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
2023-02-03 09:11:42	ga_ls8c_ard_3-2-1_089077_2023-02-02_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-12 11:45:07	ga_ls8c_ard_3-2-1_114076_2023-07-12_final
2023-07-13 10:48:18	ga_ls8c_ard_3-2-1_105073_2023-07-13_final
2023-07-18 09:32:21	ga_ls8c_ard_3-2-1_092084_2023-07-18_final
2023-07-18 11:10:26	ga_ls8c_ard_3-2-1_108082_2023-07-18_final
2023-07-21 10:00:04	ga_ls8c_ard_3-2-1_097076_2023-07-21_final
2023-07-23 11:26:37	ga_ls8c_ard_3-2-1_111076_2023-07-23_final
2023-07-26 10:17:29	ga_ls8c_ard_3-2-1_100073_2023-07-26_final
2023-07-31 10:37:16	ga_ls8c_ard_3-2-1_103076_2023-07-31_final
2023-08-01 11:20:33	ga_ls8c_ard_3-2-1_110076_2023-08-01_final
2023-08-01 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-08-01_final
2023-08-05 09:17:45	ga_ls8c_ard_3-2-1_090078_2023-08-04_final
2023-08-08 09:51:03	ga_ls8c_ard_3-2-1_095084_2023-08-08_final
2023-08-09 10:30:19	ga_ls8c_ard_3-2-1_102074_2023-08-09_final
2023-08-09 10:30:43	ga_ls8c_ard_3-2-1_102075_2023-08-09_final
2023-08-10 09:37:29	ga_ls8c_ard_3-2-1_093081_2023-08-10_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-10 11:12:47	ga_ls8c_ard_3-2-1_109072_2023-08-10_final
2023-08-12 09:23:33	ga_ls8c_ard_3-2-1_091077_2023-08-11_final
2023-08-12 09:24:21	ga_ls8c_ard_3-2-1_091079_2023-08-11_final
2023-08-14 10:46:07	ga_ls8c_ard_3-2-1_105067_2023-08-14_final
2023-08-16 10:38:58	ga_ls8c_ard_3-2-1_103080_2023-08-16_final
2023-08-17 09:43:45	ga_ls8c_ard_3-2-1_094081_2023-08-17_final
2023-08-17 11:20:39	ga_ls8c_ard_3-2-1_110076_2023-08-17_final
2023-08-18 10:24:14	ga_ls8c_ard_3-2-1_101074_2023-08-18_final
2023-08-19 09:31:01	ga_ls8c_ard_3-2-1_092080_2023-08-19_final
2023-08-19 09:31:49	ga_ls8c_ard_3-2-1_092082_2023-08-19_final
2023-08-20 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-08-20_final
2023-08-20 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-08-20_final
2023-08-22 09:58:21	ga_ls8c_ard_3-2-1_097071_2023-08-22_final
2023-08-23 10:42:25	ga_ls8c_ard_3-2-1_104073_2023-08-23_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-26 11:12:08	ga_ls8c_ard_3-2-1_109070_2023-08-26_final
2023-08-26 11:16:55	ga_ls8c_ard_3-2-1_109082_2023-08-26_final
2023-08-27 10:20:06	ga_ls8c_ard_3-2-1_100079_2023-08-27_final
2023-08-28 11:03:46	ga_ls8c_ard_3-2-1_107080_2023-08-28_final
2023-09-03 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-09-03_final
2023-09-07 10:01:07	ga_ls8c_ard_3-2-1_097078_2023-09-07_final
2023-09-08 10:43:12	ga_ls8c_ard_3-2-1_104075_2023-09-08_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-11 09:37:39	ga_ls8c_ard_3-2-1_093081_2023-09-11_final
2023-09-11 11:12:33	ga_ls8c_ard_3-2-1_109071_2023-09-11_final
2023-09-13 11:04:12	ga_ls8c_ard_3-2-1_107081_2023-09-13_final
2023-09-15 10:52:39	ga_ls8c_ard_3-2-1_105083_2023-09-15_final
2023-09-17 10:37:54	ga_ls8c_ard_3-2-1_103077_2023-09-17_final
2023-09-18 11:23:10	ga_ls8c_ard_3-2-1_110082_2023-09-18_final
2023-09-19 10:23:57	ga_ls8c_ard_3-2-1_101073_2023-09-19_final
2023-09-19 10:24:21	ga_ls8c_ard_3-2-1_101074_2023-09-19_final
2023-09-20 09:32:19	ga_ls8c_ard_3-2-1_092083_2023-09-20_final
2023-09-21 11:52:04	ga_ls8c_ard_3-2-1_115077_2023-09-21_final
