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
2017-07-17 09:33:17	ga_ls8c_ard_3-0-0_092086_2017-07-17_final
2017-07-17 11:11:46	ga_ls8c_ard_3-0-0_108085_2017-07-17_final
2017-07-18 10:16:10	ga_ls8c_ard_3-0-0_099085_2017-07-18_final
2017-07-19 09:20:33	ga_ls8c_ard_3-0-0_090085_2017-07-18_final
2017-07-19 09:20:57	ga_ls8c_ard_3-0-0_090086_2017-07-18_final
2017-07-20 10:04:13	ga_ls8c_ard_3-0-0_097086_2017-07-20_final
2017-07-27 10:10:03	ga_ls8c_ard_3-0-0_098085_2017-07-27_final
2017-07-27 10:10:27	ga_ls8c_ard_3-0-0_098086_2017-07-27_final
2017-07-28 09:14:27	ga_ls8c_ard_3-0-0_089085_2017-07-27_final
2017-07-28 09:14:51	ga_ls8c_ard_3-0-0_089086_2017-07-27_final
2017-08-02 09:33:25	ga_ls8c_ard_3-0-0_092086_2017-08-02_final
2017-08-02 11:11:54	ga_ls8c_ard_3-0-0_108085_2017-08-02_final
2017-08-03 10:16:17	ga_ls8c_ard_3-0-0_099085_2017-08-03_final
2017-08-04 09:21:04	ga_ls8c_ard_3-0-0_090086_2017-08-03_final
2017-08-05 10:03:57	ga_ls8c_ard_3-0-0_097085_2017-08-05_final
2017-08-05 10:04:20	ga_ls8c_ard_3-0-0_097086_2017-08-05_final
2017-08-18 09:33:31	ga_ls8c_ard_3-0-0_092086_2017-08-18_final
2017-08-18 11:12:00	ga_ls8c_ard_3-0-0_108085_2017-08-18_final
2017-08-20 09:20:46	ga_ls8c_ard_3-0-0_090085_2017-08-19_final
2017-08-20 09:21:10	ga_ls8c_ard_3-0-0_090086_2017-08-19_final
2017-08-21 10:04:02	ga_ls8c_ard_3-0-0_097085_2017-08-21_final
2017-08-21 10:04:25	ga_ls8c_ard_3-0-0_097086_2017-08-21_final
2017-08-30 09:58:16	ga_ls8c_ard_3-0-0_096086_2017-08-30_final
2017-08-30 11:36:45	ga_ls8c_ard_3-0-0_112085_2017-08-30_final
2017-09-04 10:16:25	ga_ls8c_ard_3-0-0_099085_2017-09-04_final
2017-09-05 09:20:48	ga_ls8c_ard_3-0-0_090085_2017-09-04_final
2017-09-05 09:21:12	ga_ls8c_ard_3-0-0_090086_2017-09-04_final
2017-10-05 09:33:42	ga_ls8c_ard_3-0-0_092086_2017-10-05_final
2017-10-06 10:16:34	ga_ls8c_ard_3-0-0_099085_2017-10-06_final
2017-10-07 09:20:57	ga_ls8c_ard_3-0-0_090085_2017-10-06_final
2017-10-07 09:21:21	ga_ls8c_ard_3-0-0_090086_2017-10-06_final
2017-10-08 10:04:13	ga_ls8c_ard_3-0-0_097085_2017-10-08_final
2017-10-08 10:04:37	ga_ls8c_ard_3-0-0_097086_2017-10-08_final
2017-10-15 10:10:49	ga_ls8c_ard_3-0-0_098086_2017-10-15_final
2017-10-16 09:15:12	ga_ls8c_ard_3-0-0_089086_2017-10-15_final
2018-09-22 09:33:06	ga_ls8c_ard_3-0-0_092086_2018-09-22_final
2018-09-22 11:11:35	ga_ls8c_ard_3-0-0_108085_2018-09-22_final
2018-09-23 10:15:59	ga_ls8c_ard_3-0-0_099085_2018-09-23_final
2018-09-24 09:20:22	ga_ls8c_ard_3-0-0_090085_2018-09-23_final
2018-09-24 09:20:46	ga_ls8c_ard_3-0-0_090086_2018-09-23_final
2018-09-25 10:03:38	ga_ls8c_ard_3-0-0_097085_2018-09-25_final
2018-09-25 10:04:02	ga_ls8c_ard_3-0-0_097086_2018-09-25_final
2018-09-27 09:51:42	ga_ls8c_ard_3-0-0_095086_2018-09-27_final
2018-09-29 09:38:57	ga_ls8c_ard_3-0-0_093085_2018-09-29_final
2018-09-29 09:39:21	ga_ls8c_ard_3-0-0_093086_2018-09-29_final
2018-10-29 09:51:54	ga_ls8c_ard_3-0-0_095086_2018-10-29_final
2018-10-31 09:39:32	ga_ls8c_ard_3-0-0_093086_2018-10-31_final
2018-12-27 09:33:20	ga_ls8c_ard_3-0-0_092086_2018-12-27_final
