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
2023-07-21 11:41:20	ga_ls8c_ard_3-2-1_113082_2023-07-21_final
2023-07-31 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-07-31_final
2023-07-31 10:39:40	ga_ls8c_ard_3-2-1_103082_2023-07-31_final
2023-08-02 10:22:56	ga_ls8c_ard_3-2-1_101071_2023-08-02_final
2023-08-02 10:24:56	ga_ls8c_ard_3-2-1_101076_2023-08-02_final
2023-08-03 09:29:19	ga_ls8c_ard_3-2-1_092076_2023-08-02_final
2023-08-04 10:11:23	ga_ls8c_ard_3-2-1_099073_2023-08-04_final
2023-08-04 10:12:35	ga_ls8c_ard_3-2-1_099076_2023-08-04_final
2023-08-05 09:17:45	ga_ls8c_ard_3-2-1_090078_2023-08-04_final
2023-08-05 10:57:02	ga_ls8c_ard_3-2-1_106079_2023-08-05_final
2023-08-08 09:50:39	ga_ls8c_ard_3-2-1_095083_2023-08-08_final
2023-08-10 09:37:29	ga_ls8c_ard_3-2-1_093081_2023-08-10_final
2023-08-10 11:16:46	ga_ls8c_ard_3-2-1_109082_2023-08-10_final
2023-08-10 11:17:10	ga_ls8c_ard_3-2-1_109083_2023-08-10_final
2023-08-12 09:25:09	ga_ls8c_ard_3-2-1_091081_2023-08-11_final
2023-08-13 10:07:37	ga_ls8c_ard_3-2-1_098079_2023-08-13_final
2023-08-14 10:50:06	ga_ls8c_ard_3-2-1_105077_2023-08-14_final
2023-08-14 10:50:30	ga_ls8c_ard_3-2-1_105078_2023-08-14_final
2023-08-14 10:51:18	ga_ls8c_ard_3-2-1_105080_2023-08-14_final
2023-08-15 09:52:06	ga_ls8c_ard_3-2-1_096071_2023-08-15_final
2023-08-16 10:34:58	ga_ls8c_ard_3-2-1_103070_2023-08-16_final
2023-08-16 10:36:34	ga_ls8c_ard_3-2-1_103074_2023-08-16_final
2023-08-16 10:39:46	ga_ls8c_ard_3-2-1_103082_2023-08-16_final
2023-08-19 09:31:01	ga_ls8c_ard_3-2-1_092080_2023-08-19_final
2023-08-20 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-08-20_final
2023-08-22 10:01:08	ga_ls8c_ard_3-2-1_097078_2023-08-22_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-26 11:16:31	ga_ls8c_ard_3-2-1_109081_2023-08-26_final
2023-08-27 10:20:06	ga_ls8c_ard_3-2-1_100079_2023-08-27_final
2023-08-28 09:24:53	ga_ls8c_ard_3-2-1_091080_2023-08-27_final
2023-08-28 11:03:46	ga_ls8c_ard_3-2-1_107080_2023-08-28_final
2023-08-28 11:04:33	ga_ls8c_ard_3-2-1_107082_2023-08-28_final
2023-08-29 11:45:26	ga_ls8c_ard_3-2-1_114076_2023-08-29_final
2023-08-30 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-08-29_final
2023-08-30 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-08-29_final
2023-09-01 10:36:38	ga_ls8c_ard_3-2-1_103074_2023-09-01_final
2023-09-03 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-09-03_final
2023-09-03 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-09-03_final
2023-09-04 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-09-03_final
2023-09-04 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-09-04_final
2023-09-06 09:20:15	ga_ls8c_ard_3-2-1_090084_2023-09-05_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-12 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-09-12_final
2023-09-14 11:45:52	ga_ls8c_ard_3-2-1_114077_2023-09-14_final
2023-09-15 10:51:03	ga_ls8c_ard_3-2-1_105079_2023-09-15_final
2023-09-16 11:32:44	ga_ls8c_ard_3-2-1_112075_2023-09-16_final
2023-09-18 09:45:05	ga_ls8c_ard_3-2-1_094084_2023-09-18_final
2023-09-18 11:22:46	ga_ls8c_ard_3-2-1_110081_2023-09-18_final
2023-09-18 11:23:10	ga_ls8c_ard_3-2-1_110082_2023-09-18_final