2023-09-22 09:18:22	ga_ls8c_ard_3-2-1_090079_2023-09-21_final
2023-09-22 09:19:34	ga_ls8c_ard_3-2-1_090082_2023-09-21_final
2023-09-23 10:04:01	ga_ls8c_ard_3-2-1_097085_2023-09-23_final
2023-09-25 11:26:35	ga_ls8c_ard_3-2-1_111075_2023-09-25_final
2023-09-25 11:30:10	ga_ls8c_ard_3-2-1_111084_2023-09-25_final
2023-09-27 11:17:50	ga_ls8c_ard_3-2-1_109084_2023-09-27_final
2023-09-29 09:27:23	ga_ls8c_ard_3-2-1_091086_2023-09-28_final
2023-09-30 10:06:16	ga_ls8c_ard_3-2-1_098075_2023-09-30_final
2023-09-30 11:45:33	ga_ls8c_ard_3-2-1_114076_2023-09-30_final
2023-09-30 11:45:57	ga_ls8c_ard_3-2-1_114077_2023-09-30_final
2023-10-01 10:48:20	ga_ls8c_ard_3-2-1_105072_2023-10-01_final
2023-10-01 10:50:20	ga_ls8c_ard_3-2-1_105077_2023-10-01_final
2023-10-01 10:52:43	ga_ls8c_ard_3-2-1_105083_2023-10-01_final
2023-10-02 09:55:54	ga_ls8c_ard_3-2-1_096080_2023-10-02_final
2023-10-02 11:34:47	ga_ls8c_ard_3-2-1_112080_2023-10-02_final
2023-10-03 10:38:22	ga_ls8c_ard_3-2-1_103078_2023-10-03_final
2023-10-03 10:39:10	ga_ls8c_ard_3-2-1_103080_2023-10-03_final
2023-10-06 09:31:10	ga_ls8c_ard_3-2-1_092080_2023-10-06_final
2023-10-07 10:12:51	ga_ls8c_ard_3-2-1_099076_2023-10-07_final
2023-10-08 09:18:50	ga_ls8c_ard_3-2-1_090080_2023-10-07_final
2023-10-08 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-10-07_final
2023-10-09 11:39:00	ga_ls8c_ard_3-2-1_113075_2023-10-09_final
2023-10-11 11:25:03	ga_ls8c_ard_3-2-1_111071_2023-10-11_final
2023-10-11 11:27:51	ga_ls8c_ard_3-2-1_111078_2023-10-11_final
2023-10-13 11:16:41	ga_ls8c_ard_3-2-1_109081_2023-10-13_final
2023-10-16 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-10-16_final
2023-10-17 10:48:22	ga_ls8c_ard_3-2-1_105072_2023-10-17_final
2023-10-18 09:52:44	ga_ls8c_ard_3-2-1_096072_2023-10-18_final
2023-10-22 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-10-22_final
2023-10-24 09:19:17	ga_ls8c_ard_3-2-1_090081_2023-10-23_final
2023-10-24 09:20:28	ga_ls8c_ard_3-2-1_090084_2023-10-23_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-27 11:29:29	ga_ls8c_ard_3-2-1_111082_2023-10-27_final
2023-10-28 10:31:04	ga_ls8c_ard_3-2-1_102075_2023-10-28_final
2023-11-01 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-01_final
2023-11-01 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-01_final
2023-11-01 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-11-01_final
2023-11-03 09:57:59	ga_ls8c_ard_3-2-1_096085_2023-11-03_final
2023-11-03 11:32:52	ga_ls8c_ard_3-2-1_112075_2023-11-03_final
2023-11-04 10:39:14	ga_ls8c_ard_3-2-1_103080_2023-11-04_final
2023-11-04 10:40:02	ga_ls8c_ard_3-2-1_103082_2023-11-04_final
2023-11-07 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-11-07_final
2023-11-07 09:35:13	ga_ls8c_ard_3-2-1_092090_2023-11-07_final
2023-11-09 10:56:31	ga_ls8c_ard_3-2-1_106077_2023-11-09_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-11 10:44:09	ga_ls8c_ard_3-2-1_104077_2023-11-11_final
2023-11-11 10:45:21	ga_ls8c_ard_3-2-1_104080_2023-11-11_final
2023-11-15 11:58:46	ga_ls8c_ard_3-2-1_116078_2023-11-15_final
2023-11-17 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-17_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