Search ga_ls7e_ard_3 across May 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:

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First 100 results (query limit)

Time (local)	Label
2020-05-01 09:31:56	ga_ls7e_ard_3-1-0_097069_2020-05-01_final
2020-05-01 09:32:20	ga_ls7e_ard_3-1-0_097070_2020-05-01_final
2020-05-01 09:32:44	ga_ls7e_ard_3-1-0_097071_2020-05-01_final
2020-05-08 09:36:54	ga_ls7e_ard_3-1-0_098067_2020-05-08_final
2020-05-08 09:37:18	ga_ls7e_ard_3-1-0_098068_2020-05-08_final
2020-05-08 09:37:42	ga_ls7e_ard_3-1-0_098069_2020-05-08_final
2020-05-08 09:38:06	ga_ls7e_ard_3-1-0_098070_2020-05-08_final
2020-05-08 09:38:30	ga_ls7e_ard_3-1-0_098071_2020-05-08_final
2020-05-08 09:38:54	ga_ls7e_ard_3-1-0_098072_2020-05-08_final
2020-05-08 09:39:18	ga_ls7e_ard_3-1-0_098073_2020-05-08_final
2020-05-08 09:39:41	ga_ls7e_ard_3-1-0_098074_2020-05-08_final
2020-05-08 09:40:05	ga_ls7e_ard_3-1-0_098075_2020-05-08_final
2020-05-08 09:40:29	ga_ls7e_ard_3-1-0_098076_2020-05-08_final
2020-05-08 09:40:53	ga_ls7e_ard_3-1-0_098077_2020-05-08_final
2020-05-08 09:41:17	ga_ls7e_ard_3-1-0_098078_2020-05-08_final
2020-05-08 09:41:41	ga_ls7e_ard_3-1-0_098079_2020-05-08_final
2020-05-08 09:42:05	ga_ls7e_ard_3-1-0_098080_2020-05-08_final
2020-05-08 09:42:29	ga_ls7e_ard_3-1-0_098081_2020-05-08_final
2020-05-08 09:42:53	ga_ls7e_ard_3-1-0_098082_2020-05-08_final
2020-05-08 09:43:17	ga_ls7e_ard_3-1-0_098083_2020-05-08_final
2020-05-08 09:43:41	ga_ls7e_ard_3-1-0_098084_2020-05-08_final
2020-05-08 09:44:05	ga_ls7e_ard_3-1-0_098085_2020-05-08_final
2020-05-08 11:15:47	ga_ls7e_ard_3-1-0_114067_2020-05-08_final
2020-05-08 11:18:34	ga_ls7e_ard_3-1-0_114074_2020-05-08_final
2020-05-08 11:18:58	ga_ls7e_ard_3-1-0_114075_2020-05-08_final
2020-05-08 11:19:22	ga_ls7e_ard_3-1-0_114076_2020-05-08_final
2020-05-08 11:19:46	ga_ls7e_ard_3-1-0_114077_2020-05-08_final
2020-05-08 11:20:10	ga_ls7e_ard_3-1-0_114078_2020-05-08_final
2020-05-08 11:20:34	ga_ls7e_ard_3-1-0_114079_2020-05-08_final
2020-05-08 11:20:58	ga_ls7e_ard_3-1-0_114080_2020-05-08_final
2020-05-08 11:21:22	ga_ls7e_ard_3-1-0_114081_2020-05-08_final
2020-05-09 08:45:36	ga_ls7e_ard_3-1-0_089078_2020-05-08_final
2020-05-09 08:46:00	ga_ls7e_ard_3-1-0_089079_2020-05-08_final
2020-05-09 08:46:24	ga_ls7e_ard_3-1-0_089080_2020-05-08_final
2020-05-09 08:46:48	ga_ls7e_ard_3-1-0_089081_2020-05-08_final
2020-05-09 08:47:12	ga_ls7e_ard_3-1-0_089082_2020-05-08_final
2020-05-09 08:47:36	ga_ls7e_ard_3-1-0_089083_2020-05-08_final
2020-05-09 08:48:00	ga_ls7e_ard_3-1-0_089084_2020-05-08_final
2020-05-09 08:48:24	ga_ls7e_ard_3-1-0_089085_2020-05-08_final
2020-05-09 08:48:48	ga_ls7e_ard_3-1-0_089086_2020-05-08_final
2020-05-09 10:20:30	ga_ls7e_ard_3-1-0_105068_2020-05-09_final
2020-05-09 10:20:54	ga_ls7e_ard_3-1-0_105069_2020-05-09_final
2020-05-09 10:21:18	ga_ls7e_ard_3-1-0_105070_2020-05-09_final
2020-05-09 10:21:42	ga_ls7e_ard_3-1-0_105071_2020-05-09_final
2020-05-09 10:22:05	ga_ls7e_ard_3-1-0_105072_2020-05-09_final
2020-05-09 10:22:29	ga_ls7e_ard_3-1-0_105073_2020-05-09_final
2020-05-09 10:22:53	ga_ls7e_ard_3-1-0_105074_2020-05-09_final
2020-05-09 10:23:17	ga_ls7e_ard_3-1-0_105075_2020-05-09_final
2020-05-09 10:23:41	ga_ls7e_ard_3-1-0_105076_2020-05-09_final
