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
2022-02-08 10:00:05	ga_ls8c_ard_3-2-1_097075_2022-02-08_final
2022-02-09 10:45:44	ga_ls8c_ard_3-2-1_104081_2022-02-09_final
2022-02-26 09:48:49	ga_ls8c_ard_3-2-1_095078_2022-02-26_final
2022-02-27 10:32:53	ga_ls8c_ard_3-2-1_102080_2022-02-27_final
2022-03-05 09:53:47	ga_ls8c_ard_3-2-1_096075_2022-03-05_final
2022-03-11 10:56:21	ga_ls8c_ard_3-2-1_106077_2022-03-11_final
2022-03-14 11:28:25	ga_ls8c_ard_3-2-1_111080_2022-03-14_final
2022-03-16 11:16:03	ga_ls8c_ard_3-2-1_109080_2022-03-16_final
2022-03-19 10:05:38	ga_ls8c_ard_3-2-1_098074_2022-03-19_final
2022-03-20 10:50:53	ga_ls8c_ard_3-2-1_105079_2022-03-20_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-11 10:14:32	ga_ls8c_ard_3-2-1_099081_2022-04-11_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-15 09:49:02	ga_ls8c_ard_3-2-1_095079_2022-04-15_final
2022-05-08 09:56:51	ga_ls8c_ard_3-2-1_096083_2022-05-08_final
2022-05-08 11:34:32	ga_ls8c_ard_3-2-1_112080_2022-05-08_final
2022-05-13 10:12:14	ga_ls8c_ard_3-2-1_099075_2022-05-13_final
2022-05-15 09:59:53	ga_ls8c_ard_3-2-1_097075_2022-05-15_final
2022-05-17 11:28:01	ga_ls8c_ard_3-2-1_111079_2022-05-17_final
2022-06-06 09:24:08	ga_ls8c_ard_3-2-1_091078_2022-06-05_final
2022-06-11 11:22:02	ga_ls8c_ard_3-2-1_110079_2022-06-11_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-22 09:24:18	ga_ls8c_ard_3-2-1_091078_2022-06-21_final
2022-06-25 09:54:01	ga_ls8c_ard_3-2-1_096075_2022-06-25_final
2022-07-02 11:39:05	ga_ls8c_ard_3-2-1_113075_2022-07-02_final
2022-07-04 11:28:43	ga_ls8c_ard_3-2-1_111080_2022-07-04_final
2022-07-12 10:37:40	ga_ls8c_ard_3-2-1_103076_2022-07-12_final
2022-07-13 09:41:39	ga_ls8c_ard_3-2-1_094075_2022-07-13_final
2022-07-22 09:38:45	ga_ls8c_ard_3-2-1_093083_2022-07-22_final
2022-07-25 10:06:05	ga_ls8c_ard_3-2-1_098074_2022-07-25_final
2022-07-27 09:52:57	ga_ls8c_ard_3-2-1_096072_2022-07-27_final
2022-07-27 09:56:57	ga_ls8c_ard_3-2-1_096082_2022-07-27_final
2022-07-27 11:35:02	ga_ls8c_ard_3-2-1_112080_2022-07-27_final
2022-07-28 10:39:25	ga_ls8c_ard_3-2-1_103080_2022-07-28_final
2022-08-05 11:28:08	ga_ls8c_ard_3-2-1_111078_2022-08-05_final
2022-08-11 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-08-11_final
2022-08-12 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-08-12_final
2022-08-17 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-08-17_final
2022-08-18 10:56:55	ga_ls8c_ard_3-2-1_106077_2022-08-18_final
2022-08-19 11:42:34	ga_ls8c_ard_3-2-1_113083_2022-08-19_final
2022-08-23 11:16:15	ga_ls8c_ard_3-2-1_109079_2022-08-23_final
2022-08-28 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-08-28_final
2022-09-11 10:09:32	ga_ls8c_ard_3-2-1_098082_2022-09-11_final
2022-09-16 10:23:19	ga_ls8c_ard_3-2-1_101070_2022-09-16_final
2022-09-20 11:40:41	ga_ls8c_ard_3-2-1_113078_2022-09-20_final
2022-09-21 10:44:40	ga_ls8c_ard_3-2-1_104077_2022-09-21_final
2022-09-28 10:51:39	ga_ls8c_ard_3-2-1_105079_2022-09-28_final
2022-09-29 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-09-29_final
