Search ga_ls8c_ard_3 across July 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
2019-07-02 10:46:07	ga_ls8c_ard_3-1-0_105067_2019-07-02_final
2019-07-02 10:46:31	ga_ls8c_ard_3-1-0_105068_2019-07-02_final
2019-07-02 10:46:55	ga_ls8c_ard_3-1-0_105069_2019-07-02_final
2019-07-02 10:47:19	ga_ls8c_ard_3-1-0_105070_2019-07-02_final
2019-07-02 10:47:43	ga_ls8c_ard_3-1-0_105071_2019-07-02_final
2019-07-02 10:48:07	ga_ls8c_ard_3-1-0_105072_2019-07-02_final
2019-07-02 10:48:31	ga_ls8c_ard_3-1-0_105073_2019-07-02_final
2019-07-02 10:48:55	ga_ls8c_ard_3-1-0_105074_2019-07-02_final
2019-07-02 10:49:19	ga_ls8c_ard_3-1-0_105075_2019-07-02_final
2019-07-02 10:49:42	ga_ls8c_ard_3-1-0_105076_2019-07-02_final
2019-07-02 10:50:06	ga_ls8c_ard_3-1-0_105077_2019-07-02_final
2019-07-02 10:50:30	ga_ls8c_ard_3-1-0_105078_2019-07-02_final
2019-07-02 10:50:54	ga_ls8c_ard_3-1-0_105079_2019-07-02_final
2019-07-02 10:51:18	ga_ls8c_ard_3-1-0_105080_2019-07-02_final
2019-07-02 10:51:42	ga_ls8c_ard_3-1-0_105081_2019-07-02_final
2019-07-02 10:52:06	ga_ls8c_ard_3-1-0_105082_2019-07-02_final
2019-07-02 10:52:30	ga_ls8c_ard_3-1-0_105083_2019-07-02_final
2019-07-03 09:50:30	ga_ls8c_ard_3-1-0_096067_2019-07-03_final
2019-07-03 09:50:54	ga_ls8c_ard_3-1-0_096068_2019-07-03_final
2019-07-03 09:51:18	ga_ls8c_ard_3-1-0_096069_2019-07-03_final
2019-07-03 09:51:42	ga_ls8c_ard_3-1-0_096070_2019-07-03_final
2019-07-03 09:52:06	ga_ls8c_ard_3-1-0_096071_2019-07-03_final
2019-07-03 09:52:30	ga_ls8c_ard_3-1-0_096072_2019-07-03_final
2019-07-03 09:52:54	ga_ls8c_ard_3-1-0_096073_2019-07-03_final
2019-07-03 09:53:17	ga_ls8c_ard_3-1-0_096074_2019-07-03_final
2019-07-03 09:53:41	ga_ls8c_ard_3-1-0_096075_2019-07-03_final
2019-07-03 09:54:05	ga_ls8c_ard_3-1-0_096076_2019-07-03_final
2019-07-03 09:54:29	ga_ls8c_ard_3-1-0_096077_2019-07-03_final
2019-07-03 09:54:53	ga_ls8c_ard_3-1-0_096078_2019-07-03_final
2019-07-03 09:55:17	ga_ls8c_ard_3-1-0_096079_2019-07-03_final
2019-07-03 09:55:41	ga_ls8c_ard_3-1-0_096080_2019-07-03_final
2019-07-03 09:56:05	ga_ls8c_ard_3-1-0_096081_2019-07-03_final
2019-07-03 09:56:29	ga_ls8c_ard_3-1-0_096082_2019-07-03_final
2019-07-03 09:56:53	ga_ls8c_ard_3-1-0_096083_2019-07-03_final
2019-07-03 09:57:17	ga_ls8c_ard_3-1-0_096084_2019-07-03_final
2019-07-03 09:57:41	ga_ls8c_ard_3-1-0_096085_2019-07-03_final
2019-07-03 09:58:05	ga_ls8c_ard_3-1-0_096086_2019-07-03_final
2019-07-03 09:58:29	ga_ls8c_ard_3-1-0_096087_2019-07-03_final
2019-07-03 11:29:23	ga_ls8c_ard_3-1-0_112067_2019-07-03_final
2019-07-03 11:29:47	ga_ls8c_ard_3-1-0_112068_2019-07-03_final
2019-07-03 11:30:11	ga_ls8c_ard_3-1-0_112069_2019-07-03_final
2019-07-03 11:30:35	ga_ls8c_ard_3-1-0_112070_2019-07-03_final
2019-07-03 11:30:59	ga_ls8c_ard_3-1-0_112071_2019-07-03_final
2019-07-03 11:31:23	ga_ls8c_ard_3-1-0_112072_2019-07-03_final
2019-07-03 11:31:47	ga_ls8c_ard_3-1-0_112073_2019-07-03_final
2019-07-03 11:32:11	ga_ls8c_ard_3-1-0_112074_2019-07-03_final
2019-07-03 11:32:35	ga_ls8c_ard_3-1-0_112075_2019-07-03_final
2019-07-03 11:32:58	ga_ls8c_ard_3-1-0_112076_2019-07-03_final
2019-07-03 11:33:22	ga_ls8c_ard_3-1-0_112077_2019-07-03_final
2019-07-03 11:33:46	ga_ls8c_ard_3-1-0_112078_2019-07-03_final
