Search ga_ls7e_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
2020-10-02 09:59:04	ga_ls7e_ard_3-1-0_103068_2020-10-02_final
2020-10-02 09:59:28	ga_ls7e_ard_3-1-0_103069_2020-10-02_final
2020-10-02 09:59:52	ga_ls7e_ard_3-1-0_103070_2020-10-02_final
2020-10-02 10:00:16	ga_ls7e_ard_3-1-0_103071_2020-10-02_final
2020-10-02 10:00:40	ga_ls7e_ard_3-1-0_103072_2020-10-02_final
2020-10-02 10:01:04	ga_ls7e_ard_3-1-0_103073_2020-10-02_final
2020-10-02 10:01:28	ga_ls7e_ard_3-1-0_103074_2020-10-02_final
2020-10-02 10:01:52	ga_ls7e_ard_3-1-0_103075_2020-10-02_final
2020-10-02 10:02:16	ga_ls7e_ard_3-1-0_103076_2020-10-02_final
2020-10-02 10:02:39	ga_ls7e_ard_3-1-0_103077_2020-10-02_final
2020-10-02 10:03:03	ga_ls7e_ard_3-1-0_103078_2020-10-02_final
2020-10-02 10:03:27	ga_ls7e_ard_3-1-0_103079_2020-10-02_final
2020-10-02 10:03:51	ga_ls7e_ard_3-1-0_103080_2020-10-02_final
2020-10-02 10:04:15	ga_ls7e_ard_3-1-0_103081_2020-10-02_final
2020-10-02 10:04:39	ga_ls7e_ard_3-1-0_103082_2020-10-02_final
2020-10-03 09:02:59	ga_ls7e_ard_3-1-0_094067_2020-10-02_final
2020-10-03 09:05:23	ga_ls7e_ard_3-1-0_094073_2020-10-02_final
2020-10-03 09:05:47	ga_ls7e_ard_3-1-0_094074_2020-10-02_final
2020-10-03 09:06:11	ga_ls7e_ard_3-1-0_094075_2020-10-02_final
2020-10-03 09:06:35	ga_ls7e_ard_3-1-0_094076_2020-10-02_final
2020-10-03 09:06:58	ga_ls7e_ard_3-1-0_094077_2020-10-02_final
2020-10-03 09:07:22	ga_ls7e_ard_3-1-0_094078_2020-10-02_final
2020-10-03 09:07:46	ga_ls7e_ard_3-1-0_094079_2020-10-02_final
2020-10-03 09:08:10	ga_ls7e_ard_3-1-0_094080_2020-10-02_final
2020-10-03 09:08:34	ga_ls7e_ard_3-1-0_094081_2020-10-02_final
2020-10-03 09:08:58	ga_ls7e_ard_3-1-0_094082_2020-10-02_final
2020-10-03 09:09:22	ga_ls7e_ard_3-1-0_094083_2020-10-02_final
2020-10-03 09:09:46	ga_ls7e_ard_3-1-0_094084_2020-10-02_final
2020-10-03 09:10:10	ga_ls7e_ard_3-1-0_094085_2020-10-02_final
2020-10-03 09:10:58	ga_ls7e_ard_3-1-0_094087_2020-10-02_final
2020-10-03 10:41:52	ga_ls7e_ard_3-1-0_110067_2020-10-03_final
2020-10-03 10:43:04	ga_ls7e_ard_3-1-0_110070_2020-10-03_final
2020-10-03 10:43:28	ga_ls7e_ard_3-1-0_110071_2020-10-03_final
2020-10-03 10:43:52	ga_ls7e_ard_3-1-0_110072_2020-10-03_final
2020-10-03 10:44:39	ga_ls7e_ard_3-1-0_110074_2020-10-03_final
2020-10-03 10:45:03	ga_ls7e_ard_3-1-0_110075_2020-10-03_final
2020-10-03 10:45:27	ga_ls7e_ard_3-1-0_110076_2020-10-03_final
2020-10-03 10:45:51	ga_ls7e_ard_3-1-0_110077_2020-10-03_final
2020-10-03 10:46:15	ga_ls7e_ard_3-1-0_110078_2020-10-03_final
2020-10-03 10:46:39	ga_ls7e_ard_3-1-0_110079_2020-10-03_final
2020-10-03 10:47:27	ga_ls7e_ard_3-1-0_110081_2020-10-03_final
2020-10-03 10:47:51	ga_ls7e_ard_3-1-0_110082_2020-10-03_final
2020-10-03 10:48:15	ga_ls7e_ard_3-1-0_110083_2020-10-03_final
2020-10-03 10:48:39	ga_ls7e_ard_3-1-0_110084_2020-10-03_final
2020-10-04 09:47:47	ga_ls7e_ard_3-1-0_101071_2020-10-04_final
2020-10-04 09:48:11	ga_ls7e_ard_3-1-0_101072_2020-10-04_final
2020-10-04 09:48:35	ga_ls7e_ard_3-1-0_101073_2020-10-04_final
2020-10-04 09:48:58	ga_ls7e_ard_3-1-0_101074_2020-10-04_final
2020-10-04 09:49:22	ga_ls7e_ard_3-1-0_101075_2020-10-04_final
2020-10-04 09:49:46	ga_ls7e_ard_3-1-0_101076_2020-10-04_final