2020-05-09 10:24:05	ga_ls7e_ard_3-1-0_105077_2020-05-09_final
2020-05-09 10:24:29	ga_ls7e_ard_3-1-0_105078_2020-05-09_final
2020-05-09 10:24:53	ga_ls7e_ard_3-1-0_105079_2020-05-09_final
2020-05-09 10:25:17	ga_ls7e_ard_3-1-0_105080_2020-05-09_final
2020-05-09 10:25:41	ga_ls7e_ard_3-1-0_105081_2020-05-09_final
2020-05-09 10:26:05	ga_ls7e_ard_3-1-0_105082_2020-05-09_final
2020-05-10 09:24:25	ga_ls7e_ard_3-1-0_096067_2020-05-09_final
2020-05-10 09:25:37	ga_ls7e_ard_3-1-0_096070_2020-05-09_final
2020-05-10 09:26:01	ga_ls7e_ard_3-1-0_096071_2020-05-09_final
2020-05-10 09:26:25	ga_ls7e_ard_3-1-0_096072_2020-05-09_final
2020-05-10 09:26:49	ga_ls7e_ard_3-1-0_096073_2020-05-09_final
2020-05-10 09:27:13	ga_ls7e_ard_3-1-0_096074_2020-05-09_final
2020-05-10 09:27:36	ga_ls7e_ard_3-1-0_096075_2020-05-09_final
2020-05-10 09:28:00	ga_ls7e_ard_3-1-0_096076_2020-05-09_final
2020-05-10 09:28:24	ga_ls7e_ard_3-1-0_096077_2020-05-09_final
2020-05-10 09:28:48	ga_ls7e_ard_3-1-0_096078_2020-05-09_final
2020-05-10 09:29:12	ga_ls7e_ard_3-1-0_096079_2020-05-09_final
2020-05-10 09:29:36	ga_ls7e_ard_3-1-0_096080_2020-05-09_final
2020-05-10 09:30:24	ga_ls7e_ard_3-1-0_096082_2020-05-10_final
2020-05-10 09:30:48	ga_ls7e_ard_3-1-0_096083_2020-05-10_final
2020-05-10 09:31:12	ga_ls7e_ard_3-1-0_096084_2020-05-10_final
2020-05-10 09:31:36	ga_ls7e_ard_3-1-0_096085_2020-05-10_final
2020-05-10 09:32:00	ga_ls7e_ard_3-1-0_096086_2020-05-10_final
2020-05-10 11:03:18	ga_ls7e_ard_3-1-0_112067_2020-05-10_final
2020-05-10 11:08:29	ga_ls7e_ard_3-1-0_112080_2020-05-10_final
2020-05-10 11:08:53	ga_ls7e_ard_3-1-0_112081_2020-05-10_final
2020-05-10 11:09:17	ga_ls7e_ard_3-1-0_112082_2020-05-10_final
2020-05-10 11:09:41	ga_ls7e_ard_3-1-0_112083_2020-05-10_final
2020-05-10 11:10:05	ga_ls7e_ard_3-1-0_112084_2020-05-10_final
2020-05-31 09:42:04	ga_ls7e_ard_3-1-0_099068_2020-05-31_final
2020-05-31 09:42:28	ga_ls7e_ard_3-1-0_099069_2020-05-31_final
2020-05-31 09:42:52	ga_ls7e_ard_3-1-0_099070_2020-05-31_final
2020-05-31 09:43:16	ga_ls7e_ard_3-1-0_099071_2020-05-31_final
2020-05-31 09:43:40	ga_ls7e_ard_3-1-0_099072_2020-05-31_final
2020-05-31 09:44:04	ga_ls7e_ard_3-1-0_099073_2020-05-31_final
2020-05-31 09:44:28	ga_ls7e_ard_3-1-0_099074_2020-05-31_final
2020-05-31 09:44:52	ga_ls7e_ard_3-1-0_099075_2020-05-31_final
2020-05-31 09:45:16	ga_ls7e_ard_3-1-0_099076_2020-05-31_final
2020-05-31 09:45:40	ga_ls7e_ard_3-1-0_099077_2020-05-31_final
2020-05-31 09:46:04	ga_ls7e_ard_3-1-0_099078_2020-05-31_final
2020-05-31 09:46:28	ga_ls7e_ard_3-1-0_099079_2020-05-31_final
2020-05-31 09:46:52	ga_ls7e_ard_3-1-0_099080_2020-05-31_final
2020-05-31 09:47:16	ga_ls7e_ard_3-1-0_099081_2020-05-31_final
2020-05-31 09:47:40	ga_ls7e_ard_3-1-0_099082_2020-05-31_final
2020-05-31 09:48:04	ga_ls7e_ard_3-1-0_099083_2020-05-31_final
2020-05-31 09:48:27	ga_ls7e_ard_3-1-0_099084_2020-05-31_final
2020-05-31 11:23:21	ga_ls7e_ard_3-1-0_115074_2020-05-31_final
2020-05-31 11:23:45	ga_ls7e_ard_3-1-0_115075_2020-05-31_final
2020-05-31 11:24:09	ga_ls7e_ard_3-1-0_115076_2020-05-31_final
2020-05-31 11:24:33	ga_ls7e_ard_3-1-0_115077_2020-05-31_final
2020-05-31 11:24:57	ga_ls7e_ard_3-1-0_115078_2020-05-31_final

Return to ga_ls7e