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
2016-08-16 10:16:23	ga_ls8c_ard_3-0-0_099085_2016-08-16_final
2016-08-17 09:21:10	ga_ls8c_ard_3-0-0_090086_2016-08-16_final
2016-08-18 10:04:02	ga_ls8c_ard_3-0-0_097085_2016-08-18_final
2016-08-18 10:04:26	ga_ls8c_ard_3-0-0_097086_2016-08-18_final
2016-09-02 09:21:17	ga_ls8c_ard_3-0-0_090086_2016-09-01_final
2016-09-03 10:04:09	ga_ls8c_ard_3-0-0_097085_2016-09-03_final
2016-09-03 10:04:33	ga_ls8c_ard_3-0-0_097086_2016-09-03_final
2016-09-08 10:22:42	ga_ls8c_ard_3-0-0_100085_2016-09-08_final
2016-09-09 09:27:29	ga_ls8c_ard_3-0-0_091086_2016-09-08_final
2016-09-12 09:58:00	ga_ls8c_ard_3-0-0_096085_2016-09-12_final
2016-09-12 09:58:24	ga_ls8c_ard_3-0-0_096086_2016-09-12_final
2016-09-12 11:36:53	ga_ls8c_ard_3-0-0_112085_2016-09-12_final
2016-09-14 09:46:02	ga_ls8c_ard_3-0-0_094086_2016-09-14_final
2016-09-14 11:24:31	ga_ls8c_ard_3-0-0_110085_2016-09-14_final
2016-09-21 09:51:50	ga_ls8c_ard_3-0-0_095085_2016-09-21_final
2016-09-21 09:52:14	ga_ls8c_ard_3-0-0_095086_2016-09-21_final
2016-09-21 11:30:43	ga_ls8c_ard_3-0-0_111085_2016-09-21_final
2016-09-23 09:39:52	ga_ls8c_ard_3-0-0_093086_2016-09-23_final
2016-09-25 09:27:30	ga_ls8c_ard_3-0-0_091086_2016-09-24_final
2016-09-25 11:05:59	ga_ls8c_ard_3-0-0_107085_2016-09-25_final
2016-09-26 10:10:46	ga_ls8c_ard_3-0-0_098086_2016-09-26_final
2016-09-27 09:15:08	ga_ls8c_ard_3-0-0_089086_2016-09-26_final
2016-09-28 09:58:00	ga_ls8c_ard_3-0-0_096085_2016-09-28_final
2016-09-28 09:58:24	ga_ls8c_ard_3-0-0_096086_2016-09-28_final
2016-09-30 09:46:02	ga_ls8c_ard_3-0-0_094086_2016-09-30_final
2016-09-30 11:24:31	ga_ls8c_ard_3-0-0_110085_2016-09-30_final
2016-10-02 09:33:42	ga_ls8c_ard_3-0-0_092086_2016-10-02_final
2016-10-02 11:12:11	ga_ls8c_ard_3-0-0_108085_2016-10-02_final
2016-10-04 09:20:57	ga_ls8c_ard_3-0-0_090085_2016-10-03_final
2016-10-04 09:21:21	ga_ls8c_ard_3-0-0_090086_2016-10-03_final
2016-10-05 10:04:37	ga_ls8c_ard_3-0-0_097086_2016-10-05_final
2016-10-07 09:52:16	ga_ls8c_ard_3-0-0_095086_2016-10-07_final
2016-10-09 09:39:56	ga_ls8c_ard_3-0-0_093086_2016-10-09_final
2016-10-20 09:21:02	ga_ls8c_ard_3-0-0_090085_2016-10-19_final
2016-10-20 09:21:26	ga_ls8c_ard_3-0-0_090086_2016-10-19_final
2016-10-21 10:04:42	ga_ls8c_ard_3-0-0_097086_2016-10-21_final
2016-10-25 11:18:28	ga_ls8c_ard_3-0-0_109085_2016-10-25_final
2016-10-30 09:58:07	ga_ls8c_ard_3-0-0_096085_2016-10-30_final
2016-10-30 09:58:31	ga_ls8c_ard_3-0-0_096086_2016-10-30_final
2016-11-01 09:46:10	ga_ls8c_ard_3-0-0_094086_2016-11-01_final
2016-11-01 11:24:39	ga_ls8c_ard_3-0-0_110085_2016-11-01_final
2016-11-06 10:04:41	ga_ls8c_ard_3-0-0_097086_2016-11-06_final
2016-11-08 09:52:19	ga_ls8c_ard_3-0-0_095086_2016-11-08_final
2016-11-08 11:30:48	ga_ls8c_ard_3-0-0_111085_2016-11-08_final
