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
2017-04-24 11:28:50	ga_ls8c_ard_3-0-0_112067_2017-04-24_final
2017-04-24 11:29:14	ga_ls8c_ard_3-0-0_112068_2017-04-24_final
2017-04-24 11:29:38	ga_ls8c_ard_3-0-0_112069_2017-04-24_final
2017-04-24 11:30:02	ga_ls8c_ard_3-0-0_112070_2017-04-24_final
2017-04-24 11:30:26	ga_ls8c_ard_3-0-0_112071_2017-04-24_final
2017-04-24 11:30:49	ga_ls8c_ard_3-0-0_112072_2017-04-24_final
2017-04-26 11:19:38	ga_ls8c_ard_3-0-0_110075_2017-04-26_final
2017-04-26 11:20:02	ga_ls8c_ard_3-0-0_110076_2017-04-26_final
2017-04-26 11:20:26	ga_ls8c_ard_3-0-0_110077_2017-04-26_final
2017-04-26 11:20:50	ga_ls8c_ard_3-0-0_110078_2017-04-26_final
2017-04-26 11:21:14	ga_ls8c_ard_3-0-0_110079_2017-04-26_final
2017-04-26 11:21:38	ga_ls8c_ard_3-0-0_110080_2017-04-26_final
2017-04-26 11:22:02	ga_ls8c_ard_3-0-0_110081_2017-04-26_final
2017-06-06 11:15:46	ga_ls8c_ard_3-0-0_109080_2017-06-06_final
2017-06-06 11:16:10	ga_ls8c_ard_3-0-0_109081_2017-06-06_final
2017-06-06 11:16:34	ga_ls8c_ard_3-0-0_109082_2017-06-06_final
2017-06-06 11:16:58	ga_ls8c_ard_3-0-0_109083_2017-06-06_final
2017-06-06 11:17:21	ga_ls8c_ard_3-0-0_109084_2017-06-06_final
2017-06-06 11:17:45	ga_ls8c_ard_3-0-0_109085_2017-06-06_final
2018-05-29 11:28:18	ga_ls8c_ard_3-0-0_112067_2018-05-29_final
2018-05-29 11:28:42	ga_ls8c_ard_3-0-0_112068_2018-05-29_final
2018-05-29 11:29:06	ga_ls8c_ard_3-0-0_112069_2018-05-29_final
2018-05-29 11:29:30	ga_ls8c_ard_3-0-0_112070_2018-05-29_final
2018-05-29 11:29:54	ga_ls8c_ard_3-0-0_112071_2018-05-29_final
2018-05-29 11:30:18	ga_ls8c_ard_3-0-0_112072_2018-05-29_final
2018-05-31 11:19:06	ga_ls8c_ard_3-0-0_110075_2018-05-31_final
2018-05-31 11:19:30	ga_ls8c_ard_3-0-0_110076_2018-05-31_final
2018-05-31 11:19:54	ga_ls8c_ard_3-0-0_110077_2018-05-31_final
2018-05-31 11:20:18	ga_ls8c_ard_3-0-0_110078_2018-05-31_final
2018-05-31 11:20:42	ga_ls8c_ard_3-0-0_110079_2018-05-31_final
2018-05-31 11:21:06	ga_ls8c_ard_3-0-0_110080_2018-05-31_final
2018-05-31 11:21:30	ga_ls8c_ard_3-0-0_110081_2018-05-31_final
2018-06-09 11:14:56	ga_ls8c_ard_3-0-0_109080_2018-06-09_final
2018-06-18 11:10:28	ga_ls8c_ard_3-0-0_108084_2018-06-18_final
2018-06-18 11:10:51	ga_ls8c_ard_3-0-0_108085_2018-06-18_final
2018-06-21 11:34:37	ga_ls8c_ard_3-0-0_113067_2018-06-21_final
2018-06-23 11:23:52	ga_ls8c_ard_3-0-0_111071_2018-06-23_final
2018-06-23 11:24:16	ga_ls8c_ard_3-0-0_111072_2018-06-23_final
2018-06-23 11:24:40	ga_ls8c_ard_3-0-0_111073_2018-06-23_final
2018-06-23 11:25:04	ga_ls8c_ard_3-0-0_111074_2018-06-23_final
2018-06-23 11:25:28	ga_ls8c_ard_3-0-0_111075_2018-06-23_final
2018-06-23 11:25:52	ga_ls8c_ard_3-0-0_111076_2018-06-23_final
2018-06-25 11:15:07	ga_ls8c_ard_3-0-0_109080_2018-06-25_final
2018-06-25 11:15:31	ga_ls8c_ard_3-0-0_109081_2018-06-25_final
2018-06-25 11:15:55	ga_ls8c_ard_3-0-0_109082_2018-06-25_final
2018-06-25 11:16:19	ga_ls8c_ard_3-0-0_109083_2018-06-25_final
2018-06-25 11:16:43	ga_ls8c_ard_3-0-0_109084_2018-06-25_final
2018-06-25 11:17:07	ga_ls8c_ard_3-0-0_109085_2018-06-25_final
2018-07-09 11:24:01	ga_ls8c_ard_3-0-0_111071_2018-07-09_final
2018-07-09 11:24:25	ga_ls8c_ard_3-0-0_111072_2018-07-09_final
