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
2023-11-14 09:34:13	ga_ls8c_ard_3-2-1_093072_2023-11-14_final
2023-11-14 09:34:37	ga_ls8c_ard_3-2-1_093073_2023-11-14_final
2023-11-14 09:35:01	ga_ls8c_ard_3-2-1_093074_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-14 11:15:54	ga_ls8c_ard_3-2-1_109079_2023-11-14_final
2023-11-15 10:18:18	ga_ls8c_ard_3-2-1_100074_2023-11-15_final
2023-11-15 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-11-15_final
2023-11-16 09:21:53	ga_ls8c_ard_3-2-1_091072_2023-11-15_final
2023-11-16 09:22:17	ga_ls8c_ard_3-2-1_091073_2023-11-15_final
2023-11-16 09:22:41	ga_ls8c_ard_3-2-1_091074_2023-11-15_final
2023-11-16 09:23:05	ga_ls8c_ard_3-2-1_091075_2023-11-15_final
2023-11-16 10:59:58	ga_ls8c_ard_3-2-1_107070_2023-11-16_final
2023-11-16 11:00:22	ga_ls8c_ard_3-2-1_107071_2023-11-16_final
2023-11-16 11:00:46	ga_ls8c_ard_3-2-1_107072_2023-11-16_final
2023-11-16 11:01:10	ga_ls8c_ard_3-2-1_107073_2023-11-16_final
2023-11-16 11:01:34	ga_ls8c_ard_3-2-1_107074_2023-11-16_final
2023-11-16 11:01:58	ga_ls8c_ard_3-2-1_107075_2023-11-16_final
2023-11-16 11:02:22	ga_ls8c_ard_3-2-1_107076_2023-11-16_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-16 11:03:10	ga_ls8c_ard_3-2-1_107078_2023-11-16_final
2023-11-16 11:03:34	ga_ls8c_ard_3-2-1_107079_2023-11-16_final
2023-11-16 11:03:58	ga_ls8c_ard_3-2-1_107080_2023-11-16_final
2023-11-16 11:04:22	ga_ls8c_ard_3-2-1_107081_2023-11-16_final
2023-11-16 11:04:45	ga_ls8c_ard_3-2-1_107082_2023-11-16_final
2023-11-16 11:05:09	ga_ls8c_ard_3-2-1_107083_2023-11-16_final
2023-11-16 11:05:33	ga_ls8c_ard_3-2-1_107084_2023-11-16_final
2023-11-17 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-11-17_final
2023-11-17 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-17_final
2023-11-17 10:03:57	ga_ls8c_ard_3-2-1_098069_2023-11-17_final
2023-11-17 10:04:21	ga_ls8c_ard_3-2-1_098070_2023-11-17_final
2023-11-17 10:04:45	ga_ls8c_ard_3-2-1_098071_2023-11-17_final
2023-11-17 10:05:09	ga_ls8c_ard_3-2-1_098072_2023-11-17_final
2023-11-17 10:05:33	ga_ls8c_ard_3-2-1_098073_2023-11-17_final
2023-11-17 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-17_final
2023-11-17 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-17_final
2023-11-17 10:06:45	ga_ls8c_ard_3-2-1_098076_2023-11-17_final
2023-11-17 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-11-17_final
2023-11-17 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-11-17_final
2023-11-17 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-11-17_final
2023-11-17 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-11-17_final
2023-11-17 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-17_final
2023-11-17 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-11-17_final
2023-11-17 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-11-17_final
2023-11-17 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-11-17_final
2023-11-17 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-17_final
2023-11-17 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-17_final
2023-11-17 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-11-17_final
