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
2022-11-01 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-11-01_final
2022-11-02 09:43:40	ga_ls8c_ard_3-2-1_094079_2022-11-02_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-04 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-11-04_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-08 10:41:03	ga_ls8c_ard_3-2-1_104068_2022-11-08_final
2022-11-09 09:50:13	ga_ls8c_ard_3-2-1_095080_2022-11-09_final
2022-11-10 10:33:04	ga_ls8c_ard_3-2-1_102079_2022-11-10_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-22 09:18:02	ga_ls8c_ard_3-2-1_090077_2022-11-21_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_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
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-28 10:20:16	ga_ls8c_ard_3-2-1_100078_2022-11-28_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-11-30 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-30_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-02 11:34:49	ga_ls8c_ard_3-2-1_112079_2022-12-02_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-03 10:38:48	ga_ls8c_ard_3-2-1_103078_2022-12-03_final
2022-12-04 09:42:23	ga_ls8c_ard_3-2-1_094076_2022-12-04_final
2022-12-06 09:35:36	ga_ls8c_ard_3-2-1_092090_2022-12-06_final
2022-12-08 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-12-08_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-12 10:34:10	ga_ls8c_ard_3-2-1_102082_2022-12-12_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-13 11:17:02	ga_ls8c_ard_3-2-1_109081_2022-12-13_final
2022-12-14 10:19:00	ga_ls8c_ard_3-2-1_100075_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
2022-12-15 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-12-15_final
2022-12-16 10:10:12	ga_ls8c_ard_3-2-1_098084_2022-12-16_final
2022-12-18 09:54:14	ga_ls8c_ard_3-2-1_096075_2022-12-18_final
2022-12-19 10:37:28	ga_ls8c_ard_3-2-1_103075_2022-12-19_final
2022-12-20 09:42:14	ga_ls8c_ard_3-2-1_094076_2022-12-20_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2022-12-27 09:49:36	ga_ls8c_ard_3-2-1_095079_2022-12-27_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2022-12-29 09:39:15	ga_ls8c_ard_3-2-1_093084_2022-12-29_final
2022-12-29 11:14:32	ga_ls8c_ard_3-2-1_109075_2022-12-29_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2023-01-02 09:11:44	ga_ls8c_ard_3-2-1_089077_2023-01-01_final
2023-01-02 09:13:20	ga_ls8c_ard_3-2-1_089081_2023-01-01_final
2023-01-02 10:51:01	ga_ls8c_ard_3-2-1_105078_2023-01-02_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-06 10:26:17	ga_ls8c_ard_3-2-1_101078_2023-01-06_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-13 10:31:13	ga_ls8c_ard_3-2-1_102075_2023-01-13_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-21 09:42:56	ga_ls8c_ard_3-2-1_094078_2023-01-21_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-25 10:55:57	ga_ls8c_ard_3-2-1_106075_2023-01-25_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-01-26 09:57:32	ga_ls8c_ard_3-2-1_097068_2023-01-26_final
2023-01-31 10:22:05	ga_ls8c_ard_3-2-1_100083_2023-01-31_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-06 09:42:59	ga_ls8c_ard_3-2-1_094078_2023-02-06_final
2023-02-08 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-02-08_final
2023-02-09 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-10 10:58:43	ga_ls8c_ard_3-2-1_106082_2023-02-10_final
2023-02-13 09:47:29	ga_ls8c_ard_3-2-1_095074_2023-02-13_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-16 10:21:09	ga_ls8c_ard_3-2-1_100081_2023-02-16_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-18 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-02-18_final
2023-02-19 10:49:36	ga_ls8c_ard_3-2-1_105075_2023-02-19_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-20 09:57:57	ga_ls8c_ard_3-2-1_096085_2023-02-20_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-25 10:14:22	ga_ls8c_ard_3-2-1_099080_2023-02-25_final
2023-03-01 09:49:15	ga_ls8c_ard_3-2-1_095079_2023-03-01_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-03 09:38:53	ga_ls8c_ard_3-2-1_093084_2023-03-03_final
2023-03-03 11:16:34	ga_ls8c_ard_3-2-1_109081_2023-03-03_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-06 10:08:57	ga_ls8c_ard_3-2-1_098082_2023-03-06_final
2023-03-07 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-03-07_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-11 10:24:16	ga_ls8c_ard_3-2-1_101074_2023-03-11_final
2023-03-12 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-03-12_final
2023-03-13 10:14:41	ga_ls8c_ard_3-2-1_099081_2023-03-13_final
2023-03-13 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-03-13_final
2023-03-13 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-03-13_final
2023-03-16 10:45:10	ga_ls8c_ard_3-2-1_104080_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