2018-07-09 11:24:49	ga_ls8c_ard_3-0-0_111073_2018-07-09_final
2018-07-09 11:25:12	ga_ls8c_ard_3-0-0_111074_2018-07-09_final
2018-07-09 11:25:36	ga_ls8c_ard_3-0-0_111075_2018-07-09_final
2018-07-09 11:26:00	ga_ls8c_ard_3-0-0_111076_2018-07-09_final
2018-07-11 11:15:15	ga_ls8c_ard_3-0-0_109080_2018-07-11_final
2018-07-11 11:15:39	ga_ls8c_ard_3-0-0_109081_2018-07-11_final
2018-07-11 11:16:03	ga_ls8c_ard_3-0-0_109082_2018-07-11_final
2018-07-11 11:16:27	ga_ls8c_ard_3-0-0_109083_2018-07-11_final
2018-07-11 11:16:51	ga_ls8c_ard_3-0-0_109084_2018-07-11_final
2018-07-11 11:17:15	ga_ls8c_ard_3-0-0_109085_2018-07-11_final
2018-07-20 11:10:44	ga_ls8c_ard_3-0-0_108084_2018-07-20_final
2018-07-20 11:11:08	ga_ls8c_ard_3-0-0_108085_2018-07-20_final
2018-07-23 11:34:52	ga_ls8c_ard_3-0-0_113067_2018-07-23_final
2018-08-17 11:28:55	ga_ls8c_ard_3-0-0_112067_2018-08-17_final
2018-08-17 11:29:19	ga_ls8c_ard_3-0-0_112068_2018-08-17_final
2018-08-17 11:29:43	ga_ls8c_ard_3-0-0_112069_2018-08-17_final
2018-08-17 11:30:07	ga_ls8c_ard_3-0-0_112070_2018-08-17_final
2018-08-17 11:30:31	ga_ls8c_ard_3-0-0_112071_2018-08-17_final
2018-08-17 11:30:55	ga_ls8c_ard_3-0-0_112072_2018-08-17_final
2018-08-19 11:19:46	ga_ls8c_ard_3-0-0_110075_2018-08-19_final
2018-08-19 11:20:10	ga_ls8c_ard_3-0-0_110076_2018-08-19_final
2018-08-19 11:20:34	ga_ls8c_ard_3-0-0_110077_2018-08-19_final
2018-08-19 11:20:58	ga_ls8c_ard_3-0-0_110078_2018-08-19_final
2018-08-19 11:21:22	ga_ls8c_ard_3-0-0_110079_2018-08-19_final
2018-08-19 11:21:46	ga_ls8c_ard_3-0-0_110080_2018-08-19_final
2018-08-19 11:22:10	ga_ls8c_ard_3-0-0_110081_2018-08-19_final
2018-08-28 11:15:39	ga_ls8c_ard_3-0-0_109080_2018-08-28_final
2018-08-28 11:16:03	ga_ls8c_ard_3-0-0_109081_2018-08-28_final
2018-08-28 11:16:27	ga_ls8c_ard_3-0-0_109082_2018-08-28_final
2018-08-28 11:16:51	ga_ls8c_ard_3-0-0_109083_2018-08-28_final
2018-08-28 11:17:15	ga_ls8c_ard_3-0-0_109084_2018-08-28_final
2018-08-28 11:17:39	ga_ls8c_ard_3-0-0_109085_2018-08-28_final
2023-10-04 11:20:25	ga_ls8c_ard_3-2-1_110075_2023-10-04_final
2023-10-04 11:20:49	ga_ls8c_ard_3-2-1_110076_2023-10-04_final
2023-10-04 11:21:13	ga_ls8c_ard_3-2-1_110077_2023-10-04_final
2023-10-04 11:21:37	ga_ls8c_ard_3-2-1_110078_2023-10-04_final
2023-10-04 11:22:01	ga_ls8c_ard_3-2-1_110079_2023-10-04_final
2023-10-04 11:22:25	ga_ls8c_ard_3-2-1_110080_2023-10-04_final
2023-10-04 11:22:49	ga_ls8c_ard_3-2-1_110081_2023-10-04_final
2023-10-06 11:11:39	ga_ls8c_ard_3-2-1_108084_2023-10-06_final
2023-10-11 11:25:03	ga_ls8c_ard_3-2-1_111071_2023-10-11_final
2023-10-11 11:25:27	ga_ls8c_ard_3-2-1_111072_2023-10-11_final
2023-10-11 11:25:51	ga_ls8c_ard_3-2-1_111073_2023-10-11_final
2023-10-11 11:26:15	ga_ls8c_ard_3-2-1_111074_2023-10-11_final
2023-10-11 11:26:39	ga_ls8c_ard_3-2-1_111075_2023-10-11_final
2023-10-11 11:27:03	ga_ls8c_ard_3-2-1_111076_2023-10-11_final
2023-10-13 11:16:17	ga_ls8c_ard_3-2-1_109080_2023-10-13_final
2023-10-13 11:16:41	ga_ls8c_ard_3-2-1_109081_2023-10-13_final
2023-10-13 11:17:05	ga_ls8c_ard_3-2-1_109082_2023-10-13_final
2023-10-13 11:17:29	ga_ls8c_ard_3-2-1_109083_2023-10-13_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