2019-07-03 11:34:10	ga_ls8c_ard_3-1-0_112079_2019-07-03_final
2019-07-03 11:34:34	ga_ls8c_ard_3-1-0_112080_2019-07-03_final
2019-07-03 11:34:58	ga_ls8c_ard_3-1-0_112081_2019-07-03_final
2019-07-03 11:35:22	ga_ls8c_ard_3-1-0_112082_2019-07-03_final
2019-07-03 11:35:46	ga_ls8c_ard_3-1-0_112083_2019-07-03_final
2019-07-03 11:36:10	ga_ls8c_ard_3-1-0_112084_2019-07-03_final
2019-07-03 11:36:34	ga_ls8c_ard_3-1-0_112085_2019-07-03_final
2019-07-11 09:05:52	ga_ls8c_ard_3-1-0_088079_2019-07-10_final
2019-07-11 09:06:16	ga_ls8c_ard_3-1-0_088080_2019-07-10_final
2019-07-11 09:06:40	ga_ls8c_ard_3-1-0_088081_2019-07-10_final
2019-07-11 09:07:04	ga_ls8c_ard_3-1-0_088082_2019-07-10_final
2019-07-11 09:07:28	ga_ls8c_ard_3-1-0_088083_2019-07-10_final
2019-07-11 09:07:52	ga_ls8c_ard_3-1-0_088084_2019-07-10_final
2019-07-11 10:39:58	ga_ls8c_ard_3-1-0_104067_2019-07-11_final
2019-07-11 10:40:22	ga_ls8c_ard_3-1-0_104068_2019-07-11_final
2019-07-11 10:40:46	ga_ls8c_ard_3-1-0_104069_2019-07-11_final
2019-07-11 10:41:10	ga_ls8c_ard_3-1-0_104070_2019-07-11_final
2019-07-11 10:41:34	ga_ls8c_ard_3-1-0_104071_2019-07-11_final
2019-07-11 10:41:58	ga_ls8c_ard_3-1-0_104072_2019-07-11_final
2019-07-11 10:42:22	ga_ls8c_ard_3-1-0_104073_2019-07-11_final
2019-07-11 10:42:45	ga_ls8c_ard_3-1-0_104074_2019-07-11_final
2019-07-11 10:43:09	ga_ls8c_ard_3-1-0_104075_2019-07-11_final
2019-07-11 10:43:33	ga_ls8c_ard_3-1-0_104076_2019-07-11_final
2019-07-11 10:43:57	ga_ls8c_ard_3-1-0_104077_2019-07-11_final
2019-07-11 10:44:21	ga_ls8c_ard_3-1-0_104078_2019-07-11_final
2019-07-11 10:44:45	ga_ls8c_ard_3-1-0_104079_2019-07-11_final
2019-07-11 10:45:09	ga_ls8c_ard_3-1-0_104080_2019-07-11_final
2019-07-11 10:45:33	ga_ls8c_ard_3-1-0_104081_2019-07-11_final
2019-07-11 10:45:57	ga_ls8c_ard_3-1-0_104082_2019-07-11_final
2019-07-11 10:46:21	ga_ls8c_ard_3-1-0_104083_2019-07-11_final
2019-07-12 09:44:21	ga_ls8c_ard_3-1-0_095067_2019-07-12_final
2019-07-12 09:45:33	ga_ls8c_ard_3-1-0_095070_2019-07-12_final
2019-07-12 09:45:56	ga_ls8c_ard_3-1-0_095071_2019-07-12_final
2019-07-12 09:46:20	ga_ls8c_ard_3-1-0_095072_2019-07-12_final
2019-07-12 09:46:44	ga_ls8c_ard_3-1-0_095073_2019-07-12_final
2019-07-12 09:47:08	ga_ls8c_ard_3-1-0_095074_2019-07-12_final
2019-07-12 09:47:32	ga_ls8c_ard_3-1-0_095075_2019-07-12_final
2019-07-12 09:47:56	ga_ls8c_ard_3-1-0_095076_2019-07-12_final
2019-07-12 09:48:20	ga_ls8c_ard_3-1-0_095077_2019-07-12_final
2019-07-12 09:48:44	ga_ls8c_ard_3-1-0_095078_2019-07-12_final
2019-07-12 09:49:08	ga_ls8c_ard_3-1-0_095079_2019-07-12_final
2019-07-12 09:49:32	ga_ls8c_ard_3-1-0_095080_2019-07-12_final
2019-07-12 09:49:56	ga_ls8c_ard_3-1-0_095081_2019-07-12_final
2019-07-12 09:50:20	ga_ls8c_ard_3-1-0_095082_2019-07-12_final
2019-07-12 09:50:44	ga_ls8c_ard_3-1-0_095083_2019-07-12_final
2019-07-12 09:51:08	ga_ls8c_ard_3-1-0_095084_2019-07-12_final
2019-07-12 09:51:32	ga_ls8c_ard_3-1-0_095085_2019-07-12_final
2019-07-12 09:51:56	ga_ls8c_ard_3-1-0_095086_2019-07-12_final
2019-07-12 09:52:20	ga_ls8c_ard_3-1-0_095087_2019-07-12_final
2019-07-12 09:52:44	ga_ls8c_ard_3-1-0_095088_2019-07-12_final

Return to ga_ls8c_ard_3 across July 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

July

All days