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
2022-11-07 10:00:35	ga_ls8c_ard_3-2-1_097075_2022-11-07_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-16 09:54:43	ga_ls8c_ard_3-2-1_096076_2022-11-16_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-16 11:35:36	ga_ls8c_ard_3-2-1_112081_2022-11-16_final
2022-11-18 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-11-18_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-23 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-11-23_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-23 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-11-23_final
2022-11-23 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-11-23_final
2022-11-25 09:50:33	ga_ls8c_ard_3-2-1_095081_2022-11-25_final
2022-12-02 11:34:02	ga_ls8c_ard_3-2-1_112077_2022-12-02_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-09 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-12-09_final
2022-12-09 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-12-09_final
2022-12-11 09:50:31	ga_ls8c_ard_3-2-1_095081_2022-12-11_final
2022-12-14 10:18:36	ga_ls8c_ard_3-2-1_100074_2022-12-14_final
2022-12-14 10:20:12	ga_ls8c_ard_3-2-1_100078_2022-12-14_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-15 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-12-14_final
2022-12-17 10:48:16	ga_ls8c_ard_3-2-1_105071_2022-12-17_final
2022-12-18 09:55:02	ga_ls8c_ard_3-2-1_096077_2022-12-18_final
2022-12-18 11:35:54	ga_ls8c_ard_3-2-1_112082_2022-12-18_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-20 09:41:02	ga_ls8c_ard_3-2-1_094073_2022-12-20_final
2022-12-20 11:19:31	ga_ls8c_ard_3-2-1_110072_2022-12-20_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-27 09:50:00	ga_ls8c_ard_3-2-1_095080_2022-12-27_final
2022-12-29 11:14:32	ga_ls8c_ard_3-2-1_109075_2022-12-29_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-06 10:27:05	ga_ls8c_ard_3-2-1_101080_2023-01-06_final
2023-01-07 09:34:15	ga_ls8c_ard_3-2-1_092087_2023-01-07_final
2023-01-18 10:49:17	ga_ls8c_ard_3-2-1_105074_2023-01-18_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-19 09:58:28	ga_ls8c_ard_3-2-1_096086_2023-01-19_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-22 10:27:01	ga_ls8c_ard_3-2-1_101080_2023-01-22_final
2023-01-23 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-01-23_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-24 10:12:17	ga_ls8c_ard_3-2-1_099074_2023-01-24_final
2023-01-26 11:38:01	ga_ls8c_ard_3-2-1_113072_2023-01-26_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-06 11:24:16	ga_ls8c_ard_3-2-1_110084_2023-02-06_final
2023-02-09 10:14:16	ga_ls8c_ard_3-2-1_099079_2023-02-09_final
2023-02-12 10:45:07	ga_ls8c_ard_3-2-1_104079_2023-02-12_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-02-14 10:30:44	ga_ls8c_ard_3-2-1_102074_2023-02-14_final
2023-02-15 09:40:18	ga_ls8c_ard_3-2-1_093087_2023-02-15_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-15 11:16:47	ga_ls8c_ard_3-2-1_109081_2023-02-15_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-20 09:54:21	ga_ls8c_ard_3-2-1_096076_2023-02-20_final
2023-02-20 11:33:38	ga_ls8c_ard_3-2-1_112077_2023-02-20_final
2023-02-21 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-02-21_final
2023-02-22 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-02-22_final
2023-02-22 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-02-22_final
2023-02-23 10:24:23	ga_ls8c_ard_3-2-1_101074_2023-02-23_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-25 10:09:11	ga_ls8c_ard_3-2-1_099067_2023-02-25_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-03-01 09:50:51	ga_ls8c_ard_3-2-1_095083_2023-03-01_final
2023-03-01 11:26:08	ga_ls8c_ard_3-2-1_111074_2023-03-01_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-02 10:29:19	ga_ls8c_ard_3-2-1_102071_2023-03-02_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-07 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-03-07_final
2023-03-07 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-03-07_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-09 10:38:13	ga_ls8c_ard_3-2-1_103078_2023-03-09_final
2023-03-12 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-03-12_final
2023-03-12 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-03-12_final
2023-03-13 10:12:18	ga_ls8c_ard_3-2-1_099075_2023-03-13_final
2023-03-13 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-03-13_final
2023-03-15 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-03-15_final
2023-03-16 10:44:22	ga_ls8c_ard_3-2-1_104078_2023-03-16_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