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
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-10-06 11:18:05	ga_ls8c_ard_3-0-0_110070_2018-10-06_final
2018-10-06 11:18:29	ga_ls8c_ard_3-0-0_110071_2018-10-06_final
2018-10-07 10:22:28	ga_ls8c_ard_3-0-0_101070_2018-10-07_final
2018-10-07 10:22:52	ga_ls8c_ard_3-0-0_101071_2018-10-07_final
2018-10-08 09:27:15	ga_ls8c_ard_3-0-0_092071_2018-10-07_final
2018-10-08 11:05:44	ga_ls8c_ard_3-0-0_108070_2018-10-08_final
2018-10-09 10:10:07	ga_ls8c_ard_3-0-0_099070_2018-10-09_final
2018-10-09 10:10:31	ga_ls8c_ard_3-0-0_099071_2018-10-09_final
2018-10-10 10:53:24	ga_ls8c_ard_3-0-0_106070_2018-10-10_final
2018-10-10 10:53:48	ga_ls8c_ard_3-0-0_106071_2018-10-10_final
2018-10-11 09:57:47	ga_ls8c_ard_3-0-0_097070_2018-10-11_final
2018-10-11 09:58:11	ga_ls8c_ard_3-0-0_097071_2018-10-11_final
2018-10-12 10:41:03	ga_ls8c_ard_3-0-0_104070_2018-10-12_final
2018-10-12 10:41:27	ga_ls8c_ard_3-0-0_104071_2018-10-12_final
2018-10-13 09:45:26	ga_ls8c_ard_3-0-0_095070_2018-10-13_final
2018-10-13 09:45:50	ga_ls8c_ard_3-0-0_095071_2018-10-13_final
2018-10-13 11:24:19	ga_ls8c_ard_3-0-0_111070_2018-10-13_final
2018-10-13 11:24:43	ga_ls8c_ard_3-0-0_111071_2018-10-13_final
2018-10-14 10:28:42	ga_ls8c_ard_3-0-0_102070_2018-10-14_final
2018-10-14 10:29:06	ga_ls8c_ard_3-0-0_102071_2018-10-14_final
2018-10-15 11:11:58	ga_ls8c_ard_3-0-0_109070_2018-10-15_final
2018-10-16 10:16:21	ga_ls8c_ard_3-1-0_100070_2018-10-16_final
2018-10-18 10:04:00	ga_ls8c_ard_3-0-0_098070_2018-10-18_final
2018-10-18 10:04:24	ga_ls8c_ard_3-0-0_098071_2018-10-18_final
2018-10-19 10:47:16	ga_ls8c_ard_3-0-0_105070_2018-10-19_final
2018-10-24 09:27:21	ga_ls8c_ard_3-0-0_092071_2018-10-23_final
2018-10-24 11:05:50	ga_ls8c_ard_3-0-0_108070_2018-10-24_final
2018-10-24 11:06:14	ga_ls8c_ard_3-0-0_108071_2018-10-24_final
2018-10-25 10:10:13	ga_ls8c_ard_3-0-0_099070_2018-10-25_final
2018-10-25 10:10:37	ga_ls8c_ard_3-0-0_099071_2018-10-25_final
2018-10-26 10:53:29	ga_ls8c_ard_3-0-0_106070_2018-10-26_final
2018-10-26 10:53:53	ga_ls8c_ard_3-0-0_106071_2018-10-26_final
2018-10-27 09:57:52	ga_ls8c_ard_3-0-0_097070_2018-10-27_final
2018-10-28 10:41:08	ga_ls8c_ard_3-0-0_104070_2018-10-28_final
2018-11-03 10:04:04	ga_ls8c_ard_3-0-0_098070_2018-11-03_final
2018-11-03 10:04:28	ga_ls8c_ard_3-1-0_098071_2018-11-03_final
2018-11-04 10:47:20	ga_ls8c_ard_3-0-0_105070_2018-11-04_final
2018-11-09 09:27:24	ga_ls8c_ard_3-0-0_092071_2018-11-08_final
2018-11-09 11:05:53	ga_ls8c_ard_3-0-0_108070_2018-11-09_final
2018-11-09 11:06:17	ga_ls8c_ard_3-0-0_108071_2018-11-09_final
2018-11-10 10:10:16	ga_ls8c_ard_3-0-0_099070_2018-11-10_final
2018-11-11 10:53:31	ga_ls8c_ard_3-0-0_106070_2018-11-11_final
2018-11-12 09:57:54	ga_ls8c_ard_3-0-0_097070_2018-11-12_final
2018-11-13 10:41:10	ga_ls8c_ard_3-0-0_104070_2018-11-13_final
2018-11-13 10:41:34	ga_ls8c_ard_3-0-0_104071_2018-11-13_final
