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
2015-01-14 10:39:52	ga_ls8c_ard_3-0-0_103082_2015-01-14_final
2015-01-15 09:44:39	ga_ls8c_ard_3-0-0_094083_2015-01-15_final
2015-01-15 11:23:32	ga_ls8c_ard_3-0-0_110083_2015-01-15_final
2015-01-16 10:27:54	ga_ls8c_ard_3-0-0_101083_2015-01-16_final
2015-01-17 09:31:52	ga_ls8c_ard_3-0-0_092082_2015-01-17_final
2015-01-17 09:32:16	ga_ls8c_ard_3-0-0_092083_2015-01-17_final
2015-01-17 11:10:45	ga_ls8c_ard_3-0-0_108082_2015-01-17_final
2015-01-17 11:11:09	ga_ls8c_ard_3-0-0_108083_2015-01-17_final
2015-01-18 10:15:07	ga_ls8c_ard_3-0-0_099082_2015-01-18_final
2015-01-18 10:15:31	ga_ls8c_ard_3-0-0_099083_2015-01-18_final
2015-01-19 09:19:29	ga_ls8c_ard_3-0-0_090082_2015-01-18_final
2015-01-19 09:19:53	ga_ls8c_ard_3-0-0_090083_2015-01-18_final
2015-01-19 10:58:22	ga_ls8c_ard_3-0-0_106082_2015-01-19_final
2015-01-19 10:58:46	ga_ls8c_ard_3-0-0_106083_2015-01-19_final
2015-02-16 09:44:25	ga_ls8c_ard_3-0-0_094083_2015-02-16_final
2015-02-16 11:23:18	ga_ls8c_ard_3-0-0_110083_2015-02-16_final
2015-02-17 10:27:41	ga_ls8c_ard_3-0-0_101083_2015-02-17_final
2015-02-18 09:32:04	ga_ls8c_ard_3-0-0_092083_2015-02-18_final
2015-02-18 11:10:33	ga_ls8c_ard_3-0-0_108082_2015-02-18_final
2015-02-18 11:10:57	ga_ls8c_ard_3-0-0_108083_2015-02-18_final
2015-02-19 10:15:20	ga_ls8c_ard_3-0-0_099083_2015-02-19_final
2015-02-20 09:19:42	ga_ls8c_ard_3-0-0_090083_2015-02-19_final
2015-02-20 10:58:11	ga_ls8c_ard_3-0-0_106082_2015-02-20_final
2015-02-20 10:58:35	ga_ls8c_ard_3-0-0_106083_2015-02-20_final
2015-02-28 10:09:07	ga_ls8c_ard_3-0-0_098083_2015-02-28_final
2015-03-01 09:13:29	ga_ls8c_ard_3-0-0_089083_2015-02-28_final
2015-03-01 10:51:58	ga_ls8c_ard_3-0-0_105082_2015-03-01_final
2015-03-01 10:52:22	ga_ls8c_ard_3-0-0_105083_2015-03-01_final
2015-03-19 10:39:49	ga_ls8c_ard_3-0-0_103083_2015-03-19_final
2015-03-20 09:44:11	ga_ls8c_ard_3-0-0_094083_2015-03-20_final
2015-03-20 11:23:04	ga_ls8c_ard_3-0-0_110083_2015-03-20_final
2015-03-21 10:27:26	ga_ls8c_ard_3-0-0_101083_2015-03-21_final
2017-04-02 10:33:13	ga_ls8c_ard_3-0-0_102082_2017-04-02_final
2017-04-02 10:33:37	ga_ls8c_ard_3-0-0_102083_2017-04-02_final
2017-04-03 09:38:00	ga_ls8c_ard_3-0-0_093083_2017-04-03_final
2017-04-03 11:16:53	ga_ls8c_ard_3-0-0_109083_2017-04-03_final
2017-04-04 10:21:15	ga_ls8c_ard_3-0-0_100083_2017-04-04_final
2017-07-04 10:02:32	ga_ls8c_ard_3-0-0_097082_2017-07-04_final
2017-07-04 10:02:56	ga_ls8c_ard_3-0-0_097083_2017-07-04_final
2017-07-04 11:41:26	ga_ls8c_ard_3-0-0_113082_2017-07-04_final
2017-07-04 11:41:49	ga_ls8c_ard_3-0-0_113083_2017-07-04_final
2017-07-05 09:07:19	ga_ls8c_ard_3-0-0_088083_2017-07-04_final
2017-07-05 10:45:48	ga_ls8c_ard_3-0-0_104082_2017-07-05_final
2017-07-05 10:46:12	ga_ls8c_ard_3-0-0_104083_2017-07-05_final
2017-07-06 09:50:11	ga_ls8c_ard_3-0-0_095082_2017-07-06_final
2017-07-06 09:50:35	ga_ls8c_ard_3-0-0_095083_2017-07-06_final
2017-07-06 11:29:04	ga_ls8c_ard_3-0-0_111082_2017-07-06_final
2017-07-06 11:29:28	ga_ls8c_ard_3-0-0_111083_2017-07-06_final
2017-07-14 10:40:03	ga_ls8c_ard_3-0-0_103083_2017-07-14_final
