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
2018-06-18 09:26:23	ga_ls8c_ard_3-0-0_092071_2018-06-17_final
2018-06-18 09:26:47	ga_ls8c_ard_3-0-0_092072_2018-06-17_final
2018-06-18 11:05:16	ga_ls8c_ard_3-0-0_108071_2018-06-18_final
2018-06-18 11:05:40	ga_ls8c_ard_3-0-0_108072_2018-06-18_final
2018-06-19 10:09:40	ga_ls8c_ard_3-0-0_099071_2018-06-19_final
2018-06-19 10:10:03	ga_ls8c_ard_3-0-0_099072_2018-06-19_final
2018-06-20 10:52:56	ga_ls8c_ard_3-0-0_106071_2018-06-20_final
2018-06-20 10:53:20	ga_ls8c_ard_3-0-0_106072_2018-06-20_final
2018-06-21 09:57:19	ga_ls8c_ard_3-0-0_097071_2018-06-21_final
2018-06-21 09:57:43	ga_ls8c_ard_3-0-0_097072_2018-06-21_final
2018-06-21 11:36:36	ga_ls8c_ard_3-0-0_113072_2018-06-21_final
2018-06-22 10:40:36	ga_ls8c_ard_3-0-0_104071_2018-06-22_final
2018-06-22 10:40:59	ga_ls8c_ard_3-0-0_104072_2018-06-22_final
2018-07-04 09:26:33	ga_ls8c_ard_3-0-0_092071_2018-07-03_final
2018-07-04 09:26:57	ga_ls8c_ard_3-0-0_092072_2018-07-03_final
2018-07-04 11:05:26	ga_ls8c_ard_3-0-0_108071_2018-07-04_final
2018-07-04 11:05:50	ga_ls8c_ard_3-0-0_108072_2018-07-04_final
2018-07-05 10:09:49	ga_ls8c_ard_3-0-0_099071_2018-07-05_final
2018-07-05 10:10:13	ga_ls8c_ard_3-0-0_099072_2018-07-05_final
2018-07-06 10:53:05	ga_ls8c_ard_3-0-0_106071_2018-07-06_final
2018-07-06 10:53:29	ga_ls8c_ard_3-0-0_106072_2018-07-06_final
2018-07-07 09:57:28	ga_ls8c_ard_3-0-0_097071_2018-07-07_final
2018-07-07 09:57:52	ga_ls8c_ard_3-0-0_097072_2018-07-07_final
2018-07-07 11:36:45	ga_ls8c_ard_3-0-0_113072_2018-07-07_final
2018-07-08 10:40:44	ga_ls8c_ard_3-0-0_104071_2018-07-08_final
2018-07-08 10:41:08	ga_ls8c_ard_3-0-0_104072_2018-07-08_final
2018-07-20 09:26:40	ga_ls8c_ard_3-0-0_092071_2018-07-19_final
2018-07-20 09:27:04	ga_ls8c_ard_3-0-0_092072_2018-07-19_final
2018-07-20 11:05:33	ga_ls8c_ard_3-0-0_108071_2018-07-20_final
2018-07-20 11:05:57	ga_ls8c_ard_3-0-0_108072_2018-07-20_final
2018-07-21 10:09:56	ga_ls8c_ard_3-0-0_099071_2018-07-21_final
2018-07-21 10:10:20	ga_ls8c_ard_3-0-0_099072_2018-07-21_final
2018-07-22 10:53:12	ga_ls8c_ard_3-0-0_106071_2018-07-22_final
2018-07-22 10:53:36	ga_ls8c_ard_3-0-0_106072_2018-07-22_final
2018-07-23 09:57:35	ga_ls8c_ard_3-0-0_097071_2018-07-23_final
2018-07-23 09:57:59	ga_ls8c_ard_3-0-0_097072_2018-07-23_final
2018-07-23 11:36:52	ga_ls8c_ard_3-0-0_113072_2018-07-23_final
2018-07-24 10:40:51	ga_ls8c_ard_3-0-0_104071_2018-07-24_final
2018-07-24 10:41:15	ga_ls8c_ard_3-0-0_104072_2018-07-24_final
2018-08-05 09:26:48	ga_ls8c_ard_3-0-0_092071_2018-08-04_final
2018-08-05 09:27:12	ga_ls8c_ard_3-0-0_092072_2018-08-04_final
2018-08-05 11:05:41	ga_ls8c_ard_3-0-0_108071_2018-08-05_final
2018-08-05 11:06:05	ga_ls8c_ard_3-0-0_108072_2018-08-05_final
2018-08-06 10:10:04	ga_ls8c_ard_3-0-0_099071_2018-08-06_final
