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
2018-05-27 10:08:59	ga_ls8c_ard_3-0-0_098085_2018-05-27_final
2018-05-28 09:13:21	ga_ls8c_ard_3-0-0_089085_2018-05-27_final
2018-06-12 10:08:59	ga_ls8c_ard_3-0-0_098085_2018-06-12_final
2018-06-13 09:13:23	ga_ls8c_ard_3-0-0_089085_2018-06-12_final
2018-06-28 10:08:46	ga_ls8c_ard_3-0-0_098084_2018-06-28_final
2018-06-28 10:09:10	ga_ls8c_ard_3-0-0_098085_2018-06-28_final
2018-06-29 09:13:09	ga_ls8c_ard_3-0-0_089084_2018-06-28_final
2018-06-29 09:13:33	ga_ls8c_ard_3-0-0_089085_2018-06-28_final
2018-07-14 10:09:18	ga_ls8c_ard_3-0-0_098085_2018-07-14_final
2018-07-15 09:13:17	ga_ls8c_ard_3-0-0_089084_2018-07-14_final
2018-07-15 09:13:41	ga_ls8c_ard_3-0-0_089085_2018-07-14_final
2018-07-30 10:09:00	ga_ls8c_ard_3-0-0_098084_2018-07-30_final
2018-07-30 10:09:24	ga_ls8c_ard_3-0-0_098085_2018-07-30_final
2018-07-31 09:13:48	ga_ls8c_ard_3-0-0_089085_2018-07-30_final
2018-08-15 10:09:10	ga_ls8c_ard_3-0-0_098084_2018-08-15_final
2018-08-15 10:09:34	ga_ls8c_ard_3-0-0_098085_2018-08-15_final
2018-08-16 09:13:57	ga_ls8c_ard_3-0-0_089085_2018-08-15_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
2018-11-05 09:57:42	ga_ls8c_ard_3-0-0_096085_2018-11-05_final
2018-11-05 11:36:11	ga_ls8c_ard_3-0-0_112084_2018-11-05_final
2018-11-05 11:36:35	ga_ls8c_ard_3-0-0_112085_2018-11-05_final
2018-11-07 09:45:20	ga_ls8c_ard_3-0-0_094085_2018-11-07_final
2018-11-07 11:23:49	ga_ls8c_ard_3-0-0_110084_2018-11-07_final
2018-11-07 11:24:13	ga_ls8c_ard_3-0-0_110085_2018-11-07_final
2018-11-08 10:28:12	ga_ls8c_ard_3-0-0_101084_2018-11-08_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
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-06-14 09:26:41	ga_ls8c_ard_3-1-0_091085_2019-06-13_final
2019-06-14 11:05:10	ga_ls8c_ard_3-1-0_107084_2019-06-14_final
2019-06-14 11:05:34	ga_ls8c_ard_3-1-0_107085_2019-06-14_final
2019-06-17 09:57:36	ga_ls8c_ard_3-1-0_096085_2019-06-17_final
2019-06-17 11:36:30	ga_ls8c_ard_3-1-0_112085_2019-06-17_final
2019-06-28 11:17:36	ga_ls8c_ard_3-1-0_109084_2019-06-28_final
2019-06-28 11:18:00	ga_ls8c_ard_3-1-0_109085_2019-06-28_final
2019-06-29 10:21:59	ga_ls8c_ard_3-1-0_100084_2019-06-29_final
2019-06-29 10:22:23	ga_ls8c_ard_3-1-0_100085_2019-06-29_final
2019-07-08 10:16:14	ga_ls8c_ard_3-1-0_099085_2019-07-08_final
2019-07-09 09:20:13	ga_ls8c_ard_3-1-0_090084_2019-07-08_final
2019-07-09 09:20:37	ga_ls8c_ard_3-1-0_090085_2019-07-08_final
2019-07-09 10:59:06	ga_ls8c_ard_3-1-0_106084_2019-07-09_final
2019-07-10 10:03:29	ga_ls8c_ard_3-1-0_097084_2019-07-10_final
2019-07-10 10:03:53	ga_ls8c_ard_3-1-0_097085_2019-07-10_final
2019-07-10 11:42:22	ga_ls8c_ard_3-1-0_113084_2019-07-10_final
