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
2018-02-15 09:51:24	ga_ls8c_ard_3-0-0_095085_2018-02-15_final
2018-02-15 11:30:17	ga_ls8c_ard_3-0-0_111085_2018-02-15_final
2018-02-17 09:39:02	ga_ls8c_ard_3-0-0_093085_2018-02-17_final
2018-02-17 11:17:55	ga_ls8c_ard_3-0-0_109085_2018-02-17_final
2018-02-18 10:21:53	ga_ls8c_ard_3-0-0_100084_2018-02-18_final
2018-02-18 10:22:17	ga_ls8c_ard_3-0-0_100085_2018-02-18_final
2018-02-22 09:57:32	ga_ls8c_ard_3-0-0_096085_2018-02-22_final
2018-02-22 11:36:25	ga_ls8c_ard_3-0-0_112085_2018-02-22_final
2018-02-24 09:44:45	ga_ls8c_ard_3-0-0_094084_2018-02-24_final
2018-02-24 09:45:09	ga_ls8c_ard_3-0-0_094085_2018-02-24_final
2018-02-24 11:24:02	ga_ls8c_ard_3-0-0_110085_2018-02-24_final
2018-03-03 09:50:53	ga_ls8c_ard_3-0-0_095084_2018-03-03_final
2018-03-03 09:51:17	ga_ls8c_ard_3-0-0_095085_2018-03-03_final
2018-03-03 11:29:46	ga_ls8c_ard_3-0-0_111084_2018-03-03_final
2018-03-03 11:30:10	ga_ls8c_ard_3-0-0_111085_2018-03-03_final
2018-03-05 09:38:54	ga_ls8c_ard_3-0-0_093085_2018-03-05_final
2018-03-05 11:17:23	ga_ls8c_ard_3-0-0_109084_2018-03-05_final
2018-03-05 11:17:47	ga_ls8c_ard_3-0-0_109085_2018-03-05_final
2018-03-06 10:22:09	ga_ls8c_ard_3-0-0_100085_2018-03-06_final
2018-03-23 09:26:23	ga_ls8c_ard_3-0-0_091085_2018-03-22_final
2018-03-23 11:05:16	ga_ls8c_ard_3-0-0_107085_2018-03-23_final
2018-04-20 09:50:51	ga_ls8c_ard_3-0-0_095085_2018-04-20_final
2018-04-20 11:29:44	ga_ls8c_ard_3-0-0_111085_2018-04-20_final
2018-04-22 09:38:29	ga_ls8c_ard_3-0-0_093085_2018-04-22_final
2018-04-22 11:17:22	ga_ls8c_ard_3-0-0_109085_2018-04-22_final
2018-04-23 10:21:44	ga_ls8c_ard_3-0-0_100085_2018-04-23_final
2018-04-24 09:26:06	ga_ls8c_ard_3-0-0_091085_2018-04-23_final
2018-04-24 11:04:59	ga_ls8c_ard_3-0-0_107085_2018-04-24_final
2018-04-25 10:09:21	ga_ls8c_ard_3-0-0_098085_2018-04-25_final
2018-04-26 09:13:43	ga_ls8c_ard_3-0-0_089085_2018-04-25_final
2018-04-27 09:56:58	ga_ls8c_ard_3-0-0_096085_2018-04-27_final
2018-04-27 11:35:52	ga_ls8c_ard_3-0-0_112085_2018-04-27_final
2018-05-02 10:15:28	ga_ls8c_ard_3-0-0_099085_2018-05-02_final
2018-05-03 09:19:50	ga_ls8c_ard_3-0-0_090085_2018-05-02_final
2018-05-04 10:03:05	ga_ls8c_ard_3-0-0_097085_2018-05-04_final
2018-05-20 10:02:54	ga_ls8c_ard_3-0-0_097085_2018-05-20_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_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 09:57:08	ga_ls8c_ard_3-0-0_096084_2018-10-04_final
2018-10-04 09:57:32	ga_ls8c_ard_3-0-0_096085_2018-10-04_final
2018-10-04 11:36:01	ga_ls8c_ard_3-0-0_112084_2018-10-04_final
2018-10-04 11:36:25	ga_ls8c_ard_3-0-0_112085_2018-10-04_final
2018-10-06 09:44:47	ga_ls8c_ard_3-0-0_094084_2018-10-06_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
2018-12-25 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-12-25_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 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_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
