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
2022-08-21 09:50:32	ga_ls8c_ard_3-2-1_095081_2022-08-21_final
2022-08-22 10:33:24	ga_ls8c_ard_3-2-1_102080_2022-08-22_final
2022-08-23 09:36:58	ga_ls8c_ard_3-2-1_093078_2022-08-23_final
2022-08-25 11:03:54	ga_ls8c_ard_3-2-1_107079_2022-08-25_final
2022-08-27 10:51:56	ga_ls8c_ard_3-2-1_105080_2022-08-27_final
2022-08-29 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-08-29_final
2022-08-29 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-08-29_final
2022-09-06 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-09-06_final
2022-09-06 09:50:33	ga_ls8c_ard_3-2-1_095081_2022-09-06_final
2022-09-07 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-09-07_final
2022-09-07 10:33:02	ga_ls8c_ard_3-2-1_102079_2022-09-07_final
2022-09-12 10:51:13	ga_ls8c_ard_3-2-1_105078_2022-09-12_final
2022-09-18 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-09-18_final
2022-09-20 10:00:36	ga_ls8c_ard_3-2-1_097075_2022-09-20_final
2022-09-24 11:16:22	ga_ls8c_ard_3-2-1_109079_2022-09-24_final
2022-09-25 11:58:50	ga_ls8c_ard_3-2-1_116077_2022-09-25_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-09-29 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-09-29_final
2022-09-29 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-09-29_final
2022-09-29 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-09-29_final
2022-09-29 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-09-29_final
2022-09-30 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-09-30_final
2022-10-04 10:12:56	ga_ls8c_ard_3-2-1_099075_2022-10-04_final
2022-10-05 10:59:23	ga_ls8c_ard_3-2-1_106083_2022-10-05_final
2022-10-06 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-06_final
2022-10-06 11:39:51	ga_ls8c_ard_3-2-1_113076_2022-10-06_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-08 11:27:52	ga_ls8c_ard_3-2-1_111077_2022-10-08_final
2022-10-14 10:51:29	ga_ls8c_ard_3-2-1_105079_2022-10-14_final
2022-10-15 09:55:29	ga_ls8c_ard_3-2-1_096078_2022-10-15_final
2022-10-15 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-10-15_final
2022-10-22 10:00:33	ga_ls8c_ard_3-2-1_097075_2022-10-22_final
2022-10-24 09:49:48	ga_ls8c_ard_3-2-1_095079_2022-10-24_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-10-26 11:16:44	ga_ls8c_ard_3-2-1_109080_2022-10-26_final
2022-10-27 10:21:07	ga_ls8c_ard_3-2-1_100080_2022-10-27_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-10-31 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-10-31_final
2022-10-31 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-10-31_final
2022-10-31 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-10-31_final
2022-11-09 11:28:18	ga_ls8c_ard_3-2-1_111078_2022-11-09_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-16 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-11-16_final
2022-11-16 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-11-16_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-18 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-11-18_final
2022-11-18 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-11-18_final
2022-11-19 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-11-19_final
2022-11-20 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-11-20_final
2022-11-20 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-11-20_final
2022-11-23 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-11-23_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-11-30 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-30_final
2022-12-02 09:55:32	ga_ls8c_ard_3-2-1_096078_2022-12-02_final
2022-12-02 09:56:20	ga_ls8c_ard_3-2-1_096080_2022-12-02_final
2022-12-02 11:34:49	ga_ls8c_ard_3-2-1_112079_2022-12-02_final
2022-12-11 11:29:00	ga_ls8c_ard_3-2-1_111080_2022-12-11_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-18 09:55:49	ga_ls8c_ard_3-2-1_096079_2022-12-18_final
2022-12-18 09:56:13	ga_ls8c_ard_3-2-1_096080_2022-12-18_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-19 10:39:04	ga_ls8c_ard_3-2-1_103079_2022-12-19_final
2022-12-27 09:48:48	ga_ls8c_ard_3-2-1_095077_2022-12-27_final
2022-12-27 11:28:53	ga_ls8c_ard_3-2-1_111080_2022-12-27_final
2022-12-29 09:37:15	ga_ls8c_ard_3-2-1_093079_2022-12-29_final
2022-12-29 11:15:44	ga_ls8c_ard_3-2-1_109078_2022-12-29_final
2022-12-30 10:18:31	ga_ls8c_ard_3-2-1_100074_2022-12-30_final
2023-01-03 11:34:17	ga_ls8c_ard_3-2-1_112078_2023-01-03_final
2023-01-12 11:28:02	ga_ls8c_ard_3-2-1_111078_2023-01-12_final
2023-01-14 09:37:34	ga_ls8c_ard_3-2-1_093080_2023-01-14_final
2023-01-16 11:04:51	ga_ls8c_ard_3-2-1_107082_2023-01-16_final
2023-01-21 09:42:32	ga_ls8c_ard_3-2-1_094077_2023-01-21_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-12 10:45:07	ga_ls8c_ard_3-2-1_104079_2023-02-12_final
2023-02-13 11:28:46	ga_ls8c_ard_3-2-1_111080_2023-02-13_final
2023-02-20 09:54:21	ga_ls8c_ard_3-2-1_096076_2023-02-20_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-20 09:56:21	ga_ls8c_ard_3-2-1_096081_2023-02-20_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-21 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-02-21_final
2023-02-22 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-02-22_final
2023-02-23 10:26:47	ga_ls8c_ard_3-2-1_101080_2023-02-23_final
2023-02-24 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-02-24_final
2023-03-01 09:48:27	ga_ls8c_ard_3-2-1_095077_2023-03-01_final
2023-03-01 09:49:15	ga_ls8c_ard_3-2-1_095079_2023-03-01_final
2023-03-02 10:32:31	ga_ls8c_ard_3-2-1_102079_2023-03-02_final
2023-03-03 09:36:29	ga_ls8c_ard_3-2-1_093078_2023-03-03_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-04 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-03-04_final
2023-03-04 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-03-04_final
2023-03-07 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-03-07_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-10 09:44:35	ga_ls8c_ard_3-2-1_094083_2023-03-10_final
2023-03-11 10:26:39	ga_ls8c_ard_3-2-1_101080_2023-03-11_final
2023-03-12 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-03-12_final
2023-03-14 10:56:21	ga_ls8c_ard_3-2-1_106077_2023-03-14_final
2023-03-16 10:44:46	ga_ls8c_ard_3-2-1_104079_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