Search ga_ls8c_ard_3 across September 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
2016-09-02 09:16:29	ga_ls8c_ard_3-0-0_090074_2016-09-01_final
2016-09-02 09:16:53	ga_ls8c_ard_3-0-0_090075_2016-09-01_final
2016-09-02 09:17:17	ga_ls8c_ard_3-0-0_090076_2016-09-01_final
2016-09-02 09:17:41	ga_ls8c_ard_3-0-0_090077_2016-09-01_final
2016-09-02 09:18:05	ga_ls8c_ard_3-1-0_090078_2016-09-01_final
2016-09-19 09:57:00	ga_ls8c_ard_3-0-0_097067_2016-09-19_final
2016-09-19 09:57:24	ga_ls8c_ard_3-0-0_097068_2016-09-19_final
2016-09-19 09:57:48	ga_ls8c_ard_3-0-0_097069_2016-09-19_final
2016-09-19 09:58:12	ga_ls8c_ard_3-1-0_097070_2016-09-19_final
2016-09-19 09:58:36	ga_ls8c_ard_3-0-0_097071_2016-09-19_final
2016-09-19 09:59:00	ga_ls8c_ard_3-0-0_097072_2016-09-19_final
2016-09-19 09:59:24	ga_ls8c_ard_3-0-0_097073_2016-09-19_final
2016-09-19 09:59:48	ga_ls8c_ard_3-0-0_097074_2016-09-19_final
2016-09-19 10:00:12	ga_ls8c_ard_3-0-0_097075_2016-09-19_final
2016-09-19 10:00:36	ga_ls8c_ard_3-0-0_097076_2016-09-19_final
2016-09-19 10:01:00	ga_ls8c_ard_3-0-0_097077_2016-09-19_final
2016-09-19 10:01:24	ga_ls8c_ard_3-0-0_097078_2016-09-19_final
2016-09-19 10:01:48	ga_ls8c_ard_3-0-0_097079_2016-09-19_final
2016-09-19 10:02:11	ga_ls8c_ard_3-0-0_097080_2016-09-19_final
2016-09-19 10:02:35	ga_ls8c_ard_3-0-0_097081_2016-09-19_final
2016-09-19 10:02:59	ga_ls8c_ard_3-0-0_097082_2016-09-19_final
2016-09-19 10:03:23	ga_ls8c_ard_3-0-0_097083_2016-09-19_final
2016-09-19 10:03:47	ga_ls8c_ard_3-0-0_097084_2016-09-19_final
2016-09-19 10:04:11	ga_ls8c_ard_3-0-0_097085_2016-09-19_final
2016-09-19 10:04:35	ga_ls8c_ard_3-0-0_097086_2016-09-19_final
2016-09-19 11:35:53	ga_ls8c_ard_3-0-0_113067_2016-09-19_final
2016-09-19 11:37:53	ga_ls8c_ard_3-0-0_113072_2016-09-19_final
2016-09-19 11:38:17	ga_ls8c_ard_3-0-0_113073_2016-09-19_final
2016-09-19 11:38:41	ga_ls8c_ard_3-0-0_113074_2016-09-19_final
2016-09-19 11:39:05	ga_ls8c_ard_3-0-0_113075_2016-09-19_final
2016-09-19 11:39:29	ga_ls8c_ard_3-0-0_113076_2016-09-19_final
2016-09-19 11:39:53	ga_ls8c_ard_3-0-0_113077_2016-09-19_final
2016-09-19 11:40:17	ga_ls8c_ard_3-0-0_113078_2016-09-19_final
2016-09-19 11:40:41	ga_ls8c_ard_3-0-0_113079_2016-09-19_final
2016-09-19 11:41:05	ga_ls8c_ard_3-0-0_113080_2016-09-19_final
2016-09-19 11:41:28	ga_ls8c_ard_3-0-0_113081_2016-09-19_final
2016-09-19 11:41:52	ga_ls8c_ard_3-0-0_113082_2016-09-19_final
2016-09-19 11:42:16	ga_ls8c_ard_3-0-0_113083_2016-09-19_final
2016-09-19 11:42:40	ga_ls8c_ard_3-0-0_113084_2016-09-19_final
2016-09-20 09:06:10	ga_ls8c_ard_3-0-0_088079_2016-09-19_final
2016-09-20 09:06:34	ga_ls8c_ard_3-0-0_088080_2016-09-19_final
2016-09-20 09:06:58	ga_ls8c_ard_3-1-0_088081_2016-09-19_final
2016-09-20 09:07:22	ga_ls8c_ard_3-0-0_088082_2016-09-19_final
2016-09-20 09:07:46	ga_ls8c_ard_3-0-0_088083_2016-09-19_final
2016-09-20 09:08:10	ga_ls8c_ard_3-0-0_088084_2016-09-19_final
2016-09-20 10:40:16	ga_ls8c_ard_3-0-0_104067_2016-09-20_final
2016-09-20 10:40:40	ga_ls8c_ard_3-0-0_104068_2016-09-20_final
2016-09-20 10:41:04	ga_ls8c_ard_3-0-0_104069_2016-09-20_final
2016-09-20 10:41:28	ga_ls8c_ard_3-0-0_104070_2016-09-20_final
2016-09-20 10:41:52	ga_ls8c_ard_3-0-0_104071_2016-09-20_final
