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
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-27 09:54:09	ga_ls8c_ard_3-2-1_096075_2022-07-27_final
2022-07-29 09:42:13	ga_ls8c_ard_3-2-1_094076_2022-07-29_final
2022-07-29 09:42:37	ga_ls8c_ard_3-2-1_094077_2022-07-29_final
2022-07-30 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-07-30_final
2022-07-31 11:07:10	ga_ls8c_ard_3-2-1_108072_2022-07-31_final
2022-07-31 11:11:09	ga_ls8c_ard_3-2-1_108082_2022-07-31_final
2022-08-05 09:48:27	ga_ls8c_ard_3-2-1_095076_2022-08-05_final
2022-08-09 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-08-08_final
2022-08-11 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-08-11_final
2022-08-21 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-08-21_final
2022-08-21 09:50:56	ga_ls8c_ard_3-2-1_095082_2022-08-21_final
2022-08-21 11:29:01	ga_ls8c_ard_3-2-1_111080_2022-08-21_final
2022-08-25 11:01:06	ga_ls8c_ard_3-2-1_107072_2022-08-25_final
2022-08-28 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-08-28_final
2022-08-31 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-31_final
2022-08-31 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-08-31_final
2022-09-03 10:56:54	ga_ls8c_ard_3-2-1_106077_2022-09-03_final
2022-09-05 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-09-05_final
2022-09-06 09:50:33	ga_ls8c_ard_3-2-1_095081_2022-09-06_final
2022-09-07 10:32:38	ga_ls8c_ard_3-2-1_102078_2022-09-07_final
2022-09-08 11:15:30	ga_ls8c_ard_3-2-1_109077_2022-09-08_final
2022-09-13 09:57:12	ga_ls8c_ard_3-2-1_096082_2022-09-13_final
2022-09-13 11:33:17	ga_ls8c_ard_3-2-1_112075_2022-09-13_final
2022-09-15 09:42:27	ga_ls8c_ard_3-2-1_094076_2022-09-15_final
2022-09-15 09:42:51	ga_ls8c_ard_3-2-1_094077_2022-09-15_final
2022-09-17 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-09-17_final
2022-09-18 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-09-18_final
2022-09-19 10:57:02	ga_ls8c_ard_3-2-1_106077_2022-09-19_final
2022-09-20 10:01:00	ga_ls8c_ard_3-2-1_097076_2022-09-20_final
2022-09-20 11:39:53	ga_ls8c_ard_3-2-1_113076_2022-09-20_final
2022-09-22 11:27:32	ga_ls8c_ard_3-2-1_111076_2022-09-22_final
2022-09-24 09:38:41	ga_ls8c_ard_3-2-1_093082_2022-09-24_final
2022-09-26 09:29:31	ga_ls8c_ard_3-2-1_091090_2022-09-25_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-29 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-09-29_final
2022-09-29 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-09-29_final
2022-09-29 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-09-29_final
2022-09-30 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-09-30_final
2022-10-06 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-06_final
2022-10-08 09:48:59	ga_ls8c_ard_3-2-1_095077_2022-10-08_final
2022-10-08 11:27:28	ga_ls8c_ard_3-2-1_111076_2022-10-08_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-10 11:16:16	ga_ls8c_ard_3-2-1_109079_2022-10-10_final
2022-10-16 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-10-16_final
2022-10-19 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-10-19_final
2022-10-25 10:31:29	ga_ls8c_ard_3-2-1_102075_2022-10-25_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-11-09 11:28:18	ga_ls8c_ard_3-2-1_111078_2022-11-09_final
2022-11-11 11:16:19	ga_ls8c_ard_3-2-1_109079_2022-11-11_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-12 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-11-12_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-16 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-11-16_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-25 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-11-25_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-12-02 09:55:08	ga_ls8c_ard_3-2-1_096077_2022-12-02_final
2022-12-02 09:55:32	ga_ls8c_ard_3-2-1_096078_2022-12-02_final
2022-12-02 11:35:13	ga_ls8c_ard_3-2-1_112080_2022-12-02_final
2022-12-05 10:24:50	ga_ls8c_ard_3-2-1_101074_2022-12-05_final
2022-12-07 11:51:21	ga_ls8c_ard_3-2-1_115074_2022-12-07_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-18 09:56:13	ga_ls8c_ard_3-2-1_096080_2022-12-18_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-27 09:49:36	ga_ls8c_ard_3-2-1_095079_2022-12-27_final
2023-01-03 09:55:24	ga_ls8c_ard_3-2-1_096078_2023-01-03_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-06 10:27:29	ga_ls8c_ard_3-2-1_101081_2023-01-06_final
2023-01-12 09:51:57	ga_ls8c_ard_3-2-1_095085_2023-01-12_final
2023-01-14 09:37:34	ga_ls8c_ard_3-2-1_093080_2023-01-14_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-19 11:35:21	ga_ls8c_ard_3-2-1_112081_2023-01-19_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-25 10:58:20	ga_ls8c_ard_3-2-1_106081_2023-01-25_final
2023-01-30 11:16:30	ga_ls8c_ard_3-2-1_109080_2023-01-30_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_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 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-20 11:34:26	ga_ls8c_ard_3-2-1_112079_2023-02-20_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-24 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-02-24_final
2023-03-01 09:48:03	ga_ls8c_ard_3-2-1_095076_2023-03-01_final
2023-03-01 09:48:27	ga_ls8c_ard_3-2-1_095077_2023-03-01_final
2023-03-03 09:37:41	ga_ls8c_ard_3-2-1_093081_2023-03-03_final
2023-03-03 11:14:58	ga_ls8c_ard_3-2-1_109077_2023-03-03_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-08 09:56:09	ga_ls8c_ard_3-2-1_096081_2023-03-08_final
2023-03-13 10:14:41	ga_ls8c_ard_3-2-1_099081_2023-03-13_final
2023-03-16 10:44:22	ga_ls8c_ard_3-2-1_104078_2023-03-16_final
2023-03-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2023-03-17_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