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
2022-01-15 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-01-15_final
2022-01-15 10:46:50	ga_ls8c_ard_3-2-1_105068_2022-01-15_final
2022-01-15 10:47:14	ga_ls8c_ard_3-2-1_105069_2022-01-15_final
2022-01-15 10:47:38	ga_ls8c_ard_3-2-1_105070_2022-01-15_final
2022-01-15 10:48:02	ga_ls8c_ard_3-2-1_105071_2022-01-15_final
2022-01-15 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-01-15_final
2022-01-15 10:48:50	ga_ls8c_ard_3-2-1_105073_2022-01-15_final
2022-01-15 10:49:13	ga_ls8c_ard_3-2-1_105074_2022-01-15_final
2022-01-15 10:49:37	ga_ls8c_ard_3-2-1_105075_2022-01-15_final
2022-01-15 10:50:01	ga_ls8c_ard_3-2-1_105076_2022-01-15_final
2022-01-15 10:50:25	ga_ls8c_ard_3-2-1_105077_2022-01-15_final
2022-01-15 10:51:13	ga_ls8c_ard_3-2-1_105079_2022-01-15_final
2022-01-15 10:51:37	ga_ls8c_ard_3-2-1_105080_2022-01-15_final
2022-01-15 10:52:25	ga_ls8c_ard_3-2-1_105082_2022-01-15_final
2022-01-15 10:52:49	ga_ls8c_ard_3-2-1_105083_2022-01-15_final
2022-01-16 09:52:00	ga_ls8c_ard_3-2-1_096070_2022-01-16_final
2022-01-16 09:53:12	ga_ls8c_ard_3-2-1_096073_2022-01-16_final
2022-01-16 09:53:36	ga_ls8c_ard_3-2-1_096074_2022-01-16_final
2022-01-16 09:54:00	ga_ls8c_ard_3-2-1_096075_2022-01-16_final
2022-01-16 09:54:24	ga_ls8c_ard_3-2-1_096076_2022-01-16_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
2022-01-16 09:58:23	ga_ls8c_ard_3-2-1_096086_2022-01-16_final
2022-01-16 11:31:41	ga_ls8c_ard_3-2-1_112072_2022-01-16_final
2022-01-16 11:32:05	ga_ls8c_ard_3-2-1_112073_2022-01-16_final
2022-01-16 11:32:29	ga_ls8c_ard_3-2-1_112074_2022-01-16_final
2022-01-16 11:32:53	ga_ls8c_ard_3-2-1_112075_2022-01-16_final
2022-01-16 11:33:17	ga_ls8c_ard_3-2-1_112076_2022-01-16_final
2022-01-16 11:33:41	ga_ls8c_ard_3-2-1_112077_2022-01-16_final
2022-01-16 11:34:05	ga_ls8c_ard_3-2-1_112078_2022-01-16_final
2022-01-16 11:34:29	ga_ls8c_ard_3-2-1_112079_2022-01-16_final
2022-01-16 11:34:53	ga_ls8c_ard_3-2-1_112080_2022-01-16_final
2022-01-16 11:35:17	ga_ls8c_ard_3-2-1_112081_2022-01-16_final
2022-01-16 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-01-16_final
2022-01-16 11:36:04	ga_ls8c_ard_3-2-1_112083_2022-01-16_final
2022-01-16 11:36:28	ga_ls8c_ard_3-2-1_112084_2022-01-16_final
2022-01-17 10:34:28	ga_ls8c_ard_3-2-1_103068_2022-01-17_final
2022-01-17 10:34:52	ga_ls8c_ard_3-2-1_103069_2022-01-17_final
2022-01-17 10:35:16	ga_ls8c_ard_3-2-1_103070_2022-01-17_final
2022-01-17 10:35:40	ga_ls8c_ard_3-2-1_103071_2022-01-17_final
2022-01-17 10:36:03	ga_ls8c_ard_3-2-1_103072_2022-01-17_final
2022-01-17 10:36:27	ga_ls8c_ard_3-2-1_103073_2022-01-17_final
2022-01-17 10:36:51	ga_ls8c_ard_3-2-1_103074_2022-01-17_final
2022-01-17 10:37:15	ga_ls8c_ard_3-2-1_103075_2022-01-17_final
2022-01-17 10:37:39	ga_ls8c_ard_3-2-1_103076_2022-01-17_final