2016-11-10 09:39:57	ga_ls8c_ard_3-0-0_093086_2016-11-10_final
2016-11-10 11:18:26	ga_ls8c_ard_3-0-0_109085_2016-11-10_final
2016-11-12 09:27:36	ga_ls8c_ard_3-0-0_091086_2016-11-11_final
2016-11-13 10:10:28	ga_ls8c_ard_3-0-0_098085_2016-11-13_final
2016-11-13 10:10:52	ga_ls8c_ard_3-0-0_098086_2016-11-13_final
2016-11-14 09:14:51	ga_ls8c_ard_3-0-0_089085_2016-11-13_final
2016-11-14 09:15:14	ga_ls8c_ard_3-0-0_089086_2016-11-13_final
2016-11-15 09:58:30	ga_ls8c_ard_3-0-0_096086_2016-11-15_final
2016-11-17 09:46:09	ga_ls8c_ard_3-0-0_094086_2016-11-17_final
2016-11-19 09:33:47	ga_ls8c_ard_3-0-0_092086_2016-11-19_final
2016-11-21 09:21:02	ga_ls8c_ard_3-0-0_090085_2016-11-20_final
2016-11-21 09:21:26	ga_ls8c_ard_3-0-0_090086_2016-11-20_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
2017-10-21 09:33:45	ga_ls8c_ard_3-0-0_092086_2017-10-21_final
2017-10-22 10:16:37	ga_ls8c_ard_3-0-0_099085_2017-10-22_final
2017-10-23 09:21:24	ga_ls8c_ard_3-0-0_090086_2017-10-22_final
2017-11-04 09:46:06	ga_ls8c_ard_3-0-0_094086_2017-11-04_final
2017-11-06 09:33:44	ga_ls8c_ard_3-0-0_092086_2017-11-06_final
2017-11-08 09:21:22	ga_ls8c_ard_3-0-0_090086_2017-11-07_final
2017-11-09 10:04:38	ga_ls8c_ard_3-0-0_097086_2017-11-09_final
2017-12-20 09:58:22	ga_ls8c_ard_3-0-0_096086_2017-12-20_final
2017-12-22 09:46:01	ga_ls8c_ard_3-0-0_094086_2017-12-22_final
2017-12-24 09:33:38	ga_ls8c_ard_3-0-0_092086_2017-12-24_final
2017-12-26 09:21:16	ga_ls8c_ard_3-0-0_090086_2017-12-25_final
2017-12-27 10:04:32	ga_ls8c_ard_3-0-0_097086_2017-12-27_final
2018-01-09 09:33:33	ga_ls8c_ard_3-0-0_092086_2018-01-09_final
2018-01-11 09:20:47	ga_ls8c_ard_3-0-0_090085_2018-01-10_final
2018-01-11 09:21:10	ga_ls8c_ard_3-0-0_090086_2018-01-10_final
2018-01-12 10:04:26	ga_ls8c_ard_3-0-0_097086_2018-01-12_final
2018-01-28 10:04:17	ga_ls8c_ard_3-0-0_097086_2018-01-28_final
2022-11-15 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-14_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-16 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-11-16_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_final
2022-11-20 09:33:58	ga_ls8c_ard_3-2-1_092086_2022-11-20_final
2022-11-22 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-11-21_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-25 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-11-25_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-11-30 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-30_final
2022-12-04 09:46:22	ga_ls8c_ard_3-2-1_094086_2022-12-04_final
2023-03-21 09:27:09	ga_ls8c_ard_3-2-1_091086_2023-03-20_final
2023-03-23 09:14:45	ga_ls8c_ard_3-2-1_089086_2023-03-22_final
2023-03-26 09:45:38	ga_ls8c_ard_3-2-1_094086_2023-03-26_final
2023-03-28 09:33:16	ga_ls8c_ard_3-2-1_092086_2023-03-28_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