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
2015-03-11 09:50:26	ga_ls8c_ard_3-0-0_095083_2015-03-11_final
2015-03-11 09:50:50	ga_ls8c_ard_3-0-0_095084_2015-03-11_final
2015-03-11 09:51:14	ga_ls8c_ard_3-0-0_095085_2015-03-11_final
2015-03-11 09:51:37	ga_ls8c_ard_3-0-0_095086_2015-03-11_final
2016-02-06 10:09:09	ga_ls8c_ard_3-0-0_099067_2016-02-06_final
2016-02-06 10:09:33	ga_ls8c_ard_3-0-0_099068_2016-02-06_final
2016-02-06 10:09:57	ga_ls8c_ard_3-0-0_099069_2016-02-06_final
2016-02-06 10:10:21	ga_ls8c_ard_3-0-0_099070_2016-02-06_final
2016-02-06 10:10:45	ga_ls8c_ard_3-0-0_099071_2016-02-06_final
2016-02-08 09:59:58	ga_ls8c_ard_3-0-0_097075_2016-02-08_final
2016-02-08 10:00:22	ga_ls8c_ard_3-0-0_097076_2016-02-08_final
2016-02-08 10:00:46	ga_ls8c_ard_3-0-0_097077_2016-02-08_final
2016-02-08 10:01:10	ga_ls8c_ard_3-0-0_097078_2016-02-08_final
2016-02-08 10:01:34	ga_ls8c_ard_3-0-0_097079_2016-02-08_final
2016-02-08 10:01:58	ga_ls8c_ard_3-0-0_097080_2016-02-08_final
2016-02-08 10:02:22	ga_ls8c_ard_3-0-0_097081_2016-02-08_final
2016-02-26 09:50:41	ga_ls8c_ard_3-0-0_095083_2016-02-26_final
2016-02-26 09:51:05	ga_ls8c_ard_3-0-0_095084_2016-02-26_final
2016-02-26 09:51:29	ga_ls8c_ard_3-0-0_095085_2016-02-26_final
2016-02-26 09:51:53	ga_ls8c_ard_3-0-0_095086_2016-02-26_final
2016-02-26 09:52:17	ga_ls8c_ard_3-0-0_095087_2016-02-26_final
2016-02-26 09:52:41	ga_ls8c_ard_3-0-0_095088_2016-02-26_final
2016-02-29 10:15:12	ga_ls8c_ard_3-0-0_100067_2016-02-29_final
2016-03-16 10:15:08	ga_ls8c_ard_3-0-0_100067_2016-03-16_final
2016-04-21 09:54:55	ga_ls8c_ard_3-0-0_096079_2016-04-21_final
2016-04-21 09:55:19	ga_ls8c_ard_3-0-0_096080_2016-04-21_final
2016-04-21 09:55:43	ga_ls8c_ard_3-0-0_096081_2016-04-21_final
2016-04-21 09:56:07	ga_ls8c_ard_3-0-0_096082_2016-04-21_final
2016-04-21 09:56:31	ga_ls8c_ard_3-0-0_096083_2016-04-21_final
2016-04-21 09:56:55	ga_ls8c_ard_3-0-0_096084_2016-04-21_final
2016-04-21 09:57:19	ga_ls8c_ard_3-0-0_096085_2016-04-21_final
2016-04-23 09:45:44	ga_ls8c_ard_3-0-0_094087_2016-04-23_final
2016-04-23 09:46:08	ga_ls8c_ard_3-0-0_094088_2016-04-23_final
2018-10-11 09:59:46	ga_ls8c_ard_3-0-0_097075_2018-10-11_final
2018-10-11 10:00:10	ga_ls8c_ard_3-0-0_097076_2018-10-11_final
2018-10-11 10:00:34	ga_ls8c_ard_3-0-0_097077_2018-10-11_final
2018-10-11 10:00:58	ga_ls8c_ard_3-0-0_097078_2018-10-11_final
2018-10-11 10:01:22	ga_ls8c_ard_3-0-0_097079_2018-10-11_final
2018-10-11 10:01:46	ga_ls8c_ard_3-0-0_097080_2018-10-11_final
2018-10-11 10:02:10	ga_ls8c_ard_3-0-0_097081_2018-10-11_final
2018-11-10 10:08:40	ga_ls8c_ard_3-2-1_099066_2018-11-10_final
2018-11-10 10:09:04	ga_ls8c_ard_3-0-0_099067_2018-11-10_final
2018-11-10 10:09:28	ga_ls8c_ard_3-0-0_099068_2018-11-10_final
2018-11-10 10:09:52	ga_ls8c_ard_3-0-0_099069_2018-11-10_final
2018-11-10 10:10:16	ga_ls8c_ard_3-0-0_099070_2018-11-10_final
2018-11-10 10:10:39	ga_ls8c_ard_3-0-0_099071_2018-11-10_final
2018-11-12 09:59:54	ga_ls8c_ard_3-0-0_097075_2018-11-12_final
2018-11-12 10:00:18	ga_ls8c_ard_3-0-0_097076_2018-11-12_final
2018-11-12 10:00:42	ga_ls8c_ard_3-0-0_097077_2018-11-12_final
2018-11-12 10:01:06	ga_ls8c_ard_3-0-0_097078_2018-11-12_final
