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
2023-07-25 09:37:48	ga_ls8c_ard_3-2-1_093082_2023-07-25_final
2023-07-25 09:38:12	ga_ls8c_ard_3-2-1_093083_2023-07-25_final
2023-08-01 09:41:40	ga_ls8c_ard_3-2-1_094076_2023-08-01_final
2023-08-03 09:30:06	ga_ls8c_ard_3-2-1_092078_2023-08-03_final
2023-08-03 09:34:06	ga_ls8c_ard_3-2-1_092088_2023-08-03_final
2023-08-06 10:01:25	ga_ls8c_ard_3-2-1_097079_2023-08-06_final
2023-08-08 09:50:39	ga_ls8c_ard_3-2-1_095083_2023-08-08_final
2023-08-10 09:35:30	ga_ls8c_ard_3-2-1_093076_2023-08-10_final
2023-08-10 09:39:53	ga_ls8c_ard_3-2-1_093087_2023-08-10_final
2023-08-12 09:25:32	ga_ls8c_ard_3-2-1_091082_2023-08-11_final
2023-08-22 09:59:09	ga_ls8c_ard_3-2-1_097073_2023-08-22_final
2023-08-22 10:00:21	ga_ls8c_ard_3-2-1_097076_2023-08-22_final
2023-08-25 10:32:27	ga_ls8c_ard_3-2-1_102079_2023-08-25_final
2023-08-26 09:39:14	ga_ls8c_ard_3-2-1_093085_2023-08-26_final
2023-08-28 09:23:41	ga_ls8c_ard_3-2-1_091077_2023-08-27_final
2023-08-28 11:01:46	ga_ls8c_ard_3-2-1_107075_2023-08-28_final
2023-08-29 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-08-29_final
2023-08-31 09:52:35	ga_ls8c_ard_3-2-1_096072_2023-08-31_final
2023-08-31 09:56:10	ga_ls8c_ard_3-2-1_096081_2023-08-31_final
2023-08-31 11:35:03	ga_ls8c_ard_3-2-1_112081_2023-08-31_final
2023-09-01 10:35:26	ga_ls8c_ard_3-2-1_103071_2023-09-01_final
2023-09-01 10:36:14	ga_ls8c_ard_3-2-1_103073_2023-09-01_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-03 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-09-03_final
2023-09-03 10:27:28	ga_ls8c_ard_3-2-1_101082_2023-09-03_final
2023-09-04 09:30:14	ga_ls8c_ard_3-2-1_092078_2023-09-04_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-06 09:18:39	ga_ls8c_ard_3-2-1_090080_2023-09-05_final
2023-09-06 10:58:20	ga_ls8c_ard_3-2-1_106082_2023-09-06_final
2023-09-07 11:38:49	ga_ls8c_ard_3-2-1_113075_2023-09-07_final
2023-09-08 10:44:00	ga_ls8c_ard_3-2-1_104077_2023-09-08_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 09:36:27	ga_ls8c_ard_3-2-1_093078_2023-09-11_final
2023-09-11 09:39:15	ga_ls8c_ard_3-2-1_093085_2023-09-11_final
2023-09-11 11:17:20	ga_ls8c_ard_3-2-1_109083_2023-09-11_final
2023-09-13 09:24:07	ga_ls8c_ard_3-2-1_091078_2023-09-12_final
2023-09-13 09:25:43	ga_ls8c_ard_3-2-1_091082_2023-09-12_final
2023-09-14 10:06:59	ga_ls8c_ard_3-2-1_098077_2023-09-14_final
2023-09-16 09:56:14	ga_ls8c_ard_3-2-1_096081_2023-09-16_final
2023-09-17 10:35:07	ga_ls8c_ard_3-2-1_103070_2023-09-17_final
2023-09-17 10:35:31	ga_ls8c_ard_3-2-1_103071_2023-09-17_final
2023-09-21 10:09:36	ga_ls8c_ard_3-2-1_099068_2023-09-21_final
2023-09-23 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-09-23_final
2023-09-24 10:44:06	ga_ls8c_ard_3-2-1_104077_2023-09-24_final
2023-09-25 11:27:47	ga_ls8c_ard_3-2-1_111078_2023-09-25_final
2023-09-27 09:38:33	ga_ls8c_ard_3-2-1_093083_2023-09-27_final
2023-09-28 11:58:18	ga_ls8c_ard_3-2-1_116077_2023-09-28_final
2023-09-29 11:01:05	ga_ls8c_ard_3-2-1_107073_2023-09-29_final
2023-09-30 10:08:16	ga_ls8c_ard_3-2-1_098080_2023-09-30_final
2023-10-03 10:36:22	ga_ls8c_ard_3-2-1_103073_2023-10-03_final
