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
2018-09-15 09:26:30	ga_ls8c_ard_3-0-0_091085_2018-09-14_final
2018-09-15 11:05:23	ga_ls8c_ard_3-0-0_107085_2018-09-15_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2018-10-04 09:57:32	ga_ls8c_ard_3-0-0_096085_2018-10-04_final
2018-10-04 11:36:25	ga_ls8c_ard_3-0-0_112085_2018-10-04_final
2018-10-06 09:45:11	ga_ls8c_ard_3-0-0_094085_2018-10-06_final
2018-10-06 11:23:40	ga_ls8c_ard_3-0-0_110084_2018-10-06_final
2018-10-06 11:24:04	ga_ls8c_ard_3-0-0_110085_2018-10-06_final
2018-10-07 10:28:03	ga_ls8c_ard_3-0-0_101084_2018-10-07_final
2018-10-10 10:58:59	ga_ls8c_ard_3-0-0_106084_2018-10-10_final
2018-10-11 10:03:46	ga_ls8c_ard_3-0-0_097085_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 09:26:43	ga_ls8c_ard_3-0-0_091085_2018-10-16_final
2018-10-17 11:05:36	ga_ls8c_ard_3-0-0_107085_2018-10-17_final
2018-11-18 09:26:48	ga_ls8c_ard_3-0-0_091085_2018-11-17_final
2018-11-18 11:05:41	ga_ls8c_ard_3-0-0_107085_2018-11-18_final
2018-12-23 09:57:39	ga_ls8c_ard_3-0-0_096085_2018-12-23_final
2018-12-23 11:36:32	ga_ls8c_ard_3-0-0_112085_2018-12-23_final
2018-12-25 09:45:17	ga_ls8c_ard_3-0-0_094085_2018-12-25_final
2018-12-25 11:24:10	ga_ls8c_ard_3-0-0_110085_2018-12-25_final
2019-01-05 09:26:44	ga_ls8c_ard_3-0-0_091085_2019-01-04_final
2019-01-05 11:05:37	ga_ls8c_ard_3-0-0_107085_2019-01-05_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-07-03 09:57:41	ga_ls8c_ard_3-1-0_096085_2019-07-03_final
2019-07-03 11:36:10	ga_ls8c_ard_3-1-0_112084_2019-07-03_final
2019-07-03 11:36:34	ga_ls8c_ard_3-1-0_112085_2019-07-03_final
2019-07-17 10:10:05	ga_ls8c_ard_3-1-0_098085_2019-07-17_final
2019-07-18 09:14:28	ga_ls8c_ard_3-1-0_089085_2019-07-17_final
2019-07-23 09:32:38	ga_ls8c_ard_3-1-0_092084_2019-07-23_final
2019-07-23 09:33:02	ga_ls8c_ard_3-1-0_092085_2019-07-23_final
2019-07-23 11:11:31	ga_ls8c_ard_3-1-0_108084_2019-07-23_final
2019-07-23 11:11:55	ga_ls8c_ard_3-1-0_108085_2019-07-23_final
2019-07-24 10:16:18	ga_ls8c_ard_3-1-0_099085_2019-07-24_final
2019-07-25 09:20:18	ga_ls8c_ard_3-1-0_090084_2019-07-24_final
2019-07-25 09:20:41	ga_ls8c_ard_3-1-0_090085_2019-07-24_final
2019-07-25 10:59:11	ga_ls8c_ard_3-1-0_106084_2019-07-25_final
2019-07-26 10:03:58	ga_ls8c_ard_3-1-0_097085_2019-07-26_final
2019-07-26 11:42:27	ga_ls8c_ard_3-1-0_113084_2019-07-26_final
2019-10-04 09:27:14	ga_ls8c_ard_3-1-0_091085_2019-10-03_final
2019-10-04 11:05:43	ga_ls8c_ard_3-1-0_107084_2019-10-04_final
2019-10-04 11:06:07	ga_ls8c_ard_3-1-0_107085_2019-10-04_final
2019-10-05 10:10:30	ga_ls8c_ard_3-1-0_098085_2019-10-05_final
2019-10-06 09:14:53	ga_ls8c_ard_3-1-0_089085_2019-10-05_final
2019-10-07 09:58:09	ga_ls8c_ard_3-1-0_096085_2019-10-07_final
2019-10-07 11:36:38	ga_ls8c_ard_3-1-0_112084_2019-10-07_final
2019-10-07 11:37:02	ga_ls8c_ard_3-1-0_112085_2019-10-07_final
2019-10-21 10:10:32	ga_ls8c_ard_3-1-0_098085_2019-10-21_final
2019-10-22 09:14:30	ga_ls8c_ard_3-1-0_089084_2019-10-21_final
