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
2013-03-31 09:36:14	ga_ls8c_ard_3-0-0_092085_2013-03-31_final
2013-04-01 10:14:49	ga_ls8c_ard_3-0-0_099085_2013-04-01_final
2013-07-24 09:22:39	ga_ls8c_ard_3-0-0_090085_2013-07-23_final
2013-07-25 10:05:55	ga_ls8c_ard_3-0-0_097085_2013-07-25_final
2013-07-27 09:53:34	ga_ls8c_ard_3-0-0_095085_2013-07-27_final
2013-08-01 10:12:08	ga_ls8c_ard_3-0-0_098085_2013-08-01_final
2013-08-02 09:16:31	ga_ls8c_ard_3-0-0_089085_2013-08-01_final
2013-08-03 09:59:47	ga_ls8c_ard_3-0-0_096085_2013-08-03_final
2013-08-09 09:22:42	ga_ls8c_ard_3-0-0_090085_2013-08-08_final
2013-08-10 10:05:58	ga_ls8c_ard_3-0-0_097085_2013-08-10_final
2013-08-12 09:53:36	ga_ls8c_ard_3-0-0_095085_2013-08-12_final
2013-11-14 10:05:40	ga_ls8c_ard_3-0-0_097085_2013-11-14_final
2018-03-26 09:57:16	ga_ls8c_ard_3-0-0_096085_2018-03-26_final
2018-03-26 11:36:09	ga_ls8c_ard_3-0-0_112085_2018-03-26_final
2018-04-13 09:44:45	ga_ls8c_ard_3-0-0_094085_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 11:11:15	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 11:17:22	ga_ls8c_ard_3-0-0_109085_2018-04-22_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
2018-04-25 10:09:21	ga_ls8c_ard_3-0-0_098085_2018-04-25_final
2018-04-26 09:13:43	ga_ls8c_ard_3-0-0_089085_2018-04-25_final
2018-04-27 09:56:58	ga_ls8c_ard_3-0-0_096085_2018-04-27_final
2018-04-27 11:35:52	ga_ls8c_ard_3-0-0_112085_2018-04-27_final
2018-05-11 10:09:12	ga_ls8c_ard_3-0-0_098085_2018-05-11_final
2018-05-12 09:13:34	ga_ls8c_ard_3-0-0_089085_2018-05-11_final
2018-05-13 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-05-13_final
2018-05-13 11:35:42	ga_ls8c_ard_3-0-0_112085_2018-05-13_final
2018-05-27 10:08:59	ga_ls8c_ard_3-0-0_098085_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
2018-06-02 09:31:50	ga_ls8c_ard_3-0-0_092085_2018-06-02_final
2018-06-02 11:10:43	ga_ls8c_ard_3-0-0_108085_2018-06-02_final
2018-06-16 09:44:19	ga_ls8c_ard_3-0-0_094085_2018-06-16_final
2018-06-16 11:23:12	ga_ls8c_ard_3-0-0_110085_2018-06-16_final
2018-06-18 09:31:58	ga_ls8c_ard_3-0-0_092085_2018-06-18_final
2018-06-18 11:10:51	ga_ls8c_ard_3-0-0_108085_2018-06-18_final
2018-07-14 10:09:18	ga_ls8c_ard_3-0-0_098085_2018-07-14_final
2018-07-15 09:13:17	ga_ls8c_ard_3-0-0_089084_2018-07-14_final
2018-07-15 09:13:41	ga_ls8c_ard_3-0-0_089085_2018-07-14_final
2018-07-16 09:56:57	ga_ls8c_ard_3-0-0_096085_2018-07-16_final
2018-07-16 11:35:50	ga_ls8c_ard_3-0-0_112085_2018-07-16_final
2019-02-04 09:39:00	ga_ls8c_ard_3-0-0_093085_2019-02-04_final
2019-02-04 11:17:53	ga_ls8c_ard_3-0-0_109085_2019-02-04_final
2019-02-05 10:22:15	ga_ls8c_ard_3-0-0_100085_2019-02-05_final
2019-02-06 09:26:38	ga_ls8c_ard_3-0-0_091085_2019-02-05_final
2019-02-06 11:05:31	ga_ls8c_ard_3-0-0_107085_2019-02-06_final
2019-02-18 09:51:19	ga_ls8c_ard_3-0-0_095085_2019-02-18_final
