28_final
2019-12-03 09:49:31	ga_ls8c_ard_3-1-0_095079_2019-12-03_final
2019-12-10 09:54:29	ga_ls8c_ard_3-1-0_096076_2019-12-10_final
2019-12-30 09:35:17	ga_ls8c_ard_3-1-0_092090_2019-12-30_final
2019-12-30 11:08:58	ga_ls8c_ard_3-1-0_108077_2019-12-30_final
2020-01-08 09:24:40	ga_ls8c_ard_3-1-0_091079_2020-01-07_final
2020-01-21 10:30:37	ga_ls8c_ard_3-1-0_102074_2020-01-21_final
2020-02-21 09:48:48	ga_ls8c_ard_3-1-0_095078_2020-02-21_final
2020-02-21 09:49:12	ga_ls8c_ard_3-1-0_095079_2020-02-21_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
2020-04-14 10:08:32	ga_ls8c_ard_3-1-0_098082_2020-04-14_final
2020-04-16 09:53:46	ga_ls8c_ard_3-1-0_096076_2020-04-16_final
2020-04-19 10:26:39	ga_ls8c_ard_3-1-0_101081_2020-04-19_final
2020-05-06 09:31:40	ga_ls8c_ard_3-1-0_092083_2020-05-06_final
2020-05-06 11:08:33	ga_ls8c_ard_3-1-0_108078_2020-05-06_final
2022-03-30 09:48:56	ga_ls8c_ard_3-2-1_095079_2022-03-30_final
2022-04-06 09:54:21	ga_ls8c_ard_3-2-1_096077_2022-04-06_final
2022-04-08 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-08_final
2022-04-15 09:48:14	ga_ls8c_ard_3-2-1_095077_2022-04-15_final
2022-04-15 09:49:02	ga_ls8c_ard_3-2-1_095079_2022-04-15_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-22 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-22 09:54:23	ga_ls8c_ard_3-2-1_096077_2022-04-22_final
2022-04-22 09:54:47	ga_ls8c_ard_3-2-1_096078_2022-04-22_final
2022-04-22 11:33:16	ga_ls8c_ard_3-2-1_112077_2022-04-22_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-26 11:08:07	ga_ls8c_ard_3-2-1_108076_2022-04-26_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-08 11:34:32	ga_ls8c_ard_3-2-1_112080_2022-05-08_final
2022-05-09 10:38:55	ga_ls8c_ard_3-2-1_103080_2022-05-09_final
2022-05-10 11:21:47	ga_ls8c_ard_3-2-1_110079_2022-05-10_final
2022-05-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2022-05-17_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-25 10:38:58	ga_ls8c_ard_3-2-1_103080_2022-05-25_final
2022-06-02 09:48:48	ga_ls8c_ard_3-2-1_095078_2022-06-02_final
2022-06-02 11:28:05	ga_ls8c_ard_3-2-1_111079_2022-06-02_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