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
2023-08-03 09:32:06	ga_ls8c_ard_3-2-1_092083_2023-08-03_final
2023-08-04 10:11:47	ga_ls8c_ard_3-2-1_099074_2023-08-04_final
2023-08-04 11:52:39	ga_ls8c_ard_3-2-1_115079_2023-08-04_final
2023-08-05 10:57:50	ga_ls8c_ard_3-2-1_106081_2023-08-05_final
2023-08-09 10:30:43	ga_ls8c_ard_3-2-1_102075_2023-08-09_final
2023-08-10 09:38:17	ga_ls8c_ard_3-2-1_093083_2023-08-10_final
2023-08-10 11:12:47	ga_ls8c_ard_3-2-1_109072_2023-08-10_final
2023-08-12 09:23:33	ga_ls8c_ard_3-2-1_091077_2023-08-11_final
2023-08-14 09:12:25	ga_ls8c_ard_3-2-1_089080_2023-08-13_final
2023-08-15 09:56:29	ga_ls8c_ard_3-2-1_096082_2023-08-15_final
2023-08-20 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-08-20_final
2023-08-21 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-08-20_final
2023-08-21 10:56:21	ga_ls8c_ard_3-2-1_106077_2023-08-21_final
2023-08-21 10:56:45	ga_ls8c_ard_3-2-1_106078_2023-08-21_final
2023-08-24 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-08-24_final
2023-08-25 10:30:51	ga_ls8c_ard_3-2-1_102075_2023-08-25_final
2023-08-27 10:20:30	ga_ls8c_ard_3-2-1_100080_2023-08-27_final
2023-08-28 11:03:22	ga_ls8c_ard_3-2-1_107079_2023-08-28_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-31 09:52:59	ga_ls8c_ard_3-2-1_096073_2023-08-31_final
2023-08-31 09:53:23	ga_ls8c_ard_3-2-1_096074_2023-08-31_final
2023-09-01 10:35:26	ga_ls8c_ard_3-2-1_103071_2023-09-01_final
2023-09-02 09:41:49	ga_ls8c_ard_3-2-1_094076_2023-09-02_final
2023-09-02 11:21:06	ga_ls8c_ard_3-2-1_110077_2023-09-02_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-04 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-09-04_final
2023-09-05 10:12:41	ga_ls8c_ard_3-2-1_099076_2023-09-05_final
2023-09-06 10:56:44	ga_ls8c_ard_3-2-1_106078_2023-09-06_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-10 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-09-10_final
2023-09-11 09:37:39	ga_ls8c_ard_3-2-1_093081_2023-09-11_final
2023-09-12 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-09-12_final
2023-09-12 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-09-12_final
2023-09-13 11:02:36	ga_ls8c_ard_3-2-1_107077_2023-09-13_final
2023-09-13 11:04:36	ga_ls8c_ard_3-2-1_107082_2023-09-13_final
2023-09-16 09:53:27	ga_ls8c_ard_3-2-1_096074_2023-09-16_final
2023-09-17 10:35:31	ga_ls8c_ard_3-2-1_103071_2023-09-17_final
2023-09-18 11:22:46	ga_ls8c_ard_3-2-1_110081_2023-09-18_final
2023-09-20 11:10:01	ga_ls8c_ard_3-2-1_108080_2023-09-20_final
2023-09-21 10:11:36	ga_ls8c_ard_3-2-1_099073_2023-09-21_final
2023-09-22 09:19:10	ga_ls8c_ard_3-2-1_090081_2023-09-21_final
2023-09-22 10:56:27	ga_ls8c_ard_3-2-1_106077_2023-09-22_final
2023-09-22 10:56:51	ga_ls8c_ard_3-2-1_106078_2023-09-22_final
2023-09-22 10:57:15	ga_ls8c_ard_3-2-1_106079_2023-09-22_final
2023-09-23 10:00:26	ga_ls8c_ard_3-2-1_097076_2023-09-23_final
2023-09-23 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-09-23_final
2023-09-25 11:26:35	ga_ls8c_ard_3-2-1_111075_2023-09-25_final
2023-09-29 11:01:05	ga_ls8c_ard_3-2-1_107073_2023-09-29_final
2023-09-29 11:03:29	ga_ls8c_ard_3-2-1_107079_2023-09-29_final
2023-10-02 09:56:18	ga_ls8c_ard_3-2-1_096081_2023-10-02_final
