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
2018-02-01 11:17:36	ga_ls8c_ard_3-0-0_109084_2018-02-01_final
2018-02-02 10:21:58	ga_ls8c_ard_3-0-0_100084_2018-02-02_final
2018-02-06 09:57:14	ga_ls8c_ard_3-0-0_096084_2018-02-06_final
2018-02-06 11:36:07	ga_ls8c_ard_3-0-0_112084_2018-02-06_final
2018-02-08 09:44:51	ga_ls8c_ard_3-0-0_094084_2018-02-08_final
2018-02-08 11:23:44	ga_ls8c_ard_3-0-0_110084_2018-02-08_final
2018-02-09 10:28:07	ga_ls8c_ard_3-0-0_101084_2018-02-09_final
2018-02-22 09:57:08	ga_ls8c_ard_3-0-0_096084_2018-02-22_final
2018-02-22 11:36:01	ga_ls8c_ard_3-0-0_112084_2018-02-22_final
2018-02-24 09:44:45	ga_ls8c_ard_3-0-0_094084_2018-02-24_final
2018-02-24 11:23:38	ga_ls8c_ard_3-0-0_110084_2018-02-24_final
2018-02-25 10:28:01	ga_ls8c_ard_3-0-0_101084_2018-02-25_final
2018-03-10 09:56:59	ga_ls8c_ard_3-0-0_096084_2018-03-10_final
2018-03-10 11:35:52	ga_ls8c_ard_3-0-0_112084_2018-03-10_final
2018-03-12 09:44:37	ga_ls8c_ard_3-0-0_094084_2018-03-12_final
2018-03-12 11:23:30	ga_ls8c_ard_3-0-0_110084_2018-03-12_final
2018-03-13 10:27:52	ga_ls8c_ard_3-0-0_101084_2018-03-13_final
2018-03-19 09:50:44	ga_ls8c_ard_3-0-0_095084_2018-03-19_final
2018-03-19 11:29:37	ga_ls8c_ard_3-0-0_111084_2018-03-19_final
2018-03-21 09:38:22	ga_ls8c_ard_3-0-0_093084_2018-03-21_final
2018-03-21 11:17:15	ga_ls8c_ard_3-0-0_109084_2018-03-21_final
2018-03-22 10:21:37	ga_ls8c_ard_3-0-0_100084_2018-03-22_final
2018-03-26 09:56:52	ga_ls8c_ard_3-0-0_096084_2018-03-26_final
2018-03-26 11:35:45	ga_ls8c_ard_3-0-0_112084_2018-03-26_final
2018-03-28 09:44:29	ga_ls8c_ard_3-0-0_094084_2018-03-28_final
2018-03-28 11:23:22	ga_ls8c_ard_3-0-0_110084_2018-03-28_final
2018-03-29 10:27:45	ga_ls8c_ard_3-0-0_101084_2018-03-29_final
2018-04-04 09:50:37	ga_ls8c_ard_3-0-0_095084_2018-04-04_final
2018-04-04 11:29:30	ga_ls8c_ard_3-0-0_111084_2018-04-04_final
2018-04-06 09:38:14	ga_ls8c_ard_3-0-0_093084_2018-04-06_final
2018-04-06 11:17:07	ga_ls8c_ard_3-0-0_109084_2018-04-06_final
2018-04-07 10:21:29	ga_ls8c_ard_3-0-0_100084_2018-04-07_final
2018-04-11 09:56:44	ga_ls8c_ard_3-0-0_096084_2018-04-11_final
2018-04-11 11:35:37	ga_ls8c_ard_3-0-0_112084_2018-04-11_final
2018-04-13 09:44:21	ga_ls8c_ard_3-0-0_094084_2018-04-13_final
2018-04-13 11:23:14	ga_ls8c_ard_3-0-0_110084_2018-04-13_final
2018-04-14 10:27:36	ga_ls8c_ard_3-0-0_101084_2018-04-14_final
2018-06-13 09:12:35	ga_ls8c_ard_3-0-0_089083_2018-06-12_final
2018-06-13 09:12:59	ga_ls8c_ard_3-0-0_089084_2018-06-12_final
2018-07-30 10:09:00	ga_ls8c_ard_3-0-0_098084_2018-07-30_final
2018-07-31 09:13:00	ga_ls8c_ard_3-0-0_089083_2018-07-30_final
2018-07-31 09:13:24	ga_ls8c_ard_3-0-0_089084_2018-07-30_final
2018-07-31 10:51:53	ga_ls8c_ard_3-0-0_105083_2018-07-31_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-10-04 09:57:08	ga_ls8c_ard_3-0-0_096084_2018-10-04_final
2018-10-04 11:36:01	ga_ls8c_ard_3-0-0_112084_2018-10-04_final
