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:

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First 100 results (query limit)

Time (local)	Label
2023-08-13 10:06:25	ga_ls8c_ard_3-2-1_098076_2023-08-13_final
2023-08-15 09:56:53	ga_ls8c_ard_3-2-1_096083_2023-08-15_final
2023-08-19 09:32:13	ga_ls8c_ard_3-2-1_092083_2023-08-19_final
2023-08-19 11:09:54	ga_ls8c_ard_3-2-1_108080_2023-08-19_final
2023-08-20 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-08-20_final
2023-08-23 10:42:01	ga_ls8c_ard_3-2-1_104072_2023-08-23_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-23 10:43:13	ga_ls8c_ard_3-2-1_104075_2023-08-23_final
2023-08-24 09:50:23	ga_ls8c_ard_3-2-1_095082_2023-08-24_final
2023-08-24 11:26:53	ga_ls8c_ard_3-2-1_111076_2023-08-24_final
2023-08-24 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-08-24_final
2023-08-28 09:24:29	ga_ls8c_ard_3-2-1_091079_2023-08-27_final
2023-08-28 09:25:40	ga_ls8c_ard_3-2-1_091082_2023-08-27_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-08-29 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-08-29_final
2023-08-29 11:46:37	ga_ls8c_ard_3-2-1_114079_2023-08-29_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-03 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-09-03_final
2023-09-07 10:01:07	ga_ls8c_ard_3-2-1_097078_2023-09-07_final
2023-09-08 10:41:36	ga_ls8c_ard_3-2-1_104071_2023-09-08_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-10 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-09-10_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-11 11:16:32	ga_ls8c_ard_3-2-1_109081_2023-09-11_final
2023-09-12 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-09-12_final
2023-09-12 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-09-12_final
2023-09-12 10:22:07	ga_ls8c_ard_3-2-1_100084_2023-09-12_final
2023-09-13 09:24:31	ga_ls8c_ard_3-2-1_091079_2023-09-12_final
2023-09-13 11:05:00	ga_ls8c_ard_3-2-1_107083_2023-09-13_final
2023-09-14 10:06:35	ga_ls8c_ard_3-2-1_098076_2023-09-14_final
2023-09-14 11:45:28	ga_ls8c_ard_3-2-1_114076_2023-09-14_final
2023-09-16 09:53:27	ga_ls8c_ard_3-2-1_096074_2023-09-16_final
2023-09-16 09:57:02	ga_ls8c_ard_3-2-1_096083_2023-09-16_final
2023-09-16 09:57:50	ga_ls8c_ard_3-2-1_096085_2023-09-16_final
2023-09-17 10:35:31	ga_ls8c_ard_3-2-1_103071_2023-09-17_final
2023-09-18 09:41:29	ga_ls8c_ard_3-2-1_094075_2023-09-18_final
2023-09-18 09:41:53	ga_ls8c_ard_3-2-1_094076_2023-09-18_final
2023-09-23 10:00:26	ga_ls8c_ard_3-2-1_097076_2023-09-23_final
2023-09-23 10:00:50	ga_ls8c_ard_3-2-1_097077_2023-09-23_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-23 10:04:01	ga_ls8c_ard_3-2-1_097085_2023-09-23_final
2023-09-25 09:50:29	ga_ls8c_ard_3-2-1_095082_2023-09-25_final
2023-09-25 09:51:17	ga_ls8c_ard_3-2-1_095084_2023-09-25_final
2023-09-26 10:31:46	ga_ls8c_ard_3-2-1_102077_2023-09-26_final
2023-09-27 09:38:33	ga_ls8c_ard_3-2-1_093083_2023-09-27_final
2023-09-27 11:16:38	ga_ls8c_ard_3-2-1_109081_2023-09-27_final
2023-10-01 10:50:20	ga_ls8c_ard_3-2-1_105077_2023-10-01_final
2023-10-03 10:35:10	ga_ls8c_ard_3-2-1_103070_2023-10-03_final
