Search ga_ls8c_ard_3 across October 2020

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
2020-10-01 09:06:15	ga_ls8c_ard_3-1-0_088079_2020-09-30_final
2020-10-01 09:06:39	ga_ls8c_ard_3-1-0_088080_2020-09-30_final
2020-10-01 09:07:03	ga_ls8c_ard_3-1-0_088081_2020-09-30_final
2020-10-01 09:07:27	ga_ls8c_ard_3-1-0_088082_2020-09-30_final
2020-10-01 09:07:51	ga_ls8c_ard_3-1-0_088083_2020-09-30_final
2020-10-01 09:08:15	ga_ls8c_ard_3-1-0_088084_2020-09-30_final
2020-10-01 10:40:21	ga_ls8c_ard_3-1-0_104067_2020-10-01_final
2020-10-01 10:40:45	ga_ls8c_ard_3-1-0_104068_2020-10-01_final
2020-10-01 10:41:08	ga_ls8c_ard_3-1-0_104069_2020-10-01_final
2020-10-01 10:41:32	ga_ls8c_ard_3-1-0_104070_2020-10-01_final
2020-10-01 10:41:56	ga_ls8c_ard_3-1-0_104071_2020-10-01_final
2020-10-01 10:42:20	ga_ls8c_ard_3-1-0_104072_2020-10-01_final
2020-10-01 10:42:44	ga_ls8c_ard_3-1-0_104073_2020-10-01_final
2020-10-01 10:43:08	ga_ls8c_ard_3-1-0_104074_2020-10-01_final
2020-10-01 10:43:32	ga_ls8c_ard_3-1-0_104075_2020-10-01_final
2020-10-01 10:43:56	ga_ls8c_ard_3-1-0_104076_2020-10-01_final
2020-10-01 10:44:20	ga_ls8c_ard_3-1-0_104077_2020-10-01_final
2020-10-01 10:44:44	ga_ls8c_ard_3-1-0_104078_2020-10-01_final
2020-10-01 10:45:08	ga_ls8c_ard_3-1-0_104079_2020-10-01_final
2020-10-01 10:45:32	ga_ls8c_ard_3-1-0_104080_2020-10-01_final
2020-10-01 10:45:56	ga_ls8c_ard_3-1-0_104081_2020-10-01_final
2020-10-01 10:46:20	ga_ls8c_ard_3-1-0_104082_2020-10-01_final
2020-10-01 10:46:44	ga_ls8c_ard_3-1-0_104083_2020-10-01_final
2020-10-02 08:11:02	ga_ls8c_ard_3-2-1_079080_2020-10-01_final
2020-10-02 08:18:13	ga_ls8c_ard_3-2-1_079098_2020-10-01_final
2020-10-02 09:44:43	ga_ls8c_ard_3-1-0_095067_2020-10-02_final
2020-10-02 09:45:55	ga_ls8c_ard_3-1-0_095070_2020-10-02_final
2020-10-02 09:46:19	ga_ls8c_ard_3-1-0_095071_2020-10-02_final
2020-10-02 09:46:43	ga_ls8c_ard_3-1-0_095072_2020-10-02_final
2020-10-02 09:47:07	ga_ls8c_ard_3-1-0_095073_2020-10-02_final
2020-10-02 09:47:31	ga_ls8c_ard_3-1-0_095074_2020-10-02_final
2020-10-02 09:47:55	ga_ls8c_ard_3-1-0_095075_2020-10-02_final
2020-10-02 09:48:19	ga_ls8c_ard_3-1-0_095076_2020-10-02_final
2020-10-02 09:48:43	ga_ls8c_ard_3-1-0_095077_2020-10-02_final
2020-10-02 09:49:07	ga_ls8c_ard_3-1-0_095078_2020-10-02_final
2020-10-02 09:49:31	ga_ls8c_ard_3-1-0_095079_2020-10-02_final
2020-10-02 09:49:55	ga_ls8c_ard_3-1-0_095080_2020-10-02_final
2020-10-02 09:50:19	ga_ls8c_ard_3-1-0_095081_2020-10-02_final
2020-10-02 09:50:43	ga_ls8c_ard_3-1-0_095082_2020-10-02_final
2020-10-02 09:51:06	ga_ls8c_ard_3-1-0_095083_2020-10-02_final
2020-10-02 09:51:30	ga_ls8c_ard_3-1-0_095084_2020-10-02_final
2020-10-02 09:51:54	ga_ls8c_ard_3-1-0_095085_2020-10-02_final
2020-10-02 09:52:18	ga_ls8c_ard_3-1-0_095086_2020-10-02_final
2020-10-02 09:52:42	ga_ls8c_ard_3-1-0_095087_2020-10-02_final
2020-10-02 09:53:06	ga_ls8c_ard_3-1-0_095088_2020-10-02_final
2020-10-02 11:23:37	ga_ls8c_ard_3-1-0_111067_2020-10-02_final
2020-10-02 11:24:00	ga_ls8c_ard_3-1-0_111068_2020-10-02_final
2020-10-02 11:24:24	ga_ls8c_ard_3-1-0_111069_2020-10-02_final
2020-10-02 11:24:48	ga_ls8c_ard_3-1-0_111070_2020-10-02_final
2020-10-02 11:25:12	ga_ls8c_ard_3-1-0_111071_2020-10-02_final