2023-10-04 09:41:32	ga_ls8c_ard_3-2-1_094075_2023-10-04_final
2023-10-04 09:41:56	ga_ls8c_ard_3-2-1_094076_2023-10-04_final
2023-10-04 09:43:08	ga_ls8c_ard_3-2-1_094079_2023-10-04_final
2023-10-05 10:25:12	ga_ls8c_ard_3-2-1_101076_2023-10-05_final
2023-10-06 11:10:03	ga_ls8c_ard_3-2-1_108080_2023-10-06_final
2023-10-06 11:10:27	ga_ls8c_ard_3-2-1_108081_2023-10-06_final
2023-10-07 10:11:39	ga_ls8c_ard_3-2-1_099073_2023-10-07_final
2023-10-08 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-10-07_final
2023-10-08 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-10-07_final
2023-10-08 09:20:02	ga_ls8c_ard_3-2-1_090083_2023-10-07_final
2023-10-08 10:56:55	ga_ls8c_ard_3-2-1_106078_2023-10-08_final
2023-10-09 10:02:06	ga_ls8c_ard_3-2-1_097080_2023-10-09_final
2023-10-09 10:03:18	ga_ls8c_ard_3-2-1_097083_2023-10-09_final
2023-10-11 09:50:09	ga_ls8c_ard_3-2-1_095081_2023-10-11_final
2023-10-13 09:35:48	ga_ls8c_ard_3-2-1_093076_2023-10-13_final
2023-10-13 09:39:00	ga_ls8c_ard_3-2-1_093084_2023-10-13_final
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-15 11:01:08	ga_ls8c_ard_3-2-1_107073_2023-10-15_final
2023-10-15 11:03:31	ga_ls8c_ard_3-2-1_107079_2023-10-15_final
2023-10-19 10:37:35	ga_ls8c_ard_3-2-1_103076_2023-10-19_final
2023-10-19 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-10-19_final
2023-10-22 09:31:37	ga_ls8c_ard_3-2-1_092081_2023-10-22_final
2023-10-22 11:08:30	ga_ls8c_ard_3-2-1_108076_2023-10-22_final
2023-10-23 10:12:54	ga_ls8c_ard_3-2-1_099076_2023-10-23_final
2023-10-23 11:52:11	ga_ls8c_ard_3-2-1_115077_2023-10-23_final
2023-10-25 10:00:57	ga_ls8c_ard_3-2-1_097077_2023-10-25_final
2023-10-27 09:49:48	ga_ls8c_ard_3-2-1_095080_2023-10-27_final
2023-10-27 11:28:41	ga_ls8c_ard_3-2-1_111080_2023-10-27_final
2023-10-28 10:29:53	ga_ls8c_ard_3-2-1_102072_2023-10-28_final
2023-10-29 09:35:51	ga_ls8c_ard_3-2-1_093076_2023-10-29_final
2023-10-30 10:18:43	ga_ls8c_ard_3-2-1_100075_2023-10-30_final
2023-10-30 10:20:43	ga_ls8c_ard_3-2-1_100080_2023-10-30_final
2023-10-31 11:03:35	ga_ls8c_ard_3-2-1_107079_2023-10-31_final
2023-11-01 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-01_final
2023-11-01 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-01_final
2023-11-02 09:13:56	ga_ls8c_ard_3-2-1_089083_2023-11-01_final
2023-11-02 10:51:13	ga_ls8c_ard_3-2-1_105079_2023-11-02_final
2023-11-03 09:57:11	ga_ls8c_ard_3-2-1_096083_2023-11-03_final
2023-11-05 09:42:25	ga_ls8c_ard_3-2-1_094077_2023-11-05_final
2023-11-05 11:22:54	ga_ls8c_ard_3-2-1_110081_2023-11-05_final
2023-11-08 10:12:04	ga_ls8c_ard_3-2-1_099074_2023-11-08_final
2023-11-10 11:38:58	ga_ls8c_ard_3-2-1_113075_2023-11-10_final
2023-11-11 10:44:09	ga_ls8c_ard_3-2-1_104077_2023-11-11_final
2023-11-12 09:49:45	ga_ls8c_ard_3-2-1_095080_2023-11-12_final
2023-11-13 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-11-13_final
2023-11-15 10:20:41	ga_ls8c_ard_3-2-1_100080_2023-11-15_final
2023-11-16 11:01:10	ga_ls8c_ard_3-2-1_107073_2023-11-16_final
2023-11-17 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-17_final
2023-11-20 10:38:28	ga_ls8c_ard_3-2-1_103078_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