2018-08-06 10:10:28	ga_ls8c_ard_3-0-0_099072_2018-08-06_final
2018-08-21 09:26:56	ga_ls8c_ard_3-0-0_092071_2018-08-20_final
2018-08-21 09:27:20	ga_ls8c_ard_3-0-0_092072_2018-08-20_final
2018-08-21 11:05:50	ga_ls8c_ard_3-0-0_108071_2018-08-21_final
2018-08-21 11:06:13	ga_ls8c_ard_3-0-0_108072_2018-08-21_final
2018-08-22 10:10:13	ga_ls8c_ard_3-0-0_099071_2018-08-22_final
2018-08-22 10:10:37	ga_ls8c_ard_3-0-0_099072_2018-08-22_final
2018-08-23 10:53:29	ga_ls8c_ard_3-0-0_106071_2018-08-23_final
2018-08-23 10:53:53	ga_ls8c_ard_3-0-0_106072_2018-08-23_final
2018-08-24 09:57:52	ga_ls8c_ard_3-0-0_097071_2018-08-24_final
2018-08-24 09:58:16	ga_ls8c_ard_3-0-0_097072_2018-08-24_final
2018-08-24 11:37:09	ga_ls8c_ard_3-0-0_113072_2018-08-24_final
2018-08-25 10:41:08	ga_ls8c_ard_3-0-0_104071_2018-08-25_final
2018-08-25 10:41:32	ga_ls8c_ard_3-0-0_104072_2018-08-25_final
2018-08-31 10:04:06	ga_ls8c_ard_3-0-0_098071_2018-08-31_final
2018-08-31 10:04:29	ga_ls8c_ard_3-0-0_098072_2018-08-31_final
2018-09-01 10:47:22	ga_ls8c_ard_3-0-0_105071_2018-09-01_final
2018-09-01 10:47:45	ga_ls8c_ard_3-0-0_105072_2018-09-01_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_2018-09-16_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-06 10:04:48	ga_ls8c_ard_3-0-0_098072_2019-01-06_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2019-01-07 10:48:04	ga_ls8c_ard_3-0-0_105072_2019-01-07_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-19 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-08-19_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-22 10:29:48	ga_ls8c_ard_3-2-1_102071_2022-08-22_final
2022-08-22 10:30:12	ga_ls8c_ard_3-2-1_102072_2022-08-22_final
2022-08-23 09:34:11	ga_ls8c_ard_3-2-1_093071_2022-08-23_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-24 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-10-24_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-10-26 09:34:16	ga_ls8c_ard_3-2-1_093071_2022-10-26_final
2022-10-26 11:13:09	ga_ls8c_ard_3-2-1_109071_2022-10-26_final
2022-10-26 11:13:33	ga_ls8c_ard_3-2-1_109072_2022-10-26_final
2022-10-27 10:17:32	ga_ls8c_ard_3-2-1_100071_2022-10-27_final
2022-10-27 10:17:56	ga_ls8c_ard_3-2-1_100072_2022-10-27_final
2022-10-28 09:22:19	ga_ls8c_ard_3-2-1_091072_2022-10-27_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-07 09:59:00	ga_ls8c_ard_3-2-1_097071_2022-11-07_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-07 11:38:17	ga_ls8c_ard_3-2-1_113072_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-12-07 10:11:17	ga_ls8c_ard_3-2-1_099071_2022-12-07_final
2022-12-07 10:11:41	ga_ls8c_ard_3-2-1_099072_2022-12-07_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-08 10:54:56	ga_ls8c_ard_3-2-1_106072_2022-12-08_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_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