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
2017-05-17 09:56:13	ga_ls8c_ard_3-0-0_097067_2017-05-17_final
2017-05-17 09:56:37	ga_ls8c_ard_3-0-0_097068_2017-05-17_final
2017-05-17 09:57:01	ga_ls8c_ard_3-0-0_097069_2017-05-17_final
2017-05-17 09:57:25	ga_ls8c_ard_3-1-0_097070_2017-05-17_final
2017-05-17 09:57:49	ga_ls8c_ard_3-0-0_097071_2017-05-17_final
2017-05-17 09:58:13	ga_ls8c_ard_3-0-0_097072_2017-05-17_final
2017-05-17 09:58:37	ga_ls8c_ard_3-0-0_097073_2017-05-17_final
2017-05-17 09:59:01	ga_ls8c_ard_3-0-0_097074_2017-05-17_final
2017-05-17 09:59:25	ga_ls8c_ard_3-0-0_097075_2017-05-17_final
2017-05-17 09:59:49	ga_ls8c_ard_3-0-0_097076_2017-05-17_final
2017-05-17 10:00:13	ga_ls8c_ard_3-0-0_097077_2017-05-17_final
2017-05-17 10:00:37	ga_ls8c_ard_3-1-0_097078_2017-05-17_final
2017-05-17 10:01:01	ga_ls8c_ard_3-0-0_097079_2017-05-17_final
2017-05-17 10:01:24	ga_ls8c_ard_3-0-0_097080_2017-05-17_final
2017-05-17 10:01:48	ga_ls8c_ard_3-0-0_097081_2017-05-17_final
2017-05-17 10:02:12	ga_ls8c_ard_3-0-0_097082_2017-05-17_final
2017-05-17 10:02:36	ga_ls8c_ard_3-0-0_097083_2017-05-17_final
2017-05-17 10:03:00	ga_ls8c_ard_3-0-0_097084_2017-05-17_final
2017-05-17 10:03:24	ga_ls8c_ard_3-0-0_097085_2017-05-17_final
2017-05-17 10:03:48	ga_ls8c_ard_3-0-0_097086_2017-05-17_final
2017-05-17 11:35:06	ga_ls8c_ard_3-0-0_113067_2017-05-17_final
2017-05-17 11:37:06	ga_ls8c_ard_3-0-0_113072_2017-05-17_final
2017-05-17 11:37:30	ga_ls8c_ard_3-1-0_113073_2017-05-17_final
2017-05-17 11:37:54	ga_ls8c_ard_3-0-0_113074_2017-05-17_final
2017-05-17 11:38:18	ga_ls8c_ard_3-0-0_113075_2017-05-17_final
2017-05-17 11:38:42	ga_ls8c_ard_3-0-0_113076_2017-05-17_final
2017-05-17 11:39:06	ga_ls8c_ard_3-0-0_113077_2017-05-17_final
2017-05-17 11:39:30	ga_ls8c_ard_3-0-0_113078_2017-05-17_final
2017-05-17 11:39:54	ga_ls8c_ard_3-0-0_113079_2017-05-17_final
2017-05-17 11:40:18	ga_ls8c_ard_3-0-0_113080_2017-05-17_final
2017-05-17 11:40:42	ga_ls8c_ard_3-0-0_113081_2017-05-17_final
2017-05-17 11:41:05	ga_ls8c_ard_3-0-0_113082_2017-05-17_final
2017-05-17 11:41:29	ga_ls8c_ard_3-0-0_113083_2017-05-17_final
2017-05-17 11:41:53	ga_ls8c_ard_3-0-0_113084_2017-05-17_final
2017-05-18 09:05:24	ga_ls8c_ard_3-0-0_088079_2017-05-17_final
2017-05-18 09:05:48	ga_ls8c_ard_3-0-0_088080_2017-05-17_final
2017-05-18 09:06:12	ga_ls8c_ard_3-1-0_088081_2017-05-17_final
2017-05-18 09:06:36	ga_ls8c_ard_3-0-0_088082_2017-05-17_final
2017-05-18 09:07:00	ga_ls8c_ard_3-0-0_088083_2017-05-17_final
2017-05-18 09:07:24	ga_ls8c_ard_3-0-0_088084_2017-05-17_final
2017-05-18 10:39:30	ga_ls8c_ard_3-0-0_104067_2017-05-18_final
2017-05-18 10:39:54	ga_ls8c_ard_3-0-0_104068_2017-05-18_final
2017-05-18 10:40:18	ga_ls8c_ard_3-0-0_104069_2017-05-18_final
2017-05-18 10:40:41	ga_ls8c_ard_3-0-0_104070_2017-05-18_final
2017-05-18 10:41:05	ga_ls8c_ard_3-0-0_104071_2017-05-18_final
2017-05-18 10:41:29	ga_ls8c_ard_3-0-0_104072_2017-05-18_final
2017-05-18 10:41:53	ga_ls8c_ard_3-0-0_104073_2017-05-18_final
2017-05-18 10:42:17	ga_ls8c_ard_3-0-0_104074_2017-05-18_final
2017-05-18 10:42:41	ga_ls8c_ard_3-0-0_104075_2017-05-18_final
2017-05-18 10:43:05	ga_ls8c_ard_3-0-0_104076_2017-05-18_final
