Search ga_ls8c_ard_3 across September 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
2017-09-01 09:38:20	ga_ls8c_ard_3-0-0_094067_2017-09-01_final
2017-09-01 09:39:56	ga_ls8c_ard_3-0-0_094071_2017-09-01_final
2017-09-01 09:40:20	ga_ls8c_ard_3-0-0_094072_2017-09-01_final
2017-09-01 09:40:44	ga_ls8c_ard_3-0-0_094073_2017-09-01_final
2017-09-01 09:41:08	ga_ls8c_ard_3-0-0_094074_2017-09-01_final
2017-09-01 09:41:31	ga_ls8c_ard_3-0-0_094075_2017-09-01_final
2017-09-01 09:41:55	ga_ls8c_ard_3-0-0_094076_2017-09-01_final
2017-09-01 09:42:19	ga_ls8c_ard_3-0-0_094077_2017-09-01_final
2017-09-01 09:42:43	ga_ls8c_ard_3-0-0_094078_2017-09-01_final
2017-09-01 09:43:07	ga_ls8c_ard_3-0-0_094079_2017-09-01_final
2017-09-01 09:43:31	ga_ls8c_ard_3-0-0_094080_2017-09-01_final
2017-09-01 09:43:55	ga_ls8c_ard_3-0-0_094081_2017-09-01_final
2017-09-01 09:44:19	ga_ls8c_ard_3-0-0_094082_2017-09-01_final
2017-09-01 09:44:43	ga_ls8c_ard_3-0-0_094083_2017-09-01_final
2017-09-01 09:45:07	ga_ls8c_ard_3-0-0_094084_2017-09-01_final
2017-09-01 09:45:31	ga_ls8c_ard_3-0-0_094085_2017-09-01_final
2017-09-01 09:45:55	ga_ls8c_ard_3-0-0_094086_2017-09-01_final
2017-09-01 09:46:19	ga_ls8c_ard_3-0-0_094087_2017-09-01_final
2017-09-01 09:46:43	ga_ls8c_ard_3-0-0_094088_2017-09-01_final
2017-09-01 11:17:13	ga_ls8c_ard_3-0-0_110067_2017-09-01_final
2017-09-01 11:17:37	ga_ls8c_ard_3-0-0_110068_2017-09-01_final
2017-09-01 11:18:01	ga_ls8c_ard_3-0-0_110069_2017-09-01_final
2017-09-01 11:18:25	ga_ls8c_ard_3-0-0_110070_2017-09-01_final
2017-09-01 11:18:49	ga_ls8c_ard_3-0-0_110071_2017-09-01_final
2017-09-01 11:19:13	ga_ls8c_ard_3-0-0_110072_2017-09-01_final
2017-09-01 11:19:37	ga_ls8c_ard_3-0-0_110073_2017-09-01_final
2017-09-01 11:20:01	ga_ls8c_ard_3-0-0_110074_2017-09-01_final
2017-09-01 11:20:24	ga_ls8c_ard_3-0-0_110075_2017-09-01_final
2017-09-01 11:20:48	ga_ls8c_ard_3-0-0_110076_2017-09-01_final
2017-09-01 11:21:12	ga_ls8c_ard_3-0-0_110077_2017-09-01_final
2017-09-01 11:21:36	ga_ls8c_ard_3-0-0_110078_2017-09-01_final
2017-09-01 11:22:00	ga_ls8c_ard_3-0-0_110079_2017-09-01_final
2017-09-01 11:22:24	ga_ls8c_ard_3-0-0_110080_2017-09-01_final
2017-09-01 11:22:48	ga_ls8c_ard_3-0-0_110081_2017-09-01_final
2017-09-01 11:23:12	ga_ls8c_ard_3-0-0_110082_2017-09-01_final
2017-09-01 11:23:36	ga_ls8c_ard_3-0-0_110083_2017-09-01_final
2017-09-01 11:24:00	ga_ls8c_ard_3-0-0_110084_2017-09-01_final
2017-09-01 11:24:24	ga_ls8c_ard_3-0-0_110085_2017-09-01_final
2017-09-02 10:21:36	ga_ls8c_ard_3-0-0_101067_2017-09-02_final
2017-09-02 10:22:00	ga_ls8c_ard_3-0-0_101068_2017-09-02_final
2017-09-02 10:22:24	ga_ls8c_ard_3-0-0_101069_2017-09-02_final
2017-09-02 10:22:48	ga_ls8c_ard_3-0-0_101070_2017-09-02_final
2017-09-02 10:23:11	ga_ls8c_ard_3-0-0_101071_2017-09-02_final
2017-09-02 10:23:35	ga_ls8c_ard_3-0-0_101072_2017-09-02_final
2017-09-02 10:23:59	ga_ls8c_ard_3-0-0_101073_2017-09-02_final
2017-09-02 10:24:23	ga_ls8c_ard_3-0-0_101074_2017-09-02_final
2017-09-02 10:24:47	ga_ls8c_ard_3-0-0_101075_2017-09-02_final
2017-09-02 10:25:11	ga_ls8c_ard_3-0-0_101076_2017-09-02_final
2017-09-02 10:25:35	ga_ls8c_ard_3-0-0_101077_2017-09-02_final
2017-09-02 10:25:59	ga_ls8c_ard_3-0-0_101078_2017-09-02_final
2017-09-02 10:26:23	ga_ls8c_ard_3-0-0_101079_2017-09-02_final