2023-10-04 09:41:32	ga_ls8c_ard_3-2-1_094075_2023-10-04_final
2023-10-04 09:43:08	ga_ls8c_ard_3-2-1_094079_2023-10-04_final
2023-10-04 11:22:25	ga_ls8c_ard_3-2-1_110080_2023-10-04_final
2023-10-08 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-10-07_final
2023-10-08 10:56:55	ga_ls8c_ard_3-2-1_106078_2023-10-08_final
2023-10-08 10:57:19	ga_ls8c_ard_3-2-1_106079_2023-10-08_final
2023-10-09 10:00:30	ga_ls8c_ard_3-2-1_097076_2023-10-09_final
2023-10-09 11:40:35	ga_ls8c_ard_3-2-1_113079_2023-10-09_final
2023-10-10 10:41:47	ga_ls8c_ard_3-2-1_104071_2023-10-10_final
2023-10-10 10:43:23	ga_ls8c_ard_3-2-1_104075_2023-10-10_final
2023-10-10 10:43:47	ga_ls8c_ard_3-2-1_104076_2023-10-10_final
2023-10-11 09:50:33	ga_ls8c_ard_3-2-1_095082_2023-10-11_final
2023-10-11 09:50:57	ga_ls8c_ard_3-2-1_095083_2023-10-11_final
2023-10-11 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-10-11_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-12 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-10-12_final
2023-10-12 10:32:13	ga_ls8c_ard_3-2-1_102078_2023-10-12_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_final
2023-10-19 10:36:47	ga_ls8c_ard_3-2-1_103074_2023-10-19_final
2023-10-19 10:37:35	ga_ls8c_ard_3-2-1_103076_2023-10-19_final
2023-10-22 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-10-22_final
2023-10-23 10:12:30	ga_ls8c_ard_3-2-1_099075_2023-10-23_final
2023-10-23 10:15:17	ga_ls8c_ard_3-2-1_099082_2023-10-23_final
2023-10-24 09:18:53	ga_ls8c_ard_3-2-1_090080_2023-10-23_final
2023-10-25 10:00:33	ga_ls8c_ard_3-2-1_097076_2023-10-25_final
2023-10-25 11:39:02	ga_ls8c_ard_3-2-1_113075_2023-10-25_final
2023-10-25 11:39:50	ga_ls8c_ard_3-2-1_113077_2023-10-25_final
2023-10-26 10:43:25	ga_ls8c_ard_3-2-1_104075_2023-10-26_final
2023-10-27 09:51:00	ga_ls8c_ard_3-2-1_095083_2023-10-27_final
2023-10-27 11:27:05	ga_ls8c_ard_3-2-1_111076_2023-10-27_final
2023-10-31 09:25:30	ga_ls8c_ard_3-2-1_091081_2023-10-30_final
2023-11-04 10:39:14	ga_ls8c_ard_3-2-1_103080_2023-11-04_final
2023-11-04 10:40:02	ga_ls8c_ard_3-2-1_103082_2023-11-04_final
2023-11-07 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-11-07_final
2023-11-07 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-11-07_final
2023-11-08 10:12:28	ga_ls8c_ard_3-2-1_099075_2023-11-08_final
2023-11-10 10:00:53	ga_ls8c_ard_3-2-1_097077_2023-11-10_final
2023-11-10 11:40:34	ga_ls8c_ard_3-2-1_113079_2023-11-10_final
2023-11-11 10:42:10	ga_ls8c_ard_3-2-1_104072_2023-11-11_final
2023-11-11 10:43:22	ga_ls8c_ard_3-2-1_104075_2023-11-11_final
2023-11-12 09:50:57	ga_ls8c_ard_3-2-1_095083_2023-11-12_final
2023-11-12 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-11-12_final
2023-11-13 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-11-13_final
2023-11-13 10:32:37	ga_ls8c_ard_3-2-1_102079_2023-11-13_final
2023-11-14 09:36:37	ga_ls8c_ard_3-2-1_093078_2023-11-14_final
2023-11-14 09:37:25	ga_ls8c_ard_3-2-1_093080_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-19 09:56:48	ga_ls8c_ard_3-2-1_096082_2023-11-19_final
2023-11-20 10:38:28	ga_ls8c_ard_3-2-1_103078_2023-11-20_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