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
2018-03-05 11:10:36	ga_ls8c_ard_3-0-0_109067_2018-03-05_final
2018-03-05 11:11:00	ga_ls8c_ard_3-0-0_109068_2018-03-05_final
2018-03-05 11:11:24	ga_ls8c_ard_3-0-0_109069_2018-03-05_final
2018-03-05 11:11:48	ga_ls8c_ard_3-0-0_109070_2018-03-05_final
2018-04-22 11:10:11	ga_ls8c_ard_3-0-0_109067_2018-04-22_final
2018-04-22 11:10:35	ga_ls8c_ard_3-0-0_109068_2018-04-22_final
2018-04-22 11:10:59	ga_ls8c_ard_3-0-0_109069_2018-04-22_final
2018-04-22 11:11:22	ga_ls8c_ard_3-0-0_109070_2018-04-22_final
2018-05-03 10:55:56	ga_ls8c_ard_3-0-0_106078_2018-05-03_final
2018-05-03 10:56:20	ga_ls8c_ard_3-0-0_106079_2018-05-03_final
2018-05-03 10:56:43	ga_ls8c_ard_3-0-0_106080_2018-05-03_final
2018-05-03 10:57:07	ga_ls8c_ard_3-0-0_106081_2018-05-03_final
2018-05-03 10:57:31	ga_ls8c_ard_3-0-0_106082_2018-05-03_final
2018-05-03 10:57:55	ga_ls8c_ard_3-0-0_106083_2018-05-03_final
2018-05-19 10:55:45	ga_ls8c_ard_3-0-0_106078_2018-05-19_final
2018-05-19 10:56:09	ga_ls8c_ard_3-0-0_106079_2018-05-19_final
2018-05-19 10:56:33	ga_ls8c_ard_3-0-0_106080_2018-05-19_final
2018-05-19 10:56:57	ga_ls8c_ard_3-0-0_106081_2018-05-19_final
2018-05-19 10:57:20	ga_ls8c_ard_3-0-0_106082_2018-05-19_final
2018-05-19 10:57:44	ga_ls8c_ard_3-0-0_106083_2018-05-19_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-12-02 11:10:51	ga_ls8c_ard_3-0-0_109067_2018-12-02_final
2018-12-02 11:11:15	ga_ls8c_ard_3-0-0_109068_2018-12-02_final
2018-12-02 11:11:39	ga_ls8c_ard_3-0-0_109069_2018-12-02_final
2018-12-02 11:12:02	ga_ls8c_ard_3-0-0_109070_2018-12-02_final
2018-12-18 11:10:48	ga_ls8c_ard_3-0-0_109067_2018-12-18_final
2018-12-18 11:11:12	ga_ls8c_ard_3-0-0_109068_2018-12-18_final
2018-12-18 11:11:36	ga_ls8c_ard_3-0-0_109069_2018-12-18_final
2018-12-18 11:12:00	ga_ls8c_ard_3-0-0_109070_2018-12-18_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2019-01-23 10:52:00	ga_ls8c_ard_3-0-0_105082_2019-01-23_final
2019-01-23 10:52:24	ga_ls8c_ard_3-0-0_105083_2019-01-23_final
2019-01-30 10:56:33	ga_ls8c_ard_3-0-0_106078_2019-01-30_final
2019-01-30 10:56:57	ga_ls8c_ard_3-0-0_106079_2019-01-30_final
2019-01-30 10:57:21	ga_ls8c_ard_3-0-0_106080_2019-01-30_final
2019-01-30 10:57:45	ga_ls8c_ard_3-0-0_106081_2019-01-30_final
2019-01-30 10:58:09	ga_ls8c_ard_3-0-0_106082_2019-01-30_final
2019-01-30 10:58:33	ga_ls8c_ard_3-0-0_106083_2019-01-30_final
2019-02-04 11:10:42	ga_ls8c_ard_3-0-0_109067_2019-02-04_final
2019-02-04 11:11:06	ga_ls8c_ard_3-0-0_109068_2019-02-04_final
2019-02-04 11:11:30	ga_ls8c_ard_3-0-0_109069_2019-02-04_final
2019-02-04 11:11:54	ga_ls8c_ard_3-0-0_109070_2019-02-04_final
2019-02-06 11:00:44	ga_ls8c_ard_3-0-0_107073_2019-02-06_final
2019-02-06 11:01:08	ga_ls8c_ard_3-0-0_107074_2019-02-06_final
2019-02-06 11:01:31	ga_ls8c_ard_3-0-0_107075_2019-02-06_final
2019-02-06 11:01:55	ga_ls8c_ard_3-0-0_107076_2019-02-06_final
2019-02-06 11:02:19	ga_ls8c_ard_3-0-0_107077_2019-02-06_final
2019-02-06 11:02:43	ga_ls8c_ard_3-0-0_107078_2019-02-06_final
2019-02-06 11:03:07	ga_ls8c_ard_3-0-0_107079_2019-02-06_final
