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

86 results

Time (local)	Label
2022-01-07 11:40:41	ga_ls8c_ard_3-2-1_113079_2022-01-07_final
2022-01-08 10:41:04	ga_ls8c_ard_3-2-1_104069_2022-01-08_final
2022-01-08 10:41:52	ga_ls8c_ard_3-2-1_104071_2022-01-08_final
2022-01-08 10:43:04	ga_ls8c_ard_3-2-1_104074_2022-01-08_final
2022-01-08 10:43:52	ga_ls8c_ard_3-2-1_104076_2022-01-08_final
2022-01-08 10:44:16	ga_ls8c_ard_3-2-1_104077_2022-01-08_final
2022-01-08 10:45:27	ga_ls8c_ard_3-2-1_104080_2022-01-08_final
2022-01-09 09:46:15	ga_ls8c_ard_3-2-1_095071_2022-01-09_final
2022-01-09 09:46:39	ga_ls8c_ard_3-2-1_095072_2022-01-09_final
2022-01-09 09:48:14	ga_ls8c_ard_3-2-1_095076_2022-01-09_final
2022-01-09 09:49:50	ga_ls8c_ard_3-2-1_095080_2022-01-09_final
2022-01-09 09:50:14	ga_ls8c_ard_3-2-1_095081_2022-01-09_final
2022-01-09 09:50:38	ga_ls8c_ard_3-2-1_095082_2022-01-09_final
2022-01-09 09:51:26	ga_ls8c_ard_3-2-1_095084_2022-01-09_final
2022-01-09 09:51:50	ga_ls8c_ard_3-2-1_095085_2022-01-09_final
2022-01-09 09:52:14	ga_ls8c_ard_3-2-1_095086_2022-01-09_final
2022-01-09 09:52:38	ga_ls8c_ard_3-2-1_095087_2022-01-09_final
2022-01-09 11:25:08	ga_ls8c_ard_3-2-1_111071_2022-01-09_final
2022-01-09 11:26:19	ga_ls8c_ard_3-2-1_111074_2022-01-09_final
2022-01-09 11:27:55	ga_ls8c_ard_3-2-1_111078_2022-01-09_final
2022-01-09 11:28:19	ga_ls8c_ard_3-2-1_111079_2022-01-09_final
2022-01-09 11:29:31	ga_ls8c_ard_3-2-1_111082_2022-01-09_final
2022-01-09 11:30:19	ga_ls8c_ard_3-2-1_111084_2022-01-09_final
2022-01-10 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-01-10_final
2022-01-10 10:30:42	ga_ls8c_ard_3-2-1_102074_2022-01-10_final
2022-01-10 10:31:30	ga_ls8c_ard_3-2-1_102076_2022-01-10_final
2022-01-10 10:31:54	ga_ls8c_ard_3-2-1_102077_2022-01-10_final
2022-01-10 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-01-10_final
2022-01-10 10:32:42	ga_ls8c_ard_3-2-1_102079_2022-01-10_final
2022-01-10 10:33:06	ga_ls8c_ard_3-2-1_102080_2022-01-10_final
2022-01-11 09:34:17	ga_ls8c_ard_3-2-1_093072_2022-01-11_final
2022-01-11 09:35:05	ga_ls8c_ard_3-2-1_093074_2022-01-11_final
2022-01-11 09:35:28	ga_ls8c_ard_3-2-1_093075_2022-01-11_final
2022-01-11 09:36:16	ga_ls8c_ard_3-2-1_093077_2022-01-11_final
2022-01-11 09:37:04	ga_ls8c_ard_3-2-1_093079_2022-01-11_final
2022-01-11 09:37:28	ga_ls8c_ard_3-2-1_093080_2022-01-11_final
2022-01-11 09:38:40	ga_ls8c_ard_3-2-1_093083_2022-01-11_final
2022-01-11 09:39:04	ga_ls8c_ard_3-2-1_093084_2022-01-11_final
2022-01-11 09:39:28	ga_ls8c_ard_3-2-1_093085_2022-01-11_final
2022-01-11 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-01-11_final
2022-01-11 09:40:40	ga_ls8c_ard_3-2-1_093088_2022-01-11_final
2022-01-11 11:13:10	ga_ls8c_ard_3-2-1_109072_2022-01-11_final
2022-01-11 11:14:21	ga_ls8c_ard_3-2-1_109075_2022-01-11_final
