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
2015-04-30 11:14:34	ga_ls8c_ard_3-0-0_109078_2015-04-30_final
2015-04-30 11:14:58	ga_ls8c_ard_3-0-0_109079_2015-04-30_final
2015-04-30 11:15:22	ga_ls8c_ard_3-0-0_109080_2015-04-30_final
2015-04-30 11:15:46	ga_ls8c_ard_3-0-0_109081_2015-04-30_final
2015-04-30 11:16:10	ga_ls8c_ard_3-0-0_109082_2015-04-30_final
2015-04-30 11:16:34	ga_ls8c_ard_3-0-0_109083_2015-04-30_final
2015-05-14 11:23:06	ga_ls8c_ard_3-0-0_111069_2015-05-14_final
2015-05-14 11:23:30	ga_ls8c_ard_3-0-0_111070_2015-05-14_final
2015-05-14 11:23:54	ga_ls8c_ard_3-0-0_111071_2015-05-14_final
2015-05-14 11:24:18	ga_ls8c_ard_3-0-0_111072_2015-05-14_final
2015-05-14 11:24:42	ga_ls8c_ard_3-0-0_111073_2015-05-14_final
2015-05-14 11:25:06	ga_ls8c_ard_3-0-0_111074_2015-05-14_final
2015-05-16 11:14:20	ga_ls8c_ard_3-0-0_109078_2015-05-16_final
2015-05-16 11:14:44	ga_ls8c_ard_3-0-0_109079_2015-05-16_final
2015-05-16 11:15:08	ga_ls8c_ard_3-0-0_109080_2015-05-16_final
2015-05-16 11:15:32	ga_ls8c_ard_3-0-0_109081_2015-05-16_final
2015-05-16 11:15:56	ga_ls8c_ard_3-0-0_109082_2015-05-16_final
2015-05-16 11:16:20	ga_ls8c_ard_3-0-0_109083_2015-05-16_final
2018-10-31 11:15:14	ga_ls8c_ard_3-0-0_109078_2018-10-31_final
2018-10-31 11:15:38	ga_ls8c_ard_3-0-0_109079_2018-10-31_final
2018-10-31 11:16:02	ga_ls8c_ard_3-0-0_109080_2018-10-31_final
2018-10-31 11:16:26	ga_ls8c_ard_3-0-0_109081_2018-10-31_final
2018-10-31 11:16:50	ga_ls8c_ard_3-0-0_109082_2018-10-31_final
2018-10-31 11:17:14	ga_ls8c_ard_3-0-0_109083_2018-10-31_final
2019-01-01 11:23:58	ga_ls8c_ard_3-0-0_111069_2019-01-01_final
2019-01-01 11:24:22	ga_ls8c_ard_3-0-0_111070_2019-01-01_final
2019-01-01 11:24:46	ga_ls8c_ard_3-0-0_111071_2019-01-01_final
2019-01-01 11:25:10	ga_ls8c_ard_3-0-0_111072_2019-01-01_final
2019-01-01 11:25:34	ga_ls8c_ard_3-0-0_111073_2019-01-01_final
2019-01-01 11:25:57	ga_ls8c_ard_3-0-0_111074_2019-01-01_final
2019-01-03 11:15:11	ga_ls8c_ard_3-0-0_109078_2019-01-03_final
2019-01-03 11:15:35	ga_ls8c_ard_3-0-0_109079_2019-01-03_final
2019-01-03 11:15:59	ga_ls8c_ard_3-0-0_109080_2019-01-03_final
2019-01-03 11:16:23	ga_ls8c_ard_3-0-0_109081_2019-01-03_final
2019-01-03 11:16:47	ga_ls8c_ard_3-0-0_109082_2019-01-03_final
2019-01-03 11:17:11	ga_ls8c_ard_3-0-0_109083_2019-01-03_final
2019-06-14 11:05:34	ga_ls8c_ard_3-1-0_107085_2019-06-14_final
2019-06-19 11:19:21	ga_ls8c_ard_3-1-0_110073_2019-06-19_final
2019-06-19 11:19:45	ga_ls8c_ard_3-1-0_110074_2019-06-19_final
2019-06-19 11:20:09	ga_ls8c_ard_3-1-0_110075_2019-06-19_final
2019-06-19 11:20:33	ga_ls8c_ard_3-1-0_110076_2019-06-19_final
2019-06-19 11:20:57	ga_ls8c_ard_3-1-0_110077_2019-06-19_final
2019-06-19 11:21:21	ga_ls8c_ard_3-1-0_110078_2019-06-19_final
2019-06-19 11:21:45	ga_ls8c_ard_3-1-0_110079_2019-06-19_final
2019-06-21 11:10:36	ga_ls8c_ard_3-1-0_108082_2019-06-21_final
2019-06-21 11:11:00	ga_ls8c_ard_3-1-0_108083_2019-06-21_final
2019-06-21 11:11:24	ga_ls8c_ard_3-1-0_108084_2019-06-21_final
2019-06-21 11:11:48	ga_ls8c_ard_3-1-0_108085_2019-06-21_final
2019-07-05 11:19:25	ga_ls8c_ard_3-1-0_110073_2019-07-05_final
2019-07-05 11:19:49	ga_ls8c_ard_3-1-0_110074_2019-07-05_final