2019-03-12 10:51:49	ga_ls8c_ard_3-1-0_105082_2019-03-12_final
2019-03-12 10:52:12	ga_ls8c_ard_3-1-0_105083_2019-03-12_final
2019-05-06 10:56:15	ga_ls8c_ard_3-0-0_106078_2019-05-06_final
2019-05-06 10:56:39	ga_ls8c_ard_3-0-0_106079_2019-05-06_final
2019-05-06 10:57:03	ga_ls8c_ard_3-0-0_106080_2019-05-06_final
2019-05-06 10:57:27	ga_ls8c_ard_3-0-0_106081_2019-05-06_final
2019-05-06 10:57:51	ga_ls8c_ard_3-0-0_106082_2019-05-06_final
2020-03-14 10:52:04	ga_ls8c_ard_3-1-0_105082_2020-03-14_final
2020-03-14 10:52:28	ga_ls8c_ard_3-1-0_105083_2020-03-14_final
2020-04-13 11:00:35	ga_ls8c_ard_3-1-0_107073_2020-04-13_final
2020-04-13 11:00:59	ga_ls8c_ard_3-1-0_107074_2020-04-13_final
2020-04-13 11:01:23	ga_ls8c_ard_3-1-0_107075_2020-04-13_final
2020-04-13 11:01:47	ga_ls8c_ard_3-1-0_107076_2020-04-13_final
2020-04-13 11:02:10	ga_ls8c_ard_3-1-0_107077_2020-04-13_final
2020-04-13 11:02:34	ga_ls8c_ard_3-1-0_107078_2020-04-13_final
2020-04-13 11:02:58	ga_ls8c_ard_3-1-0_107079_2020-04-13_final
2021-10-23 11:11:22	ga_ls8c_ard_3-2-0_109067_2021-10-23_final
2021-10-23 11:11:46	ga_ls8c_ard_3-2-0_109068_2021-10-23_final
2021-10-23 11:12:10	ga_ls8c_ard_3-2-0_109069_2021-10-23_final
2021-10-25 11:01:24	ga_ls8c_ard_3-2-0_107073_2021-10-25_final
2021-10-25 11:01:48	ga_ls8c_ard_3-2-0_107074_2021-10-25_final
2021-10-25 11:02:12	ga_ls8c_ard_3-2-0_107075_2021-10-25_final
2021-10-25 11:02:36	ga_ls8c_ard_3-2-0_107076_2021-10-25_final
2021-10-25 11:03:00	ga_ls8c_ard_3-2-0_107077_2021-10-25_final
2021-10-25 11:03:24	ga_ls8c_ard_3-2-0_107078_2021-10-25_final
2021-10-25 11:03:48	ga_ls8c_ard_3-2-0_107079_2021-10-25_final
2022-01-27 11:11:52	ga_ls8c_ard_3-2-1_109069_2022-01-27_final
2022-01-27 11:12:16	ga_ls8c_ard_3-2-1_109070_2022-01-27_final
2023-08-26 11:11:44	ga_ls8c_ard_3-2-1_109069_2023-08-26_final
2023-08-28 11:00:58	ga_ls8c_ard_3-2-1_107073_2023-08-28_final
2023-08-28 11:01:22	ga_ls8c_ard_3-2-1_107074_2023-08-28_final
2023-08-28 11:01:46	ga_ls8c_ard_3-2-1_107075_2023-08-28_final
2023-08-28 11:02:10	ga_ls8c_ard_3-2-1_107076_2023-08-28_final
2023-08-28 11:02:34	ga_ls8c_ard_3-2-1_107077_2023-08-28_final
2023-08-28 11:02:58	ga_ls8c_ard_3-2-1_107078_2023-08-28_final
2023-08-28 11:03:22	ga_ls8c_ard_3-2-1_107079_2023-08-28_final
2023-08-30 10:52:12	ga_ls8c_ard_3-2-1_105082_2023-08-30_final
2023-08-30 10:52:36	ga_ls8c_ard_3-2-1_105083_2023-08-30_final
2024-03-14 11:05:23	ga_ls8c_ard_3-2-1_108069_2024-03-14_final
2024-03-14 11:05:47	ga_ls8c_ard_3-2-1_108070_2024-03-14_final
2024-03-14 11:06:11	ga_ls8c_ard_3-2-1_108071_2024-03-14_final
2024-03-14 11:06:35	ga_ls8c_ard_3-2-1_108072_2024-03-14_final
2024-03-14 11:06:59	ga_ls8c_ard_3-2-1_108073_2024-03-14_final
2024-03-14 11:07:23	ga_ls8c_ard_3-2-1_108074_2024-03-14_final
2024-03-30 11:05:09	ga_ls8c_ard_3-2-1_108069_2024-03-30_final
2024-03-30 11:05:33	ga_ls8c_ard_3-2-1_108070_2024-03-30_final
2024-03-30 11:05:57	ga_ls8c_ard_3-2-1_108071_2024-03-30_final
2024-03-30 11:06:21	ga_ls8c_ard_3-2-1_108072_2024-03-30_final
2024-03-30 11:06:45	ga_ls8c_ard_3-2-1_108073_2024-03-30_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