2023-11-17 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-11-17_final
2023-11-18 09:10:20	ga_ls8c_ard_3-2-1_089074_2023-11-17_final
2023-11-18 09:10:44	ga_ls8c_ard_3-2-1_089075_2023-11-17_final
2023-11-18 09:11:08	ga_ls8c_ard_3-2-1_089076_2023-11-17_final
2023-11-18 09:11:32	ga_ls8c_ard_3-2-1_089077_2023-11-17_final
2023-11-18 09:11:56	ga_ls8c_ard_3-2-1_089078_2023-11-17_final
2023-11-18 09:12:20	ga_ls8c_ard_3-2-1_089079_2023-11-17_final
2023-11-18 09:13:56	ga_ls8c_ard_3-2-1_089083_2023-11-17_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_final
2023-11-18 09:14:44	ga_ls8c_ard_3-2-1_089085_2023-11-17_final
2023-11-18 09:15:08	ga_ls8c_ard_3-2-1_089086_2023-11-17_final
2023-11-18 09:16:20	ga_ls8c_ard_3-2-1_089089_2023-11-17_final
2023-11-18 09:16:44	ga_ls8c_ard_3-2-1_089090_2023-11-17_final
2023-11-18 10:46:26	ga_ls8c_ard_3-2-1_105067_2023-11-18_final
2023-11-18 10:46:50	ga_ls8c_ard_3-2-1_105068_2023-11-18_final
2023-11-18 10:47:14	ga_ls8c_ard_3-2-1_105069_2023-11-18_final
2023-11-18 10:47:38	ga_ls8c_ard_3-2-1_105070_2023-11-18_final
2023-11-18 10:48:02	ga_ls8c_ard_3-2-1_105071_2023-11-18_final
2023-11-18 10:48:26	ga_ls8c_ard_3-2-1_105072_2023-11-18_final
2023-11-18 10:48:49	ga_ls8c_ard_3-2-1_105073_2023-11-18_final
2023-11-18 10:49:13	ga_ls8c_ard_3-2-1_105074_2023-11-18_final
2023-11-18 10:49:37	ga_ls8c_ard_3-2-1_105075_2023-11-18_final
2023-11-18 10:50:01	ga_ls8c_ard_3-2-1_105076_2023-11-18_final
2023-11-18 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-18_final
2023-11-18 10:50:49	ga_ls8c_ard_3-2-1_105078_2023-11-18_final
2023-11-18 10:51:13	ga_ls8c_ard_3-2-1_105079_2023-11-18_final
2023-11-18 10:51:37	ga_ls8c_ard_3-2-1_105080_2023-11-18_final
2023-11-18 10:52:01	ga_ls8c_ard_3-2-1_105081_2023-11-18_final
2023-11-19 09:52:01	ga_ls8c_ard_3-2-1_096070_2023-11-19_final
2023-11-19 09:52:25	ga_ls8c_ard_3-2-1_096071_2023-11-19_final
2023-11-19 09:52:49	ga_ls8c_ard_3-2-1_096072_2023-11-19_final
2023-11-19 09:53:13	ga_ls8c_ard_3-2-1_096073_2023-11-19_final
2023-11-19 09:53:37	ga_ls8c_ard_3-2-1_096074_2023-11-19_final
2023-11-19 09:54:00	ga_ls8c_ard_3-2-1_096075_2023-11-19_final
2023-11-19 09:54:24	ga_ls8c_ard_3-2-1_096076_2023-11-19_final
2023-11-19 09:54:48	ga_ls8c_ard_3-2-1_096077_2023-11-19_final
2023-11-19 09:55:12	ga_ls8c_ard_3-2-1_096078_2023-11-19_final
2023-11-19 09:56:00	ga_ls8c_ard_3-2-1_096080_2023-11-19_final
2023-11-19 09:56:24	ga_ls8c_ard_3-2-1_096081_2023-11-19_final
2023-11-19 09:56:48	ga_ls8c_ard_3-2-1_096082_2023-11-19_final
2023-11-19 09:57:12	ga_ls8c_ard_3-2-1_096083_2023-11-19_final
2023-11-19 09:57:36	ga_ls8c_ard_3-2-1_096084_2023-11-19_final
2023-11-19 09:58:24	ga_ls8c_ard_3-2-1_096086_2023-11-19_final
2023-11-19 11:32:06	ga_ls8c_ard_3-2-1_112073_2023-11-19_final
2023-11-19 11:32:30	ga_ls8c_ard_3-2-1_112074_2023-11-19_final
2023-11-19 11:32:54	ga_ls8c_ard_3-2-1_112075_2023-11-19_final
2023-11-19 11:33:18	ga_ls8c_ard_3-2-1_112076_2023-11-19_final
2023-11-19 11:33:41	ga_ls8c_ard_3-2-1_112077_2023-11-19_final
2023-11-19 11:34:05	ga_ls8c_ard_3-2-1_112078_2023-11-19_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-19 11:34:53	ga_ls8c_ard_3-2-1_112080_2023-11-19_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years