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 11:04:52	ga_ls8c_ard_3-0-0_108070_2018-06-18_final
2018-06-18 11:05:16	ga_ls8c_ard_3-0-0_108071_2018-06-18_final
2018-06-19 10:09:16	ga_ls8c_ard_3-0-0_099070_2018-06-19_final
2018-07-04 09:26:33	ga_ls8c_ard_3-0-0_092071_2018-07-03_final
2018-07-04 11:05:02	ga_ls8c_ard_3-0-0_108070_2018-07-04_final
2018-07-05 10:09:25	ga_ls8c_ard_3-0-0_099070_2018-07-05_final
2018-07-05 10:09:49	ga_ls8c_ard_3-0-0_099071_2018-07-05_final
2018-07-20 09:26:40	ga_ls8c_ard_3-0-0_092071_2018-07-19_final
2018-07-20 11:05:09	ga_ls8c_ard_3-0-0_108070_2018-07-20_final
2018-07-21 10:09:32	ga_ls8c_ard_3-0-0_099070_2018-07-21_final
2018-07-21 10:09:56	ga_ls8c_ard_3-0-0_099071_2018-07-21_final
2018-07-22 10:52:48	ga_ls8c_ard_3-0-0_106070_2018-07-22_final
2018-07-23 09:57:11	ga_ls8c_ard_3-0-0_097070_2018-07-23_final
2018-07-23 09:57:35	ga_ls8c_ard_3-0-0_097071_2018-07-23_final
2018-07-24 10:40:27	ga_ls8c_ard_3-0-0_104070_2018-07-24_final
2018-07-24 10:40:51	ga_ls8c_ard_3-0-0_104071_2018-07-24_final
2018-07-30 10:03:25	ga_ls8c_ard_3-0-0_098070_2018-07-30_final
2018-07-31 10:46:42	ga_ls8c_ard_3-0-0_105070_2018-07-31_final
2018-08-05 11:05:17	ga_ls8c_ard_3-0-0_108070_2018-08-05_final
2018-08-06 10:09:40	ga_ls8c_ard_3-0-0_099070_2018-08-06_final
2018-08-06 10:10:04	ga_ls8c_ard_3-0-0_099071_2018-08-06_final
2018-08-15 10:03:35	ga_ls8c_ard_3-0-0_098070_2018-08-15_final
2018-08-15 10:03:58	ga_ls8c_ard_3-0-0_098071_2018-08-15_final
2018-08-16 10:46:51	ga_ls8c_ard_3-0-0_105070_2018-08-16_final
2018-08-16 10:47:15	ga_ls8c_ard_3-0-0_105071_2018-08-16_final
2018-08-23 10:53:05	ga_ls8c_ard_3-0-0_106070_2018-08-23_final
2018-08-23 10:53:29	ga_ls8c_ard_3-0-0_106071_2018-08-23_final
2018-08-24 09:57:28	ga_ls8c_ard_3-0-0_097070_2018-08-24_final
2018-08-24 09:57:52	ga_ls8c_ard_3-0-0_097071_2018-08-24_final
2018-08-25 10:40:44	ga_ls8c_ard_3-0-0_104070_2018-08-25_final
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
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
2022-08-13 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-08-13_final
2022-08-13 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-08-13_final
2022-08-14 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-08-14_final
2022-08-18 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-08-18_final
2022-08-19 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-08-19_final
2022-08-21 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-08-21_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-23 11:12:40	ga_ls8c_ard_3-2-1_109070_2022-08-23_final
2022-08-24 10:17:27	ga_ls8c_ard_3-2-1_100071_2022-08-24_final
2022-08-27 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-08-27_final
2022-08-28 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-08-28_final
2022-09-06 11:25:03	ga_ls8c_ard_3-2-1_111070_2022-09-06_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-08 11:12:43	ga_ls8c_ard_3-2-1_109070_2022-09-08_final
2022-09-08 11:13:06	ga_ls8c_ard_3-2-1_109071_2022-09-08_final
2022-09-18 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-09-18_final
2022-09-19 10:54:14	ga_ls8c_ard_3-2-1_106070_2022-09-19_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-20 09:58:37	ga_ls8c_ard_3-2-1_097070_2022-09-20_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-26 11:00:25	ga_ls8c_ard_3-2-1_107070_2022-09-26_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-09-28 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-09-28_final
2022-09-28 10:48:27	ga_ls8c_ard_3-2-1_105071_2022-09-28_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-09-30 10:35:41	ga_ls8c_ard_3-2-1_103070_2022-09-30_final
2022-10-01 11:18:57	ga_ls8c_ard_3-2-1_110070_2022-10-01_final
2022-10-01 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-10-01_final
2022-10-05 10:54:12	ga_ls8c_ard_3-2-1_106070_2022-10-05_final
2022-10-06 09:58:34	ga_ls8c_ard_3-2-1_097070_2022-10-06_final
2022-10-09 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-10-09_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-15 09:52:18	ga_ls8c_ard_3-2-1_096070_2022-10-15_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-16 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-10-16_final
2022-10-17 11:18:51	ga_ls8c_ard_3-2-1_110070_2022-10-17_final
2022-10-18 10:23:14	ga_ls8c_ard_3-2-1_101070_2022-10-18_final
2022-10-19 11:06:30	ga_ls8c_ard_3-2-1_108070_2022-10-19_final
2022-10-20 10:10:54	ga_ls8c_ard_3-2-1_099070_2022-10-20_final
2022-10-21 10:54:10	ga_ls8c_ard_3-2-1_106070_2022-10-21_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-10-24 11:25:06	ga_ls8c_ard_3-2-1_111070_2022-10-24_final
2022-10-25 10:29:29	ga_ls8c_ard_3-2-1_102070_2022-10-25_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-11-11 11:12:44	ga_ls8c_ard_3-2-1_109070_2022-11-11_final
2022-11-12 10:17:30	ga_ls8c_ard_3-2-1_100071_2022-11-12_final
2022-11-18 11:18:49	ga_ls8c_ard_3-2-1_110070_2022-11-18_final
2022-11-19 10:23:12	ga_ls8c_ard_3-2-1_101070_2022-11-19_final
2022-11-20 11:06:28	ga_ls8c_ard_3-2-1_108070_2022-11-20_final
2022-11-21 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-11-21_final
2022-11-21 10:11:15	ga_ls8c_ard_3-2-1_099071_2022-11-21_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-03-29 10:10:08	ga_ls8c_ard_3-2-1_099070_2023-03-29_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-03-31 09:57:45	ga_ls8c_ard_3-2-1_097070_2023-03-31_final
2023-04-01 10:41:00	ga_ls8c_ard_3-2-1_104070_2023-04-01_final
2023-04-06 10:59:27	ga_ls8c_ard_3-2-1_107070_2023-04-06_final
2023-04-07 10:03:48	ga_ls8c_ard_3-2-1_098070_2023-04-07_final
2023-04-14 10:09:53	ga_ls8c_ard_3-2-1_099070_2023-04-14_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