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
2016-05-19 10:17:41	ga_ls8c_ard_3-0-0_100074_2016-05-19_final
2016-05-19 10:18:05	ga_ls8c_ard_3-0-0_100075_2016-05-19_final
2016-05-19 10:18:29	ga_ls8c_ard_3-0-0_100076_2016-05-19_final
2016-05-19 10:18:53	ga_ls8c_ard_3-0-0_100077_2016-05-19_final
2016-05-19 10:19:17	ga_ls8c_ard_3-0-0_100078_2016-05-19_final
2016-05-19 10:19:41	ga_ls8c_ard_3-0-0_100079_2016-05-19_final
2016-05-19 10:20:05	ga_ls8c_ard_3-0-0_100080_2016-05-19_final
2016-07-22 10:18:05	ga_ls8c_ard_3-0-0_100074_2016-07-22_final
2016-07-22 10:18:29	ga_ls8c_ard_3-0-0_100075_2016-07-22_final
2016-07-22 10:18:53	ga_ls8c_ard_3-0-0_100076_2016-07-22_final
2016-07-22 10:19:17	ga_ls8c_ard_3-0-0_100077_2016-07-22_final
2016-07-22 10:19:41	ga_ls8c_ard_3-0-0_100078_2016-07-22_final
2016-07-22 10:20:05	ga_ls8c_ard_3-0-0_100079_2016-07-22_final
2016-07-22 10:20:29	ga_ls8c_ard_3-0-0_100080_2016-07-22_final
2016-07-31 10:13:56	ga_ls8c_ard_3-0-0_099079_2016-07-31_final
2016-07-31 10:14:20	ga_ls8c_ard_3-0-0_099080_2016-07-31_final
2016-07-31 10:14:44	ga_ls8c_ard_3-0-0_099081_2016-07-31_final
2016-07-31 10:15:08	ga_ls8c_ard_3-0-0_099082_2016-07-31_final
2016-07-31 10:15:32	ga_ls8c_ard_3-0-0_099083_2016-07-31_final
2016-07-31 10:15:56	ga_ls8c_ard_3-0-0_099084_2016-07-31_final
2016-08-09 10:09:22	ga_ls8c_ard_3-0-0_098083_2016-08-09_final
2016-08-09 10:09:46	ga_ls8c_ard_3-0-0_098084_2016-08-09_final
2016-08-09 10:10:10	ga_ls8c_ard_3-0-0_098085_2016-08-09_final
2016-08-09 10:10:34	ga_ls8c_ard_3-0-0_098086_2016-08-09_final
2016-10-10 10:18:24	ga_ls8c_ard_3-0-0_100074_2016-10-10_final
2016-10-10 10:18:48	ga_ls8c_ard_3-0-0_100075_2016-10-10_final
2016-10-10 10:19:12	ga_ls8c_ard_3-0-0_100076_2016-10-10_final
2016-10-10 10:19:36	ga_ls8c_ard_3-0-0_100077_2016-10-10_final
2016-10-10 10:20:00	ga_ls8c_ard_3-0-0_100078_2016-10-10_final
2016-10-10 10:20:24	ga_ls8c_ard_3-0-0_100079_2016-10-10_final
2016-10-10 10:20:48	ga_ls8c_ard_3-0-0_100080_2016-10-10_final
2016-10-12 10:09:15	ga_ls8c_ard_3-0-0_098082_2016-10-12_final
2016-10-12 10:09:39	ga_ls8c_ard_3-0-0_098083_2016-10-12_final
2016-10-12 10:10:03	ga_ls8c_ard_3-0-0_098084_2016-10-12_final
2016-10-12 10:10:27	ga_ls8c_ard_3-0-0_098085_2016-10-12_final
2016-10-12 10:10:51	ga_ls8c_ard_3-0-0_098086_2016-10-12_final
2021-01-07 10:27:55	ga_ls8c_ard_3-2-0_102067_2021-01-07_final
2021-01-07 10:28:19	ga_ls8c_ard_3-2-0_102068_2021-01-07_final
2021-01-07 10:28:42	ga_ls8c_ard_3-2-0_102069_2021-01-07_final
2021-01-07 10:29:06	ga_ls8c_ard_3-2-0_102070_2021-01-07_final
2021-02-08 10:27:47	ga_ls8c_ard_3-2-0_102067_2021-02-08_final
2021-02-08 10:28:11	ga_ls8c_ard_3-2-0_102068_2021-02-08_final
2021-02-08 10:28:35	ga_ls8c_ard_3-2-0_102069_2021-02-08_final
2021-02-08 10:28:58	ga_ls8c_ard_3-2-0_102070_2021-02-08_final
2021-02-12 10:09:25	ga_ls8c_ard_3-2-0_098083_2021-02-12_final
2021-02-12 10:09:49	ga_ls8c_ard_3-2-0_098084_2021-02-12_final
2021-02-12 10:10:13	ga_ls8c_ard_3-2-0_098085_2021-02-12_final
2021-02-12 10:10:37	ga_ls8c_ard_3-2-0_098086_2021-02-12_final
2021-02-24 10:27:42	ga_ls8c_ard_3-2-0_102067_2021-02-24_final
2021-02-24 10:28:06	ga_ls8c_ard_3-2-0_102068_2021-02-24_final
