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
2022-10-05 10:54:12	ga_ls8c_ard_3-2-1_106070_2022-10-05_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-06 09:58:34	ga_ls8c_ard_3-2-1_097070_2022-10-06_final
2022-10-08 09:52:10	ga_ls8c_ard_3-2-1_095085_2022-10-08_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-11 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-10-11_final
2022-10-12 11:00:41	ga_ls8c_ard_3-2-1_107071_2022-10-12_final
2022-10-12 11:01:05	ga_ls8c_ard_3-2-1_107072_2022-10-12_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-10-17 09:41:09	ga_ls8c_ard_3-2-1_094073_2022-10-17_final
2022-10-17 11:19:39	ga_ls8c_ard_3-2-1_110072_2022-10-17_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-20 10:16:05	ga_ls8c_ard_3-2-1_099083_2022-10-20_final
2022-10-21 10:54:34	ga_ls8c_ard_3-2-1_106071_2022-10-21_final
2022-10-26 09:35:52	ga_ls8c_ard_3-2-1_093075_2022-10-26_final
2022-10-28 11:01:12	ga_ls8c_ard_3-2-1_107072_2022-10-28_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-10-29 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-10-29_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-10-31 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-10-31_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-02 11:19:45	ga_ls8c_ard_3-2-1_110072_2022-11-02_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-12 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-11-12_final
2022-11-13 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-13_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-20 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-11-20_final
2022-11-22 09:18:26	ga_ls8c_ard_3-2-1_090078_2022-11-21_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-23 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-11-23_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-27 11:18:16	ga_ls8c_ard_3-2-1_109084_2022-11-27_final
2022-11-29 09:26:38	ga_ls8c_ard_3-2-1_091083_2022-11-28_final
2022-11-30 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-30_final
2022-12-02 09:53:09	ga_ls8c_ard_3-2-1_096072_2022-12-02_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-06 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-12-06_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-18 09:57:49	ga_ls8c_ard_3-2-1_096084_2022-12-18_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-22 11:07:08	ga_ls8c_ard_3-2-1_108072_2022-12-22_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-12 11:26:51	ga_ls8c_ard_3-2-1_111075_2023-01-12_final
2023-01-16 09:28:46	ga_ls8c_ard_3-2-1_091089_2023-01-15_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-17 10:07:13	ga_ls8c_ard_3-2-1_098077_2023-01-17_final
2023-01-18 10:49:17	ga_ls8c_ard_3-2-1_105074_2023-01-18_final
2023-01-24 10:14:40	ga_ls8c_ard_3-2-1_099080_2023-01-24_final
2023-01-25 09:22:39	ga_ls8c_ard_3-2-1_090089_2023-01-24_final
2023-01-26 11:42:24	ga_ls8c_ard_3-2-1_113083_2023-01-26_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-01-31 10:18:29	ga_ls8c_ard_3-2-1_100074_2023-01-31_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-08 09:34:12	ga_ls8c_ard_3-2-1_092087_2023-02-08_final
2023-02-08 11:07:30	ga_ls8c_ard_3-2-1_108073_2023-02-08_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-15 11:17:59	ga_ls8c_ard_3-2-1_109084_2023-02-15_final
2023-02-17 09:28:18	ga_ls8c_ard_3-2-1_091088_2023-02-16_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-23 10:24:23	ga_ls8c_ard_3-2-1_101074_2023-02-23_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-03-01 11:28:56	ga_ls8c_ard_3-2-1_111081_2023-03-01_final
2023-03-01 11:30:08	ga_ls8c_ard_3-2-1_111084_2023-03-01_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-03 09:33:41	ga_ls8c_ard_3-2-1_093071_2023-03-03_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-04 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-03-04_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-07 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-03-06_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-07 09:16:06	ga_ls8c_ard_3-2-1_089089_2023-03-06_final
2023-03-07 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-03-07_final
2023-03-08 11:31:51	ga_ls8c_ard_3-2-1_112073_2023-03-08_final
2023-03-08 11:35:50	ga_ls8c_ard_3-2-1_112083_2023-03-08_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-10 11:19:05	ga_ls8c_ard_3-2-1_110072_2023-03-10_final
2023-03-10 11:19:53	ga_ls8c_ard_3-2-1_110074_2023-03-10_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