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
2021-12-19 09:28:12	ga_ls8c_ard_3-2-1_092072_2021-12-18_final
2022-01-05 10:11:46	ga_ls8c_ard_3-2-1_099073_2022-01-05_final
2022-01-14 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-01-14_final
2022-01-14 11:46:27	ga_ls8c_ard_3-2-1_114078_2022-01-14_final
2022-01-17 10:36:27	ga_ls8c_ard_3-2-1_103073_2022-01-17_final
2022-01-22 09:22:28	ga_ls8c_ard_3-2-1_090089_2022-01-21_final
2022-01-30 10:06:17	ga_ls8c_ard_3-2-1_098075_2022-01-30_final
2022-01-30 11:47:33	ga_ls8c_ard_3-2-1_114081_2022-01-30_final
2022-02-05 09:32:47	ga_ls8c_ard_3-2-1_092084_2022-02-05_final
2022-02-05 11:05:41	ga_ls8c_ard_3-2-1_108069_2022-02-05_final
2022-02-05 11:06:29	ga_ls8c_ard_3-2-1_108071_2022-02-05_final
2022-02-16 09:16:34	ga_ls8c_ard_3-2-1_089090_2022-02-15_final
2022-02-22 10:11:09	ga_ls8c_ard_3-2-1_099072_2022-02-22_final
2022-02-22 10:11:33	ga_ls8c_ard_3-2-1_099073_2022-02-22_final
2022-02-26 09:47:14	ga_ls8c_ard_3-2-1_095074_2022-02-26_final
2022-03-04 09:12:55	ga_ls8c_ard_3-2-1_089081_2022-03-03_final
2022-03-28 11:40:12	ga_ls8c_ard_3-2-1_113079_2022-03-28_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-08 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-08_final
2022-04-14 10:42:16	ga_ls8c_ard_3-2-1_104073_2022-04-14_final
2022-04-15 09:52:14	ga_ls8c_ard_3-2-1_095087_2022-04-15_final
2022-04-29 10:01:19	ga_ls8c_ard_3-2-1_097079_2022-04-29_final
2022-04-29 10:03:18	ga_ls8c_ard_3-2-1_097084_2022-04-29_final
2022-05-03 09:34:15	ga_ls8c_ard_3-2-1_093073_2022-05-03_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-13 10:11:02	ga_ls8c_ard_3-2-1_099072_2022-05-13_final
2022-05-26 11:23:02	ga_ls8c_ard_3-2-1_110082_2022-05-26_final
2022-05-29 11:52:45	ga_ls8c_ard_3-2-1_115079_2022-05-29_final
2022-06-04 09:38:04	ga_ls8c_ard_3-2-1_093082_2022-06-04_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-06 11:01:50	ga_ls8c_ard_3-2-1_107075_2022-06-06_final
2022-06-08 09:12:12	ga_ls8c_ard_3-2-1_089079_2022-06-07_final
2022-06-10 10:39:57	ga_ls8c_ard_3-2-1_103082_2022-06-10_final
2022-06-15 10:56:09	ga_ls8c_ard_3-2-1_106076_2022-06-15_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_final
2022-06-30 11:51:51	ga_ls8c_ard_3-2-1_115076_2022-06-30_final
2022-06-30 11:52:39	ga_ls8c_ard_3-2-1_115078_2022-06-30_final
2022-07-02 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-02_final
2022-07-03 10:41:52	ga_ls8c_ard_3-2-1_104071_2022-07-03_final
2022-07-03 10:42:40	ga_ls8c_ard_3-2-1_104073_2022-07-03_final
2022-07-10 09:10:21	ga_ls8c_ard_3-2-1_089074_2022-07-09_final
2022-07-13 09:44:26	ga_ls8c_ard_3-2-1_094082_2022-07-13_final
2022-08-06 10:30:32	ga_ls8c_ard_3-2-1_102073_2022-08-06_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-15 10:26:00	ga_ls8c_ard_3-2-1_101077_2022-08-15_final
2022-08-18 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-08-18_final
2022-08-22 10:30:36	ga_ls8c_ard_3-2-1_102073_2022-08-22_final
2022-08-24 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-08-24_final
2022-08-26 11:47:33	ga_ls8c_ard_3-2-1_114080_2022-08-26_final
2022-09-05 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-09-05_final
2022-09-06 09:46:58	ga_ls8c_ard_3-2-1_095072_2022-09-06_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-11 10:10:20	ga_ls8c_ard_3-2-1_098084_2022-09-11_final
2022-09-11 11:47:14	ga_ls8c_ard_3-2-1_114079_2022-09-11_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-25 10:19:33	ga_ls8c_ard_3-2-1_100076_2022-09-25_final
2022-09-27 10:09:59	ga_ls8c_ard_3-2-1_098083_2022-09-27_final
2022-10-04 11:51:49	ga_ls8c_ard_3-2-1_115075_2022-10-04_final
2022-10-05 09:19:42	ga_ls8c_ard_3-2-1_090081_2022-10-04_final
2022-10-08 09:52:10	ga_ls8c_ard_3-2-1_095085_2022-10-08_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-26 09:34:40	ga_ls8c_ard_3-2-1_093072_2022-10-26_final
2022-10-28 11:01:12	ga_ls8c_ard_3-2-1_107072_2022-10-28_final
2022-10-28 11:02:00	ga_ls8c_ard_3-2-1_107074_2022-10-28_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-11-12 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-11-12_final
2022-11-19 10:26:00	ga_ls8c_ard_3-2-1_101077_2022-11-19_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-13 09:40:32	ga_ls8c_ard_3-2-1_093087_2022-12-13_final
2022-12-13 11:12:38	ga_ls8c_ard_3-2-1_109070_2022-12-13_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-16 10:07:01	ga_ls8c_ard_3-2-1_098076_2022-12-16_final
2022-12-16 11:45:54	ga_ls8c_ard_3-2-1_114076_2022-12-16_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-23 10:10:18	ga_ls8c_ard_3-2-1_099069_2022-12-23_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2022-12-30 10:21:43	ga_ls8c_ard_3-2-1_100082_2022-12-30_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2023-01-09 09:22:17	ga_ls8c_ard_3-2-1_090088_2023-01-08_final
2023-01-11 10:42:48	ga_ls8c_ard_3-2-1_104073_2023-01-11_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-01-30 09:35:13	ga_ls8c_ard_3-2-1_093074_2023-01-30_final
2023-02-08 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-02-08_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-22 10:03:13	ga_ls8c_ard_3-2-1_098068_2023-03-22_final
2023-03-22 10:07:12	ga_ls8c_ard_3-2-1_098078_2023-03-22_final
2023-03-28 09:28:53	ga_ls8c_ard_3-2-1_092075_2023-03-27_final
2023-03-29 10:10:32	ga_ls8c_ard_3-2-1_099071_2023-03-29_final
2023-03-29 11:52:13	ga_ls8c_ard_3-2-1_115078_2023-03-29_final
2023-03-30 09:18:06	ga_ls8c_ard_3-2-1_090079_2023-03-29_final
2023-04-04 11:16:38	ga_ls8c_ard_3-2-1_109082_2023-04-04_final
2023-04-17 10:39:58	ga_ls8c_ard_3-2-1_104068_2023-04-17_final
2023-05-04 09:46:38	ga_ls8c_ard_3-2-1_095074_2023-05-04_final
2023-05-04 11:24:44	ga_ls8c_ard_3-2-1_111072_2023-05-04_final
2023-05-08 09:22:15	ga_ls8c_ard_3-2-1_091075_2023-05-07_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