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
2022-07-06 09:33:53	ga_ls8c_ard_3-2-1_093071_2022-07-06_final
2022-07-06 09:34:17	ga_ls8c_ard_3-2-1_093072_2022-07-06_final
2022-07-06 09:34:41	ga_ls8c_ard_3-2-1_093073_2022-07-06_final
2022-07-06 09:35:05	ga_ls8c_ard_3-2-1_093074_2022-07-06_final
2022-07-06 09:36:17	ga_ls8c_ard_3-2-1_093077_2022-07-06_final
2022-07-06 09:36:41	ga_ls8c_ard_3-2-1_093078_2022-07-06_final
2022-07-06 09:39:05	ga_ls8c_ard_3-2-1_093084_2022-07-06_final
2022-07-06 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-07-06_final
2022-07-06 11:11:58	ga_ls8c_ard_3-2-1_109069_2022-07-06_final
2022-07-06 11:12:22	ga_ls8c_ard_3-2-1_109070_2022-07-06_final
2022-07-06 11:12:46	ga_ls8c_ard_3-2-1_109071_2022-07-06_final
2022-07-06 11:13:34	ga_ls8c_ard_3-2-1_109073_2022-07-06_final
2022-07-06 11:15:10	ga_ls8c_ard_3-2-1_109077_2022-07-06_final
2022-07-06 11:16:22	ga_ls8c_ard_3-2-1_109080_2022-07-06_final
2022-07-06 11:17:10	ga_ls8c_ard_3-2-1_109082_2022-07-06_final
2022-07-07 10:17:33	ga_ls8c_ard_3-2-1_100072_2022-07-07_final
2022-07-07 10:17:57	ga_ls8c_ard_3-2-1_100073_2022-07-07_final
2022-07-07 10:18:45	ga_ls8c_ard_3-2-1_100075_2022-07-07_final
2022-07-07 10:19:09	ga_ls8c_ard_3-2-1_100076_2022-07-07_final
2022-07-07 10:19:33	ga_ls8c_ard_3-2-1_100077_2022-07-07_final
2022-07-07 10:19:56	ga_ls8c_ard_3-2-1_100078_2022-07-07_final
2022-07-07 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-07-07_final
2022-07-07 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-07-07_final
2022-07-07 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-07-07_final
2022-07-08 09:24:19	ga_ls8c_ard_3-2-1_091078_2022-07-07_final
2022-07-08 09:24:43	ga_ls8c_ard_3-2-1_091079_2022-07-07_final
2022-07-08 09:25:07	ga_ls8c_ard_3-2-1_091080_2022-07-07_final
2022-07-08 09:25:31	ga_ls8c_ard_3-2-1_091081_2022-07-07_final
2022-07-08 09:25:55	ga_ls8c_ard_3-2-1_091082_2022-07-07_final
2022-07-08 09:26:19	ga_ls8c_ard_3-2-1_091083_2022-07-07_final
2022-07-08 09:26:43	ga_ls8c_ard_3-2-1_091084_2022-07-07_final
2022-07-08 09:27:07	ga_ls8c_ard_3-2-1_091085_2022-07-07_final
2022-07-08 09:27:31	ga_ls8c_ard_3-2-1_091086_2022-07-07_final
2022-07-08 09:28:19	ga_ls8c_ard_3-2-1_091088_2022-07-07_final
2022-07-08 09:28:43	ga_ls8c_ard_3-2-1_091089_2022-07-07_final
2022-07-08 11:00:01	ga_ls8c_ard_3-2-1_107070_2022-07-08_final
2022-07-08 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-07-08_final
2022-07-08 11:02:24	ga_ls8c_ard_3-2-1_107076_2022-07-08_final
2022-07-08 11:03:12	ga_ls8c_ard_3-2-1_107078_2022-07-08_final
2022-07-08 11:04:00	ga_ls8c_ard_3-2-1_107080_2022-07-08_final
2022-07-08 11:04:48	ga_ls8c_ard_3-2-1_107082_2022-07-08_final
2022-07-08 11:05:12	ga_ls8c_ard_3-2-1_107083_2022-07-08_final
2022-07-08 11:05:36	ga_ls8c_ard_3-2-1_107084_2022-07-08_final
2022-07-09 10:03:11	ga_ls8c_ard_3-2-1_098067_2022-07-09_final
2022-07-09 10:03:35	ga_ls8c_ard_3-2-1_098068_2022-07-09_final
2022-07-09 10:04:47	ga_ls8c_ard_3-2-1_098071_2022-07-09_final
2022-07-09 10:06:23	ga_ls8c_ard_3-2-1_098075_2022-07-09_final
2022-07-09 10:06:47	ga_ls8c_ard_3-2-1_098076_2022-07-09_final
2022-07-09 10:07:11	ga_ls8c_ard_3-2-1_098077_2022-07-09_final
2022-07-09 10:07:35	ga_ls8c_ard_3-2-1_098078_2022-07-09_final