2018-11-12 10:01:29	ga_ls8c_ard_3-0-0_097079_2018-11-12_final
2018-11-12 10:01:53	ga_ls8c_ard_3-0-0_097080_2018-11-12_final
2018-11-12 10:02:17	ga_ls8c_ard_3-0-0_097081_2018-11-12_final
2018-11-28 09:59:53	ga_ls8c_ard_3-0-0_097075_2018-11-28_final
2018-11-28 10:00:17	ga_ls8c_ard_3-0-0_097076_2018-11-28_final
2018-11-28 10:00:41	ga_ls8c_ard_3-0-0_097077_2018-11-28_final
2018-11-28 10:01:05	ga_ls8c_ard_3-0-0_097078_2018-11-28_final
2018-11-28 10:01:29	ga_ls8c_ard_3-0-0_097079_2018-11-28_final
2018-11-28 10:01:53	ga_ls8c_ard_3-0-0_097080_2018-11-28_final
2018-11-28 10:02:17	ga_ls8c_ard_3-0-0_097081_2018-11-28_final
2018-12-12 10:08:36	ga_ls8c_ard_3-2-1_099066_2018-12-12_final
2018-12-12 10:09:00	ga_ls8c_ard_3-0-0_099067_2018-12-12_final
2018-12-12 10:09:24	ga_ls8c_ard_3-0-0_099068_2018-12-12_final
2018-12-12 10:09:48	ga_ls8c_ard_3-0-0_099069_2018-12-12_final
2018-12-12 10:10:12	ga_ls8c_ard_3-0-0_099070_2018-12-12_final
2018-12-12 10:10:36	ga_ls8c_ard_3-0-0_099071_2018-12-12_final
2018-12-12 10:11:00	ga_ls8c_ard_3-0-0_099072_2018-12-12_final
2018-12-14 09:59:50	ga_ls8c_ard_3-0-0_097075_2018-12-14_final
2018-12-14 10:00:13	ga_ls8c_ard_3-0-0_097076_2018-12-14_final
2018-12-14 10:00:37	ga_ls8c_ard_3-0-0_097077_2018-12-14_final
2018-12-14 10:01:01	ga_ls8c_ard_3-0-0_097078_2018-12-14_final
2018-12-14 10:01:25	ga_ls8c_ard_3-0-0_097079_2018-12-14_final
2018-12-14 10:01:49	ga_ls8c_ard_3-0-0_097080_2018-12-14_final
2018-12-14 10:02:13	ga_ls8c_ard_3-0-0_097081_2018-12-14_final
2018-12-28 10:08:36	ga_ls8c_ard_3-2-1_099066_2018-12-28_final
2018-12-28 10:09:00	ga_ls8c_ard_3-0-0_099067_2018-12-28_final
2018-12-28 10:09:24	ga_ls8c_ard_3-0-0_099068_2018-12-28_final
2018-12-28 10:09:48	ga_ls8c_ard_3-0-0_099069_2018-12-28_final
2018-12-28 10:10:12	ga_ls8c_ard_3-0-0_099070_2018-12-28_final
2018-12-28 10:10:36	ga_ls8c_ard_3-0-0_099071_2018-12-28_final
2018-12-28 10:11:00	ga_ls8c_ard_3-0-0_099072_2018-12-28_final
2018-12-30 09:59:50	ga_ls8c_ard_3-0-0_097075_2018-12-30_final
2018-12-30 10:00:14	ga_ls8c_ard_3-0-0_097076_2018-12-30_final
2018-12-30 10:00:38	ga_ls8c_ard_3-0-0_097077_2018-12-30_final
2018-12-30 10:01:02	ga_ls8c_ard_3-1-0_097078_2018-12-30_final
2018-12-30 10:01:26	ga_ls8c_ard_3-0-0_097079_2018-12-30_final
2018-12-30 10:01:50	ga_ls8c_ard_3-0-0_097080_2018-12-30_final
2018-12-30 10:02:14	ga_ls8c_ard_3-0-0_097081_2018-12-30_final
2019-01-13 10:08:58	ga_ls8c_ard_3-0-0_099067_2019-01-13_final
2019-01-13 10:09:22	ga_ls8c_ard_3-0-0_099068_2019-01-13_final
2019-01-13 10:09:46	ga_ls8c_ard_3-0-0_099069_2019-01-13_final
2019-01-13 10:10:10	ga_ls8c_ard_3-0-0_099070_2019-01-13_final
2019-01-13 10:10:34	ga_ls8c_ard_3-0-0_099071_2019-01-13_final
2019-01-13 10:10:58	ga_ls8c_ard_3-0-0_099072_2019-01-13_final
2019-01-15 09:59:48	ga_ls8c_ard_3-0-0_097075_2019-01-15_final
2019-01-15 10:00:12	ga_ls8c_ard_3-0-0_097076_2019-01-15_final
2019-01-15 10:00:36	ga_ls8c_ard_3-0-0_097077_2019-01-15_final
2019-01-15 10:01:00	ga_ls8c_ard_3-0-0_097078_2019-01-15_final
2019-01-15 10:01:24	ga_ls8c_ard_3-0-0_097079_2019-01-15_final
2019-01-15 10:01:48	ga_ls8c_ard_3-0-0_097080_2019-01-15_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years