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
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-14 09:37:10	ga_ls8c_ard_3-2-1_093079_2023-01-14_final
2023-01-23 11:11:53	ga_ls8c_ard_3-2-1_108084_2023-01-23_final
2023-01-24 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-01-24_final
2023-01-29 10:31:15	ga_ls8c_ard_3-2-1_102075_2023-01-29_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-02-06 09:43:23	ga_ls8c_ard_3-2-1_094079_2023-02-06_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-06 09:44:11	ga_ls8c_ard_3-2-1_094081_2023-02-06_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-10 10:58:43	ga_ls8c_ard_3-2-1_106082_2023-02-10_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-15 09:37:06	ga_ls8c_ard_3-2-1_093079_2023-02-15_final
2023-02-15 09:37:54	ga_ls8c_ard_3-2-1_093081_2023-02-15_final
2023-02-15 11:15:11	ga_ls8c_ard_3-2-1_109077_2023-02-15_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-15 11:16:47	ga_ls8c_ard_3-2-1_109081_2023-02-15_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-20 11:35:14	ga_ls8c_ard_3-2-1_112081_2023-02-20_final
2023-02-21 10:36:48	ga_ls8c_ard_3-2-1_103074_2023-02-21_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-22 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-02-22_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-02-27 10:00:01	ga_ls8c_ard_3-2-1_097075_2023-02-27_final
2023-02-27 10:03:13	ga_ls8c_ard_3-2-1_097083_2023-02-27_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-04 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-03-04_final
2023-03-04 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-03-04_final
2023-03-04 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-03-04_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-09 10:37:01	ga_ls8c_ard_3-2-1_103075_2023-03-09_final
2023-03-09 10:37:25	ga_ls8c_ard_3-2-1_103076_2023-03-09_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-11 10:26:15	ga_ls8c_ard_3-2-1_101079_2023-03-11_final
2023-03-16 10:43:58	ga_ls8c_ard_3-2-1_104077_2023-03-16_final
2023-03-18 10:30:23	ga_ls8c_ard_3-2-1_102074_2023-03-18_final
2023-03-18 10:31:11	ga_ls8c_ard_3-2-1_102076_2023-03-18_final
2023-03-19 09:36:45	ga_ls8c_ard_3-2-1_093079_2023-03-19_final
2023-03-26 09:43:39	ga_ls8c_ard_3-2-1_094081_2023-03-26_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-31 11:39:02	ga_ls8c_ard_3-2-1_113076_2023-03-31_final
2023-04-01 10:40:36	ga_ls8c_ard_3-2-1_104069_2023-04-01_final
2023-04-02 11:27:26	ga_ls8c_ard_3-2-1_111078_2023-04-02_final
2023-04-05 10:18:12	ga_ls8c_ard_3-2-1_100075_2023-04-05_final
2023-04-06 11:03:50	ga_ls8c_ard_3-2-1_107081_2023-04-06_final
2023-04-08 10:47:26	ga_ls8c_ard_3-2-1_105071_2023-04-08_final
2023-04-11 09:40:59	ga_ls8c_ard_3-2-1_094075_2023-04-11_final
2023-04-11 11:21:52	ga_ls8c_ard_3-2-1_110080_2023-04-11_final
2023-04-13 09:29:25	ga_ls8c_ard_3-2-1_092077_2023-04-12_final