2022-09-30 10:37:17	ga_ls8c_ard_3-2-1_103074_2022-09-30_final
2022-10-06 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-06_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-17 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-10-17_final
2022-10-20 10:12:53	ga_ls8c_ard_3-2-1_099075_2022-10-20_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-22 11:39:50	ga_ls8c_ard_3-2-1_113076_2022-10-22_final
2022-10-31 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-10-31_final
2022-10-31 09:55:13	ga_ls8c_ard_3-2-1_096077_2022-10-31_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-28 10:19:04	ga_ls8c_ard_3-2-1_100075_2022-11-28_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-09 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-12-09_final
2022-12-10 10:43:45	ga_ls8c_ard_3-2-1_104075_2022-12-10_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-26 10:45:13	ga_ls8c_ard_3-2-1_104079_2022-12-26_final
2022-12-27 09:48:00	ga_ls8c_ard_3-2-1_095075_2022-12-27_final
2023-01-01 10:08:57	ga_ls8c_ard_3-2-1_098081_2023-01-01_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-12 09:49:09	ga_ls8c_ard_3-2-1_095078_2023-01-12_final
2023-01-19 11:34:33	ga_ls8c_ard_3-2-1_112079_2023-01-19_final
2023-02-11 11:40:22	ga_ls8c_ard_3-2-1_113078_2023-02-11_final
2023-02-18 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-02-18_final
2023-02-19 10:51:12	ga_ls8c_ard_3-2-1_105079_2023-02-19_final
2023-02-20 11:33:14	ga_ls8c_ard_3-2-1_112076_2023-02-20_final
2023-02-22 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-02-22_final
2023-03-08 09:56:33	ga_ls8c_ard_3-2-1_096082_2023-03-08_final
2023-03-15 10:03:07	ga_ls8c_ard_3-2-1_097083_2023-03-15_final
2023-03-16 10:43:34	ga_ls8c_ard_3-2-1_104076_2023-03-16_final
2023-04-08 10:50:38	ga_ls8c_ard_3-2-1_105079_2023-04-08_final
2023-04-11 11:21:28	ga_ls8c_ard_3-2-1_110079_2023-04-11_final
2023-04-12 10:26:14	ga_ls8c_ard_3-2-1_101080_2023-04-12_final
2023-04-17 10:44:21	ga_ls8c_ard_3-2-1_104079_2023-04-17_final
2023-04-18 09:49:31	ga_ls8c_ard_3-2-1_095081_2023-04-18_final
2023-04-18 11:26:48	ga_ls8c_ard_3-2-1_111077_2023-04-18_final
2023-04-18 11:28:00	ga_ls8c_ard_3-2-1_111080_2023-04-18_final
2023-04-20 09:36:20	ga_ls8c_ard_3-2-1_093079_2023-04-20_final
2023-04-24 10:50:07	ga_ls8c_ard_3-2-1_105078_2023-04-24_final
2023-04-25 09:56:05	ga_ls8c_ard_3-2-1_096082_2023-04-25_final
2023-04-27 11:21:48	ga_ls8c_ard_3-2-1_110080_2023-04-27_final
2023-05-02 11:38:19	ga_ls8c_ard_3-2-1_113075_2023-05-02_final
2023-05-02 11:38:42	ga_ls8c_ard_3-2-1_113076_2023-05-02_final
2023-05-03 10:43:28	ga_ls8c_ard_3-2-1_104077_2023-05-03_final
2023-05-04 09:49:02	ga_ls8c_ard_3-2-1_095080_2023-05-04_final
2023-05-04 11:26:43	ga_ls8c_ard_3-2-1_111077_2023-05-04_final
2023-05-06 09:35:27	ga_ls8c_ard_3-2-1_093077_2023-05-06_final
2023-05-10 10:49:56	ga_ls8c_ard_3-2-1_105078_2023-05-10_final
2023-05-11 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-11_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