Search ga_ls8c_ard_3 across March 2019

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
2019-03-04 09:56:26	ga_ls8c_ard_3-0-0_097067_2019-03-04_final
2019-03-04 09:56:50	ga_ls8c_ard_3-0-0_097068_2019-03-04_final
2019-03-04 09:57:14	ga_ls8c_ard_3-0-0_097069_2019-03-04_final
2019-03-04 09:57:38	ga_ls8c_ard_3-0-0_097070_2019-03-04_final
2019-03-04 09:58:02	ga_ls8c_ard_3-0-0_097071_2019-03-04_final
2019-03-04 09:58:26	ga_ls8c_ard_3-0-0_097072_2019-03-04_final
2019-03-04 09:58:50	ga_ls8c_ard_3-0-0_097073_2019-03-04_final
2019-03-04 09:59:14	ga_ls8c_ard_3-0-0_097074_2019-03-04_final
2019-03-04 09:59:38	ga_ls8c_ard_3-0-0_097075_2019-03-04_final
2019-03-04 10:00:02	ga_ls8c_ard_3-0-0_097076_2019-03-04_final
2019-03-04 10:00:25	ga_ls8c_ard_3-0-0_097077_2019-03-04_final
2019-03-04 10:00:49	ga_ls8c_ard_3-0-0_097078_2019-03-04_final
2019-03-04 10:01:13	ga_ls8c_ard_3-0-0_097079_2019-03-04_final
2019-03-04 10:01:37	ga_ls8c_ard_3-0-0_097080_2019-03-04_final
2019-03-04 10:02:01	ga_ls8c_ard_3-0-0_097081_2019-03-04_final
2019-03-04 10:02:25	ga_ls8c_ard_3-0-0_097082_2019-03-04_final
2019-03-04 10:02:49	ga_ls8c_ard_3-0-0_097083_2019-03-04_final
2019-03-04 10:03:13	ga_ls8c_ard_3-0-0_097084_2019-03-04_final
2019-03-04 10:03:37	ga_ls8c_ard_3-0-0_097085_2019-03-04_final
2019-03-04 10:04:01	ga_ls8c_ard_3-0-0_097086_2019-03-04_final
2019-03-04 11:35:19	ga_ls8c_ard_3-0-0_113067_2019-03-04_final
2019-03-04 11:36:55	ga_ls8c_ard_3-0-0_113071_2019-03-04_final
2019-03-04 11:37:19	ga_ls8c_ard_3-0-0_113072_2019-03-04_final
2019-03-04 11:37:43	ga_ls8c_ard_3-1-0_113073_2019-03-04_final
2019-03-04 11:38:07	ga_ls8c_ard_3-0-0_113074_2019-03-04_final
2019-03-04 11:38:31	ga_ls8c_ard_3-0-0_113075_2019-03-04_final
2019-03-04 11:38:55	ga_ls8c_ard_3-0-0_113076_2019-03-04_final
2019-03-04 11:39:19	ga_ls8c_ard_3-0-0_113077_2019-03-04_final
2019-03-04 11:39:42	ga_ls8c_ard_3-0-0_113078_2019-03-04_final
2019-03-04 11:40:06	ga_ls8c_ard_3-0-0_113079_2019-03-04_final
2019-03-04 11:40:30	ga_ls8c_ard_3-0-0_113080_2019-03-04_final
2019-03-04 11:40:54	ga_ls8c_ard_3-0-0_113081_2019-03-04_final
2019-03-04 11:41:18	ga_ls8c_ard_3-0-0_113082_2019-03-04_final
2019-03-04 11:41:42	ga_ls8c_ard_3-0-0_113083_2019-03-04_final
2019-03-04 11:42:06	ga_ls8c_ard_3-0-0_113084_2019-03-04_final
2019-03-05 09:05:36	ga_ls8c_ard_3-0-0_088079_2019-03-04_final
2019-03-05 09:06:00	ga_ls8c_ard_3-0-0_088080_2019-03-04_final
2019-03-05 09:06:24	ga_ls8c_ard_3-1-0_088081_2019-03-04_final
2019-03-05 09:06:48	ga_ls8c_ard_3-0-0_088082_2019-03-04_final
2019-03-05 09:07:12	ga_ls8c_ard_3-0-0_088083_2019-03-04_final
2019-03-05 09:07:35	ga_ls8c_ard_3-0-0_088084_2019-03-04_final
2019-03-05 10:39:41	ga_ls8c_ard_3-0-0_104067_2019-03-05_final
2019-03-05 10:40:05	ga_ls8c_ard_3-0-0_104068_2019-03-05_final
2019-03-05 10:40:29	ga_ls8c_ard_3-0-0_104069_2019-03-05_final
2019-03-05 10:40:53	ga_ls8c_ard_3-0-0_104070_2019-03-05_final
2019-03-05 10:41:17	ga_ls8c_ard_3-0-0_104071_2019-03-05_final
2019-03-05 10:41:41	ga_ls8c_ard_3-0-0_104072_2019-03-05_final
2019-03-05 10:42:05	ga_ls8c_ard_3-0-0_104073_2019-03-05_final
2019-03-05 10:42:29	ga_ls8c_ard_3-0-0_104074_2019-03-05_final
2019-03-05 10:42:53	ga_ls8c_ard_3-0-0_104075_2019-03-05_final