2019-02-18 11:30:12	ga_ls8c_ard_3-0-0_111085_2019-02-18_final
2019-02-20 09:38:57	ga_ls8c_ard_3-0-0_093085_2019-02-20_final
2019-02-20 11:17:50	ga_ls8c_ard_3-0-0_109085_2019-02-20_final
2019-02-21 10:22:13	ga_ls8c_ard_3-0-0_100085_2019-02-21_final
2019-02-22 09:26:35	ga_ls8c_ard_3-0-0_091085_2019-02-21_final
2019-02-22 11:05:28	ga_ls8c_ard_3-0-0_107085_2019-02-22_final
2019-04-07 09:51:06	ga_ls8c_ard_3-1-0_095085_2019-04-07_final
2019-04-07 11:29:59	ga_ls8c_ard_3-1-0_111085_2019-04-07_final
2019-05-02 09:44:26	ga_ls8c_ard_3-0-0_094084_2019-05-02_final
2019-05-02 09:44:50	ga_ls8c_ard_3-0-0_094085_2019-05-02_final
2019-05-02 11:23:43	ga_ls8c_ard_3-0-0_110085_2019-05-02_final
2019-05-03 10:27:43	ga_ls8c_ard_3-0-0_101084_2019-05-03_final
2019-05-11 09:38:45	ga_ls8c_ard_3-0-0_093085_2019-05-11_final
2019-05-12 10:21:38	ga_ls8c_ard_3-0-0_100084_2019-05-12_final
2019-05-12 10:22:02	ga_ls8c_ard_3-0-0_100085_2019-05-12_final
2019-05-13 09:26:25	ga_ls8c_ard_3-0-0_091085_2019-05-12_final
2019-05-13 11:05:18	ga_ls8c_ard_3-0-0_107085_2019-05-13_final
2019-05-24 09:07:35	ga_ls8c_ard_3-0-0_088084_2019-05-23_final
2019-05-25 09:51:16	ga_ls8c_ard_3-0-0_095085_2019-05-25_final
2019-05-25 11:30:09	ga_ls8c_ard_3-0-0_111085_2019-05-25_final
2019-06-28 09:39:07	ga_ls8c_ard_3-1-0_093085_2019-06-28_final
2019-06-28 11:17:36	ga_ls8c_ard_3-1-0_109084_2019-06-28_final
2019-06-28 11:18:00	ga_ls8c_ard_3-1-0_109085_2019-06-28_final
2019-06-29 10:21:59	ga_ls8c_ard_3-1-0_100084_2019-06-29_final
2019-06-29 10:22:23	ga_ls8c_ard_3-1-0_100085_2019-06-29_final
2019-06-30 09:26:22	ga_ls8c_ard_3-1-0_091084_2019-06-29_final
2019-06-30 09:26:46	ga_ls8c_ard_3-1-0_091085_2019-06-29_final
2019-06-30 11:05:39	ga_ls8c_ard_3-1-0_107085_2019-06-30_final
2022-01-23 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-01-23_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-04-17 09:38:40	ga_ls8c_ard_3-2-1_093084_2022-04-17_final
2022-04-17 09:39:04	ga_ls8c_ard_3-2-1_093085_2022-04-17_final
2022-04-19 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-04-18_final
2022-04-20 10:09:57	ga_ls8c_ard_3-2-1_098085_2022-04-20_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-22 09:57:11	ga_ls8c_ard_3-2-1_096084_2022-04-22_final
2022-04-22 09:57:35	ga_ls8c_ard_3-2-1_096085_2022-04-22_final
2022-04-24 09:44:49	ga_ls8c_ard_3-2-1_094084_2022-04-24_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_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 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2023-10-27 09:51:48	ga_ls8c_ard_3-2-1_095085_2023-10-27_final
2023-10-29 09:39:27	ga_ls8c_ard_3-2-1_093085_2023-10-29_final
2023-10-31 11:05:34	ga_ls8c_ard_3-2-1_107084_2023-10-31_final
2023-11-01 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-01_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