Search ga_ls8c_ard_3 across May 2017

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
2017-05-08 10:02:17	ga_ls8c_ard_3-0-0_098067_2017-05-08_final
2017-05-08 10:02:41	ga_ls8c_ard_3-0-0_098068_2017-05-08_final
2017-05-08 10:03:05	ga_ls8c_ard_3-0-0_098069_2017-05-08_final
2017-05-08 10:03:29	ga_ls8c_ard_3-0-0_098070_2017-05-08_final
2017-05-08 10:03:53	ga_ls8c_ard_3-0-0_098071_2017-05-08_final
2017-05-08 10:04:17	ga_ls8c_ard_3-0-0_098072_2017-05-08_final
2017-05-08 10:04:41	ga_ls8c_ard_3-0-0_098073_2017-05-08_final
2017-05-08 10:05:05	ga_ls8c_ard_3-0-0_098074_2017-05-08_final
2017-05-08 10:05:29	ga_ls8c_ard_3-0-0_098075_2017-05-08_final
2017-05-08 10:05:53	ga_ls8c_ard_3-0-0_098076_2017-05-08_final
2017-05-08 10:06:17	ga_ls8c_ard_3-0-0_098077_2017-05-08_final
2017-05-08 10:06:41	ga_ls8c_ard_3-0-0_098078_2017-05-08_final
2017-05-08 10:07:05	ga_ls8c_ard_3-0-0_098079_2017-05-08_final
2017-05-08 10:07:29	ga_ls8c_ard_3-0-0_098080_2017-05-08_final
2017-05-08 10:07:53	ga_ls8c_ard_3-0-0_098081_2017-05-08_final
2017-05-08 10:08:16	ga_ls8c_ard_3-0-0_098082_2017-05-08_final
2017-05-08 10:08:40	ga_ls8c_ard_3-0-0_098083_2017-05-08_final
2017-05-08 10:09:04	ga_ls8c_ard_3-0-0_098084_2017-05-08_final
2017-05-08 10:09:28	ga_ls8c_ard_3-0-0_098085_2017-05-08_final
2017-05-08 10:09:52	ga_ls8c_ard_3-0-0_098086_2017-05-08_final
2017-05-09 09:09:28	ga_ls8c_ard_3-0-0_089074_2017-05-08_final
2017-05-09 09:09:52	ga_ls8c_ard_3-0-0_089075_2017-05-08_final
2017-05-09 09:10:16	ga_ls8c_ard_3-0-0_089076_2017-05-08_final
2017-05-09 09:10:40	ga_ls8c_ard_3-0-0_089077_2017-05-08_final
2017-05-09 09:11:04	ga_ls8c_ard_3-0-0_089078_2017-05-08_final
2017-05-09 09:11:28	ga_ls8c_ard_3-0-0_089079_2017-05-08_final
2017-05-09 09:11:52	ga_ls8c_ard_3-0-0_089080_2017-05-08_final
2017-05-09 09:12:16	ga_ls8c_ard_3-0-0_089081_2017-05-08_final
2017-05-09 09:12:40	ga_ls8c_ard_3-0-0_089082_2017-05-08_final
2017-05-09 09:13:04	ga_ls8c_ard_3-0-0_089083_2017-05-08_final
2017-05-09 09:13:28	ga_ls8c_ard_3-0-0_089084_2017-05-08_final
2017-05-09 09:13:52	ga_ls8c_ard_3-0-0_089085_2017-05-08_final
2017-05-09 09:14:16	ga_ls8c_ard_3-0-0_089086_2017-05-08_final
2017-05-09 09:14:40	ga_ls8c_ard_3-0-0_089087_2017-05-08_final
2017-05-09 09:15:04	ga_ls8c_ard_3-0-0_089088_2017-05-08_final
2017-05-09 09:15:28	ga_ls8c_ard_3-0-0_089089_2017-05-08_final
2017-05-09 09:15:52	ga_ls8c_ard_3-0-0_089090_2017-05-08_final
2017-05-09 10:45:34	ga_ls8c_ard_3-0-0_105067_2017-05-09_final
2017-05-24 10:02:29	ga_ls8c_ard_3-0-0_098067_2017-05-24_final
2017-05-24 10:02:53	ga_ls8c_ard_3-0-0_098068_2017-05-24_final
2017-05-24 10:03:17	ga_ls8c_ard_3-0-0_098069_2017-05-24_final
2017-05-24 10:03:40	ga_ls8c_ard_3-0-0_098070_2017-05-24_final
2017-05-24 10:04:04	ga_ls8c_ard_3-0-0_098071_2017-05-24_final
2017-05-24 10:04:28	ga_ls8c_ard_3-0-0_098072_2017-05-24_final
2017-05-24 10:04:52	ga_ls8c_ard_3-0-0_098073_2017-05-24_final
2017-05-24 10:05:16	ga_ls8c_ard_3-0-0_098074_2017-05-24_final
2017-05-24 10:05:40	ga_ls8c_ard_3-0-0_098075_2017-05-24_final
2017-05-24 10:06:04	ga_ls8c_ard_3-0-0_098076_2017-05-24_final
2017-05-24 10:06:28	ga_ls8c_ard_3-0-0_098077_2017-05-24_final
2017-05-24 10:06:52	ga_ls8c_ard_3-0-0_098078_2017-05-24_final
