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
2018-02-03 11:01:38	ga_ls8c_ard_3-0-0_107075_2018-02-03_final
2018-02-03 11:02:02	ga_ls8c_ard_3-0-0_107076_2018-02-03_final
2018-02-03 11:02:26	ga_ls8c_ard_3-0-0_107077_2018-02-03_final
2018-02-03 11:02:50	ga_ls8c_ard_3-0-0_107078_2018-02-03_final
2018-02-03 11:03:14	ga_ls8c_ard_3-0-0_107079_2018-02-03_final
2018-02-03 11:03:38	ga_ls8c_ard_3-0-0_107080_2018-02-03_final
2018-02-03 11:04:01	ga_ls8c_ard_3-0-0_107081_2018-02-03_final
2018-02-26 11:06:05	ga_ls8c_ard_3-0-0_108071_2018-02-26_final
2018-02-26 11:06:28	ga_ls8c_ard_3-0-0_108072_2018-02-26_final
2018-02-26 11:06:52	ga_ls8c_ard_3-0-0_108073_2018-02-26_final
2018-02-26 11:07:16	ga_ls8c_ard_3-0-0_108074_2018-02-26_final
2018-02-26 11:07:40	ga_ls8c_ard_3-0-0_108075_2018-02-26_final
2018-02-26 11:08:04	ga_ls8c_ard_3-0-0_108076_2018-02-26_final
2018-02-28 10:57:17	ga_ls8c_ard_3-0-0_106080_2018-02-28_final
2018-02-28 10:57:41	ga_ls8c_ard_3-0-0_106081_2018-02-28_final
2018-02-28 10:58:05	ga_ls8c_ard_3-0-0_106082_2018-02-28_final
2018-02-28 10:58:29	ga_ls8c_ard_3-0-0_106083_2018-02-28_final
2018-02-28 10:58:53	ga_ls8c_ard_3-0-0_106084_2018-02-28_final
2018-03-07 11:01:25	ga_ls8c_ard_3-0-0_107075_2018-03-07_final
2018-03-07 11:01:49	ga_ls8c_ard_3-0-0_107076_2018-03-07_final
2018-03-07 11:02:13	ga_ls8c_ard_3-0-0_107077_2018-03-07_final
2018-03-07 11:02:36	ga_ls8c_ard_3-0-0_107078_2018-03-07_final
2018-03-07 11:03:00	ga_ls8c_ard_3-0-0_107079_2018-03-07_final
2018-03-07 11:03:24	ga_ls8c_ard_3-0-0_107080_2018-03-07_final
2018-03-07 11:03:48	ga_ls8c_ard_3-0-0_107081_2018-03-07_final
2018-03-30 11:05:49	ga_ls8c_ard_3-0-0_108071_2018-03-30_final
2018-03-30 11:06:13	ga_ls8c_ard_3-0-0_108072_2018-03-30_final
2018-03-30 11:06:37	ga_ls8c_ard_3-0-0_108073_2018-03-30_final
2018-03-30 11:07:00	ga_ls8c_ard_3-0-0_108074_2018-03-30_final
2018-03-30 11:07:24	ga_ls8c_ard_3-0-0_108075_2018-03-30_final
2018-03-30 11:07:48	ga_ls8c_ard_3-0-0_108076_2018-03-30_final
2018-04-01 10:57:02	ga_ls8c_ard_3-0-0_106080_2018-04-01_final
2018-04-01 10:57:25	ga_ls8c_ard_3-0-0_106081_2018-04-01_final
2018-04-01 10:57:49	ga_ls8c_ard_3-0-0_106082_2018-04-01_final
2018-04-01 10:58:13	ga_ls8c_ard_3-0-0_106083_2018-04-01_final
2018-04-01 10:58:37	ga_ls8c_ard_3-0-0_106084_2018-04-01_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-13 11:03:56	ga_ls8c_ard_3-2-1_107079_2022-11-13_final
2022-11-13 11:04:20	ga_ls8c_ard_3-2-1_107080_2022-11-13_final
2022-11-13 11:04:44	ga_ls8c_ard_3-2-1_107081_2022-11-13_final
2022-11-15 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-11-15_final
2022-11-20 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-11-20_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-20 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-11-20_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-20 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-11-20_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-06 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-12-06_final
2022-12-06 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-12-06_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-06 11:08:30	ga_ls8c_ard_3-2-1_108075_2022-12-06_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-17 10:53:03	ga_ls8c_ard_3-2-1_105083_2022-12-17_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-24 10:58:22	ga_ls8c_ard_3-2-1_106081_2022-12-24_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-24 10:59:09	ga_ls8c_ard_3-2-1_106083_2022-12-24_final
2022-12-29 11:12:08	ga_ls8c_ard_3-2-1_109069_2022-12-29_final
2022-12-29 11:12:32	ga_ls8c_ard_3-2-1_109070_2022-12-29_final
2022-12-29 11:12:56	ga_ls8c_ard_3-2-1_109071_2022-12-29_final
2022-12-29 11:13:20	ga_ls8c_ard_3-2-1_109072_2022-12-29_final
2023-02-01 11:02:09	ga_ls8c_ard_3-2-1_107075_2023-02-01_final
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-02-01 11:02:57	ga_ls8c_ard_3-2-1_107077_2023-02-01_final
2023-02-01 11:03:21	ga_ls8c_ard_3-2-1_107078_2023-02-01_final
2023-02-01 11:03:45	ga_ls8c_ard_3-2-1_107079_2023-02-01_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-03 10:52:59	ga_ls8c_ard_3-2-1_105083_2023-02-03_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-02-26 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-02-26_final
2023-02-26 10:58:50	ga_ls8c_ard_3-2-1_106083_2023-02-26_final
2023-03-05 11:01:47	ga_ls8c_ard_3-2-1_107075_2023-03-05_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-14 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-03-14_final
2023-07-27 11:03:33	ga_ls8c_ard_3-2-1_107080_2023-07-27_final
2023-07-27 11:03:57	ga_ls8c_ard_3-2-1_107081_2023-07-27_final
2023-07-29 10:52:25	ga_ls8c_ard_3-2-1_105083_2023-07-29_final
2023-08-10 11:11:35	ga_ls8c_ard_3-2-1_109069_2023-08-10_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-10 11:12:23	ga_ls8c_ard_3-2-1_109071_2023-08-10_final
2023-08-10 11:12:47	ga_ls8c_ard_3-2-1_109072_2023-08-10_final
2023-08-21 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-08-21_final
2023-08-21 10:57:57	ga_ls8c_ard_3-2-1_106081_2023-08-21_final
2023-08-21 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-08-21_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