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
2022-01-14 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-01-14_final
2022-11-17 10:37:10	ga_ls8c_ard_3-2-1_103074_2022-11-17_final
2022-11-20 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-11-20_final
2022-11-20 09:33:58	ga_ls8c_ard_3-2-1_092086_2022-11-20_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-01 10:51:58	ga_ls8c_ard_3-2-1_105080_2022-12-01_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_final
2022-12-11 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-12-11_final
2022-12-13 09:36:09	ga_ls8c_ard_3-2-1_093076_2022-12-13_final
2022-12-15 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-12-15_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-16 10:05:25	ga_ls8c_ard_3-2-1_098072_2022-12-16_final
2022-12-19 10:35:05	ga_ls8c_ard_3-2-1_103069_2022-12-19_final
2022-12-23 10:15:53	ga_ls8c_ard_3-2-1_099083_2022-12-23_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-25 11:39:38	ga_ls8c_ard_3-2-1_113076_2022-12-25_final
2022-12-26 10:44:49	ga_ls8c_ard_3-2-1_104078_2022-12-26_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2022-12-31 09:24:06	ga_ls8c_ard_3-2-1_091077_2022-12-30_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-21 09:46:32	ga_ls8c_ard_3-2-1_094087_2023-01-21_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-23 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-01-23_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-01-26 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-26_final
2023-01-31 10:20:05	ga_ls8c_ard_3-2-1_100078_2023-01-31_final
2023-01-31 10:22:05	ga_ls8c_ard_3-2-1_100083_2023-01-31_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-08 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-02-08_final
2023-02-12 10:43:07	ga_ls8c_ard_3-2-1_104074_2023-02-12_final
2023-02-15 11:13:35	ga_ls8c_ard_3-2-1_109073_2023-02-15_final
2023-02-17 09:25:07	ga_ls8c_ard_3-2-1_091080_2023-02-16_final
2023-02-17 11:01:36	ga_ls8c_ard_3-2-1_107074_2023-02-17_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-07 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-03-07_final
2023-03-09 10:35:25	ga_ls8c_ard_3-2-1_103071_2023-03-09_final
2023-03-09 10:36:13	ga_ls8c_ard_3-2-1_103073_2023-03-09_final
2023-03-12 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-03-11_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-17 11:25:14	ga_ls8c_ard_3-2-1_111072_2023-03-17_final
2023-03-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2023-03-18_final
2023-03-21 09:27:09	ga_ls8c_ard_3-2-1_091086_2023-03-20_final
2023-03-23 10:48:51	ga_ls8c_ard_3-2-1_105074_2023-03-23_final
2023-03-25 10:38:52	ga_ls8c_ard_3-2-1_103080_2023-03-25_final
2023-03-28 11:06:10	ga_ls8c_ard_3-2-1_108071_2023-03-28_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-03-30 10:54:59	ga_ls8c_ard_3-2-1_106074_2023-03-30_final
2023-04-02 09:47:22	ga_ls8c_ard_3-2-1_095075_2023-04-02_final
2023-04-02 11:25:51	ga_ls8c_ard_3-2-1_111074_2023-04-02_final
2023-04-04 11:12:39	ga_ls8c_ard_3-2-1_109072_2023-04-04_final
2023-04-04 11:15:27	ga_ls8c_ard_3-2-1_109079_2023-04-04_final
2023-04-06 11:01:51	ga_ls8c_ard_3-2-1_107076_2023-04-06_final
2023-04-08 10:46:38	ga_ls8c_ard_3-2-1_105069_2023-04-08_final
2023-04-10 10:39:01	ga_ls8c_ard_3-2-1_103081_2023-04-10_final
2023-04-14 11:51:34	ga_ls8c_ard_3-2-1_115077_2023-04-14_final
2023-04-16 10:03:30	ga_ls8c_ard_3-2-1_097085_2023-04-16_final
2023-04-18 09:47:08	ga_ls8c_ard_3-2-1_095075_2023-04-18_final
2023-04-24 10:48:55	ga_ls8c_ard_3-2-1_105075_2023-04-24_final
2023-04-24 10:51:43	ga_ls8c_ard_3-2-1_105082_2023-04-24_final
2023-04-25 09:52:30	ga_ls8c_ard_3-2-1_096073_2023-04-25_final
2023-04-27 11:19:01	ga_ls8c_ard_3-2-1_110073_2023-04-27_final
2023-04-29 09:29:45	ga_ls8c_ard_3-2-1_092078_2023-04-28_final
2023-04-30 11:50:41	ga_ls8c_ard_3-2-1_115075_2023-04-30_final
2023-05-01 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-04-30_final
2023-05-01 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-04-30_final
2023-05-04 11:25:31	ga_ls8c_ard_3-2-1_111074_2023-05-04_final
2023-05-05 10:29:29	ga_ls8c_ard_3-2-1_102073_2023-05-05_final
2023-05-06 09:34:39	ga_ls8c_ard_3-2-1_093075_2023-05-06_final
2023-05-06 09:39:26	ga_ls8c_ard_3-2-1_093087_2023-05-06_final
2023-05-08 09:25:51	ga_ls8c_ard_3-2-1_091084_2023-05-07_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-16 11:51:40	ga_ls8c_ard_3-2-1_115078_2023-05-16_final
2023-05-18 10:00:49	ga_ls8c_ard_3-2-1_097079_2023-05-18_final
2023-05-18 11:40:30	ga_ls8c_ard_3-2-1_113081_2023-05-18_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_final
2023-05-23 10:18:12	ga_ls8c_ard_3-2-1_100076_2023-05-23_final
2023-05-24 09:26:10	ga_ls8c_ard_3-2-1_091085_2023-05-23_final
2023-05-25 10:04:15	ga_ls8c_ard_3-2-1_098072_2023-05-25_final
2023-05-26 09:11:01	ga_ls8c_ard_3-2-1_089078_2023-05-25_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