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
2018-02-19 09:27:03	ga_ls8c_ard_3-0-0_091086_2018-02-18_final
2018-02-20 10:10:18	ga_ls8c_ard_3-0-0_098086_2018-02-20_final
2018-02-21 09:14:41	ga_ls8c_ard_3-0-0_089086_2018-02-20_final
2018-02-22 09:57:56	ga_ls8c_ard_3-0-0_096086_2018-02-22_final
2018-03-08 10:10:10	ga_ls8c_ard_3-0-0_098086_2018-03-08_final
2018-03-09 09:14:32	ga_ls8c_ard_3-0-0_089086_2018-03-08_final
2018-03-10 09:57:47	ga_ls8c_ard_3-0-0_096086_2018-03-10_final
2018-03-26 09:57:40	ga_ls8c_ard_3-0-0_096086_2018-03-26_final
2018-04-09 10:09:54	ga_ls8c_ard_3-0-0_098086_2018-04-09_final
2018-04-10 09:14:17	ga_ls8c_ard_3-0-0_089086_2018-04-09_final
2018-04-11 09:57:32	ga_ls8c_ard_3-0-0_096086_2018-04-11_final
2018-05-11 10:09:36	ga_ls8c_ard_3-0-0_098086_2018-05-11_final
2018-05-12 09:13:58	ga_ls8c_ard_3-0-0_089086_2018-05-11_final
2018-05-13 09:57:13	ga_ls8c_ard_3-0-0_096086_2018-05-13_final
2018-05-27 10:09:23	ga_ls8c_ard_3-0-0_098086_2018-05-27_final
2018-05-28 09:13:45	ga_ls8c_ard_3-0-0_089086_2018-05-27_final
2018-05-29 09:57:00	ga_ls8c_ard_3-0-0_096086_2018-05-29_final
2018-06-14 09:56:39	ga_ls8c_ard_3-0-0_096085_2018-06-14_final
2018-06-14 09:57:03	ga_ls8c_ard_3-0-0_096086_2018-06-14_final
2018-06-14 11:35:32	ga_ls8c_ard_3-0-0_112085_2018-06-14_final
2018-06-28 10:09:10	ga_ls8c_ard_3-0-0_098085_2018-06-28_final
2018-06-28 10:09:33	ga_ls8c_ard_3-0-0_098086_2018-06-28_final
2018-06-29 09:13:33	ga_ls8c_ard_3-0-0_089085_2018-06-28_final
2018-06-29 09:13:57	ga_ls8c_ard_3-0-0_089086_2018-06-28_final
2018-06-30 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-06-30_final
2018-06-30 09:57:13	ga_ls8c_ard_3-0-0_096086_2018-06-30_final
2018-06-30 11:35:42	ga_ls8c_ard_3-0-0_112085_2018-06-30_final
2018-07-02 09:44:52	ga_ls8c_ard_3-0-0_094086_2018-07-02_final
2018-07-02 11:23:22	ga_ls8c_ard_3-0-0_110085_2018-07-02_final
2018-07-04 09:32:32	ga_ls8c_ard_3-0-0_092086_2018-07-04_final
2018-07-04 11:11:01	ga_ls8c_ard_3-0-0_108085_2018-07-04_final
2018-07-14 10:09:18	ga_ls8c_ard_3-0-0_098085_2018-07-14_final
2018-07-14 10:09:41	ga_ls8c_ard_3-0-0_098086_2018-07-14_final
2018-07-15 09:13:41	ga_ls8c_ard_3-0-0_089085_2018-07-14_final
2018-07-15 09:14:05	ga_ls8c_ard_3-0-0_089086_2018-07-14_final
2018-07-16 09:57:21	ga_ls8c_ard_3-0-0_096086_2018-07-16_final
2018-07-16 11:35:50	ga_ls8c_ard_3-0-0_112085_2018-07-16_final
2019-01-31 10:04:07	ga_ls8c_ard_3-0-0_097086_2019-01-31_final
2019-02-02 09:51:45	ga_ls8c_ard_3-0-0_095086_2019-02-02_final
2019-02-02 11:30:15	ga_ls8c_ard_3-0-0_111085_2019-02-02_final
2019-02-20 09:39:21	ga_ls8c_ard_3-0-0_093086_2019-02-20_final
2019-02-22 09:26:59	ga_ls8c_ard_3-0-0_091086_2019-02-21_final
2019-03-20 10:03:56	ga_ls8c_ard_3-1-0_097086_2019-03-20_final
2019-03-22 09:51:34	ga_ls8c_ard_3-1-0_095086_2019-03-22_final
2019-03-26 09:26:50	ga_ls8c_ard_3-1-0_091086_2019-03-25_final
2019-04-04 09:20:37	ga_ls8c_ard_3-1-0_090086_2019-04-03_final
2019-04-05 10:03:52	ga_ls8c_ard_3-1-0_097086_2019-04-05_final
2019-05-07 10:03:26	ga_ls8c_ard_3-0-0_097085_2019-05-07_final
2019-05-07 10:03:50	ga_ls8c_ard_3-0-0_097086_2019-05-07_final
