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
2022-09-05 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-09-05_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-05 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-09-05_final
2022-09-05 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-09-05_final
2022-09-05 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-09-05_final
2022-09-05 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-09-05_final
2022-09-05 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-09-05_final
2022-09-05 10:44:10	ga_ls8c_ard_3-2-1_104076_2022-09-05_final
2022-09-06 09:46:34	ga_ls8c_ard_3-2-1_095071_2022-09-06_final
2022-09-06 09:47:46	ga_ls8c_ard_3-2-1_095074_2022-09-06_final
2022-09-06 09:48:10	ga_ls8c_ard_3-2-1_095075_2022-09-06_final
2022-09-06 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-09-06_final
2022-09-06 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-09-06_final
2022-09-06 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-09-06_final
2022-09-06 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-09-06_final
2022-09-06 09:50:33	ga_ls8c_ard_3-2-1_095081_2022-09-06_final
2022-09-06 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-09-06_final
2022-09-06 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-09-06_final
2022-09-06 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-09-06_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-06 09:52:57	ga_ls8c_ard_3-2-1_095087_2022-09-06_final
2022-09-06 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-09-06_final
2022-09-06 11:25:03	ga_ls8c_ard_3-2-1_111070_2022-09-06_final
2022-09-06 11:25:27	ga_ls8c_ard_3-2-1_111071_2022-09-06_final
2022-09-06 11:26:15	ga_ls8c_ard_3-2-1_111073_2022-09-06_final
2022-09-06 11:27:03	ga_ls8c_ard_3-2-1_111075_2022-09-06_final
2022-09-06 11:27:27	ga_ls8c_ard_3-2-1_111076_2022-09-06_final
2022-09-06 11:27:51	ga_ls8c_ard_3-2-1_111077_2022-09-06_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-06 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-09-06_final
2022-09-06 11:29:02	ga_ls8c_ard_3-2-1_111080_2022-09-06_final
2022-09-06 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-09-06_final
2022-09-06 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-09-06_final
2022-09-06 11:30:14	ga_ls8c_ard_3-2-1_111083_2022-09-06_final
2022-09-06 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-09-06_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-07 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-09-07_final
2022-09-07 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-09-07_final
2022-09-07 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-09-07_final
2022-09-07 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-09-07_final
2022-09-07 10:31:26	ga_ls8c_ard_3-2-1_102075_2022-09-07_final
2022-09-07 10:31:50	ga_ls8c_ard_3-2-1_102076_2022-09-07_final
2022-09-07 10:32:14	ga_ls8c_ard_3-2-1_102077_2022-09-07_final
2022-09-07 10:33:02	ga_ls8c_ard_3-2-1_102079_2022-09-07_final
2022-09-07 10:33:26	ga_ls8c_ard_3-2-1_102080_2022-09-07_final
2022-09-07 10:33:50	ga_ls8c_ard_3-2-1_102081_2022-09-07_final
2022-09-07 10:34:13	ga_ls8c_ard_3-2-1_102082_2022-09-07_final
2022-09-08 09:34:37	ga_ls8c_ard_3-2-1_093072_2022-09-08_final
2022-09-08 09:35:01	ga_ls8c_ard_3-2-1_093073_2022-09-08_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-08 09:35:49	ga_ls8c_ard_3-2-1_093075_2022-09-08_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-08 09:36:37	ga_ls8c_ard_3-2-1_093077_2022-09-08_final
2022-09-08 09:37:01	ga_ls8c_ard_3-2-1_093078_2022-09-08_final
2022-09-08 09:37:25	ga_ls8c_ard_3-2-1_093079_2022-09-08_final
2022-09-08 09:38:13	ga_ls8c_ard_3-2-1_093081_2022-09-08_final
2022-09-08 09:38:37	ga_ls8c_ard_3-2-1_093082_2022-09-08_final
2022-09-08 09:39:01	ga_ls8c_ard_3-2-1_093083_2022-09-08_final
2022-09-08 09:39:49	ga_ls8c_ard_3-2-1_093085_2022-09-08_final
2022-09-08 09:41:00	ga_ls8c_ard_3-2-1_093088_2022-09-08_final
2022-09-08 11:12:19	ga_ls8c_ard_3-2-1_109069_2022-09-08_final
2022-09-08 11:13:06	ga_ls8c_ard_3-2-1_109071_2022-09-08_final
2022-09-08 11:13:30	ga_ls8c_ard_3-2-1_109072_2022-09-08_final
2022-09-08 11:14:18	ga_ls8c_ard_3-2-1_109074_2022-09-08_final
2022-09-08 11:14:42	ga_ls8c_ard_3-2-1_109075_2022-09-08_final
2022-09-08 11:15:06	ga_ls8c_ard_3-2-1_109076_2022-09-08_final
2022-09-08 11:15:30	ga_ls8c_ard_3-2-1_109077_2022-09-08_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-08 11:16:18	ga_ls8c_ard_3-2-1_109079_2022-09-08_final
2022-09-08 11:16:42	ga_ls8c_ard_3-2-1_109080_2022-09-08_final
2022-09-08 11:17:06	ga_ls8c_ard_3-2-1_109081_2022-09-08_final
2022-09-08 11:17:30	ga_ls8c_ard_3-2-1_109082_2022-09-08_final
2022-09-08 11:17:54	ga_ls8c_ard_3-2-1_109083_2022-09-08_final
2022-09-08 11:18:18	ga_ls8c_ard_3-2-1_109084_2022-09-08_final
2022-09-09 10:19:53	ga_ls8c_ard_3-2-1_100077_2022-09-09_final
2022-09-09 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-09-09_final
2022-09-09 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-09-09_final
2022-09-09 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-09-09_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-09 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-09-09_final
2022-09-09 10:22:17	ga_ls8c_ard_3-2-1_100083_2022-09-09_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-09 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-09-09_final
2022-09-09 11:58:46	ga_ls8c_ard_3-2-1_116077_2022-09-09_final
2022-09-09 11:59:10	ga_ls8c_ard_3-2-1_116078_2022-09-09_final
2022-09-10 09:22:17	ga_ls8c_ard_3-2-1_091072_2022-09-09_final
2022-09-10 09:22:41	ga_ls8c_ard_3-2-1_091073_2022-09-09_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-10 09:23:29	ga_ls8c_ard_3-2-1_091075_2022-09-09_final
2022-09-10 09:23:53	ga_ls8c_ard_3-2-1_091076_2022-09-09_final
2022-09-10 09:24:16	ga_ls8c_ard_3-2-1_091077_2022-09-09_final
2022-09-10 09:24:40	ga_ls8c_ard_3-2-1_091078_2022-09-09_final
2022-09-10 09:25:04	ga_ls8c_ard_3-2-1_091079_2022-09-09_final
2022-09-10 09:25:28	ga_ls8c_ard_3-2-1_091080_2022-09-09_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-10 09:26:16	ga_ls8c_ard_3-2-1_091082_2022-09-09_final
2022-09-10 09:26:40	ga_ls8c_ard_3-2-1_091083_2022-09-09_final
2022-09-10 09:27:04	ga_ls8c_ard_3-2-1_091084_2022-09-09_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-10 09:27:52	ga_ls8c_ard_3-2-1_091086_2022-09-09_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