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
2016-08-06 09:39:15	ga_ls8c_ard_3-0-0_093085_2016-08-06_final
2016-08-06 09:39:39	ga_ls8c_ard_3-0-0_093086_2016-08-06_final
2016-08-06 09:40:03	ga_ls8c_ard_3-0-0_093087_2016-08-06_final
2016-08-06 09:40:27	ga_ls8c_ard_3-0-0_093088_2016-08-06_final
2017-12-18 10:02:44	ga_ls8c_ard_3-2-1_098066_2017-12-18_final
2017-12-18 10:03:08	ga_ls8c_ard_3-0-0_098067_2017-12-18_final
2017-12-18 10:03:32	ga_ls8c_ard_3-0-0_098068_2017-12-18_final
2017-12-18 10:03:56	ga_ls8c_ard_3-0-0_098069_2017-12-18_final
2017-12-20 09:53:11	ga_ls8c_ard_3-0-0_096073_2017-12-20_final
2017-12-20 09:53:35	ga_ls8c_ard_3-0-0_096074_2017-12-20_final
2017-12-20 09:53:59	ga_ls8c_ard_3-0-0_096075_2017-12-20_final
2017-12-20 09:54:22	ga_ls8c_ard_3-0-0_096076_2017-12-20_final
2017-12-20 09:54:46	ga_ls8c_ard_3-0-0_096077_2017-12-20_final
2017-12-20 09:55:10	ga_ls8c_ard_3-0-0_096078_2017-12-20_final
2017-12-20 09:55:34	ga_ls8c_ard_3-0-0_096079_2017-12-20_final
2018-01-03 10:03:05	ga_ls8c_ard_3-0-0_098067_2018-01-03_final
2018-01-03 10:03:29	ga_ls8c_ard_3-0-0_098068_2018-01-03_final
2018-01-03 10:03:53	ga_ls8c_ard_3-0-0_098069_2018-01-03_final
2018-01-05 09:53:07	ga_ls8c_ard_3-0-0_096073_2018-01-05_final
2018-01-05 09:53:31	ga_ls8c_ard_3-0-0_096074_2018-01-05_final
2018-01-05 09:53:55	ga_ls8c_ard_3-0-0_096075_2018-01-05_final
2018-01-05 09:54:18	ga_ls8c_ard_3-0-0_096076_2018-01-05_final
2018-01-05 09:54:42	ga_ls8c_ard_3-0-0_096077_2018-01-05_final
2018-01-05 09:55:06	ga_ls8c_ard_3-0-0_096078_2018-01-05_final
2018-01-05 09:55:30	ga_ls8c_ard_3-0-0_096079_2018-01-05_final
2019-07-10 09:57:30	ga_ls8c_ard_3-1-0_097069_2019-07-10_final
2019-07-10 09:57:54	ga_ls8c_ard_3-1-0_097070_2019-07-10_final
2019-07-10 09:58:18	ga_ls8c_ard_3-1-0_097071_2019-07-10_final
2019-07-10 09:58:42	ga_ls8c_ard_3-1-0_097072_2019-07-10_final
2019-07-10 09:59:06	ga_ls8c_ard_3-1-0_097073_2019-07-10_final
2019-07-10 09:59:30	ga_ls8c_ard_3-1-0_097074_2019-07-10_final
2019-09-16 09:39:31	ga_ls8c_ard_3-1-0_093085_2019-09-16_final
2019-09-16 09:39:55	ga_ls8c_ard_3-1-0_093086_2019-09-16_final
2019-09-16 09:40:19	ga_ls8c_ard_3-1-0_093087_2019-09-16_final
2019-09-16 09:40:43	ga_ls8c_ard_3-1-0_093088_2019-09-16_final
2019-09-28 09:57:55	ga_ls8c_ard_3-1-0_097069_2019-09-28_final
2019-09-28 09:58:18	ga_ls8c_ard_3-1-0_097070_2019-09-28_final
2019-09-28 09:58:42	ga_ls8c_ard_3-1-0_097071_2019-09-28_final
2019-09-28 09:59:06	ga_ls8c_ard_3-1-0_097072_2019-09-28_final
2019-09-28 09:59:30	ga_ls8c_ard_3-1-0_097073_2019-09-28_final
2019-09-28 09:59:54	ga_ls8c_ard_3-1-0_097074_2019-09-28_final
2019-10-09 09:44:36	ga_ls8c_ard_3-1-0_094082_2019-10-09_final
2019-10-09 09:44:59	ga_ls8c_ard_3-1-0_094083_2019-10-09_final
2019-10-09 09:45:23	ga_ls8c_ard_3-1-0_094084_2019-10-09_final
2019-10-09 09:45:47	ga_ls8c_ard_3-1-0_094085_2019-10-09_final
2019-10-09 09:46:11	ga_ls8c_ard_3-1-0_094086_2019-10-09_final
2019-10-09 09:46:35	ga_ls8c_ard_3-1-0_094087_2019-10-09_final
2019-10-11 09:35:02	ga_ls8c_ard_3-1-0_092089_2019-10-11_final
2019-10-11 09:35:26	ga_ls8c_ard_3-1-0_092090_2019-10-11_final
2019-10-16 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-10-16_final
