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
2022-10-04 10:12:56	ga_ls8c_ard_3-2-1_099075_2022-10-04_final
2022-10-04 10:14:08	ga_ls8c_ard_3-2-1_099078_2022-10-04_final
2022-10-04 10:16:08	ga_ls8c_ard_3-2-1_099083_2022-10-04_final
2022-10-04 11:52:13	ga_ls8c_ard_3-2-1_115076_2022-10-04_final
2022-10-04 11:52:37	ga_ls8c_ard_3-2-1_115077_2022-10-04_final
2022-10-04 11:53:01	ga_ls8c_ard_3-2-1_115078_2022-10-04_final
2022-10-05 09:18:54	ga_ls8c_ard_3-2-1_090079_2022-10-04_final
2022-10-05 09:19:42	ga_ls8c_ard_3-2-1_090081_2022-10-04_final
2022-10-05 09:20:54	ga_ls8c_ard_3-2-1_090084_2022-10-04_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-05 10:53:48	ga_ls8c_ard_3-2-1_106069_2022-10-05_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-05 10:58:11	ga_ls8c_ard_3-2-1_106080_2022-10-05_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-05 10:59:23	ga_ls8c_ard_3-2-1_106083_2022-10-05_final
2022-10-06 09:59:46	ga_ls8c_ard_3-2-1_097073_2022-10-06_final
2022-10-06 10:00:10	ga_ls8c_ard_3-2-1_097074_2022-10-06_final
2022-10-06 10:00:58	ga_ls8c_ard_3-2-1_097076_2022-10-06_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-06 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-06_final
2022-10-06 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-06_final
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-06 11:38:39	ga_ls8c_ard_3-2-1_113073_2022-10-06_final
2022-10-06 11:39:27	ga_ls8c_ard_3-2-1_113075_2022-10-06_final
2022-10-06 11:39:51	ga_ls8c_ard_3-2-1_113076_2022-10-06_final
2022-10-06 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-06_final
2022-10-07 10:43:25	ga_ls8c_ard_3-2-1_104074_2022-10-07_final
2022-10-07 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-07_final
2022-10-07 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-07_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-08 09:50:34	ga_ls8c_ard_3-2-1_095081_2022-10-08_final
2022-10-08 09:51:22	ga_ls8c_ard_3-2-1_095083_2022-10-08_final
2022-10-08 09:52:10	ga_ls8c_ard_3-2-1_095085_2022-10-08_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-08 11:26:40	ga_ls8c_ard_3-2-1_111074_2022-10-08_final
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-08 11:27:28	ga_ls8c_ard_3-2-1_111076_2022-10-08_final
2022-10-08 11:27:52	ga_ls8c_ard_3-2-1_111077_2022-10-08_final
2022-10-08 11:28:15	ga_ls8c_ard_3-2-1_111078_2022-10-08_final
2022-10-09 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-10-09_final
2022-10-09 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-10-09_final
2022-10-09 10:31:26	ga_ls8c_ard_3-2-1_102075_2022-10-09_final
2022-10-09 10:32:13	ga_ls8c_ard_3-2-1_102077_2022-10-09_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-10 09:34:12	ga_ls8c_ard_3-2-1_093071_2022-10-10_final
2022-10-10 09:34:36	ga_ls8c_ard_3-2-1_093072_2022-10-10_final
2022-10-10 09:34:59	ga_ls8c_ard_3-2-1_093073_2022-10-10_final
2022-10-10 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-10-10_final
2022-10-10 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-10-10_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-10 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-10-10_final
2022-10-10 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-10-10_final
2022-10-10 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-10-10_final
2022-10-10 09:40:59	ga_ls8c_ard_3-2-1_093088_2022-10-10_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-10 11:14:16	ga_ls8c_ard_3-2-1_109074_2022-10-10_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-11 10:19:50	ga_ls8c_ard_3-2-1_100077_2022-10-11_final
2022-10-12 09:22:12	ga_ls8c_ard_3-2-1_091072_2022-10-11_final
2022-10-12 09:22:36	ga_ls8c_ard_3-2-1_091073_2022-10-11_final
2022-10-12 09:23:00	ga_ls8c_ard_3-2-1_091074_2022-10-11_final
2022-10-12 09:25:00	ga_ls8c_ard_3-2-1_091079_2022-10-11_final
2022-10-12 09:26:11	ga_ls8c_ard_3-2-1_091082_2022-10-11_final
2022-10-12 09:29:23	ga_ls8c_ard_3-2-1_091090_2022-10-11_final
2022-10-12 11:00:17	ga_ls8c_ard_3-2-1_107070_2022-10-12_final
2022-10-12 11:01:53	ga_ls8c_ard_3-2-1_107074_2022-10-12_final
2022-10-12 11:04:40	ga_ls8c_ard_3-2-1_107081_2022-10-12_final
2022-10-12 11:05:04	ga_ls8c_ard_3-2-1_107082_2022-10-12_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-13 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-10-13_final
2022-10-13 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-10-13_final
2022-10-13 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-10-13_final
2022-10-13 10:08:38	ga_ls8c_ard_3-2-1_098080_2022-10-13_final
2022-10-13 10:09:02	ga_ls8c_ard_3-2-1_098081_2022-10-13_final
2022-10-13 10:10:14	ga_ls8c_ard_3-2-1_098084_2022-10-13_final
2022-10-14 09:10:37	ga_ls8c_ard_3-2-1_089074_2022-10-13_final
2022-10-14 09:11:01	ga_ls8c_ard_3-2-1_089075_2022-10-13_final
2022-10-14 09:11:25	ga_ls8c_ard_3-2-1_089076_2022-10-13_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-14 09:15:00	ga_ls8c_ard_3-2-1_089085_2022-10-13_final
2022-10-14 09:15:24	ga_ls8c_ard_3-2-1_089086_2022-10-13_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-14 10:47:30	ga_ls8c_ard_3-2-1_105069_2022-10-14_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-14 10:48:42	ga_ls8c_ard_3-2-1_105072_2022-10-14_final
2022-10-14 10:49:06	ga_ls8c_ard_3-2-1_105073_2022-10-14_final
2022-10-14 10:49:30	ga_ls8c_ard_3-2-1_105074_2022-10-14_final
2022-10-14 10:49:54	ga_ls8c_ard_3-2-1_105075_2022-10-14_final
2022-10-14 10:50:18	ga_ls8c_ard_3-2-1_105076_2022-10-14_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-14 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-10-14_final
2022-10-14 10:51:29	ga_ls8c_ard_3-2-1_105079_2022-10-14_final
2022-10-14 10:51:53	ga_ls8c_ard_3-2-1_105080_2022-10-14_final
2022-10-14 10:52:17	ga_ls8c_ard_3-2-1_105081_2022-10-14_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