2023-10-03 10:37:10	ga_ls8c_ard_3-2-1_103075_2023-10-03_final
2023-10-04 09:43:08	ga_ls8c_ard_3-2-1_094079_2023-10-04_final
2023-10-06 09:29:34	ga_ls8c_ard_3-2-1_092076_2023-10-05_final
2023-10-09 10:03:18	ga_ls8c_ard_3-2-1_097083_2023-10-09_final
2023-10-10 10:40:59	ga_ls8c_ard_3-2-1_104069_2023-10-10_final
2023-10-10 10:44:11	ga_ls8c_ard_3-2-1_104077_2023-10-10_final
2023-10-11 09:48:10	ga_ls8c_ard_3-2-1_095076_2023-10-11_final
2023-10-12 10:28:14	ga_ls8c_ard_3-2-1_102068_2023-10-12_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-13 09:36:36	ga_ls8c_ard_3-2-1_093078_2023-10-13_final
2023-10-13 09:38:36	ga_ls8c_ard_3-2-1_093083_2023-10-13_final
2023-10-13 11:17:29	ga_ls8c_ard_3-2-1_109083_2023-10-13_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-17 10:47:10	ga_ls8c_ard_3-2-1_105069_2023-10-17_final
2023-10-17 10:48:22	ga_ls8c_ard_3-2-1_105072_2023-10-17_final
2023-10-17 10:51:09	ga_ls8c_ard_3-2-1_105079_2023-10-17_final
2023-10-19 10:37:11	ga_ls8c_ard_3-2-1_103075_2023-10-19_final
2023-10-20 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-10-20_final
2023-10-22 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-10-22_final
2023-10-23 11:50:59	ga_ls8c_ard_3-2-1_115074_2023-10-23_final
2023-10-24 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-10-23_final
2023-10-26 10:44:13	ga_ls8c_ard_3-2-1_104077_2023-10-26_final
2023-10-27 09:48:12	ga_ls8c_ard_3-2-1_095076_2023-10-27_final
2023-10-27 09:48:36	ga_ls8c_ard_3-2-1_095077_2023-10-27_final
2023-10-29 09:36:15	ga_ls8c_ard_3-2-1_093077_2023-10-29_final
2023-10-31 09:24:42	ga_ls8c_ard_3-2-1_091079_2023-10-30_final
2023-10-31 11:02:23	ga_ls8c_ard_3-2-1_107076_2023-10-31_final
2023-11-01 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-01_final
2023-11-02 09:12:20	ga_ls8c_ard_3-2-1_089079_2023-11-01_final
2023-11-03 11:36:04	ga_ls8c_ard_3-2-1_112083_2023-11-03_final
2023-11-04 10:37:15	ga_ls8c_ard_3-2-1_103075_2023-11-04_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-04 10:38:03	ga_ls8c_ard_3-2-1_103077_2023-11-04_final
2023-11-05 09:45:12	ga_ls8c_ard_3-2-1_094084_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-07 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-11-07_final
2023-11-09 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-11-09_final
2023-11-10 10:00:05	ga_ls8c_ard_3-2-1_097075_2023-11-10_final
2023-11-10 10:02:04	ga_ls8c_ard_3-2-1_097080_2023-11-10_final
2023-11-10 10:02:52	ga_ls8c_ard_3-2-1_097082_2023-11-10_final
2023-11-11 10:44:57	ga_ls8c_ard_3-2-1_104079_2023-11-11_final
2023-11-12 09:48:33	ga_ls8c_ard_3-2-1_095077_2023-11-12_final
2023-11-12 09:50:09	ga_ls8c_ard_3-2-1_095081_2023-11-12_final
2023-11-13 10:29:02	ga_ls8c_ard_3-2-1_102070_2023-11-13_final
2023-11-14 09:37:25	ga_ls8c_ard_3-2-1_093080_2023-11-14_final
2023-11-15 10:17:54	ga_ls8c_ard_3-2-1_100073_2023-11-15_final
2023-11-15 10:20:41	ga_ls8c_ard_3-2-1_100080_2023-11-15_final
2023-11-19 09:54:00	ga_ls8c_ard_3-2-1_096075_2023-11-19_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-20 10:38:04	ga_ls8c_ard_3-2-1_103077_2023-11-20_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