2022-07-09 10:07:59	ga_ls8c_ard_3-2-1_098079_2022-07-09_final
2022-07-09 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-07-09_final
2022-07-09 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-07-09_final
2022-07-09 10:09:58	ga_ls8c_ard_3-2-1_098084_2022-07-09_final
2022-07-09 10:10:22	ga_ls8c_ard_3-2-1_098085_2022-07-09_final
2022-07-09 11:44:52	ga_ls8c_ard_3-2-1_114074_2022-07-09_final
2022-07-09 11:46:04	ga_ls8c_ard_3-2-1_114077_2022-07-09_final
2022-07-09 11:47:40	ga_ls8c_ard_3-2-1_114081_2022-07-09_final
2022-07-10 09:10:21	ga_ls8c_ard_3-2-1_089074_2022-07-09_final
2022-07-10 09:12:21	ga_ls8c_ard_3-2-1_089079_2022-07-09_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-07-10 09:13:09	ga_ls8c_ard_3-2-1_089081_2022-07-09_final
2022-07-10 09:13:33	ga_ls8c_ard_3-2-1_089082_2022-07-09_final
2022-07-10 09:13:57	ga_ls8c_ard_3-2-1_089083_2022-07-09_final
2022-07-10 09:15:09	ga_ls8c_ard_3-2-1_089086_2022-07-09_final
2022-07-10 09:16:21	ga_ls8c_ard_3-2-1_089089_2022-07-09_final
2022-07-10 10:46:27	ga_ls8c_ard_3-2-1_105067_2022-07-10_final
2022-07-10 10:46:51	ga_ls8c_ard_3-2-1_105068_2022-07-10_final
2022-07-10 10:47:39	ga_ls8c_ard_3-2-1_105070_2022-07-10_final
2022-07-10 10:48:03	ga_ls8c_ard_3-2-1_105071_2022-07-10_final
2022-07-10 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-07-10_final
2022-07-10 10:50:02	ga_ls8c_ard_3-2-1_105076_2022-07-10_final
2022-07-10 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-07-10_final
2022-07-10 10:51:14	ga_ls8c_ard_3-2-1_105079_2022-07-10_final
2022-07-10 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-07-10_final
2022-07-10 10:52:02	ga_ls8c_ard_3-2-1_105081_2022-07-10_final
2022-07-10 10:52:26	ga_ls8c_ard_3-2-1_105082_2022-07-10_final
2022-07-10 10:52:50	ga_ls8c_ard_3-2-1_105083_2022-07-10_final
2022-07-11 09:52:01	ga_ls8c_ard_3-2-1_096070_2022-07-11_final
2022-07-11 09:52:25	ga_ls8c_ard_3-2-1_096071_2022-07-11_final
2022-07-11 09:53:13	ga_ls8c_ard_3-2-1_096073_2022-07-11_final
2022-07-11 09:54:49	ga_ls8c_ard_3-2-1_096077_2022-07-11_final
2022-07-11 09:55:13	ga_ls8c_ard_3-2-1_096078_2022-07-11_final
2022-07-11 09:55:37	ga_ls8c_ard_3-2-1_096079_2022-07-11_final
2022-07-11 09:56:24	ga_ls8c_ard_3-2-1_096081_2022-07-11_final
2022-07-11 09:56:48	ga_ls8c_ard_3-2-1_096082_2022-07-11_final
2022-07-11 09:57:12	ga_ls8c_ard_3-2-1_096083_2022-07-11_final
2022-07-11 09:58:00	ga_ls8c_ard_3-2-1_096085_2022-07-11_final
2022-07-11 09:58:24	ga_ls8c_ard_3-2-1_096086_2022-07-11_final
2022-07-11 11:32:06	ga_ls8c_ard_3-2-1_112073_2022-07-11_final
2022-07-11 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-07-11_final
2022-07-11 11:36:05	ga_ls8c_ard_3-2-1_112083_2022-07-11_final
2022-07-12 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-07-12_final
2022-07-12 10:34:53	ga_ls8c_ard_3-2-1_103069_2022-07-12_final
2022-07-12 10:36:04	ga_ls8c_ard_3-2-1_103072_2022-07-12_final
2022-07-12 10:36:28	ga_ls8c_ard_3-2-1_103073_2022-07-12_final
2022-07-12 10:38:04	ga_ls8c_ard_3-2-1_103077_2022-07-12_final
2022-07-12 10:38:52	ga_ls8c_ard_3-2-1_103079_2022-07-12_final
2022-07-12 10:39:16	ga_ls8c_ard_3-2-1_103080_2022-07-12_final
2022-07-12 10:39:40	ga_ls8c_ard_3-2-1_103081_2022-07-12_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