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
2020-10-13 09:26:12	ga_ls8c_ard_3-1-0_092067_2020-10-12_final
2020-10-13 09:27:48	ga_ls8c_ard_3-1-0_092071_2020-10-12_final
2020-10-13 09:28:12	ga_ls8c_ard_3-1-0_092072_2020-10-12_final
2020-10-13 09:28:36	ga_ls8c_ard_3-1-0_092073_2020-10-12_final
2020-10-13 09:29:00	ga_ls8c_ard_3-1-0_092074_2020-10-12_final
2020-10-13 09:29:24	ga_ls8c_ard_3-1-0_092075_2020-10-12_final
2020-10-13 09:29:48	ga_ls8c_ard_3-1-0_092076_2020-10-12_final
2020-10-13 09:30:11	ga_ls8c_ard_3-1-0_092077_2020-10-13_final
2020-10-13 09:30:35	ga_ls8c_ard_3-1-0_092078_2020-10-13_final
2020-10-13 09:30:59	ga_ls8c_ard_3-1-0_092079_2020-10-13_final
2020-10-13 09:32:11	ga_ls8c_ard_3-1-0_092082_2020-10-13_final
2020-10-13 09:32:35	ga_ls8c_ard_3-1-0_092083_2020-10-13_final
2020-10-13 09:32:59	ga_ls8c_ard_3-1-0_092084_2020-10-13_final
2020-10-13 11:09:04	ga_ls8c_ard_3-1-0_108077_2020-10-13_final
2020-10-13 11:11:52	ga_ls8c_ard_3-1-0_108084_2020-10-13_final
2020-10-14 11:50:45	ga_ls8c_ard_3-1-0_115073_2020-10-14_final
2020-10-14 11:51:08	ga_ls8c_ard_3-1-0_115074_2020-10-14_final
2020-10-14 11:51:32	ga_ls8c_ard_3-1-0_115075_2020-10-14_final
2020-10-14 11:51:56	ga_ls8c_ard_3-1-0_115076_2020-10-14_final
2020-10-14 11:52:20	ga_ls8c_ard_3-1-0_115077_2020-10-14_final
2020-10-14 11:52:44	ga_ls8c_ard_3-1-0_115078_2020-10-14_final
2020-10-14 11:53:08	ga_ls8c_ard_3-1-0_115079_2020-10-14_final
2020-10-14 11:53:32	ga_ls8c_ard_3-1-0_115080_2020-10-14_final
2020-10-15 09:20:14	ga_ls8c_ard_3-1-0_090083_2020-10-14_final
2020-10-15 09:20:38	ga_ls8c_ard_3-1-0_090084_2020-10-14_final
2020-10-15 09:21:02	ga_ls8c_ard_3-1-0_090085_2020-10-14_final
2020-10-15 09:21:25	ga_ls8c_ard_3-1-0_090086_2020-10-14_final
2020-10-15 09:21:49	ga_ls8c_ard_3-1-0_090087_2020-10-14_final
2020-10-15 09:22:13	ga_ls8c_ard_3-1-0_090088_2020-10-14_final
2020-10-15 09:22:37	ga_ls8c_ard_3-1-0_090089_2020-10-14_final
2020-10-15 09:23:01	ga_ls8c_ard_3-1-0_090090_2020-10-14_final
2020-10-15 09:23:25	ga_ls8c_ard_3-1-0_090091_2020-10-14_final
2020-10-15 10:52:44	ga_ls8c_ard_3-1-0_106067_2020-10-15_final
2020-10-16 11:35:59	ga_ls8c_ard_3-1-0_113067_2020-10-16_final
2020-10-16 11:40:23	ga_ls8c_ard_3-1-0_113078_2020-10-16_final
2020-10-16 11:41:58	ga_ls8c_ard_3-1-0_113082_2020-10-16_final
2020-10-16 11:42:22	ga_ls8c_ard_3-1-0_113083_2020-10-16_final
2020-10-16 11:42:46	ga_ls8c_ard_3-1-0_113084_2020-10-16_final
2020-10-17 10:45:57	ga_ls8c_ard_3-1-0_104081_2020-10-17_final
2020-10-18 11:29:13	ga_ls8c_ard_3-1-0_111081_2020-10-18_final
2020-10-18 11:30:25	ga_ls8c_ard_3-1-0_111084_2020-10-18_final
2020-10-20 11:14:51	ga_ls8c_ard_3-1-0_109076_2020-10-20_final
2020-10-20 11:17:15	ga_ls8c_ard_3-1-0_109082_2020-10-20_final
