Search ga_ls8c_ard_3 across June 2016

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
2016-06-01 09:44:04	ga_ls8c_ard_3-0-0_095067_2016-06-01_final
2016-06-01 09:45:16	ga_ls8c_ard_3-0-0_095070_2016-06-01_final
2016-06-01 09:45:40	ga_ls8c_ard_3-0-0_095071_2016-06-01_final
2016-06-01 09:46:04	ga_ls8c_ard_3-0-0_095072_2016-06-01_final
2016-06-01 09:46:28	ga_ls8c_ard_3-0-0_095073_2016-06-01_final
2016-06-01 09:46:52	ga_ls8c_ard_3-0-0_095074_2016-06-01_final
2016-06-01 09:47:16	ga_ls8c_ard_3-0-0_095075_2016-06-01_final
2016-06-01 09:47:40	ga_ls8c_ard_3-0-0_095076_2016-06-01_final
2016-06-01 09:48:04	ga_ls8c_ard_3-0-0_095077_2016-06-01_final
2016-06-01 09:48:28	ga_ls8c_ard_3-0-0_095078_2016-06-01_final
2016-06-01 09:48:51	ga_ls8c_ard_3-0-0_095079_2016-06-01_final
2016-06-01 09:49:15	ga_ls8c_ard_3-0-0_095080_2016-06-01_final
2016-06-01 09:49:39	ga_ls8c_ard_3-0-0_095081_2016-06-01_final
2016-06-01 09:50:03	ga_ls8c_ard_3-0-0_095082_2016-06-01_final
2016-06-01 09:50:27	ga_ls8c_ard_3-0-0_095083_2016-06-01_final
2016-06-01 09:50:51	ga_ls8c_ard_3-0-0_095084_2016-06-01_final
2016-06-01 09:51:15	ga_ls8c_ard_3-0-0_095085_2016-06-01_final
2016-06-01 09:51:39	ga_ls8c_ard_3-0-0_095086_2016-06-01_final
2016-06-01 09:52:03	ga_ls8c_ard_3-0-0_095087_2016-06-01_final
2016-06-01 09:52:27	ga_ls8c_ard_3-0-0_095088_2016-06-01_final
2016-06-01 11:22:57	ga_ls8c_ard_3-0-0_111067_2016-06-01_final
2016-06-01 11:23:21	ga_ls8c_ard_3-0-0_111068_2016-06-01_final
2016-06-01 11:23:45	ga_ls8c_ard_3-0-0_111069_2016-06-01_final
2016-06-01 11:24:09	ga_ls8c_ard_3-0-0_111070_2016-06-01_final
2016-06-01 11:24:33	ga_ls8c_ard_3-0-0_111071_2016-06-01_final
2016-06-01 11:24:57	ga_ls8c_ard_3-0-0_111072_2016-06-01_final
2016-06-01 11:25:21	ga_ls8c_ard_3-0-0_111073_2016-06-01_final
2016-06-01 11:25:45	ga_ls8c_ard_3-0-0_111074_2016-06-01_final
2016-06-01 11:26:09	ga_ls8c_ard_3-0-0_111075_2016-06-01_final
2016-06-01 11:26:33	ga_ls8c_ard_3-0-0_111076_2016-06-01_final
2016-06-01 11:26:57	ga_ls8c_ard_3-0-0_111077_2016-06-01_final
2016-06-01 11:27:21	ga_ls8c_ard_3-0-0_111078_2016-06-01_final
2016-06-01 11:27:45	ga_ls8c_ard_3-0-0_111079_2016-06-01_final
2016-06-01 11:28:08	ga_ls8c_ard_3-0-0_111080_2016-06-01_final
2016-06-01 11:28:32	ga_ls8c_ard_3-0-0_111081_2016-06-01_final
2016-06-01 11:28:56	ga_ls8c_ard_3-0-0_111082_2016-06-01_final
2016-06-01 11:29:20	ga_ls8c_ard_3-0-0_111083_2016-06-01_final
2016-06-01 11:29:44	ga_ls8c_ard_3-0-0_111084_2016-06-01_final
2016-06-01 11:30:08	ga_ls8c_ard_3-0-0_111085_2016-06-01_final
2016-06-02 10:27:20	ga_ls8c_ard_3-0-0_102067_2016-06-02_final
2016-06-02 10:27:44	ga_ls8c_ard_3-0-0_102068_2016-06-02_final
2016-06-02 10:28:08	ga_ls8c_ard_3-0-0_102069_2016-06-02_final
2016-06-02 10:28:32	ga_ls8c_ard_3-0-0_102070_2016-06-02_final
2016-06-02 10:28:56	ga_ls8c_ard_3-1-0_102071_2016-06-02_final
2016-06-02 10:29:20	ga_ls8c_ard_3-0-0_102072_2016-06-02_final
2016-06-02 10:29:44	ga_ls8c_ard_3-0-0_102073_2016-06-02_final
2016-06-02 10:30:08	ga_ls8c_ard_3-0-0_102074_2016-06-02_final
2016-06-02 10:30:32	ga_ls8c_ard_3-0-0_102075_2016-06-02_final
2016-06-02 10:30:56	ga_ls8c_ard_3-0-0_102076_2016-06-02_final
2016-06-02 10:31:20	ga_ls8c_ard_3-1-0_102077_2016-06-02_final
