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
2023-02-02 10:08:55	ga_ls8c_ard_3-2-1_098081_2023-02-02_final
2023-02-02 11:45:48	ga_ls8c_ard_3-2-1_114076_2023-02-02_final
2023-03-19 11:15:14	ga_ls8c_ard_3-2-1_109078_2023-03-19_final
2023-03-20 10:18:24	ga_ls8c_ard_3-2-1_100075_2023-03-20_final
2023-07-09 09:34:55	ga_ls8c_ard_3-2-1_093075_2023-07-09_final
2023-07-12 10:08:14	ga_ls8c_ard_3-2-1_098081_2023-07-12_final
2023-07-12 11:46:19	ga_ls8c_ard_3-2-1_114079_2023-07-12_final
2023-07-14 09:52:17	ga_ls8c_ard_3-2-1_096072_2023-07-14_final
2023-07-14 09:53:05	ga_ls8c_ard_3-2-1_096074_2023-07-14_final
2023-07-15 10:35:57	ga_ls8c_ard_3-2-1_103073_2023-07-15_final
2023-07-15 10:37:57	ga_ls8c_ard_3-2-1_103078_2023-07-15_final
2023-07-17 10:25:35	ga_ls8c_ard_3-2-1_101078_2023-07-17_final
2023-07-18 11:08:03	ga_ls8c_ard_3-2-1_108076_2023-07-18_final
2023-07-20 09:18:47	ga_ls8c_ard_3-2-1_090081_2023-07-19_final
2023-07-23 09:48:56	ga_ls8c_ard_3-2-1_095079_2023-07-23_final
2023-07-27 11:00:45	ga_ls8c_ard_3-2-1_107073_2023-07-27_final
2023-07-29 10:48:25	ga_ls8c_ard_3-2-1_105073_2023-07-29_final
2023-07-29 10:52:25	ga_ls8c_ard_3-2-1_105083_2023-07-29_final
2023-07-31 10:39:40	ga_ls8c_ard_3-2-1_103082_2023-07-31_final
2023-08-02 10:22:32	ga_ls8c_ard_3-2-1_101070_2023-08-02_final
2023-08-02 10:23:44	ga_ls8c_ard_3-2-1_101073_2023-08-02_final
2023-08-03 09:31:42	ga_ls8c_ard_3-2-1_092082_2023-08-03_final
2023-08-05 10:57:02	ga_ls8c_ard_3-2-1_106079_2023-08-05_final
2023-08-06 10:02:13	ga_ls8c_ard_3-2-1_097081_2023-08-06_final
2023-08-09 10:30:19	ga_ls8c_ard_3-2-1_102074_2023-08-09_final
2023-08-10 11:16:22	ga_ls8c_ard_3-2-1_109081_2023-08-10_final
2023-08-11 10:20:21	ga_ls8c_ard_3-2-1_100080_2023-08-11_final
2023-08-11 10:20:45	ga_ls8c_ard_3-2-1_100081_2023-08-11_final
2023-08-12 09:24:21	ga_ls8c_ard_3-2-1_091079_2023-08-11_final
2023-08-12 11:00:50	ga_ls8c_ard_3-2-1_107073_2023-08-12_final
2023-08-15 09:55:41	ga_ls8c_ard_3-2-1_096080_2023-08-15_final
2023-08-16 10:36:34	ga_ls8c_ard_3-2-1_103074_2023-08-16_final
2023-08-19 11:09:30	ga_ls8c_ard_3-2-1_108079_2023-08-19_final
2023-08-21 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-08-20_final
2023-08-21 10:54:22	ga_ls8c_ard_3-2-1_106072_2023-08-21_final
2023-08-22 10:02:20	ga_ls8c_ard_3-2-1_097081_2023-08-22_final
2023-08-24 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-08-24_final
2023-08-26 09:38:26	ga_ls8c_ard_3-2-1_093083_2023-08-26_final
2023-08-26 11:12:56	ga_ls8c_ard_3-2-1_109072_2023-08-26_final
2023-08-26 11:14:55	ga_ls8c_ard_3-2-1_109077_2023-08-26_final
2023-08-27 10:18:30	ga_ls8c_ard_3-2-1_100075_2023-08-27_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_final
2023-09-04 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-09-04_final
2023-09-05 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-09-05_final
2023-09-06 09:18:15	ga_ls8c_ard_3-2-1_090079_2023-09-05_final
2023-09-06 10:58:20	ga_ls8c_ard_3-2-1_106082_2023-09-06_final
2023-09-09 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-09-09_final
2023-09-11 09:37:15	ga_ls8c_ard_3-2-1_093080_2023-09-11_final
2023-09-11 11:14:56	ga_ls8c_ard_3-2-1_109077_2023-09-11_final