2018-10-06 09:44:47	ga_ls8c_ard_3-0-0_094084_2018-10-06_final
2018-10-06 11:23:16	ga_ls8c_ard_3-0-0_110083_2018-10-06_final
2018-10-06 11:23:40	ga_ls8c_ard_3-0-0_110084_2018-10-06_final
2018-10-07 10:28:03	ga_ls8c_ard_3-0-0_101084_2018-10-07_final
2018-11-05 09:57:18	ga_ls8c_ard_3-0-0_096084_2018-11-05_final
2018-11-05 11:35:47	ga_ls8c_ard_3-0-0_112083_2018-11-05_final
2018-11-05 11:36:11	ga_ls8c_ard_3-0-0_112084_2018-11-05_final
2018-11-07 09:44:56	ga_ls8c_ard_3-0-0_094084_2018-11-07_final
2018-11-07 11:23:26	ga_ls8c_ard_3-0-0_110083_2018-11-07_final
2018-11-07 11:23:49	ga_ls8c_ard_3-0-0_110084_2018-11-07_final
2018-11-08 10:28:12	ga_ls8c_ard_3-0-0_101084_2018-11-08_final
2018-12-23 09:57:15	ga_ls8c_ard_3-0-0_096084_2018-12-23_final
2018-12-23 11:36:08	ga_ls8c_ard_3-0-0_112084_2018-12-23_final
2018-12-25 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-12-25_final
2018-12-25 11:23:46	ga_ls8c_ard_3-0-0_110084_2018-12-25_final
2018-12-26 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-12-26_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2023-07-03 10:15:33	ga_ls8c_ard_3-2-1_099084_2023-07-03_final
2023-07-04 09:19:32	ga_ls8c_ard_3-2-1_090083_2023-07-03_final
2023-07-04 09:19:56	ga_ls8c_ard_3-2-1_090084_2023-07-03_final
2023-07-04 10:58:25	ga_ls8c_ard_3-2-1_106083_2023-07-04_final
2023-07-05 10:03:12	ga_ls8c_ard_3-2-1_097084_2023-07-05_final
2023-07-05 11:42:05	ga_ls8c_ard_3-2-1_113084_2023-07-05_final
2023-07-06 09:07:12	ga_ls8c_ard_3-2-1_088083_2023-07-05_final
2023-07-07 09:50:52	ga_ls8c_ard_3-2-1_095084_2023-07-07_final
2023-07-07 11:29:21	ga_ls8c_ard_3-2-1_111083_2023-07-07_final
2023-07-07 11:29:45	ga_ls8c_ard_3-2-1_111084_2023-07-07_final
2023-07-09 11:17:24	ga_ls8c_ard_3-2-1_109084_2023-07-09_final
2023-07-10 10:21:23	ga_ls8c_ard_3-2-1_100083_2023-07-10_final
2023-07-10 10:21:47	ga_ls8c_ard_3-2-1_100084_2023-07-10_final
2023-07-11 09:25:46	ga_ls8c_ard_3-2-1_091083_2023-07-10_final
2023-07-11 09:26:10	ga_ls8c_ard_3-2-1_091084_2023-07-10_final
2023-07-11 11:05:03	ga_ls8c_ard_3-2-1_107084_2023-07-11_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-14 09:57:05	ga_ls8c_ard_3-2-1_096084_2023-07-14_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-16 09:44:19	ga_ls8c_ard_3-2-1_094083_2023-07-16_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-07-18 09:32:21	ga_ls8c_ard_3-2-1_092084_2023-07-18_final
2023-07-18 11:11:14	ga_ls8c_ard_3-2-1_108084_2023-07-18_final
2023-07-19 10:15:37	ga_ls8c_ard_3-2-1_099084_2023-07-19_final
2023-07-20 10:58:28	ga_ls8c_ard_3-2-1_106083_2023-07-20_final
2023-07-21 10:02:51	ga_ls8c_ard_3-2-1_097083_2023-07-21_final
2023-07-21 10:03:15	ga_ls8c_ard_3-2-1_097084_2023-07-21_final
2023-07-21 11:41:44	ga_ls8c_ard_3-2-1_113083_2023-07-21_final
2023-07-21 11:42:08	ga_ls8c_ard_3-2-1_113084_2023-07-21_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