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 10:10:57	ga_ls8c_ard_3-2-1_099070_2022-10-04_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-10-04 10:16:32	ga_ls8c_ard_3-2-1_099084_2022-10-04_final
2022-10-04 11:51:25	ga_ls8c_ard_3-2-1_115074_2022-10-04_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-04 11:53:49	ga_ls8c_ard_3-2-1_115080_2022-10-04_final
2022-10-05 09:16:55	ga_ls8c_ard_3-2-1_090074_2022-10-04_final
2022-10-05 09:18:06	ga_ls8c_ard_3-2-1_090077_2022-10-04_final
2022-10-05 09:18:54	ga_ls8c_ard_3-2-1_090079_2022-10-04_final
2022-10-05 09:20:54	ga_ls8c_ard_3-2-1_090084_2022-10-04_final
2022-10-05 09:21:42	ga_ls8c_ard_3-2-1_090086_2022-10-04_final
2022-10-05 09:22:54	ga_ls8c_ard_3-2-1_090089_2022-10-04_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-06 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-06_final
2022-10-06 10:01:45	ga_ls8c_ard_3-2-1_097078_2022-10-06_final
2022-10-06 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-06_final
2022-10-06 10:02:33	ga_ls8c_ard_3-2-1_097080_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 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-06_final
2022-10-06 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-06_final
2022-10-07 09:08:07	ga_ls8c_ard_3-2-1_088083_2022-10-06_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-07 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-07_final
2022-10-08 09:46:35	ga_ls8c_ard_3-2-1_095071_2022-10-08_final
2022-10-08 09:46:59	ga_ls8c_ard_3-2-1_095072_2022-10-08_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-08 09:48:59	ga_ls8c_ard_3-2-1_095077_2022-10-08_final
2022-10-08 09:49:22	ga_ls8c_ard_3-2-1_095078_2022-10-08_final
2022-10-08 09:49:46	ga_ls8c_ard_3-2-1_095079_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 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-08 11:24:40	ga_ls8c_ard_3-2-1_111069_2022-10-08_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-09 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-10-09_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-09 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-10-09_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-09 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-10-09_final
2022-10-09 10:33:49	ga_ls8c_ard_3-2-1_102081_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 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-10 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-10-10_final
2022-10-10 09:36:59	ga_ls8c_ard_3-2-1_093078_2022-10-10_final
2022-10-10 09:37:23	ga_ls8c_ard_3-2-1_093079_2022-10-10_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-10 09:38:11	ga_ls8c_ard_3-2-1_093081_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 09:40:35	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 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-10-10_final
2022-10-10 11:14:40	ga_ls8c_ard_3-2-1_109075_2022-10-10_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-10 11:17:28	ga_ls8c_ard_3-2-1_109082_2022-10-10_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-11 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-10-11_final
2022-10-11 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-10-11_final
2022-10-12 09:28:11	ga_ls8c_ard_3-2-1_091087_2022-10-11_final
2022-10-12 11:00:41	ga_ls8c_ard_3-2-1_107071_2022-10-12_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-13 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-10-13_final
2022-10-13 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-10-13_final
2022-10-13 11:45:31	ga_ls8c_ard_3-2-1_114075_2022-10-13_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-14 09:11:49	ga_ls8c_ard_3-2-1_089077_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 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
2022-10-14 10:52:41	ga_ls8c_ard_3-2-1_105082_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years