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
2022-06-21 10:17:07	ga_ls8c_ard_3-2-1_100071_2022-06-21_final
2022-06-21 10:17:31	ga_ls8c_ard_3-2-1_100072_2022-06-21_final
2022-06-21 10:17:55	ga_ls8c_ard_3-2-1_100073_2022-06-21_final
2022-06-21 10:19:07	ga_ls8c_ard_3-2-1_100076_2022-06-21_final
2022-06-21 10:19:55	ga_ls8c_ard_3-2-1_100078_2022-06-21_final
2022-06-21 10:20:19	ga_ls8c_ard_3-2-1_100079_2022-06-21_final
2022-06-21 10:20:43	ga_ls8c_ard_3-2-1_100080_2022-06-21_final
2022-06-21 11:58:48	ga_ls8c_ard_3-2-1_116078_2022-06-21_final
2022-06-22 09:21:54	ga_ls8c_ard_3-2-1_091072_2022-06-21_final
2022-06-22 09:23:06	ga_ls8c_ard_3-2-1_091075_2022-06-21_final
2022-06-22 09:23:30	ga_ls8c_ard_3-2-1_091076_2022-06-21_final
2022-06-22 09:23:54	ga_ls8c_ard_3-2-1_091077_2022-06-21_final
2022-06-22 09:27:05	ga_ls8c_ard_3-2-1_091085_2022-06-21_final
2022-06-22 09:27:29	ga_ls8c_ard_3-2-1_091086_2022-06-21_final
2022-06-22 09:27:53	ga_ls8c_ard_3-2-1_091087_2022-06-21_final
2022-06-22 09:28:17	ga_ls8c_ard_3-2-1_091088_2022-06-21_final
2022-06-22 09:28:41	ga_ls8c_ard_3-2-1_091089_2022-06-21_final
2022-06-22 09:29:05	ga_ls8c_ard_3-2-1_091090_2022-06-21_final
2022-06-22 11:01:35	ga_ls8c_ard_3-2-1_107074_2022-06-22_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-22 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-06-22_final
2022-06-22 11:05:34	ga_ls8c_ard_3-2-1_107084_2022-06-22_final
2022-06-23 10:03:10	ga_ls8c_ard_3-2-1_098067_2022-06-23_final
2022-06-23 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-06-23_final
2022-06-23 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-06-23_final
2022-06-23 10:04:22	ga_ls8c_ard_3-2-1_098070_2022-06-23_final
2022-06-23 10:04:46	ga_ls8c_ard_3-2-1_098071_2022-06-23_final
2022-06-23 10:05:34	ga_ls8c_ard_3-2-1_098073_2022-06-23_final
2022-06-23 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-06-23_final
2022-06-23 10:06:22	ga_ls8c_ard_3-2-1_098075_2022-06-23_final
2022-06-23 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-06-23_final
2022-06-23 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-06-23_final
2022-06-23 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-06-23_final
2022-06-23 11:44:51	ga_ls8c_ard_3-2-1_114074_2022-06-23_final
2022-06-23 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-06-23_final
2022-06-23 11:45:39	ga_ls8c_ard_3-2-1_114076_2022-06-23_final
2022-06-23 11:46:27	ga_ls8c_ard_3-2-1_114078_2022-06-23_final
2022-06-23 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-06-23_final
2022-06-23 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-06-23_final
2022-06-24 09:10:45	ga_ls8c_ard_3-2-1_089075_2022-06-23_final
2022-06-24 09:11:09	ga_ls8c_ard_3-2-1_089076_2022-06-23_final
2022-06-24 09:11:57	ga_ls8c_ard_3-2-1_089078_2022-06-23_final
2022-06-24 09:12:21	ga_ls8c_ard_3-2-1_089079_2022-06-23_final
2022-06-24 09:13:08	ga_ls8c_ard_3-2-1_089081_2022-06-23_final
2022-06-24 09:13:32	ga_ls8c_ard_3-2-1_089082_2022-06-23_final
2022-06-24 09:14:20	ga_ls8c_ard_3-2-1_089084_2022-06-23_final
2022-06-24 09:14:44	ga_ls8c_ard_3-2-1_089085_2022-06-23_final
2022-06-24 09:15:08	ga_ls8c_ard_3-2-1_089086_2022-06-23_final
2022-06-24 09:16:20	ga_ls8c_ard_3-2-1_089089_2022-06-23_final