2019-07-05 11:20:13	ga_ls8c_ard_3-1-0_110075_2019-07-05_final
2019-07-05 11:20:37	ga_ls8c_ard_3-1-0_110076_2019-07-05_final
2019-07-05 11:21:01	ga_ls8c_ard_3-1-0_110077_2019-07-05_final
2019-07-05 11:21:25	ga_ls8c_ard_3-1-0_110078_2019-07-05_final
2019-07-05 11:21:49	ga_ls8c_ard_3-1-0_110079_2019-07-05_final
2019-07-07 11:10:40	ga_ls8c_ard_3-1-0_108082_2019-07-07_final
2019-07-07 11:11:04	ga_ls8c_ard_3-1-0_108083_2019-07-07_final
2019-07-07 11:11:28	ga_ls8c_ard_3-1-0_108084_2019-07-07_final
2019-07-07 11:11:51	ga_ls8c_ard_3-1-0_108085_2019-07-07_final
2019-07-12 11:24:02	ga_ls8c_ard_3-1-0_111069_2019-07-12_final
2019-07-12 11:24:26	ga_ls8c_ard_3-1-0_111070_2019-07-12_final
2019-07-12 11:24:50	ga_ls8c_ard_3-1-0_111071_2019-07-12_final
2019-07-12 11:25:13	ga_ls8c_ard_3-1-0_111072_2019-07-12_final
2019-07-12 11:25:37	ga_ls8c_ard_3-1-0_111073_2019-07-12_final
2019-07-12 11:26:01	ga_ls8c_ard_3-1-0_111074_2019-07-12_final
2019-07-14 11:15:16	ga_ls8c_ard_3-1-0_109078_2019-07-14_final
2019-07-14 11:15:40	ga_ls8c_ard_3-1-0_109079_2019-07-14_final
2019-07-14 11:16:04	ga_ls8c_ard_3-1-0_109080_2019-07-14_final
2019-07-14 11:16:28	ga_ls8c_ard_3-1-0_109081_2019-07-14_final
2019-07-14 11:16:52	ga_ls8c_ard_3-1-0_109082_2019-07-14_final
2019-07-14 11:17:15	ga_ls8c_ard_3-1-0_109083_2019-07-14_final
2019-07-30 11:15:21	ga_ls8c_ard_3-1-0_109078_2019-07-30_final
2019-07-30 11:15:45	ga_ls8c_ard_3-1-0_109079_2019-07-30_final
2019-07-30 11:16:09	ga_ls8c_ard_3-1-0_109080_2019-07-30_final
2019-07-30 11:16:33	ga_ls8c_ard_3-1-0_109081_2019-07-30_final
2019-07-30 11:16:57	ga_ls8c_ard_3-1-0_109082_2019-07-30_final
2019-07-30 11:17:21	ga_ls8c_ard_3-1-0_109083_2019-07-30_final
2019-08-08 11:10:50	ga_ls8c_ard_3-1-0_108082_2019-08-08_final
2019-08-22 11:19:40	ga_ls8c_ard_3-1-0_110073_2019-08-22_final
2019-08-22 11:20:04	ga_ls8c_ard_3-1-0_110074_2019-08-22_final
2019-08-22 11:20:28	ga_ls8c_ard_3-1-0_110075_2019-08-22_final
2019-08-22 11:20:52	ga_ls8c_ard_3-1-0_110076_2019-08-22_final
2019-08-22 11:21:16	ga_ls8c_ard_3-1-0_110077_2019-08-22_final
2019-08-22 11:21:40	ga_ls8c_ard_3-1-0_110078_2019-08-22_final
2019-08-22 11:22:04	ga_ls8c_ard_3-1-0_110079_2019-08-22_final
2019-08-24 11:10:55	ga_ls8c_ard_3-1-0_108082_2019-08-24_final
2019-08-24 11:11:19	ga_ls8c_ard_3-1-0_108083_2019-08-24_final
2019-08-24 11:11:42	ga_ls8c_ard_3-1-0_108084_2019-08-24_final
2019-08-24 11:12:06	ga_ls8c_ard_3-1-0_108085_2019-08-24_final
2019-08-29 11:24:17	ga_ls8c_ard_3-1-0_111069_2019-08-29_final
2019-08-29 11:24:41	ga_ls8c_ard_3-1-0_111070_2019-08-29_final
2019-08-29 11:25:05	ga_ls8c_ard_3-1-0_111071_2019-08-29_final
2019-08-29 11:25:29	ga_ls8c_ard_3-1-0_111072_2019-08-29_final
2019-08-29 11:25:53	ga_ls8c_ard_3-1-0_111073_2019-08-29_final
2019-08-29 11:26:17	ga_ls8c_ard_3-1-0_111074_2019-08-29_final
2019-08-31 11:15:31	ga_ls8c_ard_3-1-0_109078_2019-08-31_final
2019-08-31 11:15:55	ga_ls8c_ard_3-1-0_109079_2019-08-31_final
2019-08-31 11:16:19	ga_ls8c_ard_3-1-0_109080_2019-08-31_final
2019-08-31 11:16:43	ga_ls8c_ard_3-1-0_109081_2019-08-31_final
2019-08-31 11:17:07	ga_ls8c_ard_3-1-0_109082_2019-08-31_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