2023-09-19 10:23:09	ga_ls8c_ard_3-2-1_101071_2023-09-19_final
2023-09-20 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-09-20_final
2023-09-21 11:52:04	ga_ls8c_ard_3-2-1_115077_2023-09-21_final
2023-09-22 09:17:58	ga_ls8c_ard_3-2-1_090078_2023-09-21_final
2023-09-23 10:00:50	ga_ls8c_ard_3-2-1_097077_2023-09-23_final
2023-09-24 10:41:19	ga_ls8c_ard_3-2-1_104070_2023-09-24_final
2023-09-26 10:30:34	ga_ls8c_ard_3-2-1_102074_2023-09-26_final
2023-09-29 09:28:35	ga_ls8c_ard_3-2-1_091089_2023-09-28_final
2023-09-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2023-09-30_final
2023-09-30 11:45:09	ga_ls8c_ard_3-2-1_114075_2023-09-30_final
2023-10-01 09:13:50	ga_ls8c_ard_3-2-1_089083_2023-09-30_final
2023-10-02 09:57:06	ga_ls8c_ard_3-2-1_096083_2023-10-02_final
2023-10-03 10:37:34	ga_ls8c_ard_3-2-1_103076_2023-10-03_final
2023-10-05 10:23:36	ga_ls8c_ard_3-2-1_101072_2023-10-05_final
2023-10-05 10:25:12	ga_ls8c_ard_3-2-1_101076_2023-10-05_final
2023-10-11 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-10-11_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-13 11:16:41	ga_ls8c_ard_3-2-1_109081_2023-10-13_final
2023-10-15 09:25:26	ga_ls8c_ard_3-2-1_091081_2023-10-14_final
2023-10-15 11:03:55	ga_ls8c_ard_3-2-1_107080_2023-10-15_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
2023-10-19 10:35:11	ga_ls8c_ard_3-2-1_103070_2023-10-19_final
2023-10-20 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-10-20_final
2023-10-20 09:45:57	ga_ls8c_ard_3-2-1_094086_2023-10-20_final
2023-10-20 11:23:14	ga_ls8c_ard_3-2-1_110082_2023-10-20_final
2023-10-22 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-10-22_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-27 09:50:36	ga_ls8c_ard_3-2-1_095082_2023-10-27_final
2023-10-30 10:17:55	ga_ls8c_ard_3-2-1_100073_2023-10-30_final
2023-11-01 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-11-01_final
2023-11-01 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-11-01_final
2023-11-01 11:45:15	ga_ls8c_ard_3-2-1_114075_2023-11-01_final
2023-11-01 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-01_final
2023-11-02 09:16:43	ga_ls8c_ard_3-2-1_089090_2023-11-01_final
2023-11-03 11:35:40	ga_ls8c_ard_3-2-1_112082_2023-11-03_final
2023-11-05 09:42:01	ga_ls8c_ard_3-2-1_094076_2023-11-05_final
2023-11-07 11:08:31	ga_ls8c_ard_3-2-1_108076_2023-11-07_final
2023-11-08 11:52:09	ga_ls8c_ard_3-2-1_115077_2023-11-08_final
2023-11-10 10:01:17	ga_ls8c_ard_3-2-1_097078_2023-11-10_final
2023-11-10 11:41:22	ga_ls8c_ard_3-2-1_113081_2023-11-10_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-11 10:43:45	ga_ls8c_ard_3-2-1_104076_2023-11-11_final
2023-11-12 11:27:02	ga_ls8c_ard_3-2-1_111076_2023-11-12_final
2023-11-14 11:16:42	ga_ls8c_ard_3-2-1_109081_2023-11-14_final
2023-11-14 11:17:30	ga_ls8c_ard_3-2-1_109083_2023-11-14_final
2023-11-15 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-11-15_final
2023-11-16 11:00:46	ga_ls8c_ard_3-2-1_107072_2023-11-16_final
2023-11-17 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-17_final
2023-11-17 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-11-17_final
2023-11-18 10:47:38	ga_ls8c_ard_3-2-1_105070_2023-11-18_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