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
2019-03-08 11:17:45	ga_ls8c_ard_3-1-0_109085_2019-03-08_final
2019-03-13 11:31:52	ga_ls8c_ard_3-1-0_112074_2019-03-13_final
2019-03-15 11:20:18	ga_ls8c_ard_3-1-0_110076_2019-03-15_final
2019-03-17 11:11:31	ga_ls8c_ard_3-1-0_108085_2019-03-17_final
2019-03-20 11:35:14	ga_ls8c_ard_3-1-0_113067_2019-03-20_final
2019-03-22 11:28:27	ga_ls8c_ard_3-1-0_111081_2019-03-22_final
2019-03-31 11:18:39	ga_ls8c_ard_3-1-0_110072_2019-03-31_final
2019-03-31 11:20:15	ga_ls8c_ard_3-1-0_110076_2019-03-31_final
2019-04-02 11:10:16	ga_ls8c_ard_3-1-0_108082_2019-04-02_final
2019-04-02 11:11:28	ga_ls8c_ard_3-1-0_108085_2019-04-02_final
2019-04-05 11:40:22	ga_ls8c_ard_3-1-0_113080_2019-04-05_final
2019-04-09 11:16:01	ga_ls8c_ard_3-1-0_109081_2019-04-09_final
2019-04-12 11:46:30	ga_ls8c_ard_3-1-0_114080_2019-04-12_final
2019-04-14 11:32:56	ga_ls8c_ard_3-1-0_112077_2019-04-14_final
2019-04-16 11:18:34	ga_ls8c_ard_3-1-0_110072_2019-04-16_final
2019-06-15 11:46:51	ga_ls8c_ard_3-1-0_114080_2019-06-15_final
2019-06-19 11:18:57	ga_ls8c_ard_3-1-0_110072_2019-06-19_final
2019-06-21 11:10:36	ga_ls8c_ard_3-1-0_108082_2019-06-21_final
2019-06-29 11:57:41	ga_ls8c_ard_3-1-0_116076_2019-06-29_final
2019-07-03 11:31:47	ga_ls8c_ard_3-1-0_112073_2019-07-03_final
2019-07-10 11:39:35	ga_ls8c_ard_3-1-0_113077_2019-07-10_final
2019-07-14 11:14:28	ga_ls8c_ard_3-1-0_109076_2019-07-14_final
2019-07-17 11:46:58	ga_ls8c_ard_3-1-0_114080_2019-07-17_final
2019-07-23 11:09:08	ga_ls8c_ard_3-1-0_108078_2019-07-23_final
2019-07-23 11:11:55	ga_ls8c_ard_3-1-0_108085_2019-07-23_final
2019-07-24 11:52:48	ga_ls8c_ard_3-1-0_115079_2019-07-24_final
2019-07-26 11:35:40	ga_ls8c_ard_3-1-0_113067_2019-07-26_final
2019-08-11 11:40:57	ga_ls8c_ard_3-1-0_113080_2019-08-11_final
2019-08-18 11:45:58	ga_ls8c_ard_3-1-0_114077_2019-08-18_final
2019-08-22 11:20:52	ga_ls8c_ard_3-1-0_110076_2019-08-22_final
2019-08-24 11:10:55	ga_ls8c_ard_3-1-0_108082_2019-08-24_final
2019-08-31 11:16:43	ga_ls8c_ard_3-1-0_109081_2019-08-31_final
2019-09-01 11:57:59	ga_ls8c_ard_3-1-0_116076_2019-09-01_final
2019-09-03 11:47:14	ga_ls8c_ard_3-1-0_114080_2019-09-03_final
2019-09-05 11:32:05	ga_ls8c_ard_3-1-0_112073_2019-09-05_final
2019-09-09 11:10:58	ga_ls8c_ard_3-1-0_108082_2019-09-09_final
2019-09-10 11:53:03	ga_ls8c_ard_3-1-0_115079_2019-09-10_final
2019-09-14 11:23:58	ga_ls8c_ard_3-1-0_111068_2019-09-14_final
2019-09-21 11:29:47	ga_ls8c_ard_3-1-0_112067_2019-09-21_final
2019-09-30 11:24:03	ga_ls8c_ard_3-1-0_111068_2019-09-30_final
2019-10-05 11:47:23	ga_ls8c_ard_3-1-0_114080_2019-10-05_final
2019-10-11 11:09:31	ga_ls8c_ard_3-1-0_108078_2019-10-11_final
2019-10-14 11:40:02	ga_ls8c_ard_3-1-0_113077_2019-10-14_final
2019-10-14 11:41:14	ga_ls8c_ard_3-1-0_113080_2019-10-14_final
2019-10-21 11:47:25	ga_ls8c_ard_3-1-0_114080_2019-10-21_final
2019-10-23 11:29:52	ga_ls8c_ard_3-1-0_112067_2019-10-23_final
2019-10-23 11:32:16	ga_ls8c_ard_3-1-0_112073_2019-10-23_final
2019-10-30 11:36:03	ga_ls8c_ard_3-1-0_113067_2019-10-30_final
2019-10-30 11:41:14	ga_ls8c_ard_3-1-0_113080_2019-10-30_final
2019-11-06 11:46:12	ga_ls8c_ard_3-1-0_114077_2019-11-06_final
