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
2017-04-08 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
2018-05-26 09:26:08	ga_ls8c_ard_3-0-0_091086_2018-05-25_final
2018-06-02 09:32:14	ga_ls8c_ard_3-0-0_092086_2018-06-02_final
2018-06-02 11:10:43	ga_ls8c_ard_3-0-0_108085_2018-06-02_final
2018-06-03 10:15:06	ga_ls8c_ard_3-0-0_099085_2018-06-03_final
2018-06-04 09:19:28	ga_ls8c_ard_3-0-0_090085_2018-06-03_final
2018-06-04 09:19:52	ga_ls8c_ard_3-0-0_090086_2018-06-03_final
2018-06-05 10:02:44	ga_ls8c_ard_3-0-0_097085_2018-06-05_final
2018-06-05 10:03:08	ga_ls8c_ard_3-0-0_097086_2018-06-05_final
2018-07-29 09:26:08	ga_ls8c_ard_3-0-0_091085_2018-07-28_final
2018-07-29 09:26:32	ga_ls8c_ard_3-0-0_091086_2018-07-28_final
2018-07-29 11:05:01	ga_ls8c_ard_3-0-0_107085_2018-07-29_final
2018-08-05 09:32:47	ga_ls8c_ard_3-0-0_092086_2018-08-05_final
2018-08-05 11:11:16	ga_ls8c_ard_3-0-0_108085_2018-08-05_final
2018-08-06 10:15:40	ga_ls8c_ard_3-0-0_099085_2018-08-06_final
2018-08-07 09:20:03	ga_ls8c_ard_3-0-0_090085_2018-08-06_final
2018-08-07 09:20:27	ga_ls8c_ard_3-0-0_090086_2018-08-06_final
2018-08-08 10:03:19	ga_ls8c_ard_3-0-0_097085_2018-08-08_final
2018-08-08 10:03:43	ga_ls8c_ard_3-0-0_097086_2018-08-08_final
2018-08-26 09:51:06	ga_ls8c_ard_3-0-0_095085_2018-08-26_final
2018-08-26 09:51:30	ga_ls8c_ard_3-0-0_095086_2018-08-26_final
2018-08-26 11:29:59	ga_ls8c_ard_3-0-0_111085_2018-08-26_final
2018-08-28 09:38:46	ga_ls8c_ard_3-0-0_093085_2018-08-28_final
2018-08-28 09:39:10	ga_ls8c_ard_3-0-0_093086_2018-08-28_final
2018-08-28 11:17:39	ga_ls8c_ard_3-0-0_109085_2018-08-28_final
2018-08-29 10:22:02	ga_ls8c_ard_3-0-0_100085_2018-08-29_final
2018-09-06 09:33:02	ga_ls8c_ard_3-0-0_092086_2018-09-06_final
2018-09-06 11:11:31	ga_ls8c_ard_3-0-0_108085_2018-09-06_final
2018-09-07 10:15:54	ga_ls8c_ard_3-0-0_099085_2018-09-07_final
2018-09-08 09:20:17	ga_ls8c_ard_3-0-0_090085_2018-09-07_final
2018-09-08 09:20:41	ga_ls8c_ard_3-0-0_090086_2018-09-07_final
2018-09-09 10:03:33	ga_ls8c_ard_3-0-0_097085_2018-09-09_final
2018-09-09 10:03:57	ga_ls8c_ard_3-0-0_097086_2018-09-09_final
2018-09-15 09:26:30	ga_ls8c_ard_3-0-0_091085_2018-09-14_final
2018-09-15 09:26:53	ga_ls8c_ard_3-0-0_091086_2018-09-14_final
2018-09-15 11:05:23	ga_ls8c_ard_3-0-0_107085_2018-09-15_final
2018-10-08 09:33:14	ga_ls8c_ard_3-0-0_092086_2018-10-08_final
2018-10-08 11:11:44	ga_ls8c_ard_3-0-0_108085_2018-10-08_final
2018-10-09 10:16:07	ga_ls8c_ard_3-0-0_099085_2018-10-09_final
2018-10-10 09:20:30	ga_ls8c_ard_3-0-0_090085_2018-10-09_final
2018-10-10 09:20:54	ga_ls8c_ard_3-0-0_090086_2018-10-09_final