2017-05-18 10:43:29	ga_ls8c_ard_3-1-0_104077_2017-05-18_final
2017-05-18 10:43:53	ga_ls8c_ard_3-0-0_104078_2017-05-18_final
2017-05-18 10:44:17	ga_ls8c_ard_3-0-0_104079_2017-05-18_final
2017-05-18 10:44:41	ga_ls8c_ard_3-0-0_104080_2017-05-18_final
2017-05-18 10:45:05	ga_ls8c_ard_3-0-0_104081_2017-05-18_final
2017-05-18 10:45:29	ga_ls8c_ard_3-0-0_104082_2017-05-18_final
2017-05-18 10:45:53	ga_ls8c_ard_3-0-0_104083_2017-05-18_final
2017-05-19 09:43:53	ga_ls8c_ard_3-0-0_095067_2017-05-19_final
2017-05-19 09:45:05	ga_ls8c_ard_3-0-0_095070_2017-05-19_final
2017-05-19 09:45:29	ga_ls8c_ard_3-0-0_095071_2017-05-19_final
2017-05-19 09:45:53	ga_ls8c_ard_3-0-0_095072_2017-05-19_final
2017-05-19 09:46:17	ga_ls8c_ard_3-0-0_095073_2017-05-19_final
2017-05-19 09:46:41	ga_ls8c_ard_3-0-0_095074_2017-05-19_final
2017-05-19 09:47:05	ga_ls8c_ard_3-0-0_095075_2017-05-19_final
2017-05-19 09:47:28	ga_ls8c_ard_3-0-0_095076_2017-05-19_final
2017-05-19 09:47:52	ga_ls8c_ard_3-0-0_095077_2017-05-19_final
2017-05-19 09:48:16	ga_ls8c_ard_3-0-0_095078_2017-05-19_final
2017-05-19 09:48:40	ga_ls8c_ard_3-0-0_095079_2017-05-19_final
2017-05-19 09:49:04	ga_ls8c_ard_3-0-0_095080_2017-05-19_final
2017-05-19 09:49:28	ga_ls8c_ard_3-0-0_095081_2017-05-19_final
2017-05-19 09:49:52	ga_ls8c_ard_3-0-0_095082_2017-05-19_final
2017-05-19 09:50:16	ga_ls8c_ard_3-0-0_095083_2017-05-19_final
2017-05-19 09:50:40	ga_ls8c_ard_3-0-0_095084_2017-05-19_final
2017-05-19 09:51:04	ga_ls8c_ard_3-0-0_095085_2017-05-19_final
2017-05-19 09:51:28	ga_ls8c_ard_3-0-0_095086_2017-05-19_final
2017-05-19 09:51:52	ga_ls8c_ard_3-0-0_095087_2017-05-19_final
2017-05-19 09:52:16	ga_ls8c_ard_3-0-0_095088_2017-05-19_final
2017-05-19 11:22:46	ga_ls8c_ard_3-0-0_111067_2017-05-19_final
2017-05-19 11:23:10	ga_ls8c_ard_3-0-0_111068_2017-05-19_final
2017-05-19 11:23:34	ga_ls8c_ard_3-0-0_111069_2017-05-19_final
2017-05-19 11:23:58	ga_ls8c_ard_3-0-0_111070_2017-05-19_final
2017-05-19 11:24:22	ga_ls8c_ard_3-0-0_111071_2017-05-19_final
2017-05-19 11:24:46	ga_ls8c_ard_3-0-0_111072_2017-05-19_final
2017-05-19 11:25:10	ga_ls8c_ard_3-0-0_111073_2017-05-19_final
2017-05-19 11:25:34	ga_ls8c_ard_3-0-0_111074_2017-05-19_final
2017-05-19 11:25:58	ga_ls8c_ard_3-0-0_111075_2017-05-19_final
2017-05-19 11:26:22	ga_ls8c_ard_3-0-0_111076_2017-05-19_final
2017-05-19 11:26:45	ga_ls8c_ard_3-0-0_111077_2017-05-19_final
2017-05-19 11:27:09	ga_ls8c_ard_3-0-0_111078_2017-05-19_final
2017-05-19 11:27:33	ga_ls8c_ard_3-0-0_111079_2017-05-19_final
2017-05-19 11:27:57	ga_ls8c_ard_3-0-0_111080_2017-05-19_final
2017-05-19 11:28:21	ga_ls8c_ard_3-0-0_111081_2017-05-19_final
2017-05-19 11:28:45	ga_ls8c_ard_3-0-0_111082_2017-05-19_final
2017-05-19 11:29:09	ga_ls8c_ard_3-0-0_111083_2017-05-19_final
2017-05-19 11:29:33	ga_ls8c_ard_3-0-0_111084_2017-05-19_final
2017-05-19 11:29:57	ga_ls8c_ard_3-0-0_111085_2017-05-19_final
2017-05-28 09:37:48	ga_ls8c_ard_3-0-0_094067_2017-05-28_final
2017-05-28 09:39:24	ga_ls8c_ard_3-0-0_094071_2017-05-28_final
2017-05-28 09:39:47	ga_ls8c_ard_3-0-0_094072_2017-05-28_final
2017-05-30 09:25:27	ga_ls8c_ard_3-0-0_092067_2017-05-29_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2017

May

All days