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
2018-07-05 10:08:37	ga_ls8c_ard_3-0-0_099068_2018-07-05_final
2018-07-05 10:09:01	ga_ls8c_ard_3-0-0_099069_2018-07-05_final
2018-07-05 10:09:25	ga_ls8c_ard_3-0-0_099070_2018-07-05_final
2018-07-05 10:09:49	ga_ls8c_ard_3-0-0_099071_2018-07-05_final
2018-07-05 10:10:13	ga_ls8c_ard_3-0-0_099072_2018-07-05_final
2018-07-05 10:10:37	ga_ls8c_ard_3-0-0_099073_2018-07-05_final
2018-07-05 10:11:01	ga_ls8c_ard_3-0-0_099074_2018-07-05_final
2018-07-07 10:00:16	ga_ls8c_ard_3-0-0_097078_2018-07-07_final
2018-07-07 10:00:40	ga_ls8c_ard_3-0-0_097079_2018-07-07_final
2018-07-07 10:01:04	ga_ls8c_ard_3-0-0_097080_2018-07-07_final
2018-07-07 10:01:28	ga_ls8c_ard_3-0-0_097081_2018-07-07_final
2018-07-07 10:01:52	ga_ls8c_ard_3-0-0_097082_2018-07-07_final
2018-07-07 10:02:16	ga_ls8c_ard_3-0-0_097083_2018-07-07_final
2018-07-23 10:00:23	ga_ls8c_ard_3-0-0_097078_2018-07-23_final
2018-07-23 10:00:46	ga_ls8c_ard_3-0-0_097079_2018-07-23_final
2018-07-23 10:01:10	ga_ls8c_ard_3-0-0_097080_2018-07-23_final
2018-07-23 10:01:34	ga_ls8c_ard_3-0-0_097081_2018-07-23_final
2018-07-23 10:01:58	ga_ls8c_ard_3-0-0_097082_2018-07-23_final
2018-07-23 10:02:22	ga_ls8c_ard_3-0-0_097083_2018-07-23_final
2018-08-06 10:08:52	ga_ls8c_ard_3-0-0_099068_2018-08-06_final
2018-08-06 10:09:16	ga_ls8c_ard_3-0-0_099069_2018-08-06_final
2018-08-06 10:09:40	ga_ls8c_ard_3-0-0_099070_2018-08-06_final
2018-08-06 10:10:04	ga_ls8c_ard_3-0-0_099071_2018-08-06_final
2018-08-06 10:10:28	ga_ls8c_ard_3-0-0_099072_2018-08-06_final
2018-08-06 10:10:52	ga_ls8c_ard_3-0-0_099073_2018-08-06_final
2018-08-06 10:11:16	ga_ls8c_ard_3-0-0_099074_2018-08-06_final
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-16 10:05:22	ga_ls8c_ard_3-0-0_098074_2018-09-16_final
2018-09-16 10:05:46	ga_ls8c_ard_3-0-0_098075_2018-09-16_final
2018-09-16 10:06:10	ga_ls8c_ard_3-0-0_098076_2018-09-16_final
2018-09-16 10:06:34	ga_ls8c_ard_3-0-0_098077_2018-09-16_final
2018-09-16 10:06:58	ga_ls8c_ard_3-0-0_098078_2018-09-16_final
2018-09-16 10:07:22	ga_ls8c_ard_3-0-0_098079_2018-09-16_final
2019-01-06 10:05:12	ga_ls8c_ard_3-0-0_098073_2019-01-06_final
2019-01-06 10:05:36	ga_ls8c_ard_3-0-0_098074_2019-01-06_final
2019-01-06 10:06:00	ga_ls8c_ard_3-0-0_098075_2019-01-06_final
2019-01-06 10:06:24	ga_ls8c_ard_3-0-0_098076_2019-01-06_final
2019-01-06 10:06:48	ga_ls8c_ard_3-0-0_098077_2019-01-06_final
2019-01-06 10:07:12	ga_ls8c_ard_3-0-0_098078_2019-01-06_final
2019-01-06 10:07:36	ga_ls8c_ard_3-0-0_098079_2019-01-06_final
2022-10-13 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-10-13_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-13 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-10-13_final
2022-10-13 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-10-13_final
2022-10-13 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-10-13_final
2022-10-13 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-10-13_final
2022-10-13 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-10-13_final
2022-10-15 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-10-15_final
2022-10-15 09:57:29	ga_ls8c_ard_3-2-1_096083_2022-10-15_final
2022-10-15 09:57:53	ga_ls8c_ard_3-2-1_096084_2022-10-15_final
2022-10-15 09:58:17	ga_ls8c_ard_3-2-1_096085_2022-10-15_final
2022-10-15 09:58:41	ga_ls8c_ard_3-2-1_096086_2022-10-15_final
2022-10-20 10:10:06	ga_ls8c_ard_3-2-1_099068_2022-10-20_final
2022-10-20 10:10:30	ga_ls8c_ard_3-2-1_099069_2022-10-20_final
2022-10-20 10:10:54	ga_ls8c_ard_3-2-1_099070_2022-10-20_final
2022-10-20 10:11:18	ga_ls8c_ard_3-2-1_099071_2022-10-20_final
2022-10-20 10:11:42	ga_ls8c_ard_3-2-1_099072_2022-10-20_final
2022-10-20 10:12:06	ga_ls8c_ard_3-2-1_099073_2022-10-20_final
2022-10-20 10:12:30	ga_ls8c_ard_3-2-1_099074_2022-10-20_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-05 10:10:34	ga_ls8c_ard_3-2-1_099069_2022-11-05_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-05 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-11-05_final
2022-11-05 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-11-05_final
2022-11-07 10:01:23	ga_ls8c_ard_3-2-1_097077_2022-11-07_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-07 10:02:11	ga_ls8c_ard_3-2-1_097079_2022-11-07_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-07 10:02:59	ga_ls8c_ard_3-2-1_097081_2022-11-07_final
2022-11-07 10:03:23	ga_ls8c_ard_3-2-1_097082_2022-11-07_final
2022-11-07 10:03:47	ga_ls8c_ard_3-2-1_097083_2022-11-07_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-11-30 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-30_final
2022-11-30 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-30_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-11-30 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-30_final
2022-11-30 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-30_final
2022-12-02 09:57:08	ga_ls8c_ard_3-2-1_096082_2022-12-02_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_final
2022-12-02 09:57:56	ga_ls8c_ard_3-2-1_096084_2022-12-02_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-02 09:58:44	ga_ls8c_ard_3-2-1_096086_2022-12-02_final
2023-03-06 10:05:22	ga_ls8c_ard_3-2-1_098073_2023-03-06_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-06 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-03-06_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-08 09:56:33	ga_ls8c_ard_3-2-1_096082_2023-03-08_final
2023-03-08 09:56:57	ga_ls8c_ard_3-2-1_096083_2023-03-08_final
2023-03-08 09:57:21	ga_ls8c_ard_3-2-1_096084_2023-03-08_final
2023-03-08 09:57:45	ga_ls8c_ard_3-2-1_096085_2023-03-08_final
2023-03-08 09:58:09	ga_ls8c_ard_3-2-1_096086_2023-03-08_final
2023-03-13 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-03-13_final
2023-03-13 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-03-13_final
2023-03-13 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-03-13_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