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
2022-04-02 10:16:38	ga_ls8c_ard_3-2-1_100071_2022-04-02_final
2022-04-02 10:17:02	ga_ls8c_ard_3-2-1_100072_2022-04-02_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 10:19:50	ga_ls8c_ard_3-2-1_100079_2022-04-02_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-02 10:20:38	ga_ls8c_ard_3-2-1_100081_2022-04-02_final
2022-04-02 10:21:02	ga_ls8c_ard_3-2-1_100082_2022-04-02_final
2022-04-02 10:21:26	ga_ls8c_ard_3-2-1_100083_2022-04-02_final
2022-04-02 10:21:50	ga_ls8c_ard_3-2-1_100084_2022-04-02_final
2022-04-02 11:57:31	ga_ls8c_ard_3-2-1_116076_2022-04-02_final
2022-04-02 11:57:55	ga_ls8c_ard_3-2-1_116077_2022-04-02_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-03 09:21:25	ga_ls8c_ard_3-2-1_091072_2022-04-02_final
2022-04-03 09:21:49	ga_ls8c_ard_3-2-1_091073_2022-04-02_final
2022-04-03 09:22:13	ga_ls8c_ard_3-2-1_091074_2022-04-02_final
2022-04-03 09:22:37	ga_ls8c_ard_3-2-1_091075_2022-04-02_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 09:24:13	ga_ls8c_ard_3-2-1_091079_2022-04-02_final
2022-04-03 09:24:37	ga_ls8c_ard_3-2-1_091080_2022-04-02_final
2022-04-03 09:25:00	ga_ls8c_ard_3-2-1_091081_2022-04-02_final
2022-04-03 09:25:24	ga_ls8c_ard_3-2-1_091082_2022-04-02_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-03 09:26:12	ga_ls8c_ard_3-2-1_091084_2022-04-02_final
2022-04-03 09:26:36	ga_ls8c_ard_3-2-1_091085_2022-04-02_final
2022-04-03 09:27:00	ga_ls8c_ard_3-2-1_091086_2022-04-02_final
2022-04-03 09:27:24	ga_ls8c_ard_3-2-1_091087_2022-04-02_final
2022-04-03 09:27:48	ga_ls8c_ard_3-2-1_091088_2022-04-02_final
2022-04-03 09:28:12	ga_ls8c_ard_3-2-1_091089_2022-04-02_final
2022-04-03 09:28:36	ga_ls8c_ard_3-2-1_091090_2022-04-02_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-03 11:01:06	ga_ls8c_ard_3-2-1_107074_2022-04-03_final
2022-04-03 11:01:30	ga_ls8c_ard_3-2-1_107075_2022-04-03_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-03 11:04:17	ga_ls8c_ard_3-2-1_107082_2022-04-03_final
2022-04-03 11:04:41	ga_ls8c_ard_3-2-1_107083_2022-04-03_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-04 10:02:42	ga_ls8c_ard_3-2-1_098067_2022-04-04_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-04 10:03:30	ga_ls8c_ard_3-2-1_098069_2022-04-04_final
2022-04-04 10:04:18	ga_ls8c_ard_3-2-1_098071_2022-04-04_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-04 10:06:41	ga_ls8c_ard_3-2-1_098077_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-04 10:07:29	ga_ls8c_ard_3-2-1_098079_2022-04-04_final
2022-04-04 10:07:53	ga_ls8c_ard_3-2-1_098080_2022-04-04_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-04 10:09:29	ga_ls8c_ard_3-2-1_098084_2022-04-04_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-04 11:44:23	ga_ls8c_ard_3-2-1_114074_2022-04-04_final
2022-04-04 11:44:46	ga_ls8c_ard_3-2-1_114075_2022-04-04_final
2022-04-04 11:45:10	ga_ls8c_ard_3-2-1_114076_2022-04-04_final
2022-04-04 11:45:34	ga_ls8c_ard_3-2-1_114077_2022-04-04_final
2022-04-04 11:45:58	ga_ls8c_ard_3-2-1_114078_2022-04-04_final
2022-04-04 11:46:22	ga_ls8c_ard_3-2-1_114079_2022-04-04_final
2022-04-04 11:46:46	ga_ls8c_ard_3-2-1_114080_2022-04-04_final
2022-04-04 11:47:10	ga_ls8c_ard_3-2-1_114081_2022-04-04_final
2022-04-05 09:09:53	ga_ls8c_ard_3-2-1_089074_2022-04-04_final
2022-04-05 09:10:17	ga_ls8c_ard_3-2-1_089075_2022-04-04_final
2022-04-05 09:10:41	ga_ls8c_ard_3-2-1_089076_2022-04-04_final
2022-04-05 09:11:05	ga_ls8c_ard_3-2-1_089077_2022-04-04_final
2022-04-05 09:11:29	ga_ls8c_ard_3-2-1_089078_2022-04-04_final
2022-04-05 09:11:53	ga_ls8c_ard_3-2-1_089079_2022-04-04_final
2022-04-05 09:12:16	ga_ls8c_ard_3-2-1_089080_2022-04-04_final
2022-04-05 09:12:40	ga_ls8c_ard_3-2-1_089081_2022-04-04_final
2022-04-05 09:13:04	ga_ls8c_ard_3-2-1_089082_2022-04-04_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-05 09:15:52	ga_ls8c_ard_3-2-1_089089_2022-04-04_final
2022-04-05 09:16:16	ga_ls8c_ard_3-2-1_089090_2022-04-04_final
2022-04-05 10:45:58	ga_ls8c_ard_3-2-1_105067_2022-04-05_final
2022-04-05 10:46:22	ga_ls8c_ard_3-2-1_105068_2022-04-05_final
2022-04-05 10:46:46	ga_ls8c_ard_3-2-1_105069_2022-04-05_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-05 10:48:22	ga_ls8c_ard_3-2-1_105073_2022-04-05_final
2022-04-05 10:48:46	ga_ls8c_ard_3-2-1_105074_2022-04-05_final
2022-04-05 10:49:10	ga_ls8c_ard_3-2-1_105075_2022-04-05_final
2022-04-05 10:49:34	ga_ls8c_ard_3-2-1_105076_2022-04-05_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-05 10:50:22	ga_ls8c_ard_3-2-1_105078_2022-04-05_final
2022-04-05 10:51:10	ga_ls8c_ard_3-2-1_105080_2022-04-05_final
2022-04-05 10:51:33	ga_ls8c_ard_3-2-1_105081_2022-04-05_final
2022-04-05 10:51:57	ga_ls8c_ard_3-2-1_105082_2022-04-05_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