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
2014-08-11 10:12:22	ga_ls8c_ard_3-0-0_099075_2014-08-11_final
2014-08-11 10:12:46	ga_ls8c_ard_3-0-0_099076_2014-08-11_final
2014-08-11 10:13:10	ga_ls8c_ard_3-0-0_099077_2014-08-11_final
2014-08-11 10:13:34	ga_ls8c_ard_3-0-0_099078_2014-08-11_final
2014-08-11 10:13:58	ga_ls8c_ard_3-0-0_099079_2014-08-11_final
2014-08-11 10:14:22	ga_ls8c_ard_3-0-0_099080_2014-08-11_final
2014-08-11 10:14:46	ga_ls8c_ard_3-0-0_099081_2014-08-11_final
2014-08-27 10:12:24	ga_ls8c_ard_3-0-0_099075_2014-08-27_final
2014-08-27 10:12:48	ga_ls8c_ard_3-0-0_099076_2014-08-27_final
2014-08-27 10:13:12	ga_ls8c_ard_3-0-0_099077_2014-08-27_final
2014-08-27 10:13:36	ga_ls8c_ard_3-0-0_099078_2014-08-27_final
2014-08-27 10:14:00	ga_ls8c_ard_3-0-0_099079_2014-08-27_final
2014-08-27 10:14:24	ga_ls8c_ard_3-0-0_099080_2014-08-27_final
2014-08-27 10:14:47	ga_ls8c_ard_3-0-0_099081_2014-08-27_final
2018-02-13 10:02:58	ga_ls8c_ard_3-0-0_097083_2018-02-13_final
2018-02-13 10:03:22	ga_ls8c_ard_3-0-0_097084_2018-02-13_final
2018-02-13 10:03:46	ga_ls8c_ard_3-0-0_097085_2018-02-13_final
2018-02-13 10:04:10	ga_ls8c_ard_3-0-0_097086_2018-02-13_final
2018-04-07 10:16:18	ga_ls8c_ard_3-0-0_100071_2018-04-07_final
2018-04-07 10:16:42	ga_ls8c_ard_3-0-0_100072_2018-04-07_final
2018-04-07 10:17:06	ga_ls8c_ard_3-0-0_100073_2018-04-07_final
2018-04-07 10:17:30	ga_ls8c_ard_3-0-0_100074_2018-04-07_final
2018-04-07 10:17:54	ga_ls8c_ard_3-0-0_100075_2018-04-07_final
2018-04-07 10:18:18	ga_ls8c_ard_3-0-0_100076_2018-04-07_final
2018-04-16 10:11:38	ga_ls8c_ard_3-0-0_099075_2018-04-16_final
2018-04-16 10:12:02	ga_ls8c_ard_3-0-0_099076_2018-04-16_final
2018-04-16 10:12:25	ga_ls8c_ard_3-0-0_099077_2018-04-16_final
2018-04-16 10:12:49	ga_ls8c_ard_3-0-0_099078_2018-04-16_final
2018-04-16 10:13:13	ga_ls8c_ard_3-0-0_099079_2018-04-16_final
2018-04-16 10:13:37	ga_ls8c_ard_3-0-0_099080_2018-04-16_final
2018-04-16 10:14:01	ga_ls8c_ard_3-0-0_099081_2018-04-16_final
2018-04-18 10:02:26	ga_ls8c_ard_3-0-0_097083_2018-04-18_final
2018-04-18 10:02:50	ga_ls8c_ard_3-0-0_097084_2018-04-18_final
2018-04-18 10:03:14	ga_ls8c_ard_3-0-0_097085_2018-04-18_final
2018-04-18 10:03:38	ga_ls8c_ard_3-0-0_097086_2018-04-18_final
2018-04-23 10:16:09	ga_ls8c_ard_3-0-0_100071_2018-04-23_final
2018-04-23 10:16:33	ga_ls8c_ard_3-0-0_100072_2018-04-23_final
2018-04-23 10:16:56	ga_ls8c_ard_3-0-0_100073_2018-04-23_final
2018-04-23 10:17:20	ga_ls8c_ard_3-0-0_100074_2018-04-23_final
2018-04-23 10:17:44	ga_ls8c_ard_3-0-0_100075_2018-04-23_final
2018-04-23 10:18:08	ga_ls8c_ard_3-0-0_100076_2018-04-23_final
2018-07-21 10:11:32	ga_ls8c_ard_3-0-0_099075_2018-07-21_final
2018-07-21 10:11:56	ga_ls8c_ard_3-0-0_099076_2018-07-21_final
2018-07-21 10:12:19	ga_ls8c_ard_3-0-0_099077_2018-07-21_final
2018-07-21 10:12:43	ga_ls8c_ard_3-0-0_099078_2018-07-21_final
2018-07-21 10:13:07	ga_ls8c_ard_3-0-0_099079_2018-07-21_final
2018-07-21 10:13:31	ga_ls8c_ard_3-0-0_099080_2018-07-21_final
2018-07-21 10:13:55	ga_ls8c_ard_3-0-0_099081_2018-07-21_final
