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
2022-07-18 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-18_final
2022-07-26 09:15:16	ga_ls8c_ard_3-2-1_089086_2022-07-25_final
2022-07-30 10:25:05	ga_ls8c_ard_3-2-1_101075_2022-07-30_final
2022-08-27 09:13:27	ga_ls8c_ard_3-2-1_089081_2022-08-26_final
2022-08-31 10:24:49	ga_ls8c_ard_3-2-1_101074_2022-08-31_final
2022-08-31 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-31_final
2022-09-01 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-09-01_final
2022-09-04 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-09-04_final
2022-09-06 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-09-06_final
2022-09-09 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-09-09_final
2022-09-12 10:53:12	ga_ls8c_ard_3-2-1_105083_2022-09-12_final
2022-09-15 09:43:15	ga_ls8c_ard_3-2-1_094078_2022-09-15_final
2022-09-26 11:01:13	ga_ls8c_ard_3-2-1_107072_2022-09-26_final
2022-09-30 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-09-30_final
2022-10-06 09:59:46	ga_ls8c_ard_3-2-1_097073_2022-10-06_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-12 11:04:40	ga_ls8c_ard_3-2-1_107081_2022-10-12_final
2022-10-16 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-10-16_final
2022-10-19 11:06:07	ga_ls8c_ard_3-2-1_108069_2022-10-19_final
2022-10-20 10:12:30	ga_ls8c_ard_3-2-1_099074_2022-10-20_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-23 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-23_final
2022-11-07 09:59:48	ga_ls8c_ard_3-2-1_097073_2022-11-07_final
2022-11-07 10:00:35	ga_ls8c_ard_3-2-1_097075_2022-11-07_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-21 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-11-21_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-11-24 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-11-24_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-12-04 09:41:59	ga_ls8c_ard_3-2-1_094075_2022-12-04_final
2022-12-23 11:52:23	ga_ls8c_ard_3-2-1_115077_2022-12-23_final
2022-12-28 10:33:16	ga_ls8c_ard_3-2-1_102080_2022-12-28_final
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_final
2023-01-07 09:32:15	ga_ls8c_ard_3-2-1_092082_2023-01-07_final
2023-01-09 09:18:17	ga_ls8c_ard_3-2-1_090078_2023-01-08_final
2023-01-10 10:03:32	ga_ls8c_ard_3-2-1_097083_2023-01-10_final
2023-01-12 09:49:57	ga_ls8c_ard_3-2-1_095080_2023-01-12_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-02-02 10:09:19	ga_ls8c_ard_3-2-1_098082_2023-02-02_final
2023-02-03 09:12:54	ga_ls8c_ard_3-2-1_089080_2023-02-02_final
2023-02-03 09:14:30	ga_ls8c_ard_3-2-1_089084_2023-02-02_final
2023-02-09 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-02-09_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-03-03 09:40:28	ga_ls8c_ard_3-2-1_093088_2023-03-03_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-13 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-03-13_final
2023-03-24 09:55:13	ga_ls8c_ard_3-2-1_096079_2023-03-24_final
2023-03-26 09:43:39	ga_ls8c_ard_3-2-1_094081_2023-03-26_final
2023-03-28 11:06:34	ga_ls8c_ard_3-2-1_108072_2023-03-28_final
2023-04-02 11:27:02	ga_ls8c_ard_3-2-1_111077_2023-04-02_final
2023-04-07 11:45:29	ga_ls8c_ard_3-2-1_114077_2023-04-07_final
2023-04-15 09:17:51	ga_ls8c_ard_3-2-1_090079_2023-04-14_final
2023-04-24 10:50:31	ga_ls8c_ard_3-2-1_105079_2023-04-24_final
2023-04-30 11:50:17	ga_ls8c_ard_3-2-1_115074_2023-04-30_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-10 09:12:15	ga_ls8c_ard_3-2-1_089081_2023-05-09_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-05-16 11:52:28	ga_ls8c_ard_3-2-1_115080_2023-05-16_final
2023-05-17 09:17:33	ga_ls8c_ard_3-2-1_090079_2023-05-16_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_final
2023-05-22 11:14:37	ga_ls8c_ard_3-2-1_109078_2023-05-22_final
2023-05-25 11:44:20	ga_ls8c_ard_3-2-1_114075_2023-05-25_final
2023-05-27 09:51:54	ga_ls8c_ard_3-2-1_096072_2023-05-27_final
2023-06-04 10:42:58	ga_ls8c_ard_3-2-1_104076_2023-06-04_final
2023-06-09 09:24:41	ga_ls8c_ard_3-2-1_091081_2023-06-08_final
2023-06-11 09:11:57	ga_ls8c_ard_3-2-1_089080_2023-06-10_final
2023-06-11 10:48:02	ga_ls8c_ard_3-2-1_105073_2023-06-11_final
2023-06-13 10:38:29	ga_ls8c_ard_3-2-1_103080_2023-06-13_final
2023-06-14 11:20:57	ga_ls8c_ard_3-2-1_110078_2023-06-14_final
2023-06-15 10:24:32	ga_ls8c_ard_3-2-1_101076_2023-06-15_final
2023-06-21 09:50:40	ga_ls8c_ard_3-2-1_095084_2023-06-21_final
2023-06-25 09:24:47	ga_ls8c_ard_3-2-1_091081_2023-06-24_final
2023-06-27 09:16:03	ga_ls8c_ard_3-2-1_089090_2023-06-26_final
2023-07-09 09:38:31	ga_ls8c_ard_3-2-1_093084_2023-07-09_final
2023-07-13 10:49:54	ga_ls8c_ard_3-2-1_105077_2023-07-13_final
2023-07-21 10:01:39	ga_ls8c_ard_3-2-1_097080_2023-07-21_final
2023-07-21 11:41:20	ga_ls8c_ard_3-2-1_113082_2023-07-21_final
2023-07-23 09:47:44	ga_ls8c_ard_3-2-1_095076_2023-07-23_final
2023-07-27 09:25:04	ga_ls8c_ard_3-2-1_091081_2023-07-26_final
2023-07-29 10:48:25	ga_ls8c_ard_3-2-1_105073_2023-07-29_final
2023-07-29 10:50:01	ga_ls8c_ard_3-2-1_105077_2023-07-29_final
2023-08-01 11:22:32	ga_ls8c_ard_3-2-1_110081_2023-08-01_final
2023-08-02 10:24:32	ga_ls8c_ard_3-2-1_101075_2023-08-02_final
2023-08-05 10:56:38	ga_ls8c_ard_3-2-1_106078_2023-08-05_final
2023-08-06 09:59:01	ga_ls8c_ard_3-2-1_097073_2023-08-06_final
2023-08-06 10:01:49	ga_ls8c_ard_3-2-1_097080_2023-08-06_final
2023-08-07 10:41:29	ga_ls8c_ard_3-2-1_104071_2023-08-07_final
2023-08-10 11:17:10	ga_ls8c_ard_3-2-1_109083_2023-08-10_final
2023-08-21 10:54:22	ga_ls8c_ard_3-2-1_106072_2023-08-21_final
2023-08-28 11:04:33	ga_ls8c_ard_3-2-1_107082_2023-08-28_final
2023-08-29 11:46:37	ga_ls8c_ard_3-2-1_114079_2023-08-29_final
2023-09-02 09:41:49	ga_ls8c_ard_3-2-1_094076_2023-09-02_final
2023-09-07 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-09-07_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