2023-11-01 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-11-01_final
2023-11-01 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-11-01_final
2023-11-14 11:17:54	ga_ls8c_ard_3-2-1_109084_2023-11-14_final
2023-11-15 10:22:17	ga_ls8c_ard_3-2-1_100084_2023-11-15_final
2023-11-16 09:26:40	ga_ls8c_ard_3-2-1_091084_2023-11-15_final
2023-11-16 09:27:04	ga_ls8c_ard_3-2-1_091085_2023-11-15_final
2023-12-09 09:32:46	ga_ls8c_ard_3-2-1_092084_2023-12-09_final
2023-12-09 09:33:10	ga_ls8c_ard_3-2-1_092085_2023-12-09_final
2023-12-10 10:16:26	ga_ls8c_ard_3-2-1_099085_2023-12-10_final
2023-12-11 09:20:26	ga_ls8c_ard_3-2-1_090084_2023-12-10_final
2023-12-11 09:20:50	ga_ls8c_ard_3-2-1_090085_2023-12-10_final
2024-01-03 09:26:58	ga_ls8c_ard_3-2-1_091085_2024-01-02_final
2024-01-04 10:09:49	ga_ls8c_ard_3-2-1_098084_2024-01-04_final
2024-01-04 10:10:13	ga_ls8c_ard_3-2-1_098085_2024-01-04_final
2024-01-05 09:14:11	ga_ls8c_ard_3-2-1_089084_2024-01-04_final
2024-01-05 09:14:34	ga_ls8c_ard_3-2-1_089085_2024-01-04_final
2024-01-06 09:57:27	ga_ls8c_ard_3-2-1_096084_2024-01-06_final
2024-01-06 09:57:51	ga_ls8c_ard_3-2-1_096085_2024-01-06_final
2024-01-08 09:45:07	ga_ls8c_ard_3-2-1_094084_2024-01-08_final
2024-01-08 09:45:31	ga_ls8c_ard_3-2-1_094085_2024-01-08_final
2024-01-08 11:24:24	ga_ls8c_ard_3-2-1_110085_2024-01-08_final
2024-01-10 09:32:46	ga_ls8c_ard_3-2-1_092084_2024-01-10_final
2024-01-10 09:33:10	ga_ls8c_ard_3-2-1_092085_2024-01-10_final
2024-01-12 09:20:25	ga_ls8c_ard_3-2-1_090084_2024-01-11_final
2024-01-12 09:20:49	ga_ls8c_ard_3-2-1_090085_2024-01-11_final
2024-01-13 10:04:05	ga_ls8c_ard_3-2-1_097085_2024-01-13_final
2024-01-13 11:42:34	ga_ls8c_ard_3-2-1_113084_2024-01-13_final
2024-01-15 09:51:19	ga_ls8c_ard_3-2-1_095084_2024-01-15_final
2024-01-15 09:51:43	ga_ls8c_ard_3-2-1_095085_2024-01-15_final
2024-01-17 09:38:57	ga_ls8c_ard_3-2-1_093084_2024-01-17_final
2024-01-17 09:39:21	ga_ls8c_ard_3-2-1_093085_2024-01-17_final
2024-01-19 09:26:59	ga_ls8c_ard_3-2-1_091085_2024-01-18_final
2024-01-20 10:10:14	ga_ls8c_ard_3-2-1_098085_2024-01-20_final
2024-01-22 09:57:51	ga_ls8c_ard_3-2-1_096085_2024-01-22_final
2024-01-24 09:45:27	ga_ls8c_ard_3-2-1_094085_2024-01-24_final
2024-01-24 11:24:20	ga_ls8c_ard_3-2-1_110085_2024-01-24_final
2024-03-17 10:03:21	ga_ls8c_ard_3-2-1_097084_2024-03-17_final
2024-03-17 10:03:45	ga_ls8c_ard_3-2-1_097085_2024-03-17_final
2024-03-17 11:42:14	ga_ls8c_ard_3-2-1_113084_2024-03-17_final
2024-03-23 09:26:35	ga_ls8c_ard_3-2-1_091085_2024-03-22_final
2024-03-26 09:57:24	ga_ls8c_ard_3-2-1_096085_2024-03-26_final
2024-04-04 09:51:12	ga_ls8c_ard_3-2-1_095085_2024-04-04_final
2024-04-06 09:38:50	ga_ls8c_ard_3-2-1_093085_2024-04-06_final
2024-04-22 09:38:42	ga_ls8c_ard_3-2-1_093085_2024-04-22_nrt

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