2023-09-28 10:17:01	ga_ls8c_ard_3-2-1_100071_2023-09-28_final
2023-09-28 10:17:25	ga_ls8c_ard_3-2-1_100072_2023-09-28_final
2023-09-28 10:17:49	ga_ls8c_ard_3-2-1_100073_2023-09-28_final
2023-09-28 10:18:13	ga_ls8c_ard_3-2-1_100074_2023-09-28_final
2023-09-28 10:18:37	ga_ls8c_ard_3-2-1_100075_2023-09-28_final
2023-09-28 10:19:01	ga_ls8c_ard_3-2-1_100076_2023-09-28_final
2023-09-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2023-09-30_final
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_final
2023-10-14 10:17:04	ga_ls8c_ard_3-2-1_100071_2023-10-14_nrt
2023-10-14 10:17:28	ga_ls8c_ard_3-2-1_100072_2023-10-14_final
2023-10-14 10:17:28	ga_ls8c_ard_3-2-1_100072_2023-10-14_nrt
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_nrt
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_nrt
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_final
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_nrt
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_final
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_nrt
2023-10-23 10:12:30	ga_ls8c_ard_3-2-1_099075_2023-10-23_final
2023-10-23 10:12:54	ga_ls8c_ard_3-2-1_099076_2023-10-23_final
2023-10-23 10:13:18	ga_ls8c_ard_3-2-1_099077_2023-10-23_final
2023-10-23 10:13:42	ga_ls8c_ard_3-2-1_099078_2023-10-23_final
2023-10-23 10:14:05	ga_ls8c_ard_3-2-1_099079_2023-10-23_final
2023-10-23 10:14:29	ga_ls8c_ard_3-2-1_099080_2023-10-23_final
2023-10-23 10:14:53	ga_ls8c_ard_3-2-1_099081_2023-10-23_final
2023-10-25 10:03:21	ga_ls8c_ard_3-2-1_097083_2023-10-25_final
2023-10-25 10:03:45	ga_ls8c_ard_3-2-1_097084_2023-10-25_final
2023-10-25 10:04:09	ga_ls8c_ard_3-2-1_097085_2023-10-25_final
2024-01-02 10:17:01	ga_ls8c_ard_3-2-1_100071_2024-01-02_final
2024-01-02 10:17:25	ga_ls8c_ard_3-2-1_100072_2024-01-02_final
2024-01-02 10:17:49	ga_ls8c_ard_3-2-1_100073_2024-01-02_final
2024-01-02 10:18:13	ga_ls8c_ard_3-2-1_100074_2024-01-02_final
2024-01-02 10:18:37	ga_ls8c_ard_3-2-1_100075_2024-01-02_final
2024-01-02 10:19:01	ga_ls8c_ard_3-2-1_100076_2024-01-02_final
2024-01-04 10:07:49	ga_ls8c_ard_3-2-1_098079_2024-01-04_final
2024-01-04 10:08:13	ga_ls8c_ard_3-2-1_098080_2024-01-04_final
2024-01-04 10:08:37	ga_ls8c_ard_3-2-1_098081_2024-01-04_final
2024-01-04 10:09:01	ga_ls8c_ard_3-2-1_098082_2024-01-04_final
2024-01-04 10:09:25	ga_ls8c_ard_3-2-1_098083_2024-01-04_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
2024-01-09 10:22:48	ga_ls8c_ard_3-2-1_101070_2024-01-09_final
2024-01-11 10:12:26	ga_ls8c_ard_3-2-1_099075_2024-01-11_final
2024-01-11 10:12:50	ga_ls8c_ard_3-2-1_099076_2024-01-11_final
2024-01-11 10:13:14	ga_ls8c_ard_3-2-1_099077_2024-01-11_final
2024-01-11 10:13:38	ga_ls8c_ard_3-2-1_099078_2024-01-11_final
2024-01-11 10:14:02	ga_ls8c_ard_3-2-1_099079_2024-01-11_final
2024-01-11 10:14:26	ga_ls8c_ard_3-2-1_099080_2024-01-11_final
2024-01-11 10:14:50	ga_ls8c_ard_3-2-1_099081_2024-01-11_final
2024-01-13 10:03:17	ga_ls8c_ard_3-2-1_097083_2024-01-13_final
2024-01-13 10:03:41	ga_ls8c_ard_3-2-1_097084_2024-01-13_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years