2019-10-22 09:14:54	ga_ls8c_ard_3-1-0_089085_2019-10-21_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-01 11:30:52	ga_ls8c_ard_3-1-0_111085_2019-11-01_final
2019-11-03 09:39:37	ga_ls8c_ard_3-1-0_093085_2019-11-03_final
2019-11-03 11:18:30	ga_ls8c_ard_3-1-0_109085_2019-11-03_final
2019-11-04 10:22:53	ga_ls8c_ard_3-1-0_100085_2019-11-04_final
2019-11-17 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-11-17_final
2019-11-17 11:30:49	ga_ls8c_ard_3-1-0_111085_2019-11-17_final
2019-11-19 09:39:34	ga_ls8c_ard_3-1-0_093085_2019-11-19_final
2019-11-19 11:18:27	ga_ls8c_ard_3-1-0_109085_2019-11-19_final
2019-11-20 10:22:49	ga_ls8c_ard_3-1-0_100085_2019-11-20_final
2019-12-28 09:45:39	ga_ls8c_ard_3-1-0_094085_2019-12-28_final
2019-12-28 11:24:32	ga_ls8c_ard_3-1-0_110085_2019-12-28_final
2019-12-30 09:33:17	ga_ls8c_ard_3-1-0_092085_2019-12-30_final
2019-12-30 11:12:10	ga_ls8c_ard_3-1-0_108085_2019-12-30_final
2019-12-31 10:16:32	ga_ls8c_ard_3-1-0_099085_2019-12-31_final
2020-01-01 09:20:55	ga_ls8c_ard_3-1-0_090085_2019-12-31_final
2020-01-02 10:04:10	ga_ls8c_ard_3-1-0_097085_2020-01-02_final
2020-01-04 11:30:41	ga_ls8c_ard_3-1-0_111085_2020-01-04_final
2020-01-06 09:39:26	ga_ls8c_ard_3-1-0_093085_2020-01-06_final
2020-01-06 11:18:19	ga_ls8c_ard_3-1-0_109085_2020-01-06_final
2020-01-07 10:22:42	ga_ls8c_ard_3-1-0_100085_2020-01-07_final
2020-01-29 09:45:31	ga_ls8c_ard_3-1-0_094085_2020-01-29_final
2020-01-29 11:24:24	ga_ls8c_ard_3-1-0_110085_2020-01-29_final
2020-02-05 09:51:39	ga_ls8c_ard_3-1-0_095085_2020-02-05_final
2020-02-05 11:30:32	ga_ls8c_ard_3-1-0_111085_2020-02-05_final
2020-02-07 09:39:17	ga_ls8c_ard_3-1-0_093085_2020-02-07_final
2020-02-07 11:18:10	ga_ls8c_ard_3-1-0_109085_2020-02-07_final
2020-02-08 10:22:33	ga_ls8c_ard_3-1-0_100085_2020-02-08_final
2020-02-14 09:45:27	ga_ls8c_ard_3-1-0_094085_2020-02-14_final
2020-02-14 11:24:20	ga_ls8c_ard_3-1-0_110085_2020-02-14_final
2020-02-16 09:33:05	ga_ls8c_ard_3-1-0_092085_2020-02-16_final
2020-02-16 11:11:58	ga_ls8c_ard_3-1-0_108085_2020-02-16_final
2020-02-17 10:16:20	ga_ls8c_ard_3-1-0_099085_2020-02-17_final
2020-02-23 09:39:14	ga_ls8c_ard_3-1-0_093085_2020-02-23_final
2020-02-23 11:18:07	ga_ls8c_ard_3-1-0_109085_2020-02-23_final
2020-02-24 10:22:29	ga_ls8c_ard_3-1-0_100085_2020-02-24_final
2020-02-25 09:26:52	ga_ls8c_ard_3-1-0_091085_2020-02-24_final
2020-02-25 11:05:45	ga_ls8c_ard_3-1-0_107085_2020-02-25_final
2023-07-05 10:03:36	ga_ls8c_ard_3-2-1_097085_2023-07-05_final
2023-07-07 09:51:16	ga_ls8c_ard_3-2-1_095085_2023-07-07_final
2023-07-09 11:17:24	ga_ls8c_ard_3-2-1_109084_2023-07-09_final
2023-07-11 09:26:34	ga_ls8c_ard_3-2-1_091085_2023-07-10_final
2023-07-11 11:05:03	ga_ls8c_ard_3-2-1_107084_2023-07-11_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-16 09:45:07	ga_ls8c_ard_3-2-1_094085_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_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