2017-07-15 09:44:26	ga_ls8c_ard_3-0-0_094083_2017-07-15_final
2017-07-15 11:23:19	ga_ls8c_ard_3-0-0_110083_2017-07-15_final
2017-07-16 10:27:18	ga_ls8c_ard_3-0-0_101082_2017-07-16_final
2017-07-16 10:27:42	ga_ls8c_ard_3-0-0_101083_2017-07-16_final
2019-07-11 09:07:04	ga_ls8c_ard_3-1-0_088082_2019-07-10_final
2019-07-11 09:07:28	ga_ls8c_ard_3-1-0_088083_2019-07-10_final
2019-07-11 10:45:57	ga_ls8c_ard_3-1-0_104082_2019-07-11_final
2019-07-11 10:46:21	ga_ls8c_ard_3-1-0_104083_2019-07-11_final
2019-07-12 09:50:20	ga_ls8c_ard_3-1-0_095082_2019-07-12_final
2019-07-12 09:50:44	ga_ls8c_ard_3-1-0_095083_2019-07-12_final
2019-07-12 11:29:13	ga_ls8c_ard_3-1-0_111082_2019-07-12_final
2019-07-12 11:29:37	ga_ls8c_ard_3-1-0_111083_2019-07-12_final
2019-09-06 10:40:03	ga_ls8c_ard_3-1-0_103082_2019-09-06_final
2019-09-06 10:40:27	ga_ls8c_ard_3-1-0_103083_2019-09-06_final
2019-09-07 09:44:26	ga_ls8c_ard_3-1-0_094082_2019-09-07_final
2019-09-07 09:44:50	ga_ls8c_ard_3-1-0_094083_2019-09-07_final
2019-09-07 11:23:19	ga_ls8c_ard_3-1-0_110082_2019-09-07_final
2019-09-07 11:23:43	ga_ls8c_ard_3-1-0_110083_2019-09-07_final
2019-09-08 10:27:42	ga_ls8c_ard_3-1-0_101082_2019-09-08_final
2019-09-08 10:28:06	ga_ls8c_ard_3-1-0_101083_2019-09-08_final
2019-10-24 10:40:14	ga_ls8c_ard_3-1-0_103082_2019-10-24_final
2019-10-24 10:40:38	ga_ls8c_ard_3-1-0_103083_2019-10-24_final
2019-10-25 09:44:37	ga_ls8c_ard_3-1-0_094082_2019-10-25_final
2019-10-25 09:45:01	ga_ls8c_ard_3-1-0_094083_2019-10-25_final
2019-10-25 11:23:30	ga_ls8c_ard_3-1-0_110082_2019-10-25_final
2019-10-25 11:23:54	ga_ls8c_ard_3-1-0_110083_2019-10-25_final
2019-10-26 08:48:59	ga_ls8c_ard_3-2-1_085082_2019-10-25_final
2019-10-26 10:27:52	ga_ls8c_ard_3-1-0_101082_2019-10-26_final
2019-10-26 10:28:16	ga_ls8c_ard_3-1-0_101083_2019-10-26_final
2023-01-26 10:03:31	ga_ls8c_ard_3-2-1_097083_2023-01-26_final
2023-01-26 11:42:24	ga_ls8c_ard_3-2-1_113083_2023-01-26_final
2023-01-27 09:07:50	ga_ls8c_ard_3-2-1_088082_2023-01-26_nrt
2023-01-27 09:08:14	ga_ls8c_ard_3-2-1_088083_2023-01-26_nrt
2023-01-30 09:38:49	ga_ls8c_ard_3-2-1_093083_2023-01-30_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-05 11:04:59	ga_ls8c_ard_3-2-1_107083_2023-03-05_final
2023-03-06 10:09:21	ga_ls8c_ard_3-2-1_098083_2023-03-06_final
2023-03-07 09:13:43	ga_ls8c_ard_3-2-1_089083_2023-03-06_final
2023-03-07 10:52:36	ga_ls8c_ard_3-2-1_105083_2023-03-07_final
2023-03-08 09:56:57	ga_ls8c_ard_3-2-1_096083_2023-03-08_final
2023-03-19 09:38:21	ga_ls8c_ard_3-2-1_093083_2023-03-19_final
2023-03-19 11:17:14	ga_ls8c_ard_3-2-1_109083_2023-03-19_final
2023-03-20 10:21:36	ga_ls8c_ard_3-2-1_100083_2023-03-20_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-23 10:52:26	ga_ls8c_ard_3-2-1_105083_2023-03-23_final
2023-03-24 09:56:48	ga_ls8c_ard_3-2-1_096083_2023-03-24_final
2023-10-24 09:19:41	ga_ls8c_ard_3-2-1_090082_2023-10-23_final
2023-10-24 09:20:05	ga_ls8c_ard_3-2-1_090083_2023-10-23_final
2023-10-24 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-10-24_final
2023-10-24 10:58:58	ga_ls8c_ard_3-2-1_106083_2023-10-24_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