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
2021-10-20 09:07:58	ga_ls8c_ard_3-2-0_088083_2021-10-19_final
2021-10-20 10:44:03	ga_ls8c_ard_3-2-0_104076_2021-10-20_final
2021-10-21 09:46:26	ga_ls8c_ard_3-2-0_095071_2021-10-21_final
2021-10-24 11:57:49	ga_ls8c_ard_3-2-0_116075_2021-10-24_final
2021-10-24 11:58:13	ga_ls8c_ard_3-2-0_116076_2021-10-24_final
2021-11-17 09:30:35	ga_ls8c_ard_3-2-0_092078_2021-11-17_final
2021-11-20 11:39:35	ga_ls8c_ard_3-2-0_113076_2021-11-20_final
2021-11-27 10:09:17	ga_ls8c_ard_3-2-0_098082_2021-11-27_final
2021-12-08 11:28:02	ga_ls8c_ard_3-2-1_111078_2021-12-08_final
2021-12-16 10:37:23	ga_ls8c_ard_3-2-1_103075_2021-12-16_final
2021-12-19 09:30:59	ga_ls8c_ard_3-2-1_092079_2021-12-19_final
2021-12-23 10:41:56	ga_ls8c_ard_3-2-1_104071_2021-12-23_final
2021-12-30 10:48:51	ga_ls8c_ard_3-2-1_105073_2021-12-30_final
2021-12-31 09:54:49	ga_ls8c_ard_3-2-1_096077_2021-12-31_final
2022-01-06 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-01-06_final
2022-01-16 09:55:36	ga_ls8c_ard_3-2-1_096079_2022-01-16_final
2022-01-25 11:27:26	ga_ls8c_ard_3-2-1_111077_2022-01-25_final
2022-01-29 11:03:30	ga_ls8c_ard_3-2-1_107079_2022-01-29_final
2022-02-08 10:00:29	ga_ls8c_ard_3-2-1_097076_2022-02-08_final
2022-02-09 10:41:44	ga_ls8c_ard_3-2-1_104071_2022-02-09_final
2022-02-10 11:29:47	ga_ls8c_ard_3-2-1_111083_2022-02-10_final
2022-02-11 10:29:46	ga_ls8c_ard_3-2-1_102072_2022-02-11_final
2022-02-14 09:28:09	ga_ls8c_ard_3-2-1_091088_2022-02-13_final
2022-02-19 09:43:51	ga_ls8c_ard_3-2-1_094081_2022-02-19_final
2022-02-22 10:11:57	ga_ls8c_ard_3-2-1_099074_2022-02-22_final
2022-02-26 11:27:18	ga_ls8c_ard_3-2-1_111077_2022-02-26_final
2022-03-20 10:48:05	ga_ls8c_ard_3-2-1_105072_2022-03-20_final
2022-03-25 11:09:21	ga_ls8c_ard_3-2-1_108079_2022-03-25_final
2022-03-27 10:54:34	ga_ls8c_ard_3-2-1_106073_2022-03-27_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-21 10:50:49	ga_ls8c_ard_3-2-1_105079_2022-04-21_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-13 10:11:50	ga_ls8c_ard_3-2-1_099074_2022-05-13_final
2022-05-14 09:18:37	ga_ls8c_ard_3-2-1_090080_2022-05-13_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-15 10:01:29	ga_ls8c_ard_3-2-1_097079_2022-05-15_final
2022-05-16 10:43:09	ga_ls8c_ard_3-2-1_104075_2022-05-16_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-22 10:08:29	ga_ls8c_ard_3-2-1_098081_2022-05-22_final
2022-05-26 11:21:26	ga_ls8c_ard_3-2-1_110078_2022-05-26_final
2022-05-30 10:57:56	ga_ls8c_ard_3-2-1_106081_2022-05-30_final
2022-05-31 10:02:20	ga_ls8c_ard_3-2-1_097081_2022-05-31_final
2022-06-15 09:18:52	ga_ls8c_ard_3-2-1_090080_2022-06-14_final
2022-06-20 11:16:20	ga_ls8c_ard_3-2-1_109080_2022-06-20_final
2022-06-25 11:34:30	ga_ls8c_ard_3-2-1_112079_2022-06-25_final
2022-06-27 09:44:51	ga_ls8c_ard_3-2-1_094083_2022-06-27_final
2022-06-28 10:23:43	ga_ls8c_ard_3-2-1_101072_2022-06-28_final
2022-07-06 09:35:05	ga_ls8c_ard_3-2-1_093074_2022-07-06_final
2022-07-06 11:15:34	ga_ls8c_ard_3-2-1_109078_2022-07-06_final
2022-07-07 11:58:26	ga_ls8c_ard_3-2-1_116077_2022-07-07_final
2022-07-11 11:34:30	ga_ls8c_ard_3-2-1_112079_2022-07-11_final
2022-07-14 10:24:30	ga_ls8c_ard_3-2-1_101074_2022-07-14_final
2022-07-17 10:57:25	ga_ls8c_ard_3-2-1_106079_2022-07-17_final
2022-07-20 11:26:46	ga_ls8c_ard_3-2-1_111075_2022-07-20_final
2022-07-21 10:29:58	ga_ls8c_ard_3-2-1_102072_2022-07-21_final
2022-07-27 11:34:38	ga_ls8c_ard_3-2-1_112079_2022-07-27_final
2022-08-02 09:20:19	ga_ls8c_ard_3-2-1_090083_2022-08-01_final
2022-08-04 10:42:05	ga_ls8c_ard_3-2-1_104071_2022-08-04_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-09 09:27:22	ga_ls8c_ard_3-2-1_091085_2022-08-08_final
2022-08-19 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-08-19_final
2022-08-28 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-08-28_final
2022-09-01 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-09-01_final
2022-09-19 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-09-18_final
2022-09-19 10:55:02	ga_ls8c_ard_3-2-1_106072_2022-09-19_final
2022-09-29 11:35:42	ga_ls8c_ard_3-2-1_112081_2022-09-29_final
2022-09-30 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-09-30_final
2022-10-24 09:49:48	ga_ls8c_ard_3-2-1_095079_2022-10-24_final
2022-10-24 11:27:53	ga_ls8c_ard_3-2-1_111077_2022-10-24_final
2022-10-26 09:36:16	ga_ls8c_ard_3-2-1_093076_2022-10-26_final
2022-10-27 10:21:07	ga_ls8c_ard_3-2-1_100080_2022-10-27_final
2022-11-04 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-11-04_final
2022-11-12 10:19:05	ga_ls8c_ard_3-2-1_100075_2022-11-12_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
2022-11-26 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-11-26_final
2022-11-30 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-30_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-06 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-12-06_final
2022-12-07 10:15:16	ga_ls8c_ard_3-2-1_099081_2022-12-07_final
2022-12-07 11:51:21	ga_ls8c_ard_3-2-1_115074_2022-12-07_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-16 11:47:06	ga_ls8c_ard_3-2-1_114079_2022-12-16_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-26 10:45:37	ga_ls8c_ard_3-2-1_104080_2022-12-26_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_final
2023-01-10 11:39:38	ga_ls8c_ard_3-2-1_113076_2023-01-10_final
2023-01-21 11:22:37	ga_ls8c_ard_3-2-1_110080_2023-01-21_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-23 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-01-23_final
2023-01-25 10:57:32	ga_ls8c_ard_3-2-1_106079_2023-01-25_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_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