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 10:48:11	ga_ls8c_ard_3-2-1_105071_2023-02-03_final
2023-03-19 09:35:33	ga_ls8c_ard_3-2-1_093076_2023-03-19_final
2023-05-08 09:23:51	ga_ls8c_ard_3-2-1_091079_2023-05-07_final
2023-05-09 11:45:35	ga_ls8c_ard_3-2-1_114078_2023-05-09_final
2023-05-10 10:47:33	ga_ls8c_ard_3-2-1_105072_2023-05-10_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-05-22 11:11:49	ga_ls8c_ard_3-2-1_109071_2023-05-22_final
2023-05-25 10:04:39	ga_ls8c_ard_3-2-1_098073_2023-05-25_final
2023-05-25 11:45:08	ga_ls8c_ard_3-2-1_114077_2023-05-25_final
2023-05-29 09:40:20	ga_ls8c_ard_3-2-1_094074_2023-05-29_final
2023-05-31 09:31:10	ga_ls8c_ard_3-2-1_092082_2023-05-31_final
2023-05-31 11:09:15	ga_ls8c_ard_3-2-1_108080_2023-05-31_final
2023-06-03 09:57:41	ga_ls8c_ard_3-2-1_097071_2023-06-03_final
2023-06-04 10:40:34	ga_ls8c_ard_3-2-1_104070_2023-06-04_final
2023-06-04 10:42:34	ga_ls8c_ard_3-2-1_104075_2023-06-04_final
2023-06-08 11:57:35	ga_ls8c_ard_3-2-1_116077_2023-06-08_final
2023-06-09 09:25:05	ga_ls8c_ard_3-2-1_091082_2023-06-08_final
2023-06-12 09:52:01	ga_ls8c_ard_3-2-1_096072_2023-06-12_final
2023-06-19 09:59:02	ga_ls8c_ard_3-2-1_097074_2023-06-19_final
2023-06-21 09:47:04	ga_ls8c_ard_3-2-1_095075_2023-06-21_final
2023-06-21 09:50:16	ga_ls8c_ard_3-2-1_095083_2023-06-21_final
2023-06-23 09:33:31	ga_ls8c_ard_3-2-1_093072_2023-06-23_final
2023-06-23 09:34:43	ga_ls8c_ard_3-2-1_093075_2023-06-23_final
2023-06-23 11:14:24	ga_ls8c_ard_3-2-1_109077_2023-06-23_final
2023-06-23 11:16:23	ga_ls8c_ard_3-2-1_109082_2023-06-23_final
2023-06-25 09:23:11	ga_ls8c_ard_3-2-1_091077_2023-06-24_final
2023-06-25 09:25:11	ga_ls8c_ard_3-2-1_091082_2023-06-24_final
2023-06-27 10:46:33	ga_ls8c_ard_3-2-1_105069_2023-06-27_final
2023-06-30 11:23:29	ga_ls8c_ard_3-2-1_110084_2023-06-30_final
2023-07-06 10:40:53	ga_ls8c_ard_3-2-1_104070_2023-07-06_final
2023-07-08 10:30:32	ga_ls8c_ard_3-2-1_102075_2023-07-08_final
2023-07-10 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-07-10_final
2023-07-10 10:19:47	ga_ls8c_ard_3-2-1_100079_2023-07-10_final
2023-07-11 09:25:46	ga_ls8c_ard_3-2-1_091083_2023-07-10_final
2023-07-13 10:48:18	ga_ls8c_ard_3-2-1_105073_2023-07-13_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-16 09:43:07	ga_ls8c_ard_3-2-1_094080_2023-07-16_final
2023-07-19 10:11:13	ga_ls8c_ard_3-2-1_099073_2023-07-19_final
2023-07-23 09:46:56	ga_ls8c_ard_3-2-1_095074_2023-07-23_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-08-02 10:22:56	ga_ls8c_ard_3-2-1_101071_2023-08-02_final
2023-08-02 10:24:08	ga_ls8c_ard_3-2-1_101074_2023-08-02_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-12 09:24:21	ga_ls8c_ard_3-2-1_091079_2023-08-11_final
2023-08-13 11:46:07	ga_ls8c_ard_3-2-1_114078_2023-08-13_final
2023-08-14 10:48:30	ga_ls8c_ard_3-2-1_105073_2023-08-14_final
2023-08-14 10:50:30	ga_ls8c_ard_3-2-1_105078_2023-08-14_final
2023-08-20 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-08-20_final
2023-08-22 09:59:09	ga_ls8c_ard_3-2-1_097073_2023-08-22_final
2023-08-22 11:41:13	ga_ls8c_ard_3-2-1_113081_2023-08-22_final
2023-08-24 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-08-24_final
