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
2018-03-30 09:32:07	ga_ls8c_ard_3-0-0_092084_2018-03-30_final
2018-03-30 09:32:31	ga_ls8c_ard_3-0-0_092085_2018-03-30_final
2018-03-30 11:11:00	ga_ls8c_ard_3-0-0_108084_2018-03-30_final
2018-03-30 11:11:24	ga_ls8c_ard_3-0-0_108085_2018-03-30_final
2018-04-09 10:09:07	ga_ls8c_ard_3-0-0_098084_2018-04-09_final
2018-04-09 10:09:30	ga_ls8c_ard_3-0-0_098085_2018-04-09_final
2018-04-10 09:13:29	ga_ls8c_ard_3-0-0_089084_2018-04-09_final
2018-04-10 09:13:53	ga_ls8c_ard_3-0-0_089085_2018-04-09_final
2018-04-11 09:57:08	ga_ls8c_ard_3-0-0_096085_2018-04-11_final
2018-04-11 11:35:37	ga_ls8c_ard_3-0-0_112084_2018-04-11_final
2018-04-11 11:36:01	ga_ls8c_ard_3-0-0_112085_2018-04-11_final
2018-04-13 09:44:45	ga_ls8c_ard_3-0-0_094085_2018-04-13_final
2018-04-13 11:23:14	ga_ls8c_ard_3-0-0_110084_2018-04-13_final
2018-04-13 11:23:38	ga_ls8c_ard_3-0-0_110085_2018-04-13_final
2018-04-15 09:32:22	ga_ls8c_ard_3-0-0_092085_2018-04-15_final
2018-04-15 11:10:51	ga_ls8c_ard_3-0-0_108084_2018-04-15_final
2018-04-15 11:11:15	ga_ls8c_ard_3-0-0_108085_2018-04-15_final
2018-04-22 09:38:29	ga_ls8c_ard_3-0-0_093085_2018-04-22_final
2018-04-22 11:16:58	ga_ls8c_ard_3-0-0_109084_2018-04-22_final
2018-04-22 11:17:22	ga_ls8c_ard_3-0-0_109085_2018-04-22_final
2018-04-23 10:21:20	ga_ls8c_ard_3-0-0_100084_2018-04-23_final
2018-04-23 10:21:44	ga_ls8c_ard_3-0-0_100085_2018-04-23_final
2018-04-24 09:26:06	ga_ls8c_ard_3-0-0_091085_2018-04-23_final
2018-04-24 11:04:59	ga_ls8c_ard_3-0-0_107085_2018-04-24_final
2018-04-29 09:44:12	ga_ls8c_ard_3-0-0_094084_2018-04-29_final
2018-04-29 09:44:36	ga_ls8c_ard_3-0-0_094085_2018-04-29_final
2018-04-29 11:23:05	ga_ls8c_ard_3-0-0_110084_2018-04-29_final
2018-04-29 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-04-29_final
2018-04-30 10:27:27	ga_ls8c_ard_3-0-0_101084_2018-04-30_final
2018-05-01 09:31:49	ga_ls8c_ard_3-0-0_092084_2018-05-01_final
2018-05-01 09:32:13	ga_ls8c_ard_3-0-0_092085_2018-05-01_final
2018-05-01 11:10:42	ga_ls8c_ard_3-0-0_108084_2018-05-01_final
2018-05-01 11:11:06	ga_ls8c_ard_3-0-0_108085_2018-05-01_final
2018-05-12 09:13:34	ga_ls8c_ard_3-0-0_089085_2018-05-11_final
2018-05-13 09:56:25	ga_ls8c_ard_3-0-0_096084_2018-05-13_final
2018-05-13 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-05-13_final
2018-05-13 11:35:18	ga_ls8c_ard_3-0-0_112084_2018-05-13_final
2018-05-13 11:35:42	ga_ls8c_ard_3-0-0_112085_2018-05-13_final
2018-05-27 10:08:35	ga_ls8c_ard_3-0-0_098084_2018-05-27_final
2018-05-27 10:08:59	ga_ls8c_ard_3-0-0_098085_2018-05-27_final
2018-05-28 09:12:57	ga_ls8c_ard_3-0-0_089084_2018-05-27_final
2018-05-28 09:13:21	ga_ls8c_ard_3-0-0_089085_2018-05-27_final
2018-05-29 09:56:36	ga_ls8c_ard_3-0-0_096085_2018-05-29_final
2018-05-29 11:35:29	ga_ls8c_ard_3-0-0_112085_2018-05-29_final
2018-05-31 09:43:49	ga_ls8c_ard_3-0-0_094084_2018-05-31_final
2018-05-31 09:44:13	ga_ls8c_ard_3-0-0_094085_2018-05-31_final
2018-05-31 11:22:42	ga_ls8c_ard_3-0-0_110084_2018-05-31_final
