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
2015-03-01 10:47:59	ga_ls8c_ard_3-1-0_105072_2015-03-01_final
2019-03-10 09:25:18	ga_ls8c_ard_3-1-0_091082_2019-03-09_final
2019-04-14 09:56:03	ga_ls8c_ard_3-1-0_096082_2019-04-14_final
2019-06-16 10:48:02	ga_ls8c_ard_3-1-0_105072_2019-06-16_final
2019-06-16 10:50:26	ga_ls8c_ard_3-1-0_105078_2019-06-16_final
2019-06-17 09:52:25	ga_ls8c_ard_3-1-0_096072_2019-06-17_final
2019-06-17 09:56:01	ga_ls8c_ard_3-1-0_096081_2019-06-17_final
2019-06-21 11:06:36	ga_ls8c_ard_3-1-0_108072_2019-06-21_final
2019-07-03 09:52:30	ga_ls8c_ard_3-1-0_096072_2019-07-03_final
2019-07-03 09:56:05	ga_ls8c_ard_3-1-0_096081_2019-07-03_final
2019-07-07 11:10:40	ga_ls8c_ard_3-1-0_108082_2019-07-07_final
2019-07-18 10:52:33	ga_ls8c_ard_3-1-0_105083_2019-07-18_final
2019-07-19 09:52:08	ga_ls8c_ard_3-1-0_096071_2019-07-19_final
2019-07-19 09:56:08	ga_ls8c_ard_3-1-0_096081_2019-07-19_final
2019-07-23 11:06:44	ga_ls8c_ard_3-1-0_108072_2019-07-23_final
2019-08-08 11:05:39	ga_ls8c_ard_3-1-0_108069_2019-08-08_final
2019-08-13 09:50:55	ga_ls8c_ard_3-1-0_095083_2019-08-13_final
2019-08-29 09:47:23	ga_ls8c_ard_3-1-0_095074_2019-08-29_final
2019-09-04 10:47:37	ga_ls8c_ard_3-1-0_105070_2019-09-04_final
2019-09-04 10:50:24	ga_ls8c_ard_3-1-0_105077_2019-09-04_final
2019-09-09 11:06:59	ga_ls8c_ard_3-1-0_108072_2019-09-09_final
2019-09-09 11:10:10	ga_ls8c_ard_3-1-0_108080_2019-09-09_final
2019-09-21 09:56:29	ga_ls8c_ard_3-1-0_096081_2019-09-21_final
2019-09-25 11:05:53	ga_ls8c_ard_3-1-0_108069_2019-09-25_final
2019-09-25 11:11:04	ga_ls8c_ard_3-1-0_108082_2019-09-25_final
2019-10-20 09:24:28	ga_ls8c_ard_3-1-0_091078_2019-10-19_final
2019-10-20 09:26:04	ga_ls8c_ard_3-1-0_091082_2019-10-19_final
2019-10-22 10:51:48	ga_ls8c_ard_3-1-0_105080_2019-10-22_final
2019-10-23 09:53:23	ga_ls8c_ard_3-1-0_096073_2019-10-23_final
2019-10-27 11:05:57	ga_ls8c_ard_3-1-0_108069_2019-10-27_final
2019-11-01 09:51:35	ga_ls8c_ard_3-1-0_095084_2019-11-01_final
2019-11-07 10:51:46	ga_ls8c_ard_3-1-0_105080_2019-11-07_final
2019-11-17 09:49:56	ga_ls8c_ard_3-1-0_095080_2019-11-17_final
2019-11-17 09:51:32	ga_ls8c_ard_3-1-0_095084_2019-11-17_final
2019-11-28 11:05:52	ga_ls8c_ard_3-1-0_108069_2019-11-28_final
2019-12-03 09:49:55	ga_ls8c_ard_3-1-0_095080_2019-12-03_final
2019-12-26 09:55:38	ga_ls8c_ard_3-1-0_096079_2019-12-26_final
2020-01-08 09:27:28	ga_ls8c_ard_3-1-0_091086_2020-01-07_final
2020-01-15 11:09:19	ga_ls8c_ard_3-1-0_108078_2020-01-15_final
2020-01-20 11:27:50	ga_ls8c_ard_3-1-0_111078_2020-01-20_final
2020-01-26 10:51:31	ga_ls8c_ard_3-1-0_105080_2020-01-26_final
2020-02-05 09:49:15	ga_ls8c_ard_3-1-0_095079_2020-02-05_final
2020-02-12 09:53:49	ga_ls8c_ard_3-1-0_096075_2020-02-12_final
2020-02-12 09:55:25	ga_ls8c_ard_3-1-0_096079_2020-02-12_final
2020-03-15 09:55:14	ga_ls8c_ard_3-1-0_096079_2020-03-15_final