2023-04-13 09:30:37	ga_ls8c_ard_3-2-1_092080_2023-04-13_final
2023-04-13 11:10:18	ga_ls8c_ard_3-2-1_108082_2023-04-13_final
2023-04-14 10:11:29	ga_ls8c_ard_3-2-1_099074_2023-04-14_final
2023-04-16 11:39:11	ga_ls8c_ard_3-2-1_113077_2023-04-16_final
2023-04-16 11:39:59	ga_ls8c_ard_3-2-1_113079_2023-04-16_final
2023-04-17 10:42:45	ga_ls8c_ard_3-2-1_104075_2023-04-17_final
2023-04-18 09:50:19	ga_ls8c_ard_3-2-1_095083_2023-04-18_final
2023-04-20 09:37:08	ga_ls8c_ard_3-2-1_093081_2023-04-20_final
2023-04-24 10:47:19	ga_ls8c_ard_3-2-1_105071_2023-04-24_final
2023-04-25 11:33:23	ga_ls8c_ard_3-2-1_112078_2023-04-25_final
2023-04-26 10:34:57	ga_ls8c_ard_3-2-1_103071_2023-04-26_final
2023-04-27 09:43:43	ga_ls8c_ard_3-2-1_094082_2023-04-27_final
2023-04-27 09:44:07	ga_ls8c_ard_3-2-1_094083_2023-04-27_final
2023-04-29 11:09:50	ga_ls8c_ard_3-2-1_108081_2023-04-29_final
2023-04-29 11:10:14	ga_ls8c_ard_3-2-1_108082_2023-04-29_final
2023-04-30 10:11:24	ga_ls8c_ard_3-2-1_099074_2023-04-30_final
2023-05-01 09:18:10	ga_ls8c_ard_3-2-1_090080_2023-04-30_final
2023-05-01 10:56:39	ga_ls8c_ard_3-2-1_106079_2023-05-01_final
2023-05-03 10:40:41	ga_ls8c_ard_3-2-1_104070_2023-05-03_final
2023-05-04 11:26:19	ga_ls8c_ard_3-2-1_111076_2023-05-04_final
2023-05-05 10:31:05	ga_ls8c_ard_3-2-1_102077_2023-05-05_final
2023-05-07 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-05-07_final
2023-05-08 11:02:44	ga_ls8c_ard_3-2-1_107079_2023-05-08_final
2023-05-08 11:03:32	ga_ls8c_ard_3-2-1_107081_2023-05-08_final
2023-05-09 10:05:30	ga_ls8c_ard_3-2-1_098075_2023-05-09_final
2023-05-10 10:47:09	ga_ls8c_ard_3-2-1_105071_2023-05-10_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-11 09:55:29	ga_ls8c_ard_3-2-1_096081_2023-05-11_final
2023-05-11 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-11_final
2023-05-12 10:37:08	ga_ls8c_ard_3-2-1_103077_2023-05-12_final
2023-05-13 09:40:43	ga_ls8c_ard_3-2-1_094075_2023-05-13_final
2023-05-14 10:22:46	ga_ls8c_ard_3-2-1_101072_2023-05-14_final
2023-05-14 10:25:58	ga_ls8c_ard_3-2-1_101080_2023-05-14_final
2023-05-15 11:06:01	ga_ls8c_ard_3-2-1_108072_2023-05-15_final
2023-05-17 09:17:57	ga_ls8c_ard_3-2-1_090080_2023-05-16_final
2023-05-17 10:57:14	ga_ls8c_ard_3-2-1_106081_2023-05-17_final
2023-05-19 10:40:06	ga_ls8c_ard_3-2-1_104069_2023-05-19_final
2023-05-19 10:44:29	ga_ls8c_ard_3-2-1_104080_2023-05-19_final
2023-05-20 09:50:04	ga_ls8c_ard_3-2-1_095083_2023-05-20_final
2023-05-21 10:30:57	ga_ls8c_ard_3-2-1_102077_2023-05-21_final
2023-05-22 09:34:56	ga_ls8c_ard_3-2-1_093076_2023-05-22_final
2023-05-22 09:35:20	ga_ls8c_ard_3-2-1_093077_2023-05-22_final
2023-05-22 09:38:07	ga_ls8c_ard_3-2-1_093084_2023-05-22_final
2023-05-22 11:14:13	ga_ls8c_ard_3-2-1_109077_2023-05-22_final
2023-05-25 10:05:03	ga_ls8c_ard_3-2-1_098074_2023-05-25_final
2023-05-26 10:47:31	ga_ls8c_ard_3-2-1_105072_2023-05-26_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