2022-01-11 11:15:09	ga_ls8c_ard_3-2-1_109077_2022-01-11_final
2022-01-11 11:15:33	ga_ls8c_ard_3-2-1_109078_2022-01-11_final
2022-01-11 11:15:57	ga_ls8c_ard_3-2-1_109079_2022-01-11_final
2022-01-11 11:16:45	ga_ls8c_ard_3-2-1_109081_2022-01-11_final
2022-01-11 11:17:09	ga_ls8c_ard_3-2-1_109082_2022-01-11_final
2022-01-12 10:18:20	ga_ls8c_ard_3-2-1_100074_2022-01-12_final
2022-01-12 10:19:56	ga_ls8c_ard_3-2-1_100078_2022-01-12_final
2022-01-12 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-01-12_final
2022-01-12 10:21:08	ga_ls8c_ard_3-2-1_100081_2022-01-12_final
2022-01-12 10:21:32	ga_ls8c_ard_3-2-1_100082_2022-01-12_final
2022-01-12 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-01-12_final
2022-01-13 09:24:18	ga_ls8c_ard_3-2-1_091078_2022-01-12_final
2022-01-13 09:25:06	ga_ls8c_ard_3-2-1_091080_2022-01-12_final
2022-01-13 09:25:30	ga_ls8c_ard_3-2-1_091081_2022-01-12_final
2022-01-13 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-01-12_final
2022-01-13 09:26:18	ga_ls8c_ard_3-2-1_091083_2022-01-12_final
2022-01-13 09:27:06	ga_ls8c_ard_3-2-1_091085_2022-01-12_final
2022-01-13 09:27:30	ga_ls8c_ard_3-2-1_091086_2022-01-12_final
2022-01-13 09:28:18	ga_ls8c_ard_3-2-1_091088_2022-01-12_final
2022-01-13 09:28:42	ga_ls8c_ard_3-2-1_091089_2022-01-12_final
2022-01-13 09:29:06	ga_ls8c_ard_3-2-1_091090_2022-01-12_final
2022-01-13 11:00:00	ga_ls8c_ard_3-2-1_107070_2022-01-13_final
2022-01-13 11:01:59	ga_ls8c_ard_3-2-1_107075_2022-01-13_final
2022-01-13 11:02:47	ga_ls8c_ard_3-2-1_107077_2022-01-13_final
2022-01-13 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-01-13_final
2022-01-13 11:03:35	ga_ls8c_ard_3-2-1_107079_2022-01-13_final
2022-01-13 11:03:59	ga_ls8c_ard_3-2-1_107080_2022-01-13_final
2022-01-13 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-01-13_final
2022-01-13 11:05:35	ga_ls8c_ard_3-2-1_107084_2022-01-13_final
2022-01-14 11:44:51	ga_ls8c_ard_3-2-1_114074_2022-01-14_final
2022-01-14 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-01-14_final
2022-01-14 11:46:51	ga_ls8c_ard_3-2-1_114079_2022-01-14_final
2022-01-14 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-01-14_final
2022-01-14 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-01-14_final
2022-01-15 09:10:21	ga_ls8c_ard_3-2-1_089074_2022-01-14_final
2022-01-15 09:10:44	ga_ls8c_ard_3-2-1_089075_2022-01-14_final
2022-01-15 09:11:08	ga_ls8c_ard_3-2-1_089076_2022-01-14_final
2022-01-15 09:11:32	ga_ls8c_ard_3-2-1_089077_2022-01-14_final
2022-01-15 09:12:20	ga_ls8c_ard_3-2-1_089079_2022-01-14_final
2022-01-15 09:13:32	ga_ls8c_ard_3-2-1_089082_2022-01-14_final
2022-01-15 09:13:56	ga_ls8c_ard_3-2-1_089083_2022-01-14_final
2022-01-15 09:14:44	ga_ls8c_ard_3-2-1_089085_2022-01-14_final
2022-01-15 09:16:44	ga_ls8c_ard_3-2-1_089090_2022-01-14_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