2020-04-04 11:08:01	ga_ls8c_ard_3-1-0_108076_2020-04-04_final
2020-04-13 09:23:41	ga_ls8c_ard_3-1-0_091078_2020-04-12_final
2020-04-15 10:50:36	ga_ls8c_ard_3-1-0_105079_2020-04-15_final
2020-04-16 09:54:58	ga_ls8c_ard_3-1-0_096079_2020-04-16_final
2020-04-20 11:09:54	ga_ls8c_ard_3-1-0_108081_2020-04-20_final
2020-04-25 09:49:07	ga_ls8c_ard_3-1-0_095080_2020-04-25_final
2020-05-01 10:49:40	ga_ls8c_ard_3-1-0_105077_2020-05-01_final
2022-03-31 10:31:24	ga_ls8c_ard_3-2-1_102077_2022-03-31_final
2022-04-01 09:36:10	ga_ls8c_ard_3-2-1_093078_2022-04-01_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-10 09:29:40	ga_ls8c_ard_3-2-1_092077_2022-04-09_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-12 09:19:19	ga_ls8c_ard_3-2-1_090082_2022-04-11_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-19 11:03:11	ga_ls8c_ard_3-2-1_107079_2022-04-19_final
2022-04-20 11:45:15	ga_ls8c_ard_3-2-1_114076_2022-04-20_final
2022-04-20 11:46:03	ga_ls8c_ard_3-2-1_114078_2022-04-20_final
2022-04-23 10:38:50	ga_ls8c_ard_3-2-1_103080_2022-04-23_final
2022-04-26 11:09:19	ga_ls8c_ard_3-2-1_108079_2022-04-26_final
2022-04-29 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:41:24	ga_ls8c_ard_3-2-1_104071_2022-04-30_final
2022-04-30 10:42:36	ga_ls8c_ard_3-2-1_104074_2022-04-30_final
2022-05-02 10:31:28	ga_ls8c_ard_3-2-1_102077_2022-05-02_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-05 11:04:00	ga_ls8c_ard_3-2-1_107081_2022-05-05_final
2022-05-06 10:06:23	ga_ls8c_ard_3-2-1_098076_2022-05-06_final
2022-05-06 11:45:16	ga_ls8c_ard_3-2-1_114076_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 10:47:16	ga_ls8c_ard_3-2-1_105070_2022-05-07_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-11 10:26:58	ga_ls8c_ard_3-2-1_101081_2022-05-11_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-16 10:45:33	ga_ls8c_ard_3-2-1_104081_2022-05-16_final
2022-05-19 09:36:23	ga_ls8c_ard_3-2-1_093078_2022-05-19_final
2022-05-19 11:12:04	ga_ls8c_ard_3-2-1_109070_2022-05-19_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-24 09:53:43	ga_ls8c_ard_3-2-1_096075_2022-05-24_final
2022-05-24 09:55:19	ga_ls8c_ard_3-2-1_096079_2022-05-24_final
2022-05-26 09:43:45	ga_ls8c_ard_3-2-1_094081_2022-05-26_final
2022-05-31 10:02:44	ga_ls8c_ard_3-2-1_097082_2022-05-31_final
2022-06-01 10:40:49	ga_ls8c_ard_3-2-1_104069_2022-06-01_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-02 11:28:53	ga_ls8c_ard_3-2-1_111081_2022-06-02_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-06-13 09:30:24	ga_ls8c_ard_3-2-1_092078_2022-06-13_final
2022-06-15 10:56:33	ga_ls8c_ard_3-2-1_106077_2022-06-15_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-21 10:21:07	ga_ls8c_ard_3-2-1_100081_2022-06-21_final
2022-06-22 11:01:11	ga_ls8c_ard_3-2-1_107073_2022-06-22_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