2018-12-29 09:20:34	ga_ls8c_ard_3-0-0_090085_2018-12-28_final
2018-12-29 09:20:58	ga_ls8c_ard_3-0-0_090086_2018-12-28_final
2019-01-03 11:17:59	ga_ls8c_ard_3-0-0_109085_2019-01-03_final
2019-07-05 09:45:20	ga_ls8c_ard_3-1-0_094085_2019-07-05_final
2019-07-05 09:45:44	ga_ls8c_ard_3-1-0_094086_2019-07-05_final
2019-07-05 11:24:13	ga_ls8c_ard_3-1-0_110085_2019-07-05_final
2019-07-07 09:33:22	ga_ls8c_ard_3-1-0_092086_2019-07-07_final
2019-08-17 09:27:25	ga_ls8c_ard_3-1-0_091086_2019-08-16_final
2019-08-18 10:10:17	ga_ls8c_ard_3-1-0_098085_2019-08-18_final
2019-08-18 10:10:41	ga_ls8c_ard_3-1-0_098086_2019-08-18_final
2019-08-19 09:14:40	ga_ls8c_ard_3-1-0_089085_2019-08-18_final
2019-08-19 09:15:04	ga_ls8c_ard_3-1-0_089086_2019-08-18_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
2020-03-29 10:10:15	ga_ls8c_ard_3-1-0_098086_2020-03-29_final
2020-03-30 09:14:38	ga_ls8c_ard_3-1-0_089086_2020-03-29_final
2020-03-31 09:57:53	ga_ls8c_ard_3-1-0_096086_2020-03-31_final
2020-04-06 09:20:45	ga_ls8c_ard_3-1-0_090086_2020-04-05_final
2020-04-07 10:04:00	ga_ls8c_ard_3-1-0_097086_2020-04-07_final
2020-04-22 09:20:38	ga_ls8c_ard_3-1-0_090086_2020-04-21_final
2020-04-23 10:03:53	ga_ls8c_ard_3-1-0_097086_2020-04-23_final
2020-06-21 09:45:07	ga_ls8c_ard_3-1-0_094085_2020-06-21_final
2020-06-21 09:45:31	ga_ls8c_ard_3-1-0_094086_2020-06-21_final
2020-06-21 11:24:00	ga_ls8c_ard_3-1-0_110085_2020-06-21_final
2020-06-23 09:33:10	ga_ls8c_ard_3-1-0_092086_2020-06-23_final
2020-06-23 11:11:39	ga_ls8c_ard_3-1-0_108085_2020-06-23_final
2020-06-26 10:03:42	ga_ls8c_ard_3-1-0_097085_2020-06-26_final
2020-06-26 10:04:05	ga_ls8c_ard_3-1-0_097086_2020-06-26_final
2020-06-28 09:51:45	ga_ls8c_ard_3-1-0_095086_2020-06-28_final
2020-06-28 11:30:14	ga_ls8c_ard_3-1-0_111085_2020-06-28_final
2020-07-23 09:45:19	ga_ls8c_ard_3-1-0_094085_2020-07-23_final
2020-07-23 09:45:43	ga_ls8c_ard_3-1-0_094086_2020-07-23_final
2020-07-25 09:33:22	ga_ls8c_ard_3-1-0_092086_2020-07-25_final
2020-07-25 11:11:51	ga_ls8c_ard_3-1-0_108085_2020-07-25_final
2020-09-25 09:46:06	ga_ls8c_ard_3-1-0_094086_2020-09-25_final
2020-09-27 09:33:45	ga_ls8c_ard_3-1-0_092086_2020-09-27_final
2020-09-27 11:12:14	ga_ls8c_ard_3-1-0_108085_2020-09-27_final
2023-02-01 09:27:39	ga_ls8c_ard_3-2-1_091086_2023-01-31_final
2023-02-03 09:15:17	ga_ls8c_ard_3-2-1_089086_2023-02-02_final
2023-02-04 09:58:33	ga_ls8c_ard_3-2-1_096086_2023-02-04_final
2023-02-08 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-02-08_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-15 09:39:54	ga_ls8c_ard_3-2-1_093086_2023-02-15_final
2023-02-17 09:27:30	ga_ls8c_ard_3-2-1_091086_2023-02-16_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-20 09:58:21	ga_ls8c_ard_3-2-1_096086_2023-02-20_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-24 09:33:31	ga_ls8c_ard_3-2-1_092086_2023-02-24_final
2023-02-26 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-02-25_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