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
2022-01-08 10:40:16	ga_ls8c_ard_3-2-1_104067_2022-01-08_final
2022-01-10 10:27:54	ga_ls8c_ard_3-2-1_102067_2022-01-10_final
2022-01-24 10:40:12	ga_ls8c_ard_3-2-1_104067_2022-01-24_final
2022-01-26 10:27:49	ga_ls8c_ard_3-2-1_102067_2022-01-26_final
2022-02-09 10:40:09	ga_ls8c_ard_3-2-1_104067_2022-02-09_final
2022-02-11 10:27:46	ga_ls8c_ard_3-2-1_102067_2022-02-11_final
2022-02-25 10:40:03	ga_ls8c_ard_3-2-1_104067_2022-02-25_final
2022-02-27 10:27:42	ga_ls8c_ard_3-2-1_102067_2022-02-27_final
2022-03-13 10:39:59	ga_ls8c_ard_3-2-1_104067_2022-03-13_final
2022-03-15 10:27:36	ga_ls8c_ard_3-2-1_102067_2022-03-15_final
2022-03-29 10:39:47	ga_ls8c_ard_3-2-1_104067_2022-03-29_final
2022-03-31 10:27:24	ga_ls8c_ard_3-2-1_102067_2022-03-31_final
2022-04-14 10:39:52	ga_ls8c_ard_3-2-1_104067_2022-04-14_final
2022-04-16 10:27:30	ga_ls8c_ard_3-2-1_102067_2022-04-16_final
2022-04-30 10:39:48	ga_ls8c_ard_3-2-1_104067_2022-04-30_final
2022-05-02 10:27:28	ga_ls8c_ard_3-2-1_102067_2022-05-02_final
2022-05-16 10:39:58	ga_ls8c_ard_3-2-1_104067_2022-05-16_final
2022-05-18 10:27:37	ga_ls8c_ard_3-2-1_102067_2022-05-18_final
2022-06-01 10:40:01	ga_ls8c_ard_3-2-1_104067_2022-06-01_final
2022-06-03 10:27:42	ga_ls8c_ard_3-2-1_102067_2022-06-03_final
2022-06-17 10:40:13	ga_ls8c_ard_3-2-1_104067_2022-06-17_final
2022-06-19 10:27:52	ga_ls8c_ard_3-2-1_102067_2022-06-19_final
2022-07-03 10:40:17	ga_ls8c_ard_3-2-1_104067_2022-07-03_final
2022-07-05 10:27:55	ga_ls8c_ard_3-2-1_102067_2022-07-05_final
2022-07-19 10:40:18	ga_ls8c_ard_3-2-1_104067_2022-07-19_final
2022-07-21 10:27:58	ga_ls8c_ard_3-2-1_102067_2022-07-21_final
2022-08-04 10:40:29	ga_ls8c_ard_3-2-1_104067_2022-08-04_final
2022-08-06 10:28:08	ga_ls8c_ard_3-2-1_102067_2022-08-06_final
2022-08-20 10:40:34	ga_ls8c_ard_3-2-1_104067_2022-08-20_final
2022-08-22 10:28:12	ga_ls8c_ard_3-2-1_102067_2022-08-22_final
2022-09-05 10:40:35	ga_ls8c_ard_3-2-1_104067_2022-09-05_final
2022-09-07 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-09-07_final
2022-09-21 10:40:41	ga_ls8c_ard_3-2-1_104067_2022-09-21_final
2022-09-23 10:28:19	ga_ls8c_ard_3-2-1_102067_2022-09-23_final
2022-10-07 10:40:37	ga_ls8c_ard_3-2-1_104067_2022-10-07_final
2022-10-09 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-10-09_final
2022-10-23 10:40:38	ga_ls8c_ard_3-2-1_104067_2022-10-23_final
2022-10-25 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-10-25_final
2022-11-08 10:40:39	ga_ls8c_ard_3-2-1_104067_2022-11-08_final
2022-11-10 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-11-10_final
2022-11-24 10:40:35	ga_ls8c_ard_3-2-1_104067_2022-11-24_final
2022-11-26 10:28:14	ga_ls8c_ard_3-2-1_102067_2022-11-26_final
2022-12-10 10:40:34	ga_ls8c_ard_3-2-1_104067_2022-12-10_final
2022-12-12 10:28:11	ga_ls8c_ard_3-2-1_102067_2022-12-12_final
2022-12-26 10:40:26	ga_ls8c_ard_3-2-1_104067_2022-12-26_final
2022-12-28 10:28:05	ga_ls8c_ard_3-2-1_102067_2022-12-28_final
2023-01-11 10:40:24	ga_ls8c_ard_3-2-1_104067_2023-01-11_final
2023-01-13 10:28:01	ga_ls8c_ard_3-2-1_102067_2023-01-13_final
2023-01-29 10:28:03	ga_ls8c_ard_3-2-1_102067_2023-01-29_final