2017-09-02 10:26:47	ga_ls8c_ard_3-0-0_101080_2017-09-02_final
2017-09-02 10:27:11	ga_ls8c_ard_3-0-0_101081_2017-09-02_final
2017-09-02 10:27:35	ga_ls8c_ard_3-0-0_101082_2017-09-02_final
2017-09-02 10:27:59	ga_ls8c_ard_3-0-0_101083_2017-09-02_final
2017-09-02 10:28:23	ga_ls8c_ard_3-0-0_101084_2017-09-02_final
2017-09-03 09:25:59	ga_ls8c_ard_3-0-0_092067_2017-09-02_final
2017-09-03 09:26:22	ga_ls8c_ard_3-0-0_092068_2017-09-02_final
2017-09-03 09:27:34	ga_ls8c_ard_3-0-0_092071_2017-09-02_final
2017-09-03 09:27:58	ga_ls8c_ard_3-0-0_092072_2017-09-02_final
2017-09-03 09:28:22	ga_ls8c_ard_3-1-0_092073_2017-09-02_final
2017-09-03 09:28:46	ga_ls8c_ard_3-0-0_092074_2017-09-02_final
2017-09-03 09:29:10	ga_ls8c_ard_3-0-0_092075_2017-09-02_final
2017-09-03 09:29:34	ga_ls8c_ard_3-0-0_092076_2017-09-02_final
2017-09-03 09:29:58	ga_ls8c_ard_3-0-0_092077_2017-09-02_final
2017-09-03 09:30:22	ga_ls8c_ard_3-0-0_092078_2017-09-03_final
2017-09-03 09:30:46	ga_ls8c_ard_3-0-0_092079_2017-09-03_final
2017-09-03 09:31:10	ga_ls8c_ard_3-0-0_092080_2017-09-03_final
2017-09-03 09:31:34	ga_ls8c_ard_3-0-0_092081_2017-09-03_final
2017-09-03 09:31:58	ga_ls8c_ard_3-0-0_092082_2017-09-03_final
2017-09-03 09:32:22	ga_ls8c_ard_3-0-0_092083_2017-09-03_final
2017-09-03 09:32:46	ga_ls8c_ard_3-0-0_092084_2017-09-03_final
2017-09-03 09:33:10	ga_ls8c_ard_3-0-0_092085_2017-09-03_final
2017-09-03 09:33:33	ga_ls8c_ard_3-0-0_092086_2017-09-03_final
2017-09-03 09:33:57	ga_ls8c_ard_3-0-0_092087_2017-09-03_final
2017-09-03 09:34:21	ga_ls8c_ard_3-0-0_092088_2017-09-03_final
2017-09-03 09:34:45	ga_ls8c_ard_3-0-0_092089_2017-09-03_final
2017-09-03 09:35:09	ga_ls8c_ard_3-0-0_092090_2017-09-03_final
2017-09-03 11:04:52	ga_ls8c_ard_3-0-0_108067_2017-09-03_final
2017-09-03 11:05:15	ga_ls8c_ard_3-0-0_108068_2017-09-03_final
2017-09-03 11:05:39	ga_ls8c_ard_3-0-0_108069_2017-09-03_final
2017-09-03 11:06:03	ga_ls8c_ard_3-0-0_108070_2017-09-03_final
2017-09-03 11:06:27	ga_ls8c_ard_3-0-0_108071_2017-09-03_final
2017-09-03 11:06:51	ga_ls8c_ard_3-0-0_108072_2017-09-03_final
2017-09-03 11:07:15	ga_ls8c_ard_3-0-0_108073_2017-09-03_final
2017-09-03 11:07:39	ga_ls8c_ard_3-0-0_108074_2017-09-03_final
2017-09-03 11:08:03	ga_ls8c_ard_3-0-0_108075_2017-09-03_final
2017-09-03 11:08:27	ga_ls8c_ard_3-0-0_108076_2017-09-03_final
2017-09-03 11:08:51	ga_ls8c_ard_3-0-0_108077_2017-09-03_final
2017-09-03 11:09:15	ga_ls8c_ard_3-0-0_108078_2017-09-03_final
2017-09-03 11:09:39	ga_ls8c_ard_3-0-0_108079_2017-09-03_final
2017-09-03 11:10:03	ga_ls8c_ard_3-0-0_108080_2017-09-03_final
2017-09-03 11:10:27	ga_ls8c_ard_3-0-0_108081_2017-09-03_final
2017-09-03 11:10:51	ga_ls8c_ard_3-0-0_108082_2017-09-03_final
2017-09-03 11:11:15	ga_ls8c_ard_3-0-0_108083_2017-09-03_final
2017-09-03 11:11:39	ga_ls8c_ard_3-0-0_108084_2017-09-03_final
2017-09-03 11:12:03	ga_ls8c_ard_3-0-0_108085_2017-09-03_final
2017-09-14 09:10:13	ga_ls8c_ard_3-0-0_089074_2017-09-13_final
2017-09-14 09:10:37	ga_ls8c_ard_3-0-0_089075_2017-09-13_final
2017-09-14 09:11:01	ga_ls8c_ard_3-0-0_089076_2017-09-13_final

Return to ga_ls8c_ard_3 across September 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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2017

September

All days