2022-01-17 10:38:27	ga_ls8c_ard_3-2-1_103078_2022-01-17_final
2022-01-17 10:38:51	ga_ls8c_ard_3-2-1_103079_2022-01-17_final
2022-01-17 10:39:15	ga_ls8c_ard_3-2-1_103080_2022-01-17_final
2022-01-17 10:39:39	ga_ls8c_ard_3-2-1_103081_2022-01-17_final
2022-01-17 10:40:03	ga_ls8c_ard_3-2-1_103082_2022-01-17_final
2022-01-18 09:40:02	ga_ls8c_ard_3-2-1_094071_2022-01-18_final
2022-01-18 09:40:50	ga_ls8c_ard_3-2-1_094073_2022-01-18_final
2022-01-18 09:41:38	ga_ls8c_ard_3-2-1_094075_2022-01-18_final
2022-01-18 09:42:02	ga_ls8c_ard_3-2-1_094076_2022-01-18_final
2022-01-18 09:42:26	ga_ls8c_ard_3-2-1_094077_2022-01-18_final
2022-01-18 09:42:49	ga_ls8c_ard_3-2-1_094078_2022-01-18_final
2022-01-18 09:43:13	ga_ls8c_ard_3-2-1_094079_2022-01-18_final
2022-01-18 09:43:37	ga_ls8c_ard_3-2-1_094080_2022-01-18_final
2022-01-18 09:44:01	ga_ls8c_ard_3-2-1_094081_2022-01-18_final
2022-01-18 09:44:25	ga_ls8c_ard_3-2-1_094082_2022-01-18_final
2022-01-18 09:44:49	ga_ls8c_ard_3-2-1_094083_2022-01-18_final
2022-01-18 09:45:13	ga_ls8c_ard_3-2-1_094084_2022-01-18_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
2022-01-18 11:18:07	ga_ls8c_ard_3-2-1_110069_2022-01-18_final
2022-01-18 11:18:31	ga_ls8c_ard_3-2-1_110070_2022-01-18_final
2022-01-18 11:18:55	ga_ls8c_ard_3-2-1_110071_2022-01-18_final
2022-01-18 11:19:19	ga_ls8c_ard_3-2-1_110072_2022-01-18_final
2022-01-18 11:19:43	ga_ls8c_ard_3-2-1_110073_2022-01-18_final
2022-01-18 11:20:07	ga_ls8c_ard_3-2-1_110074_2022-01-18_final
2022-01-18 11:20:31	ga_ls8c_ard_3-2-1_110075_2022-01-18_final
2022-01-18 11:20:55	ga_ls8c_ard_3-2-1_110076_2022-01-18_final
2022-01-18 11:21:19	ga_ls8c_ard_3-2-1_110077_2022-01-18_final
2022-01-18 11:21:42	ga_ls8c_ard_3-2-1_110078_2022-01-18_final
2022-01-18 11:22:06	ga_ls8c_ard_3-2-1_110079_2022-01-18_final
2022-01-18 11:22:30	ga_ls8c_ard_3-2-1_110080_2022-01-18_final
2022-01-18 11:23:18	ga_ls8c_ard_3-2-1_110082_2022-01-18_final
2022-01-18 11:24:30	ga_ls8c_ard_3-2-1_110085_2022-01-18_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
2022-01-19 10:25:17	ga_ls8c_ard_3-2-1_101076_2022-01-19_final
2022-01-19 10:25:41	ga_ls8c_ard_3-2-1_101077_2022-01-19_final
2022-01-19 10:26:05	ga_ls8c_ard_3-2-1_101078_2022-01-19_final
2022-01-19 10:26:29	ga_ls8c_ard_3-2-1_101079_2022-01-19_final
2022-01-19 10:26:53	ga_ls8c_ard_3-2-1_101080_2022-01-19_final
2022-01-19 10:27:17	ga_ls8c_ard_3-2-1_101081_2022-01-19_final
2022-01-19 10:27:41	ga_ls8c_ard_3-2-1_101082_2022-01-19_final
2022-01-19 10:28:05	ga_ls8c_ard_3-2-1_101083_2022-01-19_final
2022-01-20 09:27:40	ga_ls8c_ard_3-2-1_092071_2022-01-19_final
2022-01-20 09:28:03	ga_ls8c_ard_3-2-1_092072_2022-01-19_final
2022-01-20 09:28:27	ga_ls8c_ard_3-2-1_092073_2022-01-19_final
2022-01-20 09:28:51	ga_ls8c_ard_3-2-1_092074_2022-01-19_final
2022-01-20 09:29:15	ga_ls8c_ard_3-2-1_092075_2022-01-19_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