2019-10-16 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-10-16_final
2019-10-16 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-10-16_final
2019-10-16 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-10-16_final
2019-10-16 09:50:47	ga_ls8c_ard_3-1-0_095082_2019-10-16_final
2019-10-16 09:51:11	ga_ls8c_ard_3-1-0_095083_2019-10-16_final
2019-10-18 09:39:37	ga_ls8c_ard_3-1-0_093085_2019-10-18_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
2019-10-18 09:40:49	ga_ls8c_ard_3-1-0_093088_2019-10-18_final
2019-10-21 10:02:57	ga_ls8c_ard_3-2-1_098066_2019-10-21_final
2019-10-21 10:03:21	ga_ls8c_ard_3-1-0_098067_2019-10-21_final
2019-10-21 10:03:45	ga_ls8c_ard_3-1-0_098068_2019-10-21_final
2019-10-21 10:04:09	ga_ls8c_ard_3-1-0_098069_2019-10-21_final
2019-10-23 09:53:23	ga_ls8c_ard_3-1-0_096073_2019-10-23_final
2019-10-23 09:53:47	ga_ls8c_ard_3-1-0_096074_2019-10-23_final
2019-10-23 09:54:11	ga_ls8c_ard_3-1-0_096075_2019-10-23_final
2019-10-23 09:54:35	ga_ls8c_ard_3-1-0_096076_2019-10-23_final
2019-10-23 09:54:58	ga_ls8c_ard_3-1-0_096077_2019-10-23_final
2019-10-23 09:55:22	ga_ls8c_ard_3-1-0_096078_2019-10-23_final
2019-10-23 09:55:46	ga_ls8c_ard_3-1-0_096079_2019-10-23_final
2019-11-15 09:57:55	ga_ls8c_ard_3-1-0_097069_2019-11-15_final
2019-11-15 09:58:19	ga_ls8c_ard_3-1-0_097070_2019-11-15_final
2019-11-15 09:58:43	ga_ls8c_ard_3-1-0_097071_2019-11-15_final
2019-11-15 09:59:07	ga_ls8c_ard_3-1-0_097072_2019-11-15_final
2019-11-15 09:59:31	ga_ls8c_ard_3-1-0_097073_2019-11-15_final
2019-11-15 09:59:55	ga_ls8c_ard_3-1-0_097074_2019-11-15_final
2019-11-26 09:44:32	ga_ls8c_ard_3-1-0_094082_2019-11-26_final
2019-11-28 09:34:58	ga_ls8c_ard_3-1-0_092089_2019-11-28_final
2019-11-28 09:35:22	ga_ls8c_ard_3-1-0_092090_2019-11-28_final
2019-12-05 09:39:33	ga_ls8c_ard_3-1-0_093085_2019-12-05_final
2019-12-05 09:39:57	ga_ls8c_ard_3-1-0_093086_2019-12-05_final
2019-12-05 09:40:21	ga_ls8c_ard_3-1-0_093087_2019-12-05_final
2019-12-05 09:40:45	ga_ls8c_ard_3-1-0_093088_2019-12-05_final
2020-06-14 09:38:52	ga_ls8c_ard_3-1-0_093085_2020-06-14_final
2020-06-14 09:39:16	ga_ls8c_ard_3-1-0_093086_2020-06-14_final
2020-06-14 09:39:40	ga_ls8c_ard_3-1-0_093087_2020-06-14_final
2020-06-14 09:40:04	ga_ls8c_ard_3-1-0_093088_2020-06-14_final
2020-06-30 09:39:00	ga_ls8c_ard_3-1-0_093085_2020-06-30_final
2020-06-30 09:39:24	ga_ls8c_ard_3-1-0_093086_2020-06-30_final
2020-06-30 09:39:48	ga_ls8c_ard_3-1-0_093087_2020-06-30_final
2020-06-30 09:40:12	ga_ls8c_ard_3-1-0_093088_2020-06-30_final
2020-07-16 09:39:06	ga_ls8c_ard_3-1-0_093085_2020-07-16_final
2020-07-16 09:39:30	ga_ls8c_ard_3-1-0_093086_2020-07-16_final
2020-07-16 09:39:54	ga_ls8c_ard_3-1-0_093087_2020-07-16_final
2020-07-16 09:40:18	ga_ls8c_ard_3-1-0_093088_2020-07-16_final
2020-08-15 09:48:48	ga_ls8c_ard_3-1-0_095078_2020-08-15_final
2020-08-15 09:49:12	ga_ls8c_ard_3-1-0_095079_2020-08-15_final
2020-08-15 09:49:36	ga_ls8c_ard_3-1-0_095080_2020-08-15_final
2020-08-15 09:50:00	ga_ls8c_ard_3-1-0_095081_2020-08-15_final
2020-08-15 09:50:24	ga_ls8c_ard_3-1-0_095082_2020-08-15_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