2023-09-12 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-09-12_final
2023-09-13 11:01:00	ga_ls8c_ard_3-2-1_107073_2023-09-13_final
2023-09-17 10:36:43	ga_ls8c_ard_3-2-1_103074_2023-09-17_final
2023-09-17 10:39:06	ga_ls8c_ard_3-2-1_103080_2023-09-17_final
2023-09-18 09:41:53	ga_ls8c_ard_3-2-1_094076_2023-09-18_final
2023-09-20 11:10:01	ga_ls8c_ard_3-2-1_108080_2023-09-20_final
2023-09-22 10:57:39	ga_ls8c_ard_3-2-1_106080_2023-09-22_final
2023-09-27 11:16:38	ga_ls8c_ard_3-2-1_109081_2023-09-27_final
2023-09-28 10:21:25	ga_ls8c_ard_3-2-1_100082_2023-09-28_final
2023-09-30 10:06:16	ga_ls8c_ard_3-2-1_098075_2023-09-30_final
2023-10-01 10:52:43	ga_ls8c_ard_3-2-1_105083_2023-10-01_final
2023-10-02 09:57:06	ga_ls8c_ard_3-2-1_096083_2023-10-02_final
2023-10-05 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-10-05_final
2023-10-06 11:10:03	ga_ls8c_ard_3-2-1_108080_2023-10-06_final
2023-10-06 11:10:27	ga_ls8c_ard_3-2-1_108081_2023-10-06_final
2023-10-07 11:53:20	ga_ls8c_ard_3-2-1_115080_2023-10-07_final
2023-10-08 10:56:55	ga_ls8c_ard_3-2-1_106078_2023-10-08_final
2023-10-08 10:58:31	ga_ls8c_ard_3-2-1_106082_2023-10-08_final
2023-10-09 10:02:30	ga_ls8c_ard_3-2-1_097081_2023-10-09_final
2023-10-09 11:39:00	ga_ls8c_ard_3-2-1_113075_2023-10-09_final
2023-10-10 10:45:22	ga_ls8c_ard_3-2-1_104080_2023-10-10_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-16 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-10-16_final
2023-10-18 09:56:19	ga_ls8c_ard_3-2-1_096081_2023-10-18_final
2023-10-20 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-10-20_final
2023-10-21 10:24:26	ga_ls8c_ard_3-2-1_101074_2023-10-21_final
2023-10-22 09:31:13	ga_ls8c_ard_3-2-1_092080_2023-10-22_final
2023-10-22 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-10-22_final
2023-10-24 09:18:29	ga_ls8c_ard_3-2-1_090079_2023-10-23_final
2023-10-24 10:57:22	ga_ls8c_ard_3-2-1_106079_2023-10-24_final
2023-10-25 10:00:33	ga_ls8c_ard_3-2-1_097076_2023-10-25_final
2023-10-26 10:45:25	ga_ls8c_ard_3-2-1_104080_2023-10-26_final
2023-10-27 09:51:00	ga_ls8c_ard_3-2-1_095083_2023-10-27_final
2023-10-29 11:15:08	ga_ls8c_ard_3-2-1_109077_2023-10-29_final
2023-10-31 09:25:30	ga_ls8c_ard_3-2-1_091081_2023-10-30_final
2023-11-01 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-01_final
2023-11-03 11:34:52	ga_ls8c_ard_3-2-1_112080_2023-11-03_final
2023-11-03 11:35:16	ga_ls8c_ard_3-2-1_112081_2023-11-03_final
2023-11-04 10:35:39	ga_ls8c_ard_3-2-1_103071_2023-11-04_final
2023-11-05 09:45:12	ga_ls8c_ard_3-2-1_094084_2023-11-05_final
2023-11-05 11:22:30	ga_ls8c_ard_3-2-1_110080_2023-11-05_final
2023-11-09 10:56:31	ga_ls8c_ard_3-2-1_106077_2023-11-09_final
2023-11-12 09:50:57	ga_ls8c_ard_3-2-1_095083_2023-11-12_final
2023-11-14 09:36:37	ga_ls8c_ard_3-2-1_093078_2023-11-14_final
2023-11-14 09:38:37	ga_ls8c_ard_3-2-1_093083_2023-11-14_final
2023-11-14 11:15:06	ga_ls8c_ard_3-2-1_109077_2023-11-14_final
2023-11-16 09:28:16	ga_ls8c_ard_3-2-1_091088_2023-11-15_final
2023-11-18 10:50:49	ga_ls8c_ard_3-2-1_105078_2023-11-18_final
2023-11-21 09:43:39	ga_ls8c_ard_3-2-1_094080_2023-11-21_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