2023-02-12 10:40:20	ga_ls8c_ard_3-2-1_104067_2023-02-12_final
2023-02-14 10:27:57	ga_ls8c_ard_3-2-1_102067_2023-02-14_final
2023-02-28 10:40:05	ga_ls8c_ard_3-2-1_104067_2023-02-28_final
2023-03-02 10:27:43	ga_ls8c_ard_3-2-1_102067_2023-03-02_final
2023-03-16 10:39:59	ga_ls8c_ard_3-2-1_104067_2023-03-16_final
2023-03-18 10:27:36	ga_ls8c_ard_3-2-1_102067_2023-03-18_final
2023-04-01 10:39:48	ga_ls8c_ard_3-2-1_104067_2023-04-01_final
2023-04-03 10:27:25	ga_ls8c_ard_3-2-1_102067_2023-04-03_final
2023-04-17 10:39:34	ga_ls8c_ard_3-2-1_104067_2023-04-17_final
2023-04-19 10:27:11	ga_ls8c_ard_3-2-1_102067_2023-04-19_final
2023-05-03 10:39:29	ga_ls8c_ard_3-2-1_104067_2023-05-03_final
2023-05-05 10:27:06	ga_ls8c_ard_3-2-1_102067_2023-05-05_final
2023-05-19 10:39:18	ga_ls8c_ard_3-2-1_104067_2023-05-19_final
2023-05-21 10:26:57	ga_ls8c_ard_3-2-1_102067_2023-05-21_final
2023-06-04 10:39:22	ga_ls8c_ard_3-2-1_104067_2023-06-04_final
2023-06-06 10:27:03	ga_ls8c_ard_3-2-1_102067_2023-06-06_final
2023-06-20 10:39:30	ga_ls8c_ard_3-2-1_104067_2023-06-20_final
2023-07-06 10:39:42	ga_ls8c_ard_3-2-1_104067_2023-07-06_final
2023-07-22 10:39:45	ga_ls8c_ard_3-2-1_104067_2023-07-22_final
2023-08-07 10:39:53	ga_ls8c_ard_3-2-1_104067_2023-08-07_final
2023-08-23 10:40:01	ga_ls8c_ard_3-2-1_104067_2023-08-23_final
2023-09-08 10:40:01	ga_ls8c_ard_3-2-1_104067_2023-09-08_final
2023-09-24 10:40:07	ga_ls8c_ard_3-2-1_104067_2023-09-24_final
2023-09-26 10:27:46	ga_ls8c_ard_3-2-1_102067_2023-09-26_final
2023-10-10 10:40:11	ga_ls8c_ard_3-2-1_104067_2023-10-10_final
2023-10-26 10:40:14	ga_ls8c_ard_3-2-1_104067_2023-10-26_final
2023-10-28 10:27:53	ga_ls8c_ard_3-2-1_102067_2023-10-28_final
2023-11-11 10:40:10	ga_ls8c_ard_3-2-1_104067_2023-11-11_final
2023-11-13 10:27:50	ga_ls8c_ard_3-2-1_102067_2023-11-13_final
2023-11-27 10:40:16	ga_ls8c_ard_3-2-1_104067_2023-11-27_final
2023-12-13 10:40:12	ga_ls8c_ard_3-2-1_104067_2023-12-13_final
2023-12-29 10:40:12	ga_ls8c_ard_3-2-1_104067_2023-12-29_final
2023-12-31 10:27:49	ga_ls8c_ard_3-2-1_102067_2023-12-31_final
2024-01-14 10:40:10	ga_ls8c_ard_3-2-1_104067_2024-01-14_final
2024-01-16 10:27:48	ga_ls8c_ard_3-2-1_102067_2024-01-16_final
2024-01-30 10:40:04	ga_ls8c_ard_3-2-1_104067_2024-01-30_final
2024-02-01 10:27:44	ga_ls8c_ard_3-2-1_102067_2024-02-01_final
2024-02-15 10:40:06	ga_ls8c_ard_3-2-1_104067_2024-02-15_final
2024-02-17 10:27:44	ga_ls8c_ard_3-2-1_102067_2024-02-17_final
2024-03-02 10:39:59	ga_ls8c_ard_3-2-1_104067_2024-03-02_final
2024-03-04 10:27:36	ga_ls8c_ard_3-2-1_102067_2024-03-04_final
2024-04-03 10:40:02	ga_ls8c_ard_3-2-1_104068_2024-04-03_final
2024-04-03 10:41:14	ga_ls8c_ard_3-2-1_104071_2024-04-03_final
2024-04-05 10:29:16	ga_ls8c_ard_3-2-1_102072_2024-04-05_final
2024-04-05 10:29:40	ga_ls8c_ard_3-2-1_102073_2024-04-05_final
2024-04-05 10:30:04	ga_ls8c_ard_3-2-1_102074_2024-04-05_final
2024-04-07 10:18:06	ga_ls8c_ard_3-2-1_100075_2024-04-07_final
2024-04-07 10:18:54	ga_ls8c_ard_3-2-1_100077_2024-04-07_final
2024-04-07 10:19:18	ga_ls8c_ard_3-2-1_100078_2024-04-07_final
2024-04-07 10:19:42	ga_ls8c_ard_3-2-1_100079_2024-04-07_final
2024-04-07 10:20:06	ga_ls8c_ard_3-2-1_100080_2024-04-07_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