2021-02-24 10:28:29	ga_ls8c_ard_3-2-0_102069_2021-02-24_final
2021-02-24 10:28:53	ga_ls8c_ard_3-2-0_102070_2021-02-24_final
2021-04-06 10:22:26	ga_ls8c_ard_3-2-0_101070_2021-04-06_final
2021-04-06 10:22:50	ga_ls8c_ard_3-2-0_101071_2021-04-06_final
2021-04-06 10:23:14	ga_ls8c_ard_3-2-0_101072_2021-04-06_final
2021-04-06 10:23:38	ga_ls8c_ard_3-2-0_101073_2021-04-06_final
2021-04-06 10:24:02	ga_ls8c_ard_3-2-0_101074_2021-04-06_final
2021-04-06 10:24:26	ga_ls8c_ard_3-2-0_101075_2021-04-06_final
2021-04-08 10:13:39	ga_ls8c_ard_3-2-0_099079_2021-04-08_final
2021-04-08 10:14:03	ga_ls8c_ard_3-2-0_099080_2021-04-08_final
2021-04-08 10:14:27	ga_ls8c_ard_3-2-0_099081_2021-04-08_final
2021-04-08 10:14:51	ga_ls8c_ard_3-2-0_099082_2021-04-08_final
2021-04-08 10:15:15	ga_ls8c_ard_3-2-0_099083_2021-04-08_final
2021-04-08 10:15:39	ga_ls8c_ard_3-2-0_099084_2021-04-08_final
2021-04-10 10:04:05	ga_ls8c_ard_3-2-0_097086_2021-04-10_final
2022-01-03 10:22:56	ga_ls8c_ard_3-2-1_101070_2022-01-03_final
2022-01-03 10:23:20	ga_ls8c_ard_3-2-1_101071_2022-01-03_final
2022-01-03 10:23:44	ga_ls8c_ard_3-2-1_101072_2022-01-03_final
2022-01-03 10:24:08	ga_ls8c_ard_3-2-1_101073_2022-01-03_final
2022-01-03 10:24:32	ga_ls8c_ard_3-2-1_101074_2022-01-03_final
2022-01-03 10:24:56	ga_ls8c_ard_3-2-1_101075_2022-01-03_final
2022-01-05 10:14:10	ga_ls8c_ard_3-2-1_099079_2022-01-05_final
2022-01-05 10:14:34	ga_ls8c_ard_3-2-1_099080_2022-01-05_final
2022-01-05 10:14:58	ga_ls8c_ard_3-2-1_099081_2022-01-05_final
2022-01-05 10:15:22	ga_ls8c_ard_3-2-1_099082_2022-01-05_final
2022-01-10 10:27:54	ga_ls8c_ard_3-2-1_102067_2022-01-10_final
2022-01-10 10:28:18	ga_ls8c_ard_3-2-1_102068_2022-01-10_final
2022-01-10 10:28:42	ga_ls8c_ard_3-2-1_102069_2022-01-10_final
2022-01-10 10:29:06	ga_ls8c_ard_3-2-1_102070_2022-01-10_final
2022-01-12 10:18:20	ga_ls8c_ard_3-2-1_100074_2022-01-12_final
2022-01-12 10:18:44	ga_ls8c_ard_3-2-1_100075_2022-01-12_final
2022-01-12 10:19:08	ga_ls8c_ard_3-2-1_100076_2022-01-12_final
2022-01-12 10:19:32	ga_ls8c_ard_3-2-1_100077_2022-01-12_final
2022-01-12 10:19:56	ga_ls8c_ard_3-2-1_100078_2022-01-12_final
2022-01-12 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-01-12_final
2022-01-12 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-01-12_final
2022-01-14 10:09:34	ga_ls8c_ard_3-2-1_098083_2022-01-14_final
2022-01-14 10:09:57	ga_ls8c_ard_3-2-1_098084_2022-01-14_final
2022-01-14 10:10:21	ga_ls8c_ard_3-2-1_098085_2022-01-14_final
2022-01-19 10:22:53	ga_ls8c_ard_3-2-1_101070_2022-01-19_final
2022-01-19 10:23:17	ga_ls8c_ard_3-2-1_101071_2022-01-19_final
2022-01-19 10:23:41	ga_ls8c_ard_3-2-1_101072_2022-01-19_final
2022-01-19 10:24:05	ga_ls8c_ard_3-2-1_101073_2022-01-19_final
2022-01-19 10:24:29	ga_ls8c_ard_3-2-1_101074_2022-01-19_final
2022-01-19 10:24:53	ga_ls8c_ard_3-2-1_101075_2022-01-19_final
2022-01-21 10:14:06	ga_ls8c_ard_3-2-1_099079_2022-01-21_final
2022-01-21 10:14:30	ga_ls8c_ard_3-2-1_099080_2022-01-21_final
2022-01-21 10:14:54	ga_ls8c_ard_3-2-1_099081_2022-01-21_final
2022-01-21 10:15:18	ga_ls8c_ard_3-2-1_099082_2022-01-21_final
2022-01-21 10:15:42	ga_ls8c_ard_3-2-1_099083_2022-01-21_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