2023-08-29 11:44:38	ga_ls8c_ard_3-2-1_114074_2023-08-29_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-09-01 10:37:50	ga_ls8c_ard_3-2-1_103077_2023-09-01_final
2023-09-07 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-09-07_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-14 11:45:04	ga_ls8c_ard_3-2-1_114075_2023-09-14_final
2023-09-15 10:48:16	ga_ls8c_ard_3-2-1_105072_2023-09-15_final
2023-09-16 11:31:56	ga_ls8c_ard_3-2-1_112073_2023-09-16_final
2023-09-17 10:34:19	ga_ls8c_ard_3-2-1_103068_2023-09-17_final
2023-09-20 11:05:37	ga_ls8c_ard_3-2-1_108069_2023-09-20_final
2023-09-23 09:58:26	ga_ls8c_ard_3-2-1_097071_2023-09-23_final
2023-09-23 09:58:50	ga_ls8c_ard_3-2-1_097072_2023-09-23_final
2023-09-23 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-09-23_final
2023-09-24 10:41:19	ga_ls8c_ard_3-2-1_104070_2023-09-24_final
2023-09-26 10:29:46	ga_ls8c_ard_3-2-1_102072_2023-09-26_final
2023-09-27 09:39:21	ga_ls8c_ard_3-2-1_093085_2023-09-27_final
2023-09-27 11:13:02	ga_ls8c_ard_3-2-1_109072_2023-09-27_final
2023-09-28 10:22:13	ga_ls8c_ard_3-2-1_100084_2023-09-28_final
2023-10-01 10:47:32	ga_ls8c_ard_3-2-1_105070_2023-10-01_final
2023-10-01 10:47:56	ga_ls8c_ard_3-2-1_105071_2023-10-01_final
2023-10-02 11:35:11	ga_ls8c_ard_3-2-1_112081_2023-10-02_final
2023-10-07 10:15:38	ga_ls8c_ard_3-2-1_099083_2023-10-07_final
2023-10-09 09:59:43	ga_ls8c_ard_3-2-1_097074_2023-10-09_final
2023-10-09 11:40:59	ga_ls8c_ard_3-2-1_113080_2023-10-09_final
2023-10-10 10:41:23	ga_ls8c_ard_3-2-1_104070_2023-10-10_final
2023-10-13 11:17:05	ga_ls8c_ard_3-2-1_109082_2023-10-13_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-10-16 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-10-16_final
2023-10-19 10:34:47	ga_ls8c_ard_3-2-1_103069_2023-10-19_final
2023-10-21 10:26:02	ga_ls8c_ard_3-2-1_101078_2023-10-21_final
2023-10-22 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-10-22_final
2023-10-22 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-10-22_final
2023-10-24 09:19:17	ga_ls8c_ard_3-2-1_090081_2023-10-23_final
2023-10-27 11:29:29	ga_ls8c_ard_3-2-1_111082_2023-10-27_final
2023-11-01 10:06:45	ga_ls8c_ard_3-2-1_098076_2023-11-01_final
2023-11-02 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-02_final
2023-11-04 10:38:03	ga_ls8c_ard_3-2-1_103077_2023-11-04_final
2023-11-05 09:45:36	ga_ls8c_ard_3-2-1_094085_2023-11-05_final
2023-11-07 11:07:43	ga_ls8c_ard_3-2-1_108074_2023-11-07_final
2023-11-07 11:08:31	ga_ls8c_ard_3-2-1_108076_2023-11-07_final
2023-11-08 11:53:21	ga_ls8c_ard_3-2-1_115080_2023-11-08_final
2023-11-09 09:20:25	ga_ls8c_ard_3-2-1_090084_2023-11-08_final
2023-11-11 10:44:33	ga_ls8c_ard_3-2-1_104078_2023-11-11_final
2023-11-11 10:45:21	ga_ls8c_ard_3-2-1_104080_2023-11-11_final
2023-11-14 09:35:49	ga_ls8c_ard_3-2-1_093076_2023-11-14_final
2023-11-14 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-11-14_final
2023-11-15 10:18:18	ga_ls8c_ard_3-2-1_100074_2023-11-15_final
2023-11-17 10:05:33	ga_ls8c_ard_3-2-1_098073_2023-11-17_final
2023-11-19 09:57:12	ga_ls8c_ard_3-2-1_096083_2023-11-19_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