Search ga_ls8c_ard_3 across October 2023

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
2023-10-01 10:51:31	ga_ls8c_ard_3-2-1_105080_2023-10-01_final
2023-10-01 10:51:55	ga_ls8c_ard_3-2-1_105081_2023-10-01_final
2023-10-01 10:52:19	ga_ls8c_ard_3-2-1_105082_2023-10-01_final
2023-10-01 10:52:43	ga_ls8c_ard_3-2-1_105083_2023-10-01_final
2023-10-02 08:24:12	ga_ls8c_ard_3-2-1_080098_2023-10-01_final
2023-10-02 09:51:55	ga_ls8c_ard_3-2-1_096070_2023-10-02_final
2023-10-02 09:52:19	ga_ls8c_ard_3-2-1_096071_2023-10-02_final
2023-10-02 09:52:43	ga_ls8c_ard_3-2-1_096072_2023-10-02_final
2023-10-02 09:53:06	ga_ls8c_ard_3-2-1_096073_2023-10-02_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-02 09:53:54	ga_ls8c_ard_3-2-1_096075_2023-10-02_final
2023-10-02 09:54:18	ga_ls8c_ard_3-2-1_096076_2023-10-02_final
2023-10-02 09:54:42	ga_ls8c_ard_3-2-1_096077_2023-10-02_final
2023-10-02 09:55:06	ga_ls8c_ard_3-2-1_096078_2023-10-02_final
2023-10-02 09:55:30	ga_ls8c_ard_3-2-1_096079_2023-10-02_final
2023-10-02 09:55:54	ga_ls8c_ard_3-2-1_096080_2023-10-02_final
2023-10-02 09:56:18	ga_ls8c_ard_3-2-1_096081_2023-10-02_final
2023-10-02 09:56:42	ga_ls8c_ard_3-2-1_096082_2023-10-02_final
2023-10-02 09:57:06	ga_ls8c_ard_3-2-1_096083_2023-10-02_final
2023-10-02 09:57:30	ga_ls8c_ard_3-2-1_096084_2023-10-02_final
2023-10-02 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-10-02_final
2023-10-02 09:58:18	ga_ls8c_ard_3-2-1_096086_2023-10-02_final
2023-10-02 11:31:36	ga_ls8c_ard_3-2-1_112072_2023-10-02_final
2023-10-02 11:31:59	ga_ls8c_ard_3-2-1_112073_2023-10-02_final
2023-10-02 11:32:23	ga_ls8c_ard_3-2-1_112074_2023-10-02_final
2023-10-02 11:32:47	ga_ls8c_ard_3-2-1_112075_2023-10-02_final
2023-10-02 11:33:11	ga_ls8c_ard_3-2-1_112076_2023-10-02_final
2023-10-02 11:33:35	ga_ls8c_ard_3-2-1_112077_2023-10-02_final
2023-10-02 11:33:59	ga_ls8c_ard_3-2-1_112078_2023-10-02_final
2023-10-02 11:34:23	ga_ls8c_ard_3-2-1_112079_2023-10-02_final
2023-10-02 11:34:47	ga_ls8c_ard_3-2-1_112080_2023-10-02_final
2023-10-02 11:35:11	ga_ls8c_ard_3-2-1_112081_2023-10-02_final
2023-10-02 11:35:35	ga_ls8c_ard_3-2-1_112082_2023-10-02_final
2023-10-02 11:35:59	ga_ls8c_ard_3-2-1_112083_2023-10-02_final
2023-10-02 11:36:23	ga_ls8c_ard_3-2-1_112084_2023-10-02_final
2023-10-03 10:34:22	ga_ls8c_ard_3-2-1_103068_2023-10-03_final
2023-10-03 10:34:46	ga_ls8c_ard_3-2-1_103069_2023-10-03_final
2023-10-03 10:35:10	ga_ls8c_ard_3-2-1_103070_2023-10-03_final
2023-10-03 10:35:34	ga_ls8c_ard_3-2-1_103071_2023-10-03_final
2023-10-03 10:35:58	ga_ls8c_ard_3-2-1_103072_2023-10-03_final
2023-10-03 10:36:22	ga_ls8c_ard_3-2-1_103073_2023-10-03_final
2023-10-03 10:36:46	ga_ls8c_ard_3-2-1_103074_2023-10-03_final
2023-10-03 10:37:10	ga_ls8c_ard_3-2-1_103075_2023-10-03_final
2023-10-03 10:37:34	ga_ls8c_ard_3-2-1_103076_2023-10-03_final
2023-10-03 10:37:58	ga_ls8c_ard_3-2-1_103077_2023-10-03_final
2023-10-03 10:38:22	ga_ls8c_ard_3-2-1_103078_2023-10-03_final
2023-10-03 10:38:46	ga_ls8c_ard_3-2-1_103079_2023-10-03_final
2023-10-03 10:39:10	ga_ls8c_ard_3-2-1_103080_2023-10-03_final
2023-10-03 10:39:34	ga_ls8c_ard_3-2-1_103081_2023-10-03_final
2023-10-03 10:39:57	ga_ls8c_ard_3-2-1_103082_2023-10-03_final
