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
2017-01-18 09:57:31	ga_ls8c_ard_3-0-0_096084_2017-01-18_final
2017-02-01 10:09:47	ga_ls8c_ard_3-0-0_098084_2017-02-01_final
2017-02-02 09:14:09	ga_ls8c_ard_3-0-0_089084_2017-02-01_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
2018-09-18 09:57:00	ga_ls8c_ard_3-0-0_096084_2018-09-18_final
2018-09-18 11:35:53	ga_ls8c_ard_3-0-0_112084_2018-09-18_final
2018-09-20 09:44:39	ga_ls8c_ard_3-0-0_094084_2018-09-20_final
2018-09-20 11:23:32	ga_ls8c_ard_3-0-0_110084_2018-09-20_final
2018-09-21 10:27:55	ga_ls8c_ard_3-0-0_101084_2018-09-21_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 11:23:40	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
2018-10-20 09:57:14	ga_ls8c_ard_3-0-0_096084_2018-10-20_final
2018-10-20 11:36:07	ga_ls8c_ard_3-0-0_112084_2018-10-20_final
2018-10-22 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-10-22_final
2018-10-22 11:23:46	ga_ls8c_ard_3-0-0_110084_2018-10-22_final
2018-10-23 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-10-23_final
2018-11-05 09:57:18	ga_ls8c_ard_3-0-0_096084_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 11:23:49	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
2018-11-21 09:57:18	ga_ls8c_ard_3-0-0_096084_2018-11-21_final
2018-11-21 11:36:11	ga_ls8c_ard_3-0-0_112084_2018-11-21_final
2018-11-23 09:44:57	ga_ls8c_ard_3-0-0_094084_2018-11-23_final
2018-11-23 11:23:50	ga_ls8c_ard_3-0-0_110084_2018-11-23_final
2018-11-24 10:28:12	ga_ls8c_ard_3-0-0_101084_2018-11-24_final
2018-12-07 09:57:16	ga_ls8c_ard_3-0-0_096084_2018-12-07_final
2018-12-07 11:36:09	ga_ls8c_ard_3-0-0_112084_2018-12-07_final
2018-12-09 09:44:54	ga_ls8c_ard_3-0-0_094084_2018-12-09_final
2018-12-09 11:23:47	ga_ls8c_ard_3-0-0_110084_2018-12-09_final
2018-12-10 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-12-10_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
2019-01-08 09:57:14	ga_ls8c_ard_3-0-0_096084_2019-01-08_final
2019-01-08 11:36:07	ga_ls8c_ard_3-0-0_112084_2019-01-08_final
2019-01-10 09:44:52	ga_ls8c_ard_3-0-0_094084_2019-01-10_final
2019-01-10 11:23:45	ga_ls8c_ard_3-0-0_110084_2019-01-10_final
2019-01-11 10:28:07	ga_ls8c_ard_3-0-0_101084_2019-01-11_final
2019-03-03 10:58:51	ga_ls8c_ard_3-0-0_106084_2019-03-03_final
2019-03-04 10:03:13	ga_ls8c_ard_3-0-0_097084_2019-03-04_final
2019-03-04 11:42:06	ga_ls8c_ard_3-0-0_113084_2019-03-04_final
2019-03-05 09:07:35	ga_ls8c_ard_3-0-0_088084_2019-03-04_final
2019-06-05 09:32:25	ga_ls8c_ard_3-0-0_092084_2019-06-05_final
2019-06-05 11:11:18	ga_ls8c_ard_3-0-0_108084_2019-06-05_final
2019-06-06 10:15:41	ga_ls8c_ard_3-0-0_099084_2019-06-06_final
2019-06-06 10:16:05	ga_ls8c_ard_3-0-0_099085_2019-06-06_final
2019-06-07 09:20:04	ga_ls8c_ard_3-0-0_090084_2019-06-06_final
2019-06-07 10:58:57	ga_ls8c_ard_3-0-0_106084_2019-06-07_final
2019-06-08 10:03:20	ga_ls8c_ard_3-0-0_097084_2019-06-08_final
2019-06-08 11:42:13	ga_ls8c_ard_3-0-0_113084_2019-06-08_final
2019-06-09 09:07:43	ga_ls8c_ard_3-0-0_088084_2019-06-08_final
2019-11-30 10:59:30	ga_ls8c_ard_3-1-0_106084_2019-11-30_final
2019-12-01 10:03:52	ga_ls8c_ard_3-1-0_097084_2019-12-01_final
2019-12-01 11:42:45	ga_ls8c_ard_3-1-0_113084_2019-12-01_final
2019-12-02 09:08:15	ga_ls8c_ard_3-1-0_088084_2019-12-01_final
2020-01-09 10:09:56	ga_ls8c_ard_3-1-0_098084_2020-01-09_final
2020-01-10 09:14:18	ga_ls8c_ard_3-1-0_089084_2020-01-09_final
2020-01-25 10:09:52	ga_ls8c_ard_3-1-0_098084_2020-01-25_final
2020-01-26 09:14:14	ga_ls8c_ard_3-1-0_089084_2020-01-25_final
2023-03-03 11:17:46	ga_ls8c_ard_3-2-1_109084_2023-03-03_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-07 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-03-06_final
2023-03-20 10:22:00	ga_ls8c_ard_3-2-1_100084_2023-03-20_final
2023-03-21 09:26:21	ga_ls8c_ard_3-2-1_091084_2023-03-20_final
2023-03-21 11:05:14	ga_ls8c_ard_3-2-1_107084_2023-03-21_final
2023-06-07 09:38:13	ga_ls8c_ard_3-2-1_093084_2023-06-07_final
2023-06-07 11:17:06	ga_ls8c_ard_3-2-1_109084_2023-06-07_final
2023-06-08 10:21:29	ga_ls8c_ard_3-2-1_100084_2023-06-08_final
2023-06-09 09:25:53	ga_ls8c_ard_3-2-1_091084_2023-06-08_final
2023-06-09 09:26:17	ga_ls8c_ard_3-2-1_091085_2023-06-08_final
2023-06-09 11:04:46	ga_ls8c_ard_3-2-1_107084_2023-06-09_final
2023-06-10 10:09:09	ga_ls8c_ard_3-2-1_098084_2023-06-10_final
2023-06-12 11:35:42	ga_ls8c_ard_3-2-1_112084_2023-06-12_final
2023-06-14 09:44:28	ga_ls8c_ard_3-2-1_094084_2023-06-14_final
2023-07-07 09:50:52	ga_ls8c_ard_3-2-1_095084_2023-07-07_final
2023-07-07 11:29:45	ga_ls8c_ard_3-2-1_111084_2023-07-07_final
2023-07-09 09:38:31	ga_ls8c_ard_3-2-1_093084_2023-07-09_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 09:26:10	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 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-13 09:13:49	ga_ls8c_ard_3-2-1_089084_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 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-08-24 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-08-24_final
2023-08-24 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-08-24_final
2023-08-26 09:38:50	ga_ls8c_ard_3-2-1_093084_2023-08-26_final
2023-08-26 11:17:43	ga_ls8c_ard_3-2-1_109084_2023-08-26_final
2023-08-29 10:09:44	ga_ls8c_ard_3-2-1_098084_2023-08-29_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