2018-10-11 10:04:10	ga_ls8c_ard_3-0-0_097086_2018-10-11_final
2018-10-15 11:17:57	ga_ls8c_ard_3-0-0_109085_2018-10-15_final
2018-10-16 10:22:20	ga_ls8c_ard_3-0-0_100085_2018-10-16_final
2018-10-17 09:27:07	ga_ls8c_ard_3-0-0_091086_2018-10-16_final
2018-10-17 11:05:36	ga_ls8c_ard_3-0-0_107085_2018-10-17_final
2018-11-09 09:33:23	ga_ls8c_ard_3-0-0_092086_2018-11-09_final
2018-11-09 11:11:52	ga_ls8c_ard_3-0-0_108085_2018-11-09_final
2018-11-10 10:16:15	ga_ls8c_ard_3-0-0_099085_2018-11-10_final
2018-11-11 09:20:37	ga_ls8c_ard_3-0-0_090085_2018-11-10_final
2018-11-11 09:21:01	ga_ls8c_ard_3-0-0_090086_2018-11-10_final
2018-11-12 10:04:17	ga_ls8c_ard_3-0-0_097086_2018-11-12_final
2018-11-18 09:26:48	ga_ls8c_ard_3-0-0_091085_2018-11-17_final
2018-11-18 09:27:12	ga_ls8c_ard_3-0-0_091086_2018-11-17_final
2018-11-18 11:05:41	ga_ls8c_ard_3-0-0_107085_2018-11-18_final
2019-01-05 09:27:08	ga_ls8c_ard_3-0-0_091086_2019-01-04_final
2019-01-05 11:05:37	ga_ls8c_ard_3-0-0_107085_2019-01-05_final
2019-01-15 10:03:47	ga_ls8c_ard_3-0-0_097085_2019-01-15_final
2019-01-15 10:04:11	ga_ls8c_ard_3-0-0_097086_2019-01-15_final
2019-02-27 09:45:30	ga_ls8c_ard_3-0-0_094086_2019-02-27_final
2019-06-03 09:45:09	ga_ls8c_ard_3-0-0_094085_2019-06-03_final
2019-06-03 09:45:33	ga_ls8c_ard_3-0-0_094086_2019-06-03_final
2019-06-03 11:24:02	ga_ls8c_ard_3-0-0_110085_2019-06-03_final
2020-03-01 09:45:46	ga_ls8c_ard_3-1-0_094086_2020-03-01_final
2020-03-03 09:33:24	ga_ls8c_ard_3-1-0_092086_2020-03-03_final
2020-03-13 10:10:24	ga_ls8c_ard_3-1-0_098086_2020-03-13_final
2020-03-14 09:14:47	ga_ls8c_ard_3-1-0_089086_2020-03-13_final
2020-04-04 09:33:07	ga_ls8c_ard_3-1-0_092086_2020-04-04_final
2020-04-30 10:10:00	ga_ls8c_ard_3-1-0_098086_2020-04-30_final
2020-05-01 09:14:22	ga_ls8c_ard_3-1-0_089086_2020-04-30_final
2020-05-31 09:26:21	ga_ls8c_ard_3-1-0_091085_2020-05-30_final
2020-05-31 09:26:45	ga_ls8c_ard_3-1-0_091086_2020-05-30_final
2020-05-31 11:05:14	ga_ls8c_ard_3-1-0_107085_2020-05-31_final
2020-06-05 09:44:57	ga_ls8c_ard_3-1-0_094085_2020-06-05_final
2020-06-05 09:45:21	ga_ls8c_ard_3-1-0_094086_2020-06-05_final
2020-06-05 11:23:50	ga_ls8c_ard_3-1-0_110085_2020-06-05_final
2020-06-07 09:33:01	ga_ls8c_ard_3-1-0_092086_2020-06-07_final
2020-06-16 09:26:31	ga_ls8c_ard_3-1-0_091085_2020-06-15_final
2020-06-16 09:26:55	ga_ls8c_ard_3-1-0_091086_2020-06-15_final
2020-06-16 11:05:24	ga_ls8c_ard_3-1-0_107085_2020-06-16_final
2020-06-17 10:09:48	ga_ls8c_ard_3-1-0_098085_2020-06-17_final
2020-06-17 10:10:12	ga_ls8c_ard_3-1-0_098086_2020-06-17_final
2020-06-18 09:14:11	ga_ls8c_ard_3-1-0_089085_2020-06-17_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