2020-10-21 11:57:19	ga_ls8c_ard_3-1-0_116074_2020-10-21_final
2020-10-21 11:57:43	ga_ls8c_ard_3-1-0_116075_2020-10-21_final
2020-10-21 11:58:07	ga_ls8c_ard_3-1-0_116076_2020-10-21_final
2020-10-21 11:58:31	ga_ls8c_ard_3-1-0_116077_2020-10-21_final
2020-10-21 11:58:55	ga_ls8c_ard_3-1-0_116078_2020-10-21_final
2020-10-22 09:20:25	ga_ls8c_ard_3-1-0_091068_2020-10-21_final
2020-10-22 09:22:01	ga_ls8c_ard_3-1-0_091072_2020-10-21_final
2020-10-22 09:22:25	ga_ls8c_ard_3-1-0_091073_2020-10-21_final
2020-10-22 09:22:49	ga_ls8c_ard_3-1-0_091074_2020-10-21_final
2020-10-22 09:23:13	ga_ls8c_ard_3-1-0_091075_2020-10-21_final
2020-10-22 09:23:37	ga_ls8c_ard_3-1-0_091076_2020-10-21_final
2020-10-22 09:24:01	ga_ls8c_ard_3-1-0_091077_2020-10-21_final
2020-10-22 09:24:25	ga_ls8c_ard_3-1-0_091078_2020-10-21_final
2020-10-22 09:24:49	ga_ls8c_ard_3-1-0_091079_2020-10-21_final
2020-10-22 09:26:24	ga_ls8c_ard_3-1-0_091083_2020-10-21_final
2020-10-22 09:27:36	ga_ls8c_ard_3-1-0_091086_2020-10-21_final
2020-10-22 09:28:48	ga_ls8c_ard_3-1-0_091089_2020-10-21_final
2020-10-22 09:29:12	ga_ls8c_ard_3-1-0_091090_2020-10-21_final
2020-10-22 11:02:54	ga_ls8c_ard_3-1-0_107077_2020-10-22_final
2020-10-22 11:03:42	ga_ls8c_ard_3-1-0_107079_2020-10-22_final
2020-10-24 09:10:51	ga_ls8c_ard_3-1-0_089075_2020-10-23_final
2020-10-24 09:11:15	ga_ls8c_ard_3-1-0_089076_2020-10-23_final
2020-10-24 09:12:03	ga_ls8c_ard_3-1-0_089078_2020-10-23_final
2020-10-24 09:12:51	ga_ls8c_ard_3-1-0_089080_2020-10-23_final
2020-10-24 09:13:15	ga_ls8c_ard_3-1-0_089081_2020-10-23_final
2020-10-24 09:14:03	ga_ls8c_ard_3-1-0_089083_2020-10-23_final
2020-10-24 09:14:51	ga_ls8c_ard_3-1-0_089085_2020-10-23_final
2020-10-24 09:15:15	ga_ls8c_ard_3-1-0_089086_2020-10-23_final
2020-10-24 09:15:38	ga_ls8c_ard_3-1-0_089087_2020-10-23_final
2020-10-24 09:16:02	ga_ls8c_ard_3-1-0_089088_2020-10-23_final
2020-10-24 09:16:26	ga_ls8c_ard_3-1-0_089089_2020-10-23_final
2020-10-24 09:16:50	ga_ls8c_ard_3-1-0_089090_2020-10-23_final
2020-10-29 09:26:12	ga_ls8c_ard_3-1-0_092067_2020-10-28_final
2020-10-29 09:26:35	ga_ls8c_ard_3-1-0_092068_2020-10-28_final
2020-10-29 09:28:11	ga_ls8c_ard_3-1-0_092072_2020-10-28_final
2020-10-29 09:28:35	ga_ls8c_ard_3-1-0_092073_2020-10-28_final
2020-10-29 09:28:59	ga_ls8c_ard_3-1-0_092074_2020-10-28_final
2020-10-29 09:29:23	ga_ls8c_ard_3-1-0_092075_2020-10-28_final
2020-10-29 09:30:35	ga_ls8c_ard_3-1-0_092078_2020-10-29_final
2020-10-29 09:30:59	ga_ls8c_ard_3-1-0_092079_2020-10-29_final
2020-10-29 09:32:11	ga_ls8c_ard_3-1-0_092082_2020-10-29_final
2020-10-29 09:32:35	ga_ls8c_ard_3-1-0_092083_2020-10-29_final
2020-10-29 09:32:59	ga_ls8c_ard_3-1-0_092084_2020-10-29_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