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
2017-03-25 09:45:26	ga_ls8c_ard_3-0-0_094086_2017-03-25_final
2017-03-25 11:23:55	ga_ls8c_ard_3-0-0_110085_2017-03-25_final
2017-04-08 09:57:42	ga_ls8c_ard_3-0-0_096086_2017-04-08_final
2017-04-10 09:45:19	ga_ls8c_ard_3-0-0_094086_2017-04-10_final
2017-04-24 09:57:32	ga_ls8c_ard_3-0-0_096086_2017-04-24_final
2017-04-26 09:45:09	ga_ls8c_ard_3-0-0_094086_2017-04-26_final
2017-05-12 09:44:48	ga_ls8c_ard_3-0-0_094085_2017-05-12_final
2017-05-12 09:45:12	ga_ls8c_ard_3-0-0_094086_2017-05-12_final
2017-05-12 11:23:41	ga_ls8c_ard_3-0-0_110085_2017-05-12_final
2017-06-11 09:57:27	ga_ls8c_ard_3-0-0_096085_2017-06-11_final
2017-06-11 09:57:51	ga_ls8c_ard_3-0-0_096086_2017-06-11_final
2017-06-11 11:36:20	ga_ls8c_ard_3-0-0_112085_2017-06-11_final
2017-06-13 09:45:30	ga_ls8c_ard_3-0-0_094086_2017-06-13_final
2017-06-13 11:23:59	ga_ls8c_ard_3-0-0_110085_2017-06-13_final
2017-06-27 09:57:32	ga_ls8c_ard_3-0-0_096085_2017-06-27_final
2017-06-27 09:57:56	ga_ls8c_ard_3-0-0_096086_2017-06-27_final
2017-06-27 11:36:25	ga_ls8c_ard_3-0-0_112085_2017-06-27_final
2017-06-29 09:45:35	ga_ls8c_ard_3-0-0_094086_2017-06-29_final
2017-06-29 11:24:04	ga_ls8c_ard_3-0-0_110085_2017-06-29_final
2018-02-10 09:33:17	ga_ls8c_ard_3-0-0_092086_2018-02-10_final
2018-02-12 09:20:31	ga_ls8c_ard_3-0-0_090085_2018-02-11_final
2018-02-12 09:20:55	ga_ls8c_ard_3-0-0_090086_2018-02-11_final
2018-02-13 10:03:46	ga_ls8c_ard_3-0-0_097085_2018-02-13_final
2018-02-13 10:04:10	ga_ls8c_ard_3-0-0_097086_2018-02-13_final
2018-02-17 11:17:55	ga_ls8c_ard_3-0-0_109085_2018-02-17_final
2018-02-26 09:33:11	ga_ls8c_ard_3-0-0_092086_2018-02-26_final
2018-02-26 11:11:40	ga_ls8c_ard_3-0-0_108085_2018-02-26_final
2018-02-28 09:20:48	ga_ls8c_ard_3-0-0_090086_2018-02-27_final
2018-03-01 10:04:03	ga_ls8c_ard_3-0-0_097086_2018-03-01_final
2018-03-30 09:32:55	ga_ls8c_ard_3-0-0_092086_2018-03-30_final
2018-04-01 09:20:08	ga_ls8c_ard_3-0-0_090085_2018-03-31_final
2018-04-01 09:20:32	ga_ls8c_ard_3-0-0_090086_2018-03-31_final
2018-04-02 10:03:47	ga_ls8c_ard_3-0-0_097086_2018-04-02_final
2018-04-15 09:32:46	ga_ls8c_ard_3-0-0_092086_2018-04-15_final
2018-04-16 10:15:37	ga_ls8c_ard_3-0-0_099085_2018-04-16_final
2018-04-17 09:20:23	ga_ls8c_ard_3-0-0_090086_2018-04-16_final
2018-04-18 10:03:38	ga_ls8c_ard_3-0-0_097086_2018-04-18_final
2018-04-20 09:51:15	ga_ls8c_ard_3-0-0_095086_2018-04-20_final
2018-04-22 09:38:53	ga_ls8c_ard_3-0-0_093086_2018-04-22_final
2018-10-02 10:09:53	ga_ls8c_ard_3-0-0_098085_2018-10-02_final
2018-10-02 10:10:17	ga_ls8c_ard_3-0-0_098086_2018-10-02_final
2018-10-03 09:14:16	ga_ls8c_ard_3-0-0_089085_2018-10-02_final
2018-10-03 09:14:40	ga_ls8c_ard_3-0-0_089086_2018-10-02_final
2018-10-18 10:09:59	ga_ls8c_ard_3-0-0_098085_2018-10-18_final
2018-10-18 10:10:23	ga_ls8c_ard_3-0-0_098086_2018-10-18_final
2018-10-19 09:14:22	ga_ls8c_ard_3-0-0_089085_2018-10-18_final
2018-10-19 09:14:46	ga_ls8c_ard_3-0-0_089086_2018-10-18_final
2018-10-24 09:33:20	ga_ls8c_ard_3-0-0_092086_2018-10-24_final