2018-05-31 11:23:06	ga_ls8c_ard_3-0-0_110085_2018-05-31_final
2018-06-01 10:27:04	ga_ls8c_ard_3-0-0_101084_2018-06-01_final
2018-06-02 09:31:26	ga_ls8c_ard_3-0-0_092084_2018-06-02_final
2018-06-02 09:31:50	ga_ls8c_ard_3-0-0_092085_2018-06-02_final
2018-06-02 11:10:19	ga_ls8c_ard_3-0-0_108084_2018-06-02_final
2018-06-02 11:10:43	ga_ls8c_ard_3-0-0_108085_2018-06-02_final
2018-06-12 10:08:35	ga_ls8c_ard_3-0-0_098084_2018-06-12_final
2018-06-12 10:08:59	ga_ls8c_ard_3-0-0_098085_2018-06-12_final
2018-06-13 09:12:59	ga_ls8c_ard_3-0-0_089084_2018-06-12_final
2018-06-13 09:13:23	ga_ls8c_ard_3-0-0_089085_2018-06-12_final
2018-06-14 09:56:15	ga_ls8c_ard_3-0-0_096084_2018-06-14_final
2018-06-14 09:56:39	ga_ls8c_ard_3-0-0_096085_2018-06-14_final
2018-06-14 11:35:08	ga_ls8c_ard_3-0-0_112084_2018-06-14_final
2018-06-14 11:35:32	ga_ls8c_ard_3-0-0_112085_2018-06-14_final
2018-06-28 10:08:46	ga_ls8c_ard_3-0-0_098084_2018-06-28_final
2018-06-28 10:09:10	ga_ls8c_ard_3-0-0_098085_2018-06-28_final
2018-06-29 09:13:09	ga_ls8c_ard_3-0-0_089084_2018-06-28_final
2018-06-29 09:13:33	ga_ls8c_ard_3-0-0_089085_2018-06-28_final
2018-06-30 09:56:25	ga_ls8c_ard_3-0-0_096084_2018-06-30_final
2018-06-30 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-06-30_final
2018-06-30 11:35:18	ga_ls8c_ard_3-0-0_112084_2018-06-30_final
2018-06-30 11:35:42	ga_ls8c_ard_3-0-0_112085_2018-06-30_final
2022-01-23 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-01-23_final
2022-01-23 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-01-23_final
2022-01-23 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-01-23_final
2022-01-25 09:51:21	ga_ls8c_ard_3-2-1_095084_2022-01-25_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-02-24 10:03:35	ga_ls8c_ard_3-2-1_097084_2022-02-24_final
2022-02-24 10:03:59	ga_ls8c_ard_3-2-1_097085_2022-02-24_final
2022-02-24 11:42:28	ga_ls8c_ard_3-2-1_113084_2022-02-24_final
2022-02-26 09:51:13	ga_ls8c_ard_3-2-1_095084_2022-02-26_final
2022-02-26 09:51:37	ga_ls8c_ard_3-2-1_095085_2022-02-26_final
2022-02-26 11:30:06	ga_ls8c_ard_3-2-1_111084_2022-02-26_final
2022-02-28 09:38:51	ga_ls8c_ard_3-2-1_093084_2022-02-28_final
2022-02-28 09:39:15	ga_ls8c_ard_3-2-1_093085_2022-02-28_final
2022-02-28 11:17:44	ga_ls8c_ard_3-2-1_109084_2022-02-28_final
2022-03-01 10:22:07	ga_ls8c_ard_3-2-1_100084_2022-03-01_final
2022-03-02 09:26:53	ga_ls8c_ard_3-2-1_091085_2022-03-01_final
2022-03-02 11:05:22	ga_ls8c_ard_3-2-1_107084_2022-03-02_final
2022-03-30 09:50:56	ga_ls8c_ard_3-2-1_095084_2022-03-30_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-01 09:38:58	ga_ls8c_ard_3-2-1_093085_2022-04-01_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-06 09:57:33	ga_ls8c_ard_3-2-1_096085_2022-04-06_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-05 11:05:12	ga_ls8c_ard_3-2-1_107084_2022-05-05_final
2022-05-06 10:09:35	ga_ls8c_ard_3-2-1_098084_2022-05-06_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years