2019-11-08 11:29:51	ga_ls8c_ard_3-1-0_112067_2019-11-08_final
2019-11-15 11:41:11	ga_ls8c_ard_3-1-0_113080_2019-11-15_final
2019-11-17 11:29:13	ga_ls8c_ard_3-1-0_111081_2019-11-17_final
2019-11-17 11:29:37	ga_ls8c_ard_3-1-0_111082_2019-11-17_final
2019-11-19 11:14:51	ga_ls8c_ard_3-1-0_109076_2019-11-19_final
2019-11-22 11:46:08	ga_ls8c_ard_3-1-0_114077_2019-11-22_final
2019-11-22 11:47:20	ga_ls8c_ard_3-1-0_114080_2019-11-22_final
2019-11-24 11:32:35	ga_ls8c_ard_3-1-0_112074_2019-11-24_final
2019-11-29 11:53:07	ga_ls8c_ard_3-1-0_115079_2019-11-29_final
2019-12-01 11:35:58	ga_ls8c_ard_3-1-0_113067_2019-12-01_final
2019-12-03 11:29:36	ga_ls8c_ard_3-1-0_111082_2019-12-03_final
2019-12-08 11:46:08	ga_ls8c_ard_3-1-0_114077_2019-12-08_final
2019-12-08 11:47:20	ga_ls8c_ard_3-1-0_114080_2019-12-08_final
2019-12-12 11:19:25	ga_ls8c_ard_3-1-0_110072_2019-12-12_final
2019-12-24 11:46:05	ga_ls8c_ard_3-1-0_114077_2019-12-24_final
2019-12-28 11:21:45	ga_ls8c_ard_3-1-0_110078_2019-12-28_final
2019-12-31 11:53:02	ga_ls8c_ard_3-1-0_115079_2019-12-31_final
2020-01-04 11:29:05	ga_ls8c_ard_3-1-0_111081_2020-01-04_final
2020-01-04 11:29:29	ga_ls8c_ard_3-1-0_111082_2020-01-04_final
2020-01-20 11:23:51	ga_ls8c_ard_3-1-0_111068_2020-01-20_final
2020-01-25 11:47:09	ga_ls8c_ard_3-1-0_114080_2020-01-25_final
2020-01-29 11:20:48	ga_ls8c_ard_3-1-0_110076_2020-01-29_final
2020-02-03 11:40:55	ga_ls8c_ard_3-1-0_113080_2020-02-03_final
2020-02-05 11:29:20	ga_ls8c_ard_3-1-0_111082_2020-02-05_final
2020-02-10 11:47:04	ga_ls8c_ard_3-1-0_114080_2020-02-10_final
2020-02-21 11:23:42	ga_ls8c_ard_3-1-0_111068_2020-02-21_final
2020-02-21 11:28:53	ga_ls8c_ard_3-1-0_111081_2020-02-21_final
2020-02-23 11:16:31	ga_ls8c_ard_3-1-0_109081_2020-02-23_final
2020-02-28 11:31:50	ga_ls8c_ard_3-1-0_112073_2020-02-28_final
2020-02-28 11:32:14	ga_ls8c_ard_3-1-0_112074_2020-02-28_final
2020-03-03 11:11:53	ga_ls8c_ard_3-1-0_108085_2020-03-03_final
2020-03-15 11:29:20	ga_ls8c_ard_3-1-0_112067_2020-03-15_final
2020-03-15 11:31:44	ga_ls8c_ard_3-1-0_112073_2020-03-15_final
2020-03-17 11:20:33	ga_ls8c_ard_3-1-0_110076_2020-03-17_final
2020-03-19 11:08:58	ga_ls8c_ard_3-1-0_108078_2020-03-19_final
2020-03-19 11:11:45	ga_ls8c_ard_3-1-0_108085_2020-03-19_final
2020-03-27 11:57:32	ga_ls8c_ard_3-1-0_116076_2020-03-27_final
2020-03-29 11:46:45	ga_ls8c_ard_3-1-0_114080_2020-03-29_final
2020-03-31 11:29:11	ga_ls8c_ard_3-1-0_112067_2020-03-31_final
2020-04-07 11:40:29	ga_ls8c_ard_3-1-0_113080_2020-04-07_final
2020-04-11 11:14:09	ga_ls8c_ard_3-1-0_109076_2020-04-11_final
2020-04-11 11:16:09	ga_ls8c_ard_3-1-0_109081_2020-04-11_final
2020-04-16 11:29:04	ga_ls8c_ard_3-1-0_112067_2020-04-16_final
2020-04-16 11:31:51	ga_ls8c_ard_3-1-0_112074_2020-04-16_final
2020-04-18 11:18:41	ga_ls8c_ard_3-1-0_110072_2020-04-18_final
2020-04-23 11:35:12	ga_ls8c_ard_3-1-0_113067_2020-04-23_final
2020-04-25 11:28:24	ga_ls8c_ard_3-1-0_111081_2020-04-25_final
2020-05-02 11:31:19	ga_ls8c_ard_3-1-0_112073_2020-05-02_final
2020-05-02 11:31:43	ga_ls8c_ard_3-1-0_112074_2020-05-02_final
2020-05-06 11:10:09	ga_ls8c_ard_3-1-0_108082_2020-05-06_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