2016-09-20 10:42:16	ga_ls8c_ard_3-0-0_104072_2016-09-20_final
2016-09-20 10:42:40	ga_ls8c_ard_3-0-0_104073_2016-09-20_final
2016-09-20 10:43:04	ga_ls8c_ard_3-0-0_104074_2016-09-20_final
2016-09-20 10:43:27	ga_ls8c_ard_3-0-0_104075_2016-09-20_final
2016-09-20 10:43:51	ga_ls8c_ard_3-0-0_104076_2016-09-20_final
2016-09-20 10:44:15	ga_ls8c_ard_3-1-0_104077_2016-09-20_final
2016-09-20 10:44:39	ga_ls8c_ard_3-0-0_104078_2016-09-20_final
2016-09-20 10:45:03	ga_ls8c_ard_3-0-0_104079_2016-09-20_final
2016-09-20 10:45:27	ga_ls8c_ard_3-0-0_104080_2016-09-20_final
2016-09-20 10:45:51	ga_ls8c_ard_3-0-0_104081_2016-09-20_final
2016-09-20 10:46:15	ga_ls8c_ard_3-0-0_104082_2016-09-20_final
2016-09-20 10:46:39	ga_ls8c_ard_3-0-0_104083_2016-09-20_final
2016-09-21 09:44:39	ga_ls8c_ard_3-0-0_095067_2016-09-21_final
2016-09-21 09:45:50	ga_ls8c_ard_3-0-0_095070_2016-09-21_final
2016-09-21 09:46:14	ga_ls8c_ard_3-0-0_095071_2016-09-21_final
2016-09-21 09:46:38	ga_ls8c_ard_3-0-0_095072_2016-09-21_final
2016-09-21 09:47:02	ga_ls8c_ard_3-0-0_095073_2016-09-21_final
2016-09-21 09:47:26	ga_ls8c_ard_3-0-0_095074_2016-09-21_final
2016-09-21 09:47:50	ga_ls8c_ard_3-0-0_095075_2016-09-21_final
2016-09-21 09:48:14	ga_ls8c_ard_3-0-0_095076_2016-09-21_final
2016-09-21 09:48:38	ga_ls8c_ard_3-0-0_095077_2016-09-21_final
2016-09-21 09:49:02	ga_ls8c_ard_3-0-0_095078_2016-09-21_final
2016-09-21 09:49:26	ga_ls8c_ard_3-0-0_095079_2016-09-21_final
2016-09-21 09:49:50	ga_ls8c_ard_3-0-0_095080_2016-09-21_final
2016-09-21 09:50:14	ga_ls8c_ard_3-0-0_095081_2016-09-21_final
2016-09-21 09:50:38	ga_ls8c_ard_3-0-0_095082_2016-09-21_final
2016-09-21 09:51:02	ga_ls8c_ard_3-0-0_095083_2016-09-21_final
2016-09-21 09:51:26	ga_ls8c_ard_3-0-0_095084_2016-09-21_final
2016-09-21 09:51:50	ga_ls8c_ard_3-0-0_095085_2016-09-21_final
2016-09-21 09:52:14	ga_ls8c_ard_3-0-0_095086_2016-09-21_final
2016-09-21 09:52:38	ga_ls8c_ard_3-0-0_095087_2016-09-21_final
2016-09-21 09:53:01	ga_ls8c_ard_3-0-0_095088_2016-09-21_final
2016-09-21 11:23:32	ga_ls8c_ard_3-0-0_111067_2016-09-21_final
2016-09-21 11:23:56	ga_ls8c_ard_3-0-0_111068_2016-09-21_final
2016-09-21 11:24:20	ga_ls8c_ard_3-0-0_111069_2016-09-21_final
2016-09-21 11:24:44	ga_ls8c_ard_3-0-0_111070_2016-09-21_final
2016-09-21 11:25:07	ga_ls8c_ard_3-0-0_111071_2016-09-21_final
2016-09-21 11:25:31	ga_ls8c_ard_3-0-0_111072_2016-09-21_final
2016-09-21 11:25:55	ga_ls8c_ard_3-0-0_111073_2016-09-21_final
2016-09-21 11:26:19	ga_ls8c_ard_3-0-0_111074_2016-09-21_final
2016-09-21 11:26:43	ga_ls8c_ard_3-0-0_111075_2016-09-21_final
2016-09-21 11:27:07	ga_ls8c_ard_3-0-0_111076_2016-09-21_final
2016-09-21 11:27:31	ga_ls8c_ard_3-0-0_111077_2016-09-21_final
2016-09-21 11:27:55	ga_ls8c_ard_3-0-0_111078_2016-09-21_final
2016-09-21 11:28:19	ga_ls8c_ard_3-0-0_111079_2016-09-21_final
2016-09-21 11:28:43	ga_ls8c_ard_3-0-0_111080_2016-09-21_final
2016-09-21 11:29:07	ga_ls8c_ard_3-0-0_111081_2016-09-21_final
2016-09-21 11:29:31	ga_ls8c_ard_3-0-0_111082_2016-09-21_final
2016-09-21 11:29:55	ga_ls8c_ard_3-0-0_111083_2016-09-21_final
2016-09-21 11:30:19	ga_ls8c_ard_3-0-0_111084_2016-09-21_final

Return to ga_ls8c_ard_3 across September 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

September

All days