2019-05-09 09:51:30	ga_ls8c_ard_3-0-0_095086_2019-05-09_final
2019-05-09 11:29:59	ga_ls8c_ard_3-0-0_111085_2019-05-09_final
2019-05-11 09:38:45	ga_ls8c_ard_3-0-0_093085_2019-05-11_final
2019-05-11 09:39:09	ga_ls8c_ard_3-0-0_093086_2019-05-11_final
2019-05-11 11:17:38	ga_ls8c_ard_3-0-0_109085_2019-05-11_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 09:26:49	ga_ls8c_ard_3-0-0_091086_2019-05-12_final
2019-05-13 11:05:18	ga_ls8c_ard_3-0-0_107085_2019-05-13_final
2019-05-21 10:15:57	ga_ls8c_ard_3-0-0_099085_2019-05-21_final
2019-05-22 09:20:20	ga_ls8c_ard_3-0-0_090085_2019-05-21_final
2019-05-22 09:20:44	ga_ls8c_ard_3-0-0_090086_2019-05-21_final
2019-05-23 10:03:36	ga_ls8c_ard_3-0-0_097085_2019-05-23_final
2019-05-23 10:04:00	ga_ls8c_ard_3-0-0_097086_2019-05-23_final
2019-06-16 09:14:20	ga_ls8c_ard_3-1-0_089085_2019-06-15_final
2019-06-16 09:14:44	ga_ls8c_ard_3-1-0_089086_2019-06-15_final
2019-06-21 09:33:18	ga_ls8c_ard_3-1-0_092086_2019-06-21_final
2019-06-21 11:11:48	ga_ls8c_ard_3-1-0_108085_2019-06-21_final
2019-06-22 10:16:10	ga_ls8c_ard_3-1-0_099085_2019-06-22_final
2019-06-23 09:20:33	ga_ls8c_ard_3-1-0_090085_2019-06-22_final
2019-06-23 09:20:57	ga_ls8c_ard_3-1-0_090086_2019-06-22_final
2019-06-24 10:03:49	ga_ls8c_ard_3-1-0_097085_2019-06-24_final
2019-06-24 10:04:13	ga_ls8c_ard_3-1-0_097086_2019-06-24_final
2019-06-26 09:51:52	ga_ls8c_ard_3-1-0_095086_2019-06-26_final
2019-06-26 11:30:21	ga_ls8c_ard_3-1-0_111085_2019-06-26_final
2019-06-28 09:39:31	ga_ls8c_ard_3-1-0_093086_2019-06-28_final
2019-06-28 11:18:00	ga_ls8c_ard_3-1-0_109085_2019-06-28_final
2019-06-29 10:22:23	ga_ls8c_ard_3-1-0_100085_2019-06-29_final
2019-06-30 09:27:10	ga_ls8c_ard_3-1-0_091086_2019-06-29_final
2019-06-30 11:05:39	ga_ls8c_ard_3-1-0_107085_2019-06-30_final
2019-08-22 09:45:35	ga_ls8c_ard_3-1-0_094085_2019-08-22_final
2019-08-22 09:45:59	ga_ls8c_ard_3-1-0_094086_2019-08-22_final
2019-08-22 11:24:28	ga_ls8c_ard_3-1-0_110085_2019-08-22_final
2019-08-24 09:33:37	ga_ls8c_ard_3-1-0_092086_2019-08-24_final
2019-09-23 09:45:44	ga_ls8c_ard_3-1-0_094085_2019-09-23_final
2019-09-23 09:46:08	ga_ls8c_ard_3-1-0_094086_2019-09-23_final
2019-09-23 11:24:37	ga_ls8c_ard_3-1-0_110085_2019-09-23_final
2019-09-25 09:33:47	ga_ls8c_ard_3-1-0_092086_2019-09-25_final
2019-09-25 11:12:16	ga_ls8c_ard_3-1-0_108085_2019-09-25_final
2019-10-18 09:39:37	ga_ls8c_ard_3-1-0_093085_2019-10-18_final
2019-10-18 09:40:01	ga_ls8c_ard_3-1-0_093086_2019-10-18_final
2019-10-18 11:18:31	ga_ls8c_ard_3-1-0_109085_2019-10-18_final
2019-10-19 10:22:53	ga_ls8c_ard_3-1-0_100085_2019-10-19_final
2019-12-05 09:39:33	ga_ls8c_ard_3-1-0_093085_2019-12-05_final
2019-12-05 09:39:57	ga_ls8c_ard_3-1-0_093086_2019-12-05_final
2019-12-06 10:22:48	ga_ls8c_ard_3-1-0_100085_2019-12-06_final
2021-01-04 10:04:13	ga_ls8c_ard_3-2-0_097085_2021-01-04_final
2021-01-04 10:04:37	ga_ls8c_ard_3-2-0_097086_2021-01-04_final
2021-01-06 09:52:14	ga_ls8c_ard_3-2-0_095086_2021-01-06_final
2021-02-02 09:33:35	ga_ls8c_ard_3-2-0_092086_2021-02-02_final
2021-04-09 09:20:49	ga_ls8c_ard_3-2-0_090086_2021-04-08_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