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
2017-03-23 09:57:48	ga_ls8c_ard_3-0-0_096086_2017-03-23_final
2017-03-25 09:45:02	ga_ls8c_ard_3-0-0_094085_2017-03-25_final
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
2017-04-24 09:57:32	ga_ls8c_ard_3-0-0_096086_2017-04-24_final
2017-04-24 11:36:01	ga_ls8c_ard_3-0-0_112085_2017-04-24_final
2017-04-26 09:45:09	ga_ls8c_ard_3-0-0_094086_2017-04-26_final
2017-05-10 09:57:08	ga_ls8c_ard_3-0-0_096085_2017-05-10_final
2017-05-10 09:57:32	ga_ls8c_ard_3-0-0_096086_2017-05-10_final
2017-05-10 11:36:01	ga_ls8c_ard_3-0-0_112085_2017-05-10_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
2017-05-19 09:51:04	ga_ls8c_ard_3-0-0_095085_2017-05-19_final
2017-05-19 09:51:28	ga_ls8c_ard_3-0-0_095086_2017-05-19_final
2017-05-19 11:29:57	ga_ls8c_ard_3-0-0_111085_2017-05-19_final
2017-05-21 09:38:44	ga_ls8c_ard_3-0-0_093085_2017-05-21_final
2017-05-21 09:39:08	ga_ls8c_ard_3-0-0_093086_2017-05-21_final
2017-05-21 11:17:37	ga_ls8c_ard_3-0-0_109085_2017-05-21_final
2017-05-22 10:22:00	ga_ls8c_ard_3-0-0_100085_2017-05-22_final
2017-05-28 09:44:59	ga_ls8c_ard_3-0-0_094085_2017-05-28_final
2017-05-28 11:23:52	ga_ls8c_ard_3-0-0_110085_2017-05-28_final
2017-06-04 09:51:13	ga_ls8c_ard_3-0-0_095085_2017-06-04_final
2017-06-04 09:51:37	ga_ls8c_ard_3-0-0_095086_2017-06-04_final
2017-06-04 11:30:06	ga_ls8c_ard_3-0-0_111085_2017-06-04_final
2017-06-06 09:38:52	ga_ls8c_ard_3-0-0_093085_2017-06-06_final
2017-06-06 09:39:16	ga_ls8c_ard_3-0-0_093086_2017-06-06_final
2017-06-06 11:17:45	ga_ls8c_ard_3-0-0_109085_2017-06-06_final
2017-06-07 10:22:09	ga_ls8c_ard_3-0-0_100085_2017-06-07_final
2017-06-13 09:45:06	ga_ls8c_ard_3-0-0_094085_2017-06-13_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
2017-06-20 09:51:19	ga_ls8c_ard_3-0-0_095085_2017-06-20_final
2017-06-20 09:51:43	ga_ls8c_ard_3-0-0_095086_2017-06-20_final
2017-06-20 11:30:12	ga_ls8c_ard_3-0-0_111085_2017-06-20_final
2017-06-22 09:38:58	ga_ls8c_ard_3-0-0_093085_2017-06-22_final
2017-06-22 09:39:22	ga_ls8c_ard_3-0-0_093086_2017-06-22_final
2017-06-22 11:17:51	ga_ls8c_ard_3-0-0_109085_2017-06-22_final
2017-06-23 10:22:14	ga_ls8c_ard_3-0-0_100085_2017-06-23_final
2017-07-06 09:51:23	ga_ls8c_ard_3-0-0_095085_2017-07-06_final
2017-07-06 09:51:47	ga_ls8c_ard_3-0-0_095086_2017-07-06_final
2017-07-06 11:30:16	ga_ls8c_ard_3-0-0_111085_2017-07-06_final
2017-07-08 09:39:02	ga_ls8c_ard_3-0-0_093085_2017-07-08_final
2017-07-08 09:39:26	ga_ls8c_ard_3-0-0_093086_2017-07-08_final
2017-07-08 11:17:55	ga_ls8c_ard_3-0-0_109085_2017-07-08_final
2017-07-09 10:22:17	ga_ls8c_ard_3-0-0_100085_2017-07-09_final
2018-05-15 09:44:50	ga_ls8c_ard_3-0-0_094086_2018-05-15_final
