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 10:09:10	ga_ls8c_ard_3-2-1_098082_2022-01-14_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-21 11:00:55	ga_ls8c_ard_3-2-1_107073_2022-05-21_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-12 10:26:01	ga_ls8c_ard_3-2-1_101078_2022-06-12_final
2022-06-18 09:50:59	ga_ls8c_ard_3-2-1_095083_2022-06-18_final
2022-06-19 10:31:52	ga_ls8c_ard_3-2-1_102077_2022-06-19_final
2022-06-22 11:05:34	ga_ls8c_ard_3-2-1_107084_2022-06-22_final
2022-06-24 09:14:44	ga_ls8c_ard_3-2-1_089085_2022-06-23_final
2022-06-27 09:44:03	ga_ls8c_ard_3-2-1_094081_2022-06-27_final
2022-06-27 11:21:44	ga_ls8c_ard_3-2-1_110078_2022-06-27_final
2022-06-27 11:23:20	ga_ls8c_ard_3-2-1_110082_2022-06-27_final
2022-07-02 09:58:37	ga_ls8c_ard_3-2-1_097071_2022-07-02_final
2022-07-02 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-02_final
2022-07-02 11:39:53	ga_ls8c_ard_3-2-1_113077_2022-07-02_final
2022-07-08 11:01:12	ga_ls8c_ard_3-2-1_107073_2022-07-08_final
2022-07-11 09:56:01	ga_ls8c_ard_3-2-1_096080_2022-07-11_final
2022-07-13 11:23:43	ga_ls8c_ard_3-2-1_110083_2022-07-13_final
2022-07-18 11:39:54	ga_ls8c_ard_3-2-1_113077_2022-07-18_final
2022-07-26 10:52:57	ga_ls8c_ard_3-2-1_105083_2022-07-26_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-07-28 10:35:26	ga_ls8c_ard_3-2-1_103070_2022-07-28_final
2022-07-31 11:10:45	ga_ls8c_ard_3-2-1_108081_2022-07-31_final
2022-08-05 09:50:03	ga_ls8c_ard_3-2-1_095080_2022-08-05_final
2022-08-05 09:50:51	ga_ls8c_ard_3-2-1_095082_2022-08-05_final
2022-08-11 10:48:19	ga_ls8c_ard_3-2-1_105071_2022-08-11_final
2022-08-16 11:06:04	ga_ls8c_ard_3-2-1_108069_2022-08-16_final
2022-08-16 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-08-16_final
2022-08-23 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-08-23_final
2022-08-25 11:03:06	ga_ls8c_ard_3-2-1_107077_2022-08-25_final
2022-08-26 10:07:05	ga_ls8c_ard_3-2-1_098076_2022-08-26_final
2022-08-28 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-08-28_final
2022-08-31 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-31_final
2022-09-06 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-09-06_final
2022-09-07 10:34:13	ga_ls8c_ard_3-2-1_102082_2022-09-07_final
2022-09-08 11:15:30	ga_ls8c_ard_3-2-1_109077_2022-09-08_final
2022-09-13 09:53:12	ga_ls8c_ard_3-2-1_096072_2022-09-13_final
2022-09-16 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-09-16_final
2022-09-17 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-09-17_final
2022-09-25 10:19:09	ga_ls8c_ard_3-2-1_100075_2022-09-25_final
2022-09-26 09:25:08	ga_ls8c_ard_3-2-1_091079_2022-09-25_final
2022-10-01 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-10-01_final
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-14 10:49:06	ga_ls8c_ard_3-2-1_105073_2022-10-14_final
2022-10-15 09:55:29	ga_ls8c_ard_3-2-1_096078_2022-10-15_final
2022-10-16 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-10-16_final
2022-11-04 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-11-04_final
2022-11-05 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-11-05_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-10 10:33:04	ga_ls8c_ard_3-2-1_102079_2022-11-10_final
2022-11-11 09:37:02	ga_ls8c_ard_3-2-1_093078_2022-11-11_final
2022-11-11 11:13:31	ga_ls8c_ard_3-2-1_109072_2022-11-11_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-20 11:06:04	ga_ls8c_ard_3-2-1_108069_2022-11-20_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-12-04 09:44:22	ga_ls8c_ard_3-2-1_094081_2022-12-04_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-09 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-12-09_final
2022-12-12 10:32:59	ga_ls8c_ard_3-2-1_102079_2022-12-12_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-16 10:09:25	ga_ls8c_ard_3-2-1_098082_2022-12-16_final
2022-12-18 09:57:25	ga_ls8c_ard_3-2-1_096083_2022-12-18_final
2022-12-19 10:35:53	ga_ls8c_ard_3-2-1_103071_2022-12-19_final
2022-12-25 10:03:33	ga_ls8c_ard_3-2-1_097083_2022-12-25_final
2022-12-27 09:50:00	ga_ls8c_ard_3-2-1_095080_2022-12-27_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2023-01-01 10:09:21	ga_ls8c_ard_3-2-1_098082_2023-01-01_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-09 10:59:10	ga_ls8c_ard_3-2-1_106083_2023-01-09_final
2023-01-13 10:34:00	ga_ls8c_ard_3-2-1_102082_2023-01-13_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-29 10:31:15	ga_ls8c_ard_3-2-1_102075_2023-01-29_final
2023-01-30 11:16:54	ga_ls8c_ard_3-2-1_109081_2023-01-30_final
2023-02-06 11:22:40	ga_ls8c_ard_3-2-1_110080_2023-02-06_final
2023-02-13 09:47:53	ga_ls8c_ard_3-2-1_095075_2023-02-13_final
2023-02-15 09:36:18	ga_ls8c_ard_3-2-1_093077_2023-02-15_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-21 10:37:12	ga_ls8c_ard_3-2-1_103075_2023-02-21_final
2023-02-21 10:37:36	ga_ls8c_ard_3-2-1_103076_2023-02-21_final
2023-02-21 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-02-21_final
2023-02-26 10:56:26	ga_ls8c_ard_3-2-1_106077_2023-02-26_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-08 11:31:51	ga_ls8c_ard_3-2-1_112073_2023-03-08_final
2023-03-12 09:32:14	ga_ls8c_ard_3-2-1_092083_2023-03-12_final
2023-03-14 10:57:57	ga_ls8c_ard_3-2-1_106081_2023-03-14_final
2023-03-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2023-03-17_final
2023-03-20 10:18:24	ga_ls8c_ard_3-2-1_100075_2023-03-20_final
2023-03-26 09:44:26	ga_ls8c_ard_3-2-1_094083_2023-03-26_final
2023-03-29 10:16:07	ga_ls8c_ard_3-2-1_099085_2023-03-29_final
2023-04-01 10:42:36	ga_ls8c_ard_3-2-1_104074_2023-04-01_final
2023-04-09 11:33:52	ga_ls8c_ard_3-2-1_112079_2023-04-09_final
2023-04-26 10:36:33	ga_ls8c_ard_3-2-1_103075_2023-04-26_final
2023-04-29 11:09:26	ga_ls8c_ard_3-2-1_108080_2023-04-29_final
2023-05-06 09:35:03	ga_ls8c_ard_3-2-1_093076_2023-05-06_final
2023-05-10 10:47:09	ga_ls8c_ard_3-2-1_105071_2023-05-10_final
2023-05-14 10:25:10	ga_ls8c_ard_3-2-1_101078_2023-05-14_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