2018-10-24 11:11:49	ga_ls8c_ard_3-0-0_108085_2018-10-24_final
2018-10-25 10:16:12	ga_ls8c_ard_3-0-0_099085_2018-10-25_final
2018-10-26 09:20:35	ga_ls8c_ard_3-0-0_090085_2018-10-25_final
2018-10-26 09:20:59	ga_ls8c_ard_3-0-0_090086_2018-10-25_final
2018-10-27 10:03:51	ga_ls8c_ard_3-0-0_097085_2018-10-27_final
2018-10-27 10:04:15	ga_ls8c_ard_3-0-0_097086_2018-10-27_final
2018-11-03 10:10:03	ga_ls8c_ard_3-0-0_098085_2018-11-03_final
2018-11-03 10:10:27	ga_ls8c_ard_3-0-0_098086_2018-11-03_final
2018-11-04 09:14:26	ga_ls8c_ard_3-0-0_089085_2018-11-03_final
2018-11-04 09:14:50	ga_ls8c_ard_3-0-0_089086_2018-11-03_final
2018-11-25 09:33:23	ga_ls8c_ard_3-0-0_092086_2018-11-25_final
2018-11-25 11:11:52	ga_ls8c_ard_3-0-0_108085_2018-11-25_final
2018-11-26 10:16:14	ga_ls8c_ard_3-0-0_099085_2018-11-26_final
2018-11-27 09:20:37	ga_ls8c_ard_3-0-0_090085_2018-11-26_final
2018-11-27 09:21:01	ga_ls8c_ard_3-0-0_090086_2018-11-26_final
2018-11-28 10:03:52	ga_ls8c_ard_3-0-0_097085_2018-11-28_final
2018-11-28 10:04:16	ga_ls8c_ard_3-0-0_097086_2018-11-28_final
2018-12-05 10:10:02	ga_ls8c_ard_3-0-0_098085_2018-12-05_final
2018-12-05 10:10:26	ga_ls8c_ard_3-0-0_098086_2018-12-05_final
2018-12-06 09:14:25	ga_ls8c_ard_3-0-0_089085_2018-12-05_final
2018-12-06 09:14:49	ga_ls8c_ard_3-0-0_089086_2018-12-05_final
2018-12-14 10:03:49	ga_ls8c_ard_3-0-0_097085_2018-12-14_final
2018-12-14 10:04:13	ga_ls8c_ard_3-0-0_097086_2018-12-14_final
2018-12-21 10:10:00	ga_ls8c_ard_3-0-0_098085_2018-12-21_final
2018-12-21 10:10:24	ga_ls8c_ard_3-0-0_098086_2018-12-21_final
2018-12-22 09:14:23	ga_ls8c_ard_3-0-0_089085_2018-12-21_final
2018-12-22 09:14:47	ga_ls8c_ard_3-0-0_089086_2018-12-21_final
2019-01-30 09:20:28	ga_ls8c_ard_3-0-0_090085_2019-01-29_final
2019-01-30 09:20:52	ga_ls8c_ard_3-0-0_090086_2019-01-29_final
2019-01-31 10:03:43	ga_ls8c_ard_3-0-0_097085_2019-01-31_final
2019-01-31 10:04:07	ga_ls8c_ard_3-0-0_097086_2019-01-31_final
2019-02-02 09:51:21	ga_ls8c_ard_3-0-0_095085_2019-02-02_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
2019-02-23 10:10:15	ga_ls8c_ard_3-0-0_098086_2019-02-23_final
2019-02-24 09:14:37	ga_ls8c_ard_3-0-0_089086_2019-02-23_final
2019-04-09 11:17:37	ga_ls8c_ard_3-1-0_109085_2019-04-09_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
2019-05-14 10:09:41	ga_ls8c_ard_3-0-0_098085_2019-05-14_final
2019-05-14 10:10:05	ga_ls8c_ard_3-0-0_098086_2019-05-14_final
2019-05-15 09:14:05	ga_ls8c_ard_3-0-0_089085_2019-05-14_final
2019-05-15 09:14:29	ga_ls8c_ard_3-0-0_089086_2019-05-14_final
2019-05-16 09:57:21	ga_ls8c_ard_3-0-0_096085_2019-05-16_final
2019-05-16 09:57:45	ga_ls8c_ard_3-0-0_096086_2019-05-16_final
2019-05-16 11:36:14	ga_ls8c_ard_3-0-0_112085_2019-05-16_final
2019-05-25 09:51:39	ga_ls8c_ard_3-0-0_095086_2019-05-25_final
2019-05-25 11:30:09	ga_ls8c_ard_3-0-0_111085_2019-05-25_final
2019-05-27 09:38:55	ga_ls8c_ard_3-0-0_093085_2019-05-27_final
2019-05-27 09:39:19	ga_ls8c_ard_3-0-0_093086_2019-05-27_final
2019-05-27 11:17:48	ga_ls8c_ard_3-0-0_109085_2019-05-27_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