2017-05-24 10:07:16	ga_ls8c_ard_3-0-0_098079_2017-05-24_final
2017-05-24 10:07:40	ga_ls8c_ard_3-0-0_098080_2017-05-24_final
2017-05-24 10:08:04	ga_ls8c_ard_3-0-0_098081_2017-05-24_final
2017-05-24 10:08:28	ga_ls8c_ard_3-0-0_098082_2017-05-24_final
2017-05-24 10:08:52	ga_ls8c_ard_3-0-0_098083_2017-05-24_final
2017-05-24 10:09:16	ga_ls8c_ard_3-0-0_098084_2017-05-24_final
2017-05-24 10:09:40	ga_ls8c_ard_3-0-0_098085_2017-05-24_final
2017-05-24 10:10:04	ga_ls8c_ard_3-0-0_098086_2017-05-24_final
2017-05-24 11:41:22	ga_ls8c_ard_3-0-0_114067_2017-05-24_final
2017-05-24 11:44:09	ga_ls8c_ard_3-0-0_114074_2017-05-24_final
2017-05-24 11:44:33	ga_ls8c_ard_3-0-0_114075_2017-05-24_final
2017-05-24 11:44:57	ga_ls8c_ard_3-0-0_114076_2017-05-24_final
2017-05-24 11:45:21	ga_ls8c_ard_3-0-0_114077_2017-05-24_final
2017-05-24 11:45:45	ga_ls8c_ard_3-0-0_114078_2017-05-24_final
2017-05-24 11:46:09	ga_ls8c_ard_3-0-0_114079_2017-05-24_final
2017-05-24 11:46:33	ga_ls8c_ard_3-0-0_114080_2017-05-24_final
2017-05-24 11:46:57	ga_ls8c_ard_3-0-0_114081_2017-05-24_final
2017-05-25 09:09:40	ga_ls8c_ard_3-0-0_089074_2017-05-24_final
2017-05-25 09:10:03	ga_ls8c_ard_3-0-0_089075_2017-05-24_final
2017-05-25 09:10:27	ga_ls8c_ard_3-0-0_089076_2017-05-24_final
2017-05-25 09:10:51	ga_ls8c_ard_3-0-0_089077_2017-05-24_final
2017-05-25 09:11:15	ga_ls8c_ard_3-0-0_089078_2017-05-24_final
2017-05-25 09:11:39	ga_ls8c_ard_3-0-0_089079_2017-05-24_final
2017-05-25 09:12:03	ga_ls8c_ard_3-0-0_089080_2017-05-24_final
2017-05-25 09:12:27	ga_ls8c_ard_3-0-0_089081_2017-05-24_final
2017-05-25 09:12:51	ga_ls8c_ard_3-0-0_089082_2017-05-24_final
2017-05-25 09:13:15	ga_ls8c_ard_3-0-0_089083_2017-05-24_final
2017-05-25 09:13:39	ga_ls8c_ard_3-0-0_089084_2017-05-24_final
2017-05-25 09:14:03	ga_ls8c_ard_3-0-0_089085_2017-05-24_final
2017-05-25 09:14:27	ga_ls8c_ard_3-0-0_089086_2017-05-24_final
2017-05-25 09:14:51	ga_ls8c_ard_3-0-0_089087_2017-05-24_final
2017-05-25 09:15:15	ga_ls8c_ard_3-0-0_089088_2017-05-24_final
2017-05-25 09:15:39	ga_ls8c_ard_3-0-0_089089_2017-05-24_final
2017-05-25 09:16:03	ga_ls8c_ard_3-0-0_089090_2017-05-24_final
2017-05-25 10:45:45	ga_ls8c_ard_3-0-0_105067_2017-05-25_final
2017-05-25 10:46:09	ga_ls8c_ard_3-0-0_105068_2017-05-25_final
2017-05-25 10:46:33	ga_ls8c_ard_3-0-0_105069_2017-05-25_final
2017-05-25 10:46:57	ga_ls8c_ard_3-0-0_105070_2017-05-25_final
2017-05-25 10:47:21	ga_ls8c_ard_3-0-0_105071_2017-05-25_final
2017-05-25 10:47:45	ga_ls8c_ard_3-0-0_105072_2017-05-25_final
2017-05-25 10:48:09	ga_ls8c_ard_3-0-0_105073_2017-05-25_final
2017-05-25 10:48:33	ga_ls8c_ard_3-0-0_105074_2017-05-25_final
2017-05-25 10:48:56	ga_ls8c_ard_3-0-0_105075_2017-05-25_final
2017-05-25 10:49:20	ga_ls8c_ard_3-0-0_105076_2017-05-25_final
2017-05-25 10:49:44	ga_ls8c_ard_3-0-0_105077_2017-05-25_final
2017-05-25 10:50:08	ga_ls8c_ard_3-0-0_105078_2017-05-25_final
2017-05-25 10:50:32	ga_ls8c_ard_3-0-0_105079_2017-05-25_final
2017-05-25 10:50:56	ga_ls8c_ard_3-0-0_105080_2017-05-25_final
2017-05-25 10:51:20	ga_ls8c_ard_3-0-0_105081_2017-05-25_final
2017-05-25 10:51:44	ga_ls8c_ard_3-0-0_105082_2017-05-25_final

Return to ga_ls8c_ard_3 across May 2017 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

2017

May

All days