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

72 results

Time (local)	Label
2023-06-01 10:10:26	ga_ls8c_ard_3-2-1_099072_2023-06-01_final
2023-06-01 10:11:14	ga_ls8c_ard_3-2-1_099074_2023-06-01_final
2023-06-01 10:12:26	ga_ls8c_ard_3-2-1_099077_2023-06-01_final
2023-06-01 10:12:50	ga_ls8c_ard_3-2-1_099078_2023-06-01_final
2023-06-01 10:14:25	ga_ls8c_ard_3-2-1_099082_2023-06-01_final
2023-06-01 10:14:49	ga_ls8c_ard_3-2-1_099083_2023-06-01_final
2023-06-01 11:51:19	ga_ls8c_ard_3-2-1_115077_2023-06-01_final
2023-06-02 09:15:36	ga_ls8c_ard_3-2-1_090074_2023-06-01_final
2023-06-02 09:16:00	ga_ls8c_ard_3-2-1_090075_2023-06-01_final
2023-06-02 09:16:24	ga_ls8c_ard_3-2-1_090076_2023-06-01_final
2023-06-02 09:16:48	ga_ls8c_ard_3-2-1_090077_2023-06-01_final
2023-06-02 09:17:12	ga_ls8c_ard_3-2-1_090078_2023-06-01_final
2023-06-02 09:18:24	ga_ls8c_ard_3-2-1_090081_2023-06-01_final
2023-06-02 09:20:24	ga_ls8c_ard_3-2-1_090086_2023-06-01_final
2023-06-02 09:21:36	ga_ls8c_ard_3-2-1_090089_2023-06-01_final
2023-06-02 09:22:00	ga_ls8c_ard_3-2-1_090090_2023-06-01_final
2023-06-02 10:52:06	ga_ls8c_ard_3-2-1_106068_2023-06-02_final
2023-06-02 10:54:06	ga_ls8c_ard_3-2-1_106073_2023-06-02_final
2023-06-02 10:54:29	ga_ls8c_ard_3-2-1_106074_2023-06-02_final
2023-06-02 10:56:29	ga_ls8c_ard_3-2-1_106079_2023-06-02_final
2023-06-02 10:56:53	ga_ls8c_ard_3-2-1_106080_2023-06-02_final
2023-06-02 10:57:41	ga_ls8c_ard_3-2-1_106082_2023-06-02_final
2023-06-03 09:56:30	ga_ls8c_ard_3-2-1_097068_2023-06-03_final
2023-06-03 09:58:05	ga_ls8c_ard_3-2-1_097072_2023-06-03_final
2023-06-03 09:58:53	ga_ls8c_ard_3-2-1_097074_2023-06-03_final
2023-06-03 09:59:17	ga_ls8c_ard_3-2-1_097075_2023-06-03_final
2023-06-03 10:01:17	ga_ls8c_ard_3-2-1_097080_2023-06-03_final
2023-06-03 10:01:41	ga_ls8c_ard_3-2-1_097081_2023-06-03_final
2023-06-03 10:02:05	ga_ls8c_ard_3-2-1_097082_2023-06-03_final
2023-06-03 11:36:58	ga_ls8c_ard_3-2-1_113072_2023-06-03_final
2023-06-03 11:37:22	ga_ls8c_ard_3-2-1_113073_2023-06-03_final
2023-06-03 11:39:46	ga_ls8c_ard_3-2-1_113079_2023-06-03_final
2023-06-04 10:40:10	ga_ls8c_ard_3-2-1_104069_2023-06-04_final
2023-06-04 10:40:34	ga_ls8c_ard_3-2-1_104070_2023-06-04_final
2023-06-04 10:42:34	ga_ls8c_ard_3-2-1_104075_2023-06-04_final
2023-06-04 10:42:58	ga_ls8c_ard_3-2-1_104076_2023-06-04_final
2023-06-04 10:43:22	ga_ls8c_ard_3-2-1_104077_2023-06-04_final
2023-06-04 10:44:57	ga_ls8c_ard_3-2-1_104081_2023-06-04_final
2023-06-05 09:45:22	ga_ls8c_ard_3-2-1_095071_2023-06-05_final
2023-06-05 09:45:46	ga_ls8c_ard_3-2-1_095072_2023-06-05_final
2023-06-05 09:46:10	ga_ls8c_ard_3-2-1_095073_2023-06-05_final
2023-06-05 09:46:33	ga_ls8c_ard_3-2-1_095074_2023-06-05_final
2023-06-05 09:46:57	ga_ls8c_ard_3-2-1_095075_2023-06-05_final
2023-06-05 09:47:21	ga_ls8c_ard_3-2-1_095076_2023-06-05_final
2023-06-05 09:47:45	ga_ls8c_ard_3-2-1_095077_2023-06-05_final
2023-06-05 09:48:09	ga_ls8c_ard_3-2-1_095078_2023-06-05_final
2023-06-05 09:48:33	ga_ls8c_ard_3-2-1_095079_2023-06-05_final
2023-06-05 09:48:57	ga_ls8c_ard_3-2-1_095080_2023-06-05_final
2023-06-05 09:49:21	ga_ls8c_ard_3-2-1_095081_2023-06-05_final
2023-06-05 09:49:45	ga_ls8c_ard_3-2-1_095082_2023-06-05_final
2023-06-05 09:50:09	ga_ls8c_ard_3-2-1_095083_2023-06-05_final
2023-06-05 09:50:33	ga_ls8c_ard_3-2-1_095084_2023-06-05_final
2023-06-05 09:50:57	ga_ls8c_ard_3-2-1_095085_2023-06-05_final
2023-06-05 09:51:21	ga_ls8c_ard_3-2-1_095086_2023-06-05_final
2023-06-05 09:51:45	ga_ls8c_ard_3-2-1_095087_2023-06-05_final
2023-06-05 11:23:03	ga_ls8c_ard_3-2-1_111068_2023-06-05_final
2023-06-05 11:23:27	ga_ls8c_ard_3-2-1_111069_2023-06-05_final
2023-06-05 11:23:51	ga_ls8c_ard_3-2-1_111070_2023-06-05_final
2023-06-05 11:24:15	ga_ls8c_ard_3-2-1_111071_2023-06-05_final
2023-06-05 11:24:39	ga_ls8c_ard_3-2-1_111072_2023-06-05_final
2023-06-05 11:25:03	ga_ls8c_ard_3-2-1_111073_2023-06-05_final
2023-06-05 11:25:27	ga_ls8c_ard_3-2-1_111074_2023-06-05_final
2023-06-05 11:25:51	ga_ls8c_ard_3-2-1_111075_2023-06-05_final
2023-06-05 11:26:14	ga_ls8c_ard_3-2-1_111076_2023-06-05_final
2023-06-05 11:26:38	ga_ls8c_ard_3-2-1_111077_2023-06-05_final
2023-06-05 11:27:02	ga_ls8c_ard_3-2-1_111078_2023-06-05_final
2023-06-05 11:27:26	ga_ls8c_ard_3-2-1_111079_2023-06-05_final
2023-06-05 11:27:50	ga_ls8c_ard_3-2-1_111080_2023-06-05_final
2023-06-05 11:28:14	ga_ls8c_ard_3-2-1_111081_2023-06-05_final
2023-06-05 11:28:38	ga_ls8c_ard_3-2-1_111082_2023-06-05_final
2023-06-05 11:29:02	ga_ls8c_ard_3-2-1_111083_2023-06-05_final
2023-06-05 11:29:26	ga_ls8c_ard_3-2-1_111084_2023-06-05_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years