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
2016-05-18 09:40:00	ga_ls8c_ard_3-0-0_093088_2016-05-18_final
2016-07-31 10:09:09	ga_ls8c_ard_3-0-0_099067_2016-07-31_final
2016-07-31 10:09:33	ga_ls8c_ard_3-0-0_099068_2016-07-31_final
2016-07-31 10:09:57	ga_ls8c_ard_3-0-0_099069_2016-07-31_final
2016-10-09 09:40:43	ga_ls8c_ard_3-0-0_093088_2016-10-09_final
2016-10-12 10:03:40	ga_ls8c_ard_3-0-0_098068_2016-10-12_final
2016-10-12 10:04:04	ga_ls8c_ard_3-0-0_098069_2016-10-12_final
2016-10-12 10:04:28	ga_ls8c_ard_3-0-0_098070_2016-10-12_final
2016-10-12 10:04:51	ga_ls8c_ard_3-1-0_098071_2016-10-12_final
2016-10-12 10:05:15	ga_ls8c_ard_3-0-0_098072_2016-10-12_final
2016-10-12 10:05:39	ga_ls8c_ard_3-0-0_098073_2016-10-12_final
2016-10-12 10:06:03	ga_ls8c_ard_3-0-0_098074_2016-10-12_final
2016-10-14 09:54:54	ga_ls8c_ard_3-0-0_096077_2016-10-14_final
2016-10-14 09:55:18	ga_ls8c_ard_3-0-0_096078_2016-10-14_final
2016-10-14 09:55:42	ga_ls8c_ard_3-0-0_096079_2016-10-14_final
2016-10-14 09:56:06	ga_ls8c_ard_3-0-0_096080_2016-10-14_final
2016-10-14 09:56:30	ga_ls8c_ard_3-0-0_096081_2016-10-14_final
2016-10-14 09:56:54	ga_ls8c_ard_3-0-0_096082_2016-10-14_final
2016-10-14 09:57:18	ga_ls8c_ard_3-0-0_096083_2016-10-14_final
2021-02-07 09:50:06	ga_ls8c_ard_3-2-0_095081_2021-02-07_final
2021-02-07 09:50:30	ga_ls8c_ard_3-2-0_095082_2021-02-07_final
2021-02-07 09:50:54	ga_ls8c_ard_3-2-0_095083_2021-02-07_final
2021-02-07 09:51:18	ga_ls8c_ard_3-2-0_095084_2021-02-07_final
2021-02-07 09:51:42	ga_ls8c_ard_3-2-0_095085_2021-02-07_final
2021-02-07 09:52:06	ga_ls8c_ard_3-2-0_095086_2021-02-07_final
2021-02-07 09:52:30	ga_ls8c_ard_3-2-0_095087_2021-02-07_final
2021-02-12 10:03:26	ga_ls8c_ard_3-2-0_098068_2021-02-12_final
2021-02-12 10:03:50	ga_ls8c_ard_3-2-0_098069_2021-02-12_final
2021-02-12 10:04:14	ga_ls8c_ard_3-2-0_098070_2021-02-12_final
2021-02-12 10:04:38	ga_ls8c_ard_3-2-0_098071_2021-02-12_final
2021-02-12 10:05:02	ga_ls8c_ard_3-2-0_098072_2021-02-12_final
2021-02-12 10:05:26	ga_ls8c_ard_3-2-0_098073_2021-02-12_final
2021-02-12 10:05:50	ga_ls8c_ard_3-2-0_098074_2021-02-12_final
2021-02-23 09:50:01	ga_ls8c_ard_3-2-0_095081_2021-02-23_final
2021-02-23 09:50:25	ga_ls8c_ard_3-2-0_095082_2021-02-23_final
2021-02-23 09:50:49	ga_ls8c_ard_3-2-0_095083_2021-02-23_final
2021-02-23 09:51:13	ga_ls8c_ard_3-2-0_095084_2021-02-23_final
2021-02-23 09:51:37	ga_ls8c_ard_3-2-0_095085_2021-02-23_final
2021-02-23 09:52:01	ga_ls8c_ard_3-2-0_095086_2021-02-23_final
2021-02-23 09:52:25	ga_ls8c_ard_3-2-0_095087_2021-02-23_final
2021-05-14 09:49:34	ga_ls8c_ard_3-2-0_095081_2021-05-14_final
2021-05-14 09:49:58	ga_ls8c_ard_3-2-0_095082_2021-05-14_final
2021-05-14 09:50:22	ga_ls8c_ard_3-2-0_095083_2021-05-14_final
2021-05-14 09:50:46	ga_ls8c_ard_3-2-0_095084_2021-05-14_final
2022-01-02 09:45:39	ga_ls8c_ard_3-2-1_094085_2022-01-02_final
2022-01-02 09:46:03	ga_ls8c_ard_3-2-1_094086_2022-01-02_final
2022-01-02 09:46:27	ga_ls8c_ard_3-2-1_094087_2022-01-02_final