2018-11-18 10:59:42	ga_ls8c_ard_3-0-0_107070_2018-11-18_final
2018-11-19 10:04:05	ga_ls8c_ard_3-0-0_098070_2018-11-19_final
2018-11-20 10:47:21	ga_ls8c_ard_3-0-0_105070_2018-11-20_final
2018-11-20 10:47:44	ga_ls8c_ard_3-0-0_105071_2018-11-20_final
2018-12-05 10:04:03	ga_ls8c_ard_3-0-0_098070_2018-12-05_final
2018-12-06 10:47:18	ga_ls8c_ard_3-0-0_105070_2018-12-06_final
2018-12-11 09:27:20	ga_ls8c_ard_3-0-0_092071_2018-12-10_final
2018-12-11 11:05:50	ga_ls8c_ard_3-0-0_108070_2018-12-11_final
2018-12-12 10:10:12	ga_ls8c_ard_3-0-0_099070_2018-12-12_final
2018-12-13 10:53:27	ga_ls8c_ard_3-0-0_106070_2018-12-13_final
2018-12-13 10:53:51	ga_ls8c_ard_3-0-0_106071_2018-12-13_final
2018-12-14 09:57:50	ga_ls8c_ard_3-1-0_097070_2018-12-14_final
2018-12-15 10:41:06	ga_ls8c_ard_3-0-0_104070_2018-12-15_final
2018-12-23 09:51:40	ga_ls8c_ard_3-0-0_096070_2018-12-23_final
2018-12-23 11:30:33	ga_ls8c_ard_3-0-0_112070_2018-12-23_final
2018-12-24 10:34:55	ga_ls8c_ard_3-0-0_103070_2018-12-24_final
2018-12-25 09:39:42	ga_ls8c_ard_3-0-0_094071_2018-12-25_final
2018-12-25 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-12-25_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2018-12-26 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-26_final
2019-01-05 10:59:38	ga_ls8c_ard_3-0-0_107070_2019-01-05_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2023-07-21 09:57:40	ga_ls8c_ard_3-2-1_097070_2023-07-21_final
2023-07-24 10:28:37	ga_ls8c_ard_3-2-1_102070_2023-07-24_final
2023-07-24 10:29:01	ga_ls8c_ard_3-2-1_102071_2023-07-24_final
2023-07-26 10:16:41	ga_ls8c_ard_3-2-1_100071_2023-07-26_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-07-27 10:59:58	ga_ls8c_ard_3-2-1_107071_2023-07-27_final
2023-08-08 11:24:21	ga_ls8c_ard_3-2-1_111070_2023-08-08_final
2023-08-08 11:24:45	ga_ls8c_ard_3-2-1_111071_2023-08-08_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-09 10:29:07	ga_ls8c_ard_3-2-1_102071_2023-08-09_final
2023-08-12 10:59:38	ga_ls8c_ard_3-2-1_107070_2023-08-12_final
2023-08-12 11:00:02	ga_ls8c_ard_3-2-1_107071_2023-08-12_final
2023-08-13 10:04:02	ga_ls8c_ard_3-2-1_098070_2023-08-13_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-29 10:04:09	ga_ls8c_ard_3-2-1_098070_2023-08-29_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-08-30 10:47:24	ga_ls8c_ard_3-2-1_105070_2023-08-30_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_final
2023-09-01 10:35:26	ga_ls8c_ard_3-2-1_103071_2023-09-01_final
2023-09-17 10:35:07	ga_ls8c_ard_3-2-1_103070_2023-09-17_final
2023-09-18 09:39:54	ga_ls8c_ard_3-2-1_094071_2023-09-18_final
2023-09-19 10:22:45	ga_ls8c_ard_3-2-1_101070_2023-09-19_final
2023-09-19 10:23:09	ga_ls8c_ard_3-2-1_101071_2023-09-19_final
2023-09-20 09:27:32	ga_ls8c_ard_3-2-1_092071_2023-09-19_final
2023-09-24 10:41:19	ga_ls8c_ard_3-2-1_104070_2023-09-24_final
2023-09-25 09:46:06	ga_ls8c_ard_3-2-1_095071_2023-09-25_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