2016-06-02 10:31:43	ga_ls8c_ard_3-0-0_102078_2016-06-02_final
2016-06-02 10:32:07	ga_ls8c_ard_3-0-0_102079_2016-06-02_final
2016-06-02 10:32:31	ga_ls8c_ard_3-1-0_102080_2016-06-02_final
2016-06-02 10:32:55	ga_ls8c_ard_3-0-0_102081_2016-06-02_final
2016-06-02 10:33:19	ga_ls8c_ard_3-0-0_102082_2016-06-02_final
2016-06-02 10:33:43	ga_ls8c_ard_3-0-0_102083_2016-06-02_final
2016-06-03 09:31:43	ga_ls8c_ard_3-0-0_093067_2016-06-03_final
2016-06-03 09:32:07	ga_ls8c_ard_3-0-0_093068_2016-06-03_final
2016-06-03 09:33:19	ga_ls8c_ard_3-0-0_093071_2016-06-03_final
2016-06-03 09:33:43	ga_ls8c_ard_3-0-0_093072_2016-06-03_final
2016-06-03 09:34:07	ga_ls8c_ard_3-0-0_093073_2016-06-03_final
2016-06-03 09:34:31	ga_ls8c_ard_3-0-0_093074_2016-06-03_final
2016-06-03 09:34:55	ga_ls8c_ard_3-0-0_093075_2016-06-03_final
2016-06-03 09:35:18	ga_ls8c_ard_3-0-0_093076_2016-06-03_final
2016-06-03 09:35:42	ga_ls8c_ard_3-0-0_093077_2016-06-03_final
2016-06-03 09:36:06	ga_ls8c_ard_3-0-0_093078_2016-06-03_final
2016-06-03 09:36:30	ga_ls8c_ard_3-0-0_093079_2016-06-03_final
2016-06-03 09:36:54	ga_ls8c_ard_3-0-0_093080_2016-06-03_final
2016-06-03 09:37:18	ga_ls8c_ard_3-0-0_093081_2016-06-03_final
2016-06-03 09:37:42	ga_ls8c_ard_3-0-0_093082_2016-06-03_final
2016-06-03 09:38:06	ga_ls8c_ard_3-0-0_093083_2016-06-03_final
2016-06-03 09:38:30	ga_ls8c_ard_3-0-0_093084_2016-06-03_final
2016-06-03 09:38:54	ga_ls8c_ard_3-0-0_093085_2016-06-03_final
2016-06-03 09:39:18	ga_ls8c_ard_3-0-0_093086_2016-06-03_final
2016-06-03 09:39:42	ga_ls8c_ard_3-0-0_093087_2016-06-03_final
2016-06-03 09:40:06	ga_ls8c_ard_3-0-0_093088_2016-06-03_final
2016-06-03 11:10:36	ga_ls8c_ard_3-0-0_109067_2016-06-03_final
2016-06-03 11:11:00	ga_ls8c_ard_3-0-0_109068_2016-06-03_final
2016-06-03 11:11:24	ga_ls8c_ard_3-0-0_109069_2016-06-03_final
2016-06-03 11:11:48	ga_ls8c_ard_3-0-0_109070_2016-06-03_final
2016-06-03 11:12:12	ga_ls8c_ard_3-0-0_109071_2016-06-03_final
2016-06-04 10:14:59	ga_ls8c_ard_3-0-0_100067_2016-06-04_final
2016-06-04 10:15:23	ga_ls8c_ard_3-0-0_100068_2016-06-04_final
2016-06-04 10:15:47	ga_ls8c_ard_3-0-0_100069_2016-06-04_final
2016-06-04 10:16:11	ga_ls8c_ard_3-0-0_100070_2016-06-04_final
2016-06-04 10:16:35	ga_ls8c_ard_3-0-0_100071_2016-06-04_final
2016-06-04 10:16:59	ga_ls8c_ard_3-0-0_100072_2016-06-04_final
2016-06-04 10:17:23	ga_ls8c_ard_3-0-0_100073_2016-06-04_final
2016-06-04 10:17:47	ga_ls8c_ard_3-0-0_100074_2016-06-04_final
2016-06-04 10:18:10	ga_ls8c_ard_3-0-0_100075_2016-06-04_final
2016-06-04 10:18:34	ga_ls8c_ard_3-0-0_100076_2016-06-04_final
2016-06-04 10:18:58	ga_ls8c_ard_3-0-0_100077_2016-06-04_final
2016-06-04 10:19:22	ga_ls8c_ard_3-0-0_100078_2016-06-04_final
2016-06-04 10:19:46	ga_ls8c_ard_3-0-0_100079_2016-06-04_final
2016-06-04 10:20:10	ga_ls8c_ard_3-0-0_100080_2016-06-04_final
2016-06-04 10:20:34	ga_ls8c_ard_3-0-0_100081_2016-06-04_final
2016-06-04 10:20:58	ga_ls8c_ard_3-0-0_100082_2016-06-04_final
2016-06-04 10:21:22	ga_ls8c_ard_3-0-0_100083_2016-06-04_final
2016-06-04 10:21:46	ga_ls8c_ard_3-0-0_100084_2016-06-04_final
2016-06-04 10:22:10	ga_ls8c_ard_3-0-0_100085_2016-06-04_final

Return to ga_ls8c_ard_3 across June 2016 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

2016

June

All days