2019-07-11 09:07:52	ga_ls8c_ard_3-1-0_088084_2019-07-10_final
2019-07-16 09:26:49	ga_ls8c_ard_3-1-0_091085_2019-07-15_final
2019-07-16 11:05:18	ga_ls8c_ard_3-1-0_107084_2019-07-16_final
2019-07-16 11:05:42	ga_ls8c_ard_3-1-0_107085_2019-07-16_final
2019-08-02 10:10:11	ga_ls8c_ard_3-1-0_098085_2019-08-02_final
2019-08-03 09:14:34	ga_ls8c_ard_3-1-0_089085_2019-08-02_final
2019-08-04 09:57:27	ga_ls8c_ard_3-1-0_096084_2019-08-04_final
2019-08-04 09:57:51	ga_ls8c_ard_3-1-0_096085_2019-08-04_final
2019-08-04 11:36:44	ga_ls8c_ard_3-1-0_112085_2019-08-04_final
2019-08-27 10:04:08	ga_ls8c_ard_3-1-0_097085_2019-08-27_final
2019-08-28 09:08:07	ga_ls8c_ard_3-1-0_088084_2019-08-27_final
2019-09-02 09:27:04	ga_ls8c_ard_3-1-0_091085_2019-09-01_final
2019-09-02 11:05:57	ga_ls8c_ard_3-1-0_107085_2019-09-02_final
2019-09-18 09:27:10	ga_ls8c_ard_3-1-0_091085_2019-09-17_final
2019-09-18 11:06:03	ga_ls8c_ard_3-1-0_107085_2019-09-18_final
2019-09-19 10:10:02	ga_ls8c_ard_3-1-0_098084_2019-09-19_final
2019-09-19 10:10:26	ga_ls8c_ard_3-1-0_098085_2019-09-19_final
2019-09-20 09:14:49	ga_ls8c_ard_3-1-0_089085_2019-09-19_final
2019-09-21 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-09-21_final
2019-09-21 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-09-21_final
2019-09-21 11:36:58	ga_ls8c_ard_3-1-0_112085_2019-09-21_final
2019-09-30 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-09-30_final
2019-09-30 11:30:26	ga_ls8c_ard_3-1-0_111084_2019-09-30_final
2019-09-30 11:30:50	ga_ls8c_ard_3-1-0_111085_2019-09-30_final
2019-10-02 09:39:11	ga_ls8c_ard_3-1-0_093084_2019-10-02_final
2019-10-02 09:39:35	ga_ls8c_ard_3-1-0_093085_2019-10-02_final
2019-10-02 11:18:04	ga_ls8c_ard_3-1-0_109084_2019-10-02_final
2019-10-02 11:18:28	ga_ls8c_ard_3-1-0_109085_2019-10-02_final
2019-10-03 10:22:27	ga_ls8c_ard_3-1-0_100084_2019-10-03_final
2019-10-03 10:22:51	ga_ls8c_ard_3-1-0_100085_2019-10-03_final
2019-10-09 09:45:23	ga_ls8c_ard_3-1-0_094084_2019-10-09_final
2019-10-09 09:45:47	ga_ls8c_ard_3-1-0_094085_2019-10-09_final
2019-10-09 11:24:40	ga_ls8c_ard_3-1-0_110085_2019-10-09_final
2019-10-10 10:28:39	ga_ls8c_ard_3-1-0_101084_2019-10-10_final
2019-10-11 09:33:26	ga_ls8c_ard_3-1-0_092085_2019-10-11_final
2019-10-11 11:12:19	ga_ls8c_ard_3-1-0_108085_2019-10-11_final
2019-10-12 10:16:42	ga_ls8c_ard_3-1-0_099085_2019-10-12_final
2019-10-13 09:21:05	ga_ls8c_ard_3-1-0_090085_2019-10-12_final
2019-10-14 10:04:20	ga_ls8c_ard_3-1-0_097085_2019-10-14_final
2019-10-15 09:08:19	ga_ls8c_ard_3-1-0_088084_2019-10-14_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
2023-07-10 10:21:47	ga_ls8c_ard_3-2-1_100084_2023-07-10_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