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
2022-04-29 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-04-29_final
2022-04-30 10:41:24	ga_ls8c_ard_3-2-1_104071_2022-04-30_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-12 11:06:39	ga_ls8c_ard_3-2-1_108072_2022-05-12_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-15 11:38:46	ga_ls8c_ard_3-2-1_113075_2022-05-15_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-22 10:08:53	ga_ls8c_ard_3-2-1_098082_2022-05-22_final
2022-05-22 11:45:46	ga_ls8c_ard_3-2-1_114077_2022-05-22_final
2022-05-25 10:38:58	ga_ls8c_ard_3-2-1_103080_2022-05-25_final
2022-06-11 09:41:33	ga_ls8c_ard_3-2-1_094075_2022-06-11_final
2022-06-13 11:08:54	ga_ls8c_ard_3-2-1_108077_2022-06-13_final
2022-06-18 09:49:23	ga_ls8c_ard_3-2-1_095079_2022-06-18_final
2022-06-24 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-06-24_final
2022-06-26 10:37:17	ga_ls8c_ard_3-2-1_103075_2022-06-26_final
2022-07-01 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-01_final
2022-07-01 10:57:25	ga_ls8c_ard_3-2-1_106079_2022-07-01_final
2022-07-02 10:03:00	ga_ls8c_ard_3-2-1_097082_2022-07-02_final
2022-07-03 10:44:16	ga_ls8c_ard_3-2-1_104077_2022-07-03_final
2022-07-04 09:49:26	ga_ls8c_ard_3-2-1_095079_2022-07-04_final
2022-07-10 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-07-10_final
2022-07-11 09:54:25	ga_ls8c_ard_3-2-1_096076_2022-07-11_final
2022-07-13 09:42:51	ga_ls8c_ard_3-2-1_094078_2022-07-13_final
2022-07-13 11:18:32	ga_ls8c_ard_3-2-1_110070_2022-07-13_final
2022-07-14 10:26:30	ga_ls8c_ard_3-2-1_101079_2022-07-14_final
2022-07-18 10:00:13	ga_ls8c_ard_3-2-1_097075_2022-07-18_final
2022-07-19 10:43:05	ga_ls8c_ard_3-2-1_104074_2022-07-19_final
2022-07-19 10:43:53	ga_ls8c_ard_3-2-1_104076_2022-07-19_final
2022-07-19 10:44:17	ga_ls8c_ard_3-2-1_104077_2022-07-19_final
2022-07-21 10:32:21	ga_ls8c_ard_3-2-1_102078_2022-07-21_final
2022-07-26 10:50:34	ga_ls8c_ard_3-2-1_105077_2022-07-26_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
2022-07-29 09:43:01	ga_ls8c_ard_3-2-1_094078_2022-07-29_final
2022-07-31 11:09:09	ga_ls8c_ard_3-2-1_108077_2022-07-31_final
2022-08-01 10:12:45	ga_ls8c_ard_3-2-1_099075_2022-08-01_final
2022-08-12 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-08-12_final
2022-08-14 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-08-14_final
2022-08-15 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-15_final
2022-08-16 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-08-16_final
2022-08-17 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-08-17_final
2022-08-19 11:42:34	ga_ls8c_ard_3-2-1_113083_2022-08-19_final
2022-08-23 11:12:40	ga_ls8c_ard_3-2-1_109070_2022-08-23_final
2022-08-23 11:18:15	ga_ls8c_ard_3-2-1_109084_2022-08-23_final
2022-08-25 09:22:13	ga_ls8c_ard_3-2-1_091072_2022-08-24_final
2022-08-27 10:50:44	ga_ls8c_ard_3-2-1_105077_2022-08-27_final
2022-08-28 11:33:12	ga_ls8c_ard_3-2-1_112075_2022-08-28_final
2022-08-29 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-08-29_final
2022-09-01 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-08-31_final
2022-09-05 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-09-05_final
2022-09-05 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-09-05_final
2022-09-13 09:54:48	ga_ls8c_ard_3-2-1_096076_2022-09-13_final
2022-09-13 09:55:12	ga_ls8c_ard_3-2-1_096077_2022-09-13_final
2022-09-13 09:56:24	ga_ls8c_ard_3-2-1_096080_2022-09-13_final
2022-09-15 11:22:08	ga_ls8c_ard_3-2-1_110078_2022-09-15_final
2022-09-20 11:39:53	ga_ls8c_ard_3-2-1_113076_2022-09-20_final
2022-09-20 11:40:41	ga_ls8c_ard_3-2-1_113078_2022-09-20_final
2022-09-21 10:42:16	ga_ls8c_ard_3-2-1_104071_2022-09-21_final
2022-09-22 11:28:20	ga_ls8c_ard_3-2-1_111078_2022-09-22_final
2022-09-30 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-09-30_final
2022-10-09 10:31:49	ga_ls8c_ard_3-2-1_102076_2022-10-09_final
2022-10-15 09:54:41	ga_ls8c_ard_3-2-1_096076_2022-10-15_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-22 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-22_final
2022-10-22 11:41:02	ga_ls8c_ard_3-2-1_113079_2022-10-22_final
2022-10-23 10:42:14	ga_ls8c_ard_3-2-1_104071_2022-10-23_final
2022-10-24 09:49:24	ga_ls8c_ard_3-2-1_095078_2022-10-24_final
2022-11-01 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-11-01_final
2022-11-02 09:43:16	ga_ls8c_ard_3-2-1_094078_2022-11-02_final
2022-11-02 11:22:09	ga_ls8c_ard_3-2-1_110078_2022-11-02_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-12 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-11-12_final
2022-11-19 10:25:36	ga_ls8c_ard_3-2-1_101076_2022-11-19_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-12-01 10:51:10	ga_ls8c_ard_3-2-1_105078_2022-12-01_final
2022-12-02 09:54:45	ga_ls8c_ard_3-2-1_096076_2022-12-02_final
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-09 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-12-09_final
2022-12-11 09:49:19	ga_ls8c_ard_3-2-1_095078_2022-12-11_final
2022-12-11 09:49:43	ga_ls8c_ard_3-2-1_095079_2022-12-11_final
2022-12-26 10:46:01	ga_ls8c_ard_3-2-1_104081_2022-12-26_final
2023-01-02 10:51:01	ga_ls8c_ard_3-2-1_105078_2023-01-02_final
2023-01-04 10:39:03	ga_ls8c_ard_3-2-1_103079_2023-01-04_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_final
2023-01-23 11:09:29	ga_ls8c_ard_3-2-1_108078_2023-01-23_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-20 09:55:57	ga_ls8c_ard_3-2-1_096080_2023-02-20_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-20 11:33:38	ga_ls8c_ard_3-2-1_112077_2023-02-20_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-01 09:48:27	ga_ls8c_ard_3-2-1_095077_2023-03-01_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-08 11:33:03	ga_ls8c_ard_3-2-1_112076_2023-03-08_final
2023-03-10 09:43:24	ga_ls8c_ard_3-2-1_094080_2023-03-10_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