2022-01-05 10:08:59	ga_ls8c_ard_3-2-1_099066_2022-01-05_final
2022-01-05 10:09:22	ga_ls8c_ard_3-2-1_099067_2022-01-05_final
2022-01-05 10:09:46	ga_ls8c_ard_3-2-1_099068_2022-01-05_final
2022-01-05 10:10:10	ga_ls8c_ard_3-2-1_099069_2022-01-05_final
2022-01-09 09:50:14	ga_ls8c_ard_3-2-1_095081_2022-01-09_final
2022-01-09 09:50:38	ga_ls8c_ard_3-2-1_095082_2022-01-09_final
2022-01-09 09:51:02	ga_ls8c_ard_3-2-1_095083_2022-01-09_final
2022-01-09 09:51:26	ga_ls8c_ard_3-2-1_095084_2022-01-09_final
2022-01-09 09:51:50	ga_ls8c_ard_3-2-1_095085_2022-01-09_final
2022-01-09 09:52:14	ga_ls8c_ard_3-2-1_095086_2022-01-09_final
2022-01-09 09:52:38	ga_ls8c_ard_3-2-1_095087_2022-01-09_final
2022-01-14 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-01-14_final
2022-01-14 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-01-14_final
2022-01-14 10:04:22	ga_ls8c_ard_3-2-1_098070_2022-01-14_final
2022-01-14 10:04:46	ga_ls8c_ard_3-2-1_098071_2022-01-14_final
2022-01-14 10:05:10	ga_ls8c_ard_3-2-1_098072_2022-01-14_final
2022-01-14 10:05:34	ga_ls8c_ard_3-2-1_098073_2022-01-14_final
2022-01-14 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-01-14_final
2022-01-16 09:54:48	ga_ls8c_ard_3-2-1_096077_2022-01-16_final
2022-01-16 09:55:12	ga_ls8c_ard_3-2-1_096078_2022-01-16_final
2022-01-16 09:55:36	ga_ls8c_ard_3-2-1_096079_2022-01-16_final
2022-01-16 09:56:00	ga_ls8c_ard_3-2-1_096080_2022-01-16_final
2022-01-16 09:56:24	ga_ls8c_ard_3-2-1_096081_2022-01-16_final
2022-01-16 09:56:47	ga_ls8c_ard_3-2-1_096082_2022-01-16_final
2022-01-16 09:57:11	ga_ls8c_ard_3-2-1_096083_2022-01-16_final
2022-01-18 09:45:37	ga_ls8c_ard_3-2-1_094085_2022-01-18_final
2022-01-18 09:46:01	ga_ls8c_ard_3-2-1_094086_2022-01-18_final
2022-01-18 09:46:25	ga_ls8c_ard_3-2-1_094087_2022-01-18_final
2022-01-21 10:08:55	ga_ls8c_ard_3-2-1_099066_2022-01-21_final
2022-01-21 10:09:19	ga_ls8c_ard_3-2-1_099067_2022-01-21_final
2022-01-21 10:09:43	ga_ls8c_ard_3-2-1_099068_2022-01-21_final
2022-01-21 10:10:07	ga_ls8c_ard_3-2-1_099069_2022-01-21_final
2022-10-31 09:55:13	ga_ls8c_ard_3-2-1_096077_2022-10-31_final
2022-10-31 09:57:13	ga_ls8c_ard_3-2-1_096082_2022-10-31_final
2022-10-31 09:57:37	ga_ls8c_ard_3-2-1_096083_2022-10-31_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-02 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-11-02_final
2022-11-02 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-11-02_final
2022-11-07 09:59:48	ga_ls8c_ard_3-2-1_097073_2022-11-07_final
2022-11-07 10:00:12	ga_ls8c_ard_3-2-1_097074_2022-11-07_final
2022-11-07 10:00:35	ga_ls8c_ard_3-2-1_097075_2022-11-07_final
2022-11-07 10:00:59	ga_ls8c_ard_3-2-1_097076_2022-11-07_final
2022-11-07 10:01:23	ga_ls8c_ard_3-2-1_097077_2022-11-07_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-16 09:55:31	ga_ls8c_ard_3-2-1_096078_2022-11-16_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_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