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
2018-02-20 11:41:37	ga_ls8c_ard_3-0-0_114067_2018-02-20_final
2018-03-03 11:28:34	ga_ls8c_ard_3-0-0_111081_2018-03-03_final
2018-03-03 11:28:58	ga_ls8c_ard_3-0-0_111082_2018-03-03_final
2018-03-03 11:29:22	ga_ls8c_ard_3-0-0_111083_2018-03-03_final
2018-03-03 11:29:46	ga_ls8c_ard_3-0-0_111084_2018-03-03_final
2018-03-03 11:30:10	ga_ls8c_ard_3-0-0_111085_2018-03-03_final
2018-03-17 11:37:12	ga_ls8c_ard_3-0-0_113072_2018-03-17_final
2018-03-17 11:37:36	ga_ls8c_ard_3-0-0_113073_2018-03-17_final
2018-03-17 11:38:00	ga_ls8c_ard_3-0-0_113074_2018-03-17_final
2018-03-17 11:38:24	ga_ls8c_ard_3-0-0_113075_2018-03-17_final
2018-03-17 11:38:48	ga_ls8c_ard_3-0-0_113076_2018-03-17_final
2018-03-17 11:39:12	ga_ls8c_ard_3-0-0_113077_2018-03-17_final
2018-03-17 11:39:36	ga_ls8c_ard_3-0-0_113078_2018-03-17_final
2018-03-19 11:28:25	ga_ls8c_ard_3-0-0_111081_2018-03-19_final
2018-03-19 11:28:49	ga_ls8c_ard_3-0-0_111082_2018-03-19_final
2018-03-19 11:29:13	ga_ls8c_ard_3-0-0_111083_2018-03-19_final
2018-03-19 11:29:37	ga_ls8c_ard_3-0-0_111084_2018-03-19_final
2018-03-19 11:30:01	ga_ls8c_ard_3-0-0_111085_2018-03-19_final
2018-05-22 11:27:48	ga_ls8c_ard_3-0-0_111081_2018-05-22_final
2018-05-22 11:28:12	ga_ls8c_ard_3-0-0_111082_2018-05-22_final
2018-05-22 11:28:36	ga_ls8c_ard_3-0-0_111083_2018-05-22_final
2018-05-22 11:29:00	ga_ls8c_ard_3-0-0_111084_2018-05-22_final
2018-06-05 11:36:25	ga_ls8c_ard_3-0-0_113072_2018-06-05_final
2018-06-05 11:36:49	ga_ls8c_ard_3-1-0_113073_2018-06-05_final
2018-06-05 11:37:13	ga_ls8c_ard_3-0-0_113074_2018-06-05_final
2018-06-05 11:37:37	ga_ls8c_ard_3-0-0_113075_2018-06-05_final
2018-06-05 11:38:01	ga_ls8c_ard_3-0-0_113076_2018-06-05_final
2018-06-05 11:38:25	ga_ls8c_ard_3-0-0_113077_2018-06-05_final
2018-06-05 11:38:49	ga_ls8c_ard_3-0-0_113078_2018-06-05_final
2018-06-07 11:27:40	ga_ls8c_ard_3-0-0_111081_2018-06-07_final
2018-06-07 11:28:04	ga_ls8c_ard_3-0-0_111082_2018-06-07_final
2018-06-07 11:28:28	ga_ls8c_ard_3-0-0_111083_2018-06-07_final
2018-06-07 11:28:52	ga_ls8c_ard_3-0-0_111084_2018-06-07_final
2018-06-07 11:29:16	ga_ls8c_ard_3-0-0_111085_2018-06-07_final
2018-07-18 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-07-18_final
2019-01-31 11:37:25	ga_ls8c_ard_3-0-0_113072_2019-01-31_final
2019-01-31 11:37:49	ga_ls8c_ard_3-1-0_113073_2019-01-31_final
2019-01-31 11:38:13	ga_ls8c_ard_3-0-0_113074_2019-01-31_final
2019-01-31 11:38:37	ga_ls8c_ard_3-0-0_113075_2019-01-31_final
2019-01-31 11:39:01	ga_ls8c_ard_3-0-0_113076_2019-01-31_final
2019-01-31 11:39:25	ga_ls8c_ard_3-0-0_113077_2019-01-31_final
2019-01-31 11:39:49	ga_ls8c_ard_3-0-0_113078_2019-01-31_final
2019-02-02 11:28:39	ga_ls8c_ard_3-0-0_111081_2019-02-02_final
2019-02-02 11:29:03	ga_ls8c_ard_3-0-0_111082_2019-02-02_final
2019-02-02 11:29:27	ga_ls8c_ard_3-0-0_111083_2019-02-02_final
2019-02-02 11:29:51	ga_ls8c_ard_3-0-0_111084_2019-02-02_final
2019-02-02 11:30:15	ga_ls8c_ard_3-0-0_111085_2019-02-02_final
2019-02-23 11:41:33	ga_ls8c_ard_3-0-0_114067_2019-02-23_final
2019-02-23 11:43:56	ga_ls8c_ard_3-0-0_114073_2019-02-23_final
2019-02-25 11:33:10	ga_ls8c_ard_3-0-0_112077_2019-02-25_final
