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
2023-08-09 10:33:07	ga_ls8c_ard_3-2-1_102081_2023-08-09_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-10 11:15:10	ga_ls8c_ard_3-2-1_109078_2023-08-10_final
2023-08-12 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-08-12_final
2023-08-13 10:04:02	ga_ls8c_ard_3-2-1_098070_2023-08-13_final
2023-08-13 11:44:31	ga_ls8c_ard_3-2-1_114074_2023-08-13_final
2023-08-13 11:45:43	ga_ls8c_ard_3-2-1_114077_2023-08-13_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-19 11:09:30	ga_ls8c_ard_3-2-1_108079_2023-08-19_final
2023-08-20 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-08-20_final
2023-08-20 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-08-20_final
2023-08-24 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-08-24_final
2023-08-24 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-08-24_final
2023-08-25 10:32:27	ga_ls8c_ard_3-2-1_102079_2023-08-25_final
2023-08-26 11:12:08	ga_ls8c_ard_3-2-1_109070_2023-08-26_final
2023-08-26 11:15:19	ga_ls8c_ard_3-2-1_109078_2023-08-26_final
2023-08-27 10:22:06	ga_ls8c_ard_3-2-1_100084_2023-08-27_final
2023-08-29 10:08:08	ga_ls8c_ard_3-2-1_098080_2023-08-29_final
2023-08-30 09:11:43	ga_ls8c_ard_3-2-1_089078_2023-08-29_final
2023-08-30 09:13:43	ga_ls8c_ard_3-2-1_089083_2023-08-29_final
2023-08-31 09:55:46	ga_ls8c_ard_3-2-1_096080_2023-08-31_final
2023-08-31 09:57:22	ga_ls8c_ard_3-2-1_096084_2023-08-31_final
2023-09-02 11:23:05	ga_ls8c_ard_3-2-1_110082_2023-09-02_final
2023-09-03 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-09-03_final
2023-09-04 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-09-04_final
2023-09-04 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-09-04_final
2023-09-07 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-09-07_final
2023-09-09 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-09-09_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 11:12:09	ga_ls8c_ard_3-2-1_109070_2023-09-11_final
2023-09-11 11:14:56	ga_ls8c_ard_3-2-1_109077_2023-09-11_final
2023-09-15 09:11:46	ga_ls8c_ard_3-2-1_089078_2023-09-14_final
2023-09-15 09:12:34	ga_ls8c_ard_3-2-1_089080_2023-09-14_final
2023-09-15 09:13:46	ga_ls8c_ard_3-2-1_089083_2023-09-14_final
2023-09-15 10:46:40	ga_ls8c_ard_3-2-1_105068_2023-09-15_final
2023-09-15 10:47:04	ga_ls8c_ard_3-2-1_105069_2023-09-15_final
2023-09-18 11:20:46	ga_ls8c_ard_3-2-1_110076_2023-09-18_final
2023-09-20 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-09-20_final
2023-09-20 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-09-20_final
2023-09-21 10:14:23	ga_ls8c_ard_3-2-1_099080_2023-09-21_final
2023-09-23 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-09-23_final
2023-09-25 09:50:05	ga_ls8c_ard_3-2-1_095081_2023-09-25_final
2023-09-26 10:31:22	ga_ls8c_ard_3-2-1_102076_2023-09-26_final
2023-09-27 09:35:21	ga_ls8c_ard_3-2-1_093075_2023-09-27_final
2023-09-27 09:37:21	ga_ls8c_ard_3-2-1_093080_2023-09-27_final
2023-09-28 11:58:18	ga_ls8c_ard_3-2-1_116077_2023-09-28_final
2023-09-29 09:24:36	ga_ls8c_ard_3-2-1_091079_2023-09-28_final
2023-09-30 11:46:21	ga_ls8c_ard_3-2-1_114078_2023-09-30_final
2023-10-01 09:12:38	ga_ls8c_ard_3-2-1_089080_2023-09-30_final