2023-10-03 14:03:43	ga_ls8c_ard_3-2-1_135097_2023-10-03_final
2023-10-04 09:39:57	ga_ls8c_ard_3-2-1_094071_2023-10-04_final
2023-10-04 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-04_final
2023-10-04 09:40:44	ga_ls8c_ard_3-2-1_094073_2023-10-04_final
2023-10-04 09:41:08	ga_ls8c_ard_3-2-1_094074_2023-10-04_final
2023-10-04 09:41:32	ga_ls8c_ard_3-2-1_094075_2023-10-04_final
2023-10-04 09:41:56	ga_ls8c_ard_3-2-1_094076_2023-10-04_final
2023-10-04 09:42:20	ga_ls8c_ard_3-2-1_094077_2023-10-04_final
2023-10-04 09:42:44	ga_ls8c_ard_3-2-1_094078_2023-10-04_final
2023-10-04 09:43:08	ga_ls8c_ard_3-2-1_094079_2023-10-04_final
2023-10-04 09:43:32	ga_ls8c_ard_3-2-1_094080_2023-10-04_final
2023-10-04 09:43:56	ga_ls8c_ard_3-2-1_094081_2023-10-04_final
2023-10-04 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-10-04_final
2023-10-04 09:44:44	ga_ls8c_ard_3-2-1_094083_2023-10-04_final
2023-10-04 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-10-04_final
2023-10-04 09:45:32	ga_ls8c_ard_3-2-1_094085_2023-10-04_final
2023-10-04 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-10-04_final
2023-10-04 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-10-04_final
2023-10-13 09:40:36	ga_ls8c_ard_3-2-1_093088_2023-10-13_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-13 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-10-13_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_final
2023-10-15 09:25:02	ga_ls8c_ard_3-2-1_091080_2023-10-14_final
2023-10-15 09:25:26	ga_ls8c_ard_3-2-1_091081_2023-10-14_final
2023-10-15 09:25:50	ga_ls8c_ard_3-2-1_091082_2023-10-14_final
2023-10-15 09:26:14	ga_ls8c_ard_3-2-1_091083_2023-10-14_final
2023-10-15 09:26:38	ga_ls8c_ard_3-2-1_091084_2023-10-14_final
2023-10-15 09:27:02	ga_ls8c_ard_3-2-1_091085_2023-10-14_final
2023-10-15 09:27:26	ga_ls8c_ard_3-2-1_091086_2023-10-14_final
2023-10-15 09:27:50	ga_ls8c_ard_3-2-1_091087_2023-10-14_final
2023-10-15 09:28:14	ga_ls8c_ard_3-2-1_091088_2023-10-14_final
2023-10-15 09:28:38	ga_ls8c_ard_3-2-1_091089_2023-10-14_final
2023-10-15 09:29:02	ga_ls8c_ard_3-2-1_091090_2023-10-14_final
2023-10-15 10:59:08	ga_ls8c_ard_3-2-1_107068_2023-10-15_final
2023-10-15 10:59:32	ga_ls8c_ard_3-2-1_107069_2023-10-15_final
2023-10-15 10:59:56	ga_ls8c_ard_3-2-1_107070_2023-10-15_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-15 11:01:08	ga_ls8c_ard_3-2-1_107073_2023-10-15_final
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_final
2023-10-15 11:01:56	ga_ls8c_ard_3-2-1_107075_2023-10-15_final
2023-10-15 11:02:20	ga_ls8c_ard_3-2-1_107076_2023-10-15_final
2023-10-15 11:02:44	ga_ls8c_ard_3-2-1_107077_2023-10-15_final
2023-10-15 11:03:07	ga_ls8c_ard_3-2-1_107078_2023-10-15_final
2023-10-15 11:03:31	ga_ls8c_ard_3-2-1_107079_2023-10-15_final
2023-10-15 11:03:55	ga_ls8c_ard_3-2-1_107080_2023-10-15_final
2023-10-15 11:04:19	ga_ls8c_ard_3-2-1_107081_2023-10-15_final
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_final
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_final
2023-10-15 11:05:31	ga_ls8c_ard_3-2-1_107084_2023-10-15_final

Return to ga_ls8c_ard_3 across October 2023 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

2023

October

All days