2020-10-04 09:50:10	ga_ls7e_ard_3-1-0_101077_2020-10-04_final
2020-10-04 09:50:34	ga_ls7e_ard_3-1-0_101078_2020-10-04_final
2020-10-04 09:50:58	ga_ls7e_ard_3-1-0_101079_2020-10-04_final
2020-10-05 08:53:41	ga_ls7e_ard_3-1-0_092075_2020-10-04_final
2020-10-05 08:54:05	ga_ls7e_ard_3-1-0_092076_2020-10-04_final
2020-10-05 08:54:29	ga_ls7e_ard_3-1-0_092077_2020-10-04_final
2020-10-05 08:54:53	ga_ls7e_ard_3-1-0_092078_2020-10-04_final
2020-10-05 08:55:17	ga_ls7e_ard_3-1-0_092079_2020-10-04_final
2020-10-05 08:55:41	ga_ls7e_ard_3-1-0_092080_2020-10-04_final
2020-10-05 08:56:05	ga_ls7e_ard_3-1-0_092081_2020-10-04_final
2020-10-05 08:56:29	ga_ls7e_ard_3-1-0_092082_2020-10-04_final
2020-10-05 08:56:53	ga_ls7e_ard_3-1-0_092083_2020-10-04_final
2020-10-05 08:57:17	ga_ls7e_ard_3-1-0_092084_2020-10-04_final
2020-10-05 10:30:11	ga_ls7e_ard_3-1-0_108069_2020-10-05_final
2020-10-05 10:30:34	ga_ls7e_ard_3-1-0_108070_2020-10-05_final
2020-10-05 10:30:58	ga_ls7e_ard_3-1-0_108071_2020-10-05_final
2020-10-05 10:31:22	ga_ls7e_ard_3-1-0_108072_2020-10-05_final
2020-10-05 10:31:46	ga_ls7e_ard_3-1-0_108073_2020-10-05_final
2020-10-05 10:32:10	ga_ls7e_ard_3-1-0_108074_2020-10-05_final
2020-10-05 10:32:34	ga_ls7e_ard_3-1-0_108075_2020-10-05_final
2020-10-05 10:32:58	ga_ls7e_ard_3-1-0_108076_2020-10-05_final
2020-10-05 10:33:22	ga_ls7e_ard_3-1-0_108077_2020-10-05_final
2020-10-05 10:33:46	ga_ls7e_ard_3-1-0_108078_2020-10-05_final
2020-10-05 10:34:10	ga_ls7e_ard_3-1-0_108079_2020-10-05_final
2020-10-05 10:34:34	ga_ls7e_ard_3-1-0_108080_2020-10-05_final
2020-10-05 10:34:58	ga_ls7e_ard_3-1-0_108081_2020-10-05_final
2020-10-06 09:37:17	ga_ls7e_ard_3-2-0_099076_2020-10-06_final
2020-10-06 09:37:41	ga_ls7e_ard_3-1-0_099077_2020-10-06_final
2020-10-06 09:39:41	ga_ls7e_ard_3-1-0_099082_2020-10-06_final
2020-10-06 09:40:05	ga_ls7e_ard_3-1-0_099083_2020-10-06_final
2020-10-06 11:15:22	ga_ls7e_ard_3-1-0_115074_2020-10-06_final
2020-10-06 11:15:46	ga_ls7e_ard_3-1-0_115075_2020-10-06_final
2020-10-06 11:16:10	ga_ls7e_ard_3-1-0_115076_2020-10-06_final
2020-10-06 11:16:34	ga_ls7e_ard_3-1-0_115077_2020-10-06_final
2020-10-06 11:16:58	ga_ls7e_ard_3-1-0_115078_2020-10-06_final
2020-10-06 11:17:22	ga_ls7e_ard_3-1-0_115079_2020-10-06_final
2020-10-07 08:42:24	ga_ls7e_ard_3-1-0_090078_2020-10-06_final
2020-10-07 08:42:48	ga_ls7e_ard_3-1-0_090079_2020-10-06_final
2020-10-07 08:43:12	ga_ls7e_ard_3-1-0_090080_2020-10-06_final
2020-10-07 08:43:36	ga_ls7e_ard_3-1-0_090081_2020-10-06_final
2020-10-07 08:44:00	ga_ls7e_ard_3-1-0_090082_2020-10-06_final
2020-10-21 08:52:39	ga_ls7e_ard_3-1-0_092075_2020-10-20_final
2020-10-21 08:53:51	ga_ls7e_ard_3-1-0_092078_2020-10-20_final
2020-10-21 08:54:15	ga_ls7e_ard_3-1-0_092079_2020-10-20_final
2020-10-21 08:54:39	ga_ls7e_ard_3-1-0_092080_2020-10-20_final
2020-10-21 08:55:03	ga_ls7e_ard_3-1-0_092081_2020-10-20_final
2020-10-21 08:55:27	ga_ls7e_ard_3-1-0_092082_2020-10-20_final
2020-10-21 08:55:51	ga_ls7e_ard_3-1-0_092083_2020-10-20_final
2020-10-21 08:56:15	ga_ls7e_ard_3-1-0_092084_2020-10-20_final
2020-10-21 08:56:39	ga_ls7e_ard_3-1-0_092085_2020-10-20_final

Return to ga_ls7e_ard_3 across October 2020 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2020

October

All days