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
2022-05-02 10:29:52	ga_ls8c_ard_3-2-1_102073_2022-05-02_final
2022-05-09 10:34:08	ga_ls8c_ard_3-2-1_103068_2022-05-09_final
2022-05-10 11:19:24	ga_ls8c_ard_3-2-1_110073_2022-05-10_final
2022-05-14 09:20:13	ga_ls8c_ard_3-2-1_090084_2022-05-13_final
2022-05-21 09:22:49	ga_ls8c_ard_3-2-1_091075_2022-05-20_final
2022-05-21 11:01:18	ga_ls8c_ard_3-2-1_107074_2022-05-21_final
2022-05-21 11:02:54	ga_ls8c_ard_3-2-1_107078_2022-05-21_final
2022-05-26 09:40:33	ga_ls8c_ard_3-2-1_094073_2022-05-26_final
2022-05-30 09:21:03	ga_ls8c_ard_3-2-1_090086_2022-05-29_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-03 10:32:29	ga_ls8c_ard_3-2-1_102079_2022-06-03_final
2022-06-11 11:18:26	ga_ls8c_ard_3-2-1_110070_2022-06-11_final
2022-06-11 11:19:14	ga_ls8c_ard_3-2-1_110072_2022-06-11_final
2022-06-11 11:22:50	ga_ls8c_ard_3-2-1_110081_2022-06-11_final
2022-06-15 09:19:16	ga_ls8c_ard_3-2-1_090081_2022-06-14_final
2022-06-21 10:17:31	ga_ls8c_ard_3-2-1_100072_2022-06-21_final
2022-06-21 11:58:00	ga_ls8c_ard_3-2-1_116076_2022-06-21_final
2022-06-22 11:01:35	ga_ls8c_ard_3-2-1_107074_2022-06-22_final
2022-06-24 09:12:21	ga_ls8c_ard_3-2-1_089079_2022-06-23_final
2022-06-25 11:36:29	ga_ls8c_ard_3-2-1_112084_2022-06-25_final
2022-06-30 10:14:34	ga_ls8c_ard_3-2-1_099080_2022-06-30_final
2022-07-09 11:46:04	ga_ls8c_ard_3-2-1_114077_2022-07-09_final
2022-07-10 09:11:33	ga_ls8c_ard_3-2-1_089077_2022-07-09_final
2022-07-14 10:23:42	ga_ls8c_ard_3-2-1_101072_2022-07-14_final
2022-07-20 11:24:22	ga_ls8c_ard_3-2-1_111069_2022-07-20_final
2022-07-21 10:30:22	ga_ls8c_ard_3-2-1_102073_2022-07-21_final
2022-07-24 09:26:48	ga_ls8c_ard_3-2-1_091084_2022-07-23_final
2022-07-25 10:08:05	ga_ls8c_ard_3-2-1_098079_2022-07-25_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-08-01 10:14:20	ga_ls8c_ard_3-2-1_099079_2022-08-01_final
2022-08-02 09:22:43	ga_ls8c_ard_3-2-1_090089_2022-08-01_final
2022-08-02 10:58:49	ga_ls8c_ard_3-2-1_106082_2022-08-02_final
2022-08-09 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-08-08_final
2022-08-10 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-08-10_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-29 10:35:59	ga_ls8c_ard_3-2-1_103071_2022-08-29_final
2022-09-04 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-09-04_final
2022-09-09 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-09-09_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-17 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-09-17_final
2022-09-26 11:00:25	ga_ls8c_ard_3-2-1_107070_2022-09-26_final
2022-09-29 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-09-29_final
2022-10-01 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-10-01_final
2022-10-09 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-10-09_final
2022-10-16 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-10-16_final
2022-10-26 11:14:45	ga_ls8c_ard_3-2-1_109075_2022-10-26_final
2022-10-28 09:22:43	ga_ls8c_ard_3-2-1_091073_2022-10-27_final
2022-10-28 09:25:54	ga_ls8c_ard_3-2-1_091081_2022-10-27_final
2022-10-28 11:05:11	ga_ls8c_ard_3-2-1_107082_2022-10-28_final
2022-11-03 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-11-03_final
2022-11-07 09:59:48	ga_ls8c_ard_3-2-1_097073_2022-11-07_final
2022-11-09 09:48:13	ga_ls8c_ard_3-2-1_095075_2022-11-09_final
2022-11-11 11:12:44	ga_ls8c_ard_3-2-1_109070_2022-11-11_final
2022-11-13 09:28:15	ga_ls8c_ard_3-2-1_091087_2022-11-12_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-20 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-11-20_final
2022-11-21 10:16:03	ga_ls8c_ard_3-2-1_099083_2022-11-21_final
2022-11-21 10:16:27	ga_ls8c_ard_3-2-1_099084_2022-11-21_final
2022-11-22 09:18:26	ga_ls8c_ard_3-2-1_090078_2022-11-21_final
2022-11-22 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-11-22_final
2022-11-23 09:58:07	ga_ls8c_ard_3-2-1_097069_2022-11-23_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-11-30 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-30_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-01 10:51:58	ga_ls8c_ard_3-2-1_105080_2022-12-01_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_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 11:13:50	ga_ls8c_ard_3-2-1_109073_2022-12-13_final
2022-12-14 10:17:48	ga_ls8c_ard_3-2-1_100072_2022-12-14_final
2022-12-17 09:11:47	ga_ls8c_ard_3-2-1_089077_2022-12-16_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-26 10:44:25	ga_ls8c_ard_3-2-1_104077_2022-12-26_final
2022-12-31 09:27:17	ga_ls8c_ard_3-2-1_091085_2022-12-30_final
2022-12-31 09:29:17	ga_ls8c_ard_3-2-1_091090_2022-12-30_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-08 11:51:36	ga_ls8c_ard_3-2-1_115075_2023-01-08_final
2023-01-11 10:44:00	ga_ls8c_ard_3-2-1_104076_2023-01-11_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-12 09:52:45	ga_ls8c_ard_3-2-1_095087_2023-01-12_final
2023-01-23 11:07:29	ga_ls8c_ard_3-2-1_108073_2023-01-23_final
2023-01-25 09:22:15	ga_ls8c_ard_3-2-1_090088_2023-01-24_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-01-26 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-26_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-08 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-02-08_final
2023-02-14 10:31:56	ga_ls8c_ard_3-2-1_102077_2023-02-14_final
2023-02-18 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-02-18_final
2023-02-18 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-02-18_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-06 10:10:09	ga_ls8c_ard_3-2-1_098085_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_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