2019-03-05 10:43:17	ga_ls8c_ard_3-0-0_104076_2019-03-05_final
2019-03-05 10:43:41	ga_ls8c_ard_3-0-0_104077_2019-03-05_final
2019-03-05 10:44:05	ga_ls8c_ard_3-0-0_104078_2019-03-05_final
2019-03-05 10:44:29	ga_ls8c_ard_3-0-0_104079_2019-03-05_final
2019-03-05 10:44:53	ga_ls8c_ard_3-0-0_104080_2019-03-05_final
2019-03-05 10:45:17	ga_ls8c_ard_3-0-0_104081_2019-03-05_final
2019-03-05 10:45:41	ga_ls8c_ard_3-0-0_104082_2019-03-05_final
2019-03-05 10:46:04	ga_ls8c_ard_3-0-0_104083_2019-03-05_final
2019-03-06 09:44:04	ga_ls8c_ard_3-0-0_095067_2019-03-06_final
2019-03-06 09:45:16	ga_ls8c_ard_3-0-0_095070_2019-03-06_final
2019-03-06 09:45:40	ga_ls8c_ard_3-0-0_095071_2019-03-06_final
2019-03-06 09:46:03	ga_ls8c_ard_3-0-0_095072_2019-03-06_final
2019-03-06 09:46:27	ga_ls8c_ard_3-0-0_095073_2019-03-06_final
2019-03-06 09:46:51	ga_ls8c_ard_3-0-0_095074_2019-03-06_final
2019-03-06 09:47:15	ga_ls8c_ard_3-0-0_095075_2019-03-06_final
2019-03-06 09:47:39	ga_ls8c_ard_3-0-0_095076_2019-03-06_final
2019-03-06 09:48:03	ga_ls8c_ard_3-0-0_095077_2019-03-06_final
2019-03-06 09:48:27	ga_ls8c_ard_3-0-0_095078_2019-03-06_final
2019-03-06 09:48:51	ga_ls8c_ard_3-0-0_095079_2019-03-06_final
2019-03-06 09:49:15	ga_ls8c_ard_3-0-0_095080_2019-03-06_final
2019-03-06 09:49:39	ga_ls8c_ard_3-0-0_095081_2019-03-06_final
2019-03-06 09:50:03	ga_ls8c_ard_3-0-0_095082_2019-03-06_final
2019-03-06 09:50:27	ga_ls8c_ard_3-0-0_095083_2019-03-06_final
2019-03-06 09:50:51	ga_ls8c_ard_3-0-0_095084_2019-03-06_final
2019-03-06 09:51:15	ga_ls8c_ard_3-0-0_095085_2019-03-06_final
2019-03-06 09:51:39	ga_ls8c_ard_3-0-0_095086_2019-03-06_final
2019-03-06 09:52:03	ga_ls8c_ard_3-0-0_095087_2019-03-06_final
2019-03-06 09:52:27	ga_ls8c_ard_3-0-0_095088_2019-03-06_final
2019-03-06 11:22:57	ga_ls8c_ard_3-0-0_111067_2019-03-06_final
2019-03-06 11:23:21	ga_ls8c_ard_3-0-0_111068_2019-03-06_final
2019-03-06 11:23:45	ga_ls8c_ard_3-0-0_111069_2019-03-06_final
2019-03-06 11:24:09	ga_ls8c_ard_3-0-0_111070_2019-03-06_final
2019-03-06 11:24:33	ga_ls8c_ard_3-0-0_111071_2019-03-06_final
2019-03-06 11:24:56	ga_ls8c_ard_3-0-0_111072_2019-03-06_final
2019-03-06 11:25:20	ga_ls8c_ard_3-0-0_111073_2019-03-06_final
2019-03-06 11:25:44	ga_ls8c_ard_3-0-0_111074_2019-03-06_final
2019-03-06 11:26:08	ga_ls8c_ard_3-0-0_111075_2019-03-06_final
2019-03-06 11:26:32	ga_ls8c_ard_3-0-0_111076_2019-03-06_final
2019-03-06 11:26:56	ga_ls8c_ard_3-0-0_111077_2019-03-06_final
2019-03-06 11:27:20	ga_ls8c_ard_3-0-0_111078_2019-03-06_final
2019-03-06 11:27:44	ga_ls8c_ard_3-0-0_111079_2019-03-06_final
2019-03-06 11:28:08	ga_ls8c_ard_3-0-0_111080_2019-03-06_final
2019-03-06 11:28:32	ga_ls8c_ard_3-0-0_111081_2019-03-06_final
2019-03-06 11:28:56	ga_ls8c_ard_3-0-0_111082_2019-03-06_final
2019-03-06 11:29:20	ga_ls8c_ard_3-0-0_111083_2019-03-06_final
2019-03-06 11:29:44	ga_ls8c_ard_3-0-0_111084_2019-03-06_final
2019-03-06 11:30:08	ga_ls8c_ard_3-0-0_111085_2019-03-06_final
2019-03-08 09:31:41	ga_ls8c_ard_3-1-0_093067_2019-03-08_final
2019-03-08 09:32:05	ga_ls8c_ard_3-1-0_093068_2019-03-08_final
2019-03-08 09:33:17	ga_ls8c_ard_3-1-0_093071_2019-03-08_final

Return to ga_ls8c_ard_3 across March 2019 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

2019

March

All days