2023-10-01 09:13:50	ga_ls8c_ard_3-2-1_089083_2023-09-30_final
2023-10-01 10:47:56	ga_ls8c_ard_3-2-1_105071_2023-10-01_final
2023-10-04 09:39:57	ga_ls8c_ard_3-2-1_094071_2023-10-04_final
2023-10-04 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-10-04_final
2023-10-04 11:20:49	ga_ls8c_ard_3-2-1_110076_2023-10-04_final
2023-10-06 09:30:22	ga_ls8c_ard_3-2-1_092078_2023-10-06_final
2023-10-06 11:11:15	ga_ls8c_ard_3-2-1_108083_2023-10-06_final
2023-10-07 11:50:56	ga_ls8c_ard_3-2-1_115074_2023-10-07_final
2023-10-09 10:01:18	ga_ls8c_ard_3-2-1_097078_2023-10-09_final
2023-10-10 10:45:22	ga_ls8c_ard_3-2-1_104080_2023-10-10_final
2023-10-11 11:26:39	ga_ls8c_ard_3-2-1_111075_2023-10-11_final
2023-10-11 11:27:51	ga_ls8c_ard_3-2-1_111078_2023-10-11_final
2023-10-12 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-10-12_final
2023-10-15 09:25:02	ga_ls8c_ard_3-2-1_091080_2023-10-14_final
2023-10-19 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-10-19_final
2023-10-20 11:22:50	ga_ls8c_ard_3-2-1_110081_2023-10-20_final
2023-10-21 10:26:26	ga_ls8c_ard_3-2-1_101079_2023-10-21_final
2023-10-22 11:09:18	ga_ls8c_ard_3-2-1_108078_2023-10-22_final
2023-10-23 10:09:42	ga_ls8c_ard_3-2-1_099068_2023-10-23_final
2023-10-24 09:17:41	ga_ls8c_ard_3-2-1_090077_2023-10-23_final
2023-10-25 11:39:02	ga_ls8c_ard_3-2-1_113075_2023-10-25_final
2023-10-25 11:39:26	ga_ls8c_ard_3-2-1_113076_2023-10-25_final
2023-10-25 11:40:14	ga_ls8c_ard_3-2-1_113078_2023-10-25_final
2023-10-26 10:45:49	ga_ls8c_ard_3-2-1_104081_2023-10-26_final
2023-10-27 09:47:25	ga_ls8c_ard_3-2-1_095074_2023-10-27_final
2023-10-29 11:15:32	ga_ls8c_ard_3-2-1_109078_2023-10-29_final
2023-10-30 10:17:31	ga_ls8c_ard_3-2-1_100072_2023-10-30_final
2023-10-31 11:03:59	ga_ls8c_ard_3-2-1_107080_2023-10-31_final
2023-11-01 11:45:15	ga_ls8c_ard_3-2-1_114075_2023-11-01_final
2023-11-04 10:36:27	ga_ls8c_ard_3-2-1_103073_2023-11-04_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-05 11:18:54	ga_ls8c_ard_3-2-1_110071_2023-11-05_final
2023-11-07 09:34:49	ga_ls8c_ard_3-2-1_092089_2023-11-07_final
2023-11-07 11:08:55	ga_ls8c_ard_3-2-1_108077_2023-11-07_final
2023-11-07 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-11-07_final
2023-11-08 11:50:57	ga_ls8c_ard_3-2-1_115074_2023-11-08_final
2023-11-10 11:38:58	ga_ls8c_ard_3-2-1_113075_2023-11-10_final
2023-11-10 11:39:22	ga_ls8c_ard_3-2-1_113076_2023-11-10_final
2023-11-10 11:40:10	ga_ls8c_ard_3-2-1_113078_2023-11-10_final
2023-11-12 11:25:50	ga_ls8c_ard_3-2-1_111073_2023-11-12_final
2023-11-12 11:27:02	ga_ls8c_ard_3-2-1_111076_2023-11-12_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-15 10:21:53	ga_ls8c_ard_3-2-1_100083_2023-11-15_final
2023-11-16 11:03:34	ga_ls8c_ard_3-2-1_107079_2023-11-16_final
2023-11-19 09:55:12	ga_ls8c_ard_3-2-1_096078_2023-11-19_final
2023-11-19 09:58:00	ga_ls8c_ard_3-2-1_096085_2023-11-19_final
2023-11-19 11:34:05	ga_ls8c_ard_3-2-1_112078_2023-11-19_final
2023-11-20 10:38:04	ga_ls8c_ard_3-2-1_103077_2023-11-20_final
2023-11-20 10:38:52	ga_ls8c_ard_3-2-1_103079_2023-11-20_final
2023-11-25 10:53:50	ga_ls8c_ard_3-2-1_106070_2023-11-25_final
2023-11-26 09:57:49	ga_ls8c_ard_3-2-1_097069_2023-11-26_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