2018-05-15 11:23:19	ga_ls8c_ard_3-0-0_110085_2018-05-15_final
2018-05-17 09:32:26	ga_ls8c_ard_3-0-0_092086_2018-05-17_final
2018-05-22 09:50:55	ga_ls8c_ard_3-0-0_095086_2018-05-22_final
2018-05-24 09:38:32	ga_ls8c_ard_3-0-0_093086_2018-05-24_final
2018-06-07 09:50:23	ga_ls8c_ard_3-0-0_095085_2018-06-07_final
2018-06-07 09:50:47	ga_ls8c_ard_3-0-0_095086_2018-06-07_final
2018-06-07 11:29:16	ga_ls8c_ard_3-0-0_111085_2018-06-07_final
2018-06-09 09:38:03	ga_ls8c_ard_3-0-0_093085_2018-06-09_final
2018-06-09 09:38:27	ga_ls8c_ard_3-0-0_093086_2018-06-09_final
2018-06-09 11:16:56	ga_ls8c_ard_3-0-0_109085_2018-06-09_final
2018-06-10 10:21:19	ga_ls8c_ard_3-0-0_100085_2018-06-10_final
2018-06-11 09:25:43	ga_ls8c_ard_3-0-0_091085_2018-06-10_final
2018-06-11 09:26:07	ga_ls8c_ard_3-0-0_091086_2018-06-10_final
2018-06-11 11:04:36	ga_ls8c_ard_3-0-0_107085_2018-06-11_final
2018-07-13 09:26:01	ga_ls8c_ard_3-0-0_091085_2018-07-12_final
2018-07-13 09:26:25	ga_ls8c_ard_3-0-0_091086_2018-07-12_final
2018-07-13 11:04:54	ga_ls8c_ard_3-0-0_107085_2018-07-13_final
2018-08-10 09:50:59	ga_ls8c_ard_3-0-0_095085_2018-08-10_final
2018-08-10 09:51:23	ga_ls8c_ard_3-0-0_095086_2018-08-10_final
2018-08-10 11:29:52	ga_ls8c_ard_3-0-0_111085_2018-08-10_final
2018-08-12 09:38:38	ga_ls8c_ard_3-0-0_093085_2018-08-12_final
2018-08-12 09:39:02	ga_ls8c_ard_3-0-0_093086_2018-08-12_final
2018-08-12 11:17:31	ga_ls8c_ard_3-0-0_109085_2018-08-12_final
2018-08-13 10:21:54	ga_ls8c_ard_3-0-0_100085_2018-08-13_final
2018-08-14 09:26:17	ga_ls8c_ard_3-0-0_091085_2018-08-13_final
2018-08-14 09:26:41	ga_ls8c_ard_3-0-0_091086_2018-08-13_final
2018-08-14 11:05:11	ga_ls8c_ard_3-0-0_107085_2018-08-14_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
2018-10-13 09:51:25	ga_ls8c_ard_3-0-0_095085_2018-10-13_final
2018-10-13 09:51:49	ga_ls8c_ard_3-0-0_095086_2018-10-13_final
2018-10-13 11:30:18	ga_ls8c_ard_3-0-0_111085_2018-10-13_final
2018-10-15 09:39:04	ga_ls8c_ard_3-0-0_093085_2018-10-15_final
2018-10-15 09:39:28	ga_ls8c_ard_3-0-0_093086_2018-10-15_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
2018-11-25 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
2018-12-11 09:33:20	ga_ls8c_ard_3-0-0_092086_2018-12-11_final
2018-12-11 11:11:49	ga_ls8c_ard_3-0-0_108085_2018-12-11_final
2018-12-12 10:16:11	ga_ls8c_ard_3-0-0_099085_2018-12-12_final
2018-12-13 09:20:33	ga_ls8c_ard_3-0-0_090085_2018-12-12_final
2018-12-13 09:20:57	ga_ls8c_ard_3-0-0_090086_2018-12-12_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
2020-03-03 09:33:24	ga_ls8c_ard_3-1-0_092086_2020-03-03_final
2020-04-02 09:45:30	ga_ls8c_ard_3-1-0_094086_2020-04-02_final
2020-04-04 09:33:07	ga_ls8c_ard_3-1-0_092086_2020-04-04_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