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
2022-01-14 10:06:22	ga_ls8c_ard_3-2-1_098075_2022-01-14_final
2022-05-29 10:11:28	ga_ls8c_ard_3-2-1_099073_2022-05-29_final
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-13 09:34:48	ga_ls8c_ard_3-2-1_092089_2022-06-13_final
2022-06-29 11:10:35	ga_ls8c_ard_3-2-1_108081_2022-06-29_final
2022-07-06 11:12:22	ga_ls8c_ard_3-2-1_109070_2022-07-06_final
2022-07-08 09:25:07	ga_ls8c_ard_3-2-1_091080_2022-07-07_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-18 09:59:25	ga_ls8c_ard_3-2-1_097073_2022-07-18_final
2022-07-22 09:35:57	ga_ls8c_ard_3-2-1_093076_2022-07-22_final
2022-07-22 11:15:14	ga_ls8c_ard_3-2-1_109077_2022-07-22_final
2022-07-24 09:25:37	ga_ls8c_ard_3-2-1_091081_2022-07-23_final
2022-07-24 11:01:18	ga_ls8c_ard_3-2-1_107073_2022-07-24_final
2022-07-31 11:10:21	ga_ls8c_ard_3-2-1_108080_2022-07-31_final
2022-08-02 10:54:49	ga_ls8c_ard_3-2-1_106072_2022-08-02_final
2022-08-10 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-08-10_final
2022-08-11 09:11:49	ga_ls8c_ard_3-2-1_089077_2022-08-10_final
2022-08-14 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-08-14_final
2022-08-17 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-08-17_final
2022-08-18 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-08-18_final
2022-08-28 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-08-28_final
2022-09-10 09:25:28	ga_ls8c_ard_3-2-1_091080_2022-09-09_final
2022-09-12 10:48:01	ga_ls8c_ard_3-2-1_105070_2022-09-12_final
2022-09-15 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-09-15_final
2022-10-01 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-10-01_final
2022-10-07 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-07_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-26 11:13:09	ga_ls8c_ard_3-2-1_109071_2022-10-26_final
2022-11-14 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-14_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-11-27 11:17:29	ga_ls8c_ard_3-2-1_109082_2022-11-27_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-21 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-12-21_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-02-04 11:36:14	ga_ls8c_ard_3-2-1_112083_2023-02-04_final
2023-02-08 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-02-08_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-15 09:40:18	ga_ls8c_ard_3-2-1_093087_2023-02-15_final
2023-02-16 10:18:45	ga_ls8c_ard_3-2-1_100075_2023-02-16_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-03-03 11:15:22	ga_ls8c_ard_3-2-1_109078_2023-03-03_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-14 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-03-13_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-24 09:53:13	ga_ls8c_ard_3-2-1_096074_2023-03-24_final
2023-04-08 09:10:09	ga_ls8c_ard_3-2-1_089075_2023-04-07_final
2023-04-15 09:18:39	ga_ls8c_ard_3-2-1_090081_2023-04-14_final
2023-04-27 09:44:07	ga_ls8c_ard_3-2-1_094083_2023-04-27_final
2023-05-01 09:18:34	ga_ls8c_ard_3-2-1_090081_2023-04-30_final
2023-05-01 09:20:34	ga_ls8c_ard_3-2-1_090086_2023-04-30_final
2023-05-04 11:27:07	ga_ls8c_ard_3-2-1_111078_2023-05-04_final
2023-05-07 10:20:41	ga_ls8c_ard_3-2-1_100082_2023-05-07_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-18 10:00:01	ga_ls8c_ard_3-2-1_097077_2023-05-18_final
2023-05-18 11:40:06	ga_ls8c_ard_3-2-1_113080_2023-05-18_final
2023-05-20 09:45:17	ga_ls8c_ard_3-2-1_095071_2023-05-20_final
2023-05-31 09:28:46	ga_ls8c_ard_3-2-1_092076_2023-05-30_final
2023-06-03 11:40:58	ga_ls8c_ard_3-2-1_113082_2023-06-03_final
2023-06-09 11:00:22	ga_ls8c_ard_3-2-1_107073_2023-06-09_final
2023-06-10 10:02:22	ga_ls8c_ard_3-2-1_098067_2023-06-10_final
2023-06-14 11:22:09	ga_ls8c_ard_3-2-1_110081_2023-06-14_final
2023-06-25 11:02:04	ga_ls8c_ard_3-2-1_107077_2023-06-25_final
2023-06-30 11:22:41	ga_ls8c_ard_3-2-1_110082_2023-06-30_final
2023-07-05 09:58:49	ga_ls8c_ard_3-2-1_097073_2023-07-05_final
2023-07-05 11:40:06	ga_ls8c_ard_3-2-1_113079_2023-07-05_final
2023-07-13 09:11:01	ga_ls8c_ard_3-2-1_089077_2023-07-12_final
2023-07-23 09:48:56	ga_ls8c_ard_3-2-1_095079_2023-07-23_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-07-28 10:05:33	ga_ls8c_ard_3-2-1_098074_2023-07-28_final
2023-08-06 09:59:01	ga_ls8c_ard_3-2-1_097073_2023-08-06_final
2023-08-06 11:41:06	ga_ls8c_ard_3-2-1_113081_2023-08-06_final
2023-08-10 11:16:22	ga_ls8c_ard_3-2-1_109081_2023-08-10_final
2023-08-23 10:43:13	ga_ls8c_ard_3-2-1_104075_2023-08-23_final
2023-09-14 10:06:11	ga_ls8c_ard_3-2-1_098075_2023-09-14_final
2023-09-16 11:31:56	ga_ls8c_ard_3-2-1_112073_2023-09-16_final
2023-09-16 11:35:07	ga_ls8c_ard_3-2-1_112081_2023-09-16_final
2023-09-23 09:59:38	ga_ls8c_ard_3-2-1_097074_2023-09-23_final
2023-09-27 09:33:45	ga_ls8c_ard_3-2-1_093071_2023-09-27_final
2023-09-27 11:11:50	ga_ls8c_ard_3-2-1_109069_2023-09-27_final
2023-09-30 10:06:16	ga_ls8c_ard_3-2-1_098075_2023-09-30_final
2023-10-22 11:07:42	ga_ls8c_ard_3-2-1_108074_2023-10-22_final
2023-11-01 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-01_final
2023-11-01 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-01_final
2023-11-10 10:00:53	ga_ls8c_ard_3-2-1_097077_2023-11-10_final
2023-11-10 11:38:58	ga_ls8c_ard_3-2-1_113075_2023-11-10_final
2023-11-11 10:43:45	ga_ls8c_ard_3-2-1_104076_2023-11-11_final
2023-11-14 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_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