2019-02-25 11:33:34	ga_ls8c_ard_3-0-0_112078_2019-02-25_final
2019-02-25 11:33:58	ga_ls8c_ard_3-0-0_112079_2019-02-25_final
2019-02-25 11:34:22	ga_ls8c_ard_3-0-0_112080_2019-02-25_final
2019-02-25 11:34:46	ga_ls8c_ard_3-0-0_112081_2019-02-25_final
2019-02-25 11:35:10	ga_ls8c_ard_3-0-0_112082_2019-02-25_final
2019-03-20 11:37:14	ga_ls8c_ard_3-1-0_113072_2019-03-20_final
2019-03-20 11:37:38	ga_ls8c_ard_3-1-0_113073_2019-03-20_final
2019-03-20 11:38:02	ga_ls8c_ard_3-1-0_113074_2019-03-20_final
2019-03-20 11:38:26	ga_ls8c_ard_3-1-0_113075_2019-03-20_final
2019-03-20 11:38:50	ga_ls8c_ard_3-1-0_113076_2019-03-20_final
2019-03-20 11:39:14	ga_ls8c_ard_3-1-0_113077_2019-03-20_final
2019-03-20 11:39:38	ga_ls8c_ard_3-1-0_113078_2019-03-20_final
2019-03-22 11:28:27	ga_ls8c_ard_3-1-0_111081_2019-03-22_final
2019-03-22 11:28:51	ga_ls8c_ard_3-1-0_111082_2019-03-22_final
2019-03-22 11:29:15	ga_ls8c_ard_3-1-0_111083_2019-03-22_final
2019-03-22 11:29:39	ga_ls8c_ard_3-1-0_111084_2019-03-22_final
2019-03-22 11:30:03	ga_ls8c_ard_3-1-0_111085_2019-03-22_final
2019-05-07 11:37:08	ga_ls8c_ard_3-0-0_113072_2019-05-07_final
2019-05-07 11:37:32	ga_ls8c_ard_3-0-0_113073_2019-05-07_final
2019-05-07 11:37:56	ga_ls8c_ard_3-0-0_113074_2019-05-07_final
2019-05-07 11:38:20	ga_ls8c_ard_3-0-0_113075_2019-05-07_final
2019-05-07 11:38:43	ga_ls8c_ard_3-0-0_113076_2019-05-07_final
2019-05-07 11:39:07	ga_ls8c_ard_3-0-0_113077_2019-05-07_final
2019-05-07 11:39:31	ga_ls8c_ard_3-0-0_113078_2019-05-07_final
2019-05-09 11:28:23	ga_ls8c_ard_3-0-0_111081_2019-05-09_final
2019-05-09 11:28:47	ga_ls8c_ard_3-0-0_111082_2019-05-09_final
2019-05-09 11:29:11	ga_ls8c_ard_3-0-0_111083_2019-05-09_final
2019-05-09 11:29:35	ga_ls8c_ard_3-0-0_111084_2019-05-09_final
2019-05-09 11:29:59	ga_ls8c_ard_3-0-0_111085_2019-05-09_final
2020-03-01 11:24:15	ga_ls8c_ard_3-1-0_110085_2020-03-01_final
2020-03-06 11:37:35	ga_ls8c_ard_3-1-0_113072_2020-03-06_final
2020-03-06 11:37:58	ga_ls8c_ard_3-1-0_113073_2020-03-06_final
2020-03-06 11:38:22	ga_ls8c_ard_3-1-0_113074_2020-03-06_final
2020-03-06 11:38:46	ga_ls8c_ard_3-1-0_113075_2020-03-06_final
2020-03-06 11:39:10	ga_ls8c_ard_3-1-0_113076_2020-03-06_final
2020-03-06 11:39:34	ga_ls8c_ard_3-1-0_113077_2020-03-06_final
2020-03-06 11:39:58	ga_ls8c_ard_3-1-0_113078_2020-03-06_final
2020-03-08 11:28:48	ga_ls8c_ard_3-1-0_111081_2020-03-08_final
2020-03-08 11:29:11	ga_ls8c_ard_3-1-0_111082_2020-03-08_final
2020-03-08 11:29:35	ga_ls8c_ard_3-1-0_111083_2020-03-08_final
2020-03-08 11:29:59	ga_ls8c_ard_3-1-0_111084_2020-03-08_final
2020-03-08 11:30:23	ga_ls8c_ard_3-1-0_111085_2020-03-08_final
2020-03-13 11:41:43	ga_ls8c_ard_3-1-0_114067_2020-03-13_final
2020-04-23 11:37:11	ga_ls8c_ard_3-1-0_113072_2020-04-23_final
2020-04-23 11:37:35	ga_ls8c_ard_3-1-0_113073_2020-04-23_final
2020-04-23 11:37:59	ga_ls8c_ard_3-1-0_113074_2020-04-23_final
2020-04-23 11:38:23	ga_ls8c_ard_3-1-0_113075_2020-04-23_final
2020-04-23 11:38:47	ga_ls8c_ard_3-1-0_113076_2020-04-23_final
2020-04-23 11:39:11	ga_ls8c_ard_3-1-0_113077_2020-04-23_final
2020-04-23 11:39:35	ga_ls8c_ard_3-1-0_113078_2020-04-23_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