2020-10-02 11:25:36	ga_ls8c_ard_3-1-0_111072_2020-10-02_final
2020-10-02 11:26:00	ga_ls8c_ard_3-1-0_111073_2020-10-02_final
2020-10-02 11:26:24	ga_ls8c_ard_3-1-0_111074_2020-10-02_final
2020-10-02 11:26:48	ga_ls8c_ard_3-1-0_111075_2020-10-02_final
2020-10-02 11:27:12	ga_ls8c_ard_3-1-0_111076_2020-10-02_final
2020-10-02 11:27:36	ga_ls8c_ard_3-1-0_111077_2020-10-02_final
2020-10-02 11:28:00	ga_ls8c_ard_3-1-0_111078_2020-10-02_final
2020-10-02 11:28:24	ga_ls8c_ard_3-1-0_111079_2020-10-02_final
2020-10-02 11:28:48	ga_ls8c_ard_3-1-0_111080_2020-10-02_final
2020-10-02 11:29:12	ga_ls8c_ard_3-1-0_111081_2020-10-02_final
2020-10-02 11:29:36	ga_ls8c_ard_3-1-0_111082_2020-10-02_final
2020-10-02 11:30:00	ga_ls8c_ard_3-1-0_111083_2020-10-02_final
2020-10-02 11:30:23	ga_ls8c_ard_3-1-0_111084_2020-10-02_final
2020-10-02 11:30:47	ga_ls8c_ard_3-1-0_111085_2020-10-02_final
2020-10-03 10:27:59	ga_ls8c_ard_3-1-0_102067_2020-10-03_final
2020-10-03 10:28:23	ga_ls8c_ard_3-1-0_102068_2020-10-03_final
2020-10-03 10:28:47	ga_ls8c_ard_3-1-0_102069_2020-10-03_final
2020-10-03 10:29:11	ga_ls8c_ard_3-1-0_102070_2020-10-03_final
2020-10-03 10:29:35	ga_ls8c_ard_3-1-0_102071_2020-10-03_final
2020-10-03 10:29:59	ga_ls8c_ard_3-1-0_102072_2020-10-03_final
2020-10-03 10:30:23	ga_ls8c_ard_3-1-0_102073_2020-10-03_final
2020-10-03 10:30:47	ga_ls8c_ard_3-1-0_102074_2020-10-03_final
2020-10-03 10:31:11	ga_ls8c_ard_3-1-0_102075_2020-10-03_final
2020-10-03 10:31:35	ga_ls8c_ard_3-1-0_102076_2020-10-03_final
2020-10-03 10:31:59	ga_ls8c_ard_3-1-0_102077_2020-10-03_final
2020-10-03 10:32:23	ga_ls8c_ard_3-1-0_102078_2020-10-03_final
2020-10-03 10:32:47	ga_ls8c_ard_3-1-0_102079_2020-10-03_final
2020-10-03 10:33:10	ga_ls8c_ard_3-1-0_102080_2020-10-03_final
2020-10-03 10:33:34	ga_ls8c_ard_3-1-0_102081_2020-10-03_final
2020-10-03 10:33:58	ga_ls8c_ard_3-1-0_102082_2020-10-03_final
2020-10-03 10:34:22	ga_ls8c_ard_3-1-0_102083_2020-10-03_final
2020-10-04 09:32:22	ga_ls8c_ard_3-1-0_093067_2020-10-04_final
2020-10-04 09:32:46	ga_ls8c_ard_3-1-0_093068_2020-10-04_final
2020-10-17 09:06:16	ga_ls8c_ard_3-1-0_088079_2020-10-16_final
2020-10-17 09:06:40	ga_ls8c_ard_3-1-0_088080_2020-10-16_final
2020-10-17 09:07:04	ga_ls8c_ard_3-1-0_088081_2020-10-16_final
2020-10-17 09:07:28	ga_ls8c_ard_3-1-0_088082_2020-10-16_final
2020-10-17 09:07:52	ga_ls8c_ard_3-1-0_088083_2020-10-16_final
2020-10-17 09:08:16	ga_ls8c_ard_3-1-0_088084_2020-10-16_final
2020-10-18 09:44:45	ga_ls8c_ard_3-1-0_095067_2020-10-18_final
2020-10-18 09:45:57	ga_ls8c_ard_3-1-0_095070_2020-10-18_final
2020-10-18 09:46:20	ga_ls8c_ard_3-1-0_095071_2020-10-18_final
2020-10-18 09:46:44	ga_ls8c_ard_3-1-0_095072_2020-10-18_final
2020-10-18 09:47:08	ga_ls8c_ard_3-1-0_095073_2020-10-18_final
2020-10-18 09:47:32	ga_ls8c_ard_3-1-0_095074_2020-10-18_final
2020-10-18 09:47:56	ga_ls8c_ard_3-1-0_095075_2020-10-18_final
2020-10-18 09:48:20	ga_ls8c_ard_3-1-0_095076_2020-10-18_final
2020-10-18 09:48:44	ga_ls8c_ard_3-1-0_095077_2020-10-18_final
2020-10-18 09:49:08	ga_ls8c_ard_3-1-0_095078_2020-10-18_final
2020-10-20 09:32:23	ga_ls8c_ard_3-1-0_093067_2020-10-20_final

Return to ga_ls8c_ard_3 across October 2020 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

2020

October

All days