2022-06-24 10:48:02	ga_ls8c_ard_3-2-1_105071_2022-06-24_final
2022-06-24 10:49:14	ga_ls8c_ard_3-2-1_105074_2022-06-24_final
2022-06-24 10:49:38	ga_ls8c_ard_3-2-1_105075_2022-06-24_final
2022-06-24 10:50:02	ga_ls8c_ard_3-2-1_105076_2022-06-24_final
2022-06-25 09:52:25	ga_ls8c_ard_3-2-1_096071_2022-06-25_final
2022-06-25 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-06-25_final
2022-06-25 09:58:00	ga_ls8c_ard_3-2-1_096085_2022-06-25_final
2022-06-25 09:58:24	ga_ls8c_ard_3-2-1_096086_2022-06-25_final
2022-06-25 11:32:30	ga_ls8c_ard_3-2-1_112074_2022-06-25_final
2022-06-25 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-06-25_final
2022-06-25 11:33:42	ga_ls8c_ard_3-2-1_112077_2022-06-25_final
2022-06-25 11:36:05	ga_ls8c_ard_3-2-1_112083_2022-06-25_final
2022-06-26 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-06-26_final
2022-06-26 10:35:17	ga_ls8c_ard_3-2-1_103070_2022-06-26_final
2022-06-26 10:36:05	ga_ls8c_ard_3-2-1_103072_2022-06-26_final
2022-06-26 10:36:53	ga_ls8c_ard_3-2-1_103074_2022-06-26_final
2022-06-26 10:37:17	ga_ls8c_ard_3-2-1_103075_2022-06-26_final
2022-06-26 10:37:41	ga_ls8c_ard_3-2-1_103076_2022-06-26_final
2022-06-26 10:38:04	ga_ls8c_ard_3-2-1_103077_2022-06-26_final
2022-06-26 10:38:28	ga_ls8c_ard_3-2-1_103078_2022-06-26_final
2022-06-26 10:38:52	ga_ls8c_ard_3-2-1_103079_2022-06-26_final
2022-06-26 10:39:16	ga_ls8c_ard_3-2-1_103080_2022-06-26_final
2022-06-26 10:40:04	ga_ls8c_ard_3-2-1_103082_2022-06-26_final
2022-06-27 09:43:15	ga_ls8c_ard_3-2-1_094079_2022-06-27_final
2022-06-27 09:43:39	ga_ls8c_ard_3-2-1_094080_2022-06-27_final
2022-06-27 09:44:27	ga_ls8c_ard_3-2-1_094082_2022-06-27_final
2022-06-27 09:45:15	ga_ls8c_ard_3-2-1_094084_2022-06-27_final
2022-06-27 09:45:39	ga_ls8c_ard_3-2-1_094085_2022-06-27_final
2022-06-27 09:46:03	ga_ls8c_ard_3-2-1_094086_2022-06-27_final
2022-06-27 09:46:27	ga_ls8c_ard_3-2-1_094087_2022-06-27_final
2022-06-27 11:19:21	ga_ls8c_ard_3-2-1_110072_2022-06-27_final
2022-06-27 11:20:32	ga_ls8c_ard_3-2-1_110075_2022-06-27_final
2022-06-27 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-06-27_final
2022-06-27 11:21:20	ga_ls8c_ard_3-2-1_110077_2022-06-27_final
2022-06-27 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-06-27_final
2022-06-27 11:22:32	ga_ls8c_ard_3-2-1_110080_2022-06-27_final
2022-06-27 11:23:44	ga_ls8c_ard_3-2-1_110083_2022-06-27_final
2022-06-27 11:24:08	ga_ls8c_ard_3-2-1_110084_2022-06-27_final
2022-06-27 11:24:32	ga_ls8c_ard_3-2-1_110085_2022-06-27_final
2022-06-28 10:22:56	ga_ls8c_ard_3-2-1_101070_2022-06-28_final
2022-06-28 10:23:20	ga_ls8c_ard_3-2-1_101071_2022-06-28_final
2022-06-28 10:23:43	ga_ls8c_ard_3-2-1_101072_2022-06-28_final
2022-06-28 10:24:07	ga_ls8c_ard_3-2-1_101073_2022-06-28_final
2022-06-28 10:24:55	ga_ls8c_ard_3-2-1_101075_2022-06-28_final
2022-06-28 10:25:19	ga_ls8c_ard_3-2-1_101076_2022-06-28_final
2022-06-28 10:25:43	ga_ls8c_ard_3-2-1_101077_2022-06-28_final
2022-06-28 10:26:31	ga_ls8c_ard_3-2-1_101079_2022-06-28_final
2022-06-28 10:26:55	ga_ls8c_ard_3-2-1_101080_2022-06-28_final
2022-06-28 10:27:19	ga_ls8c_ard_3-2-1_101081_2022-06-28_final
2022-06-28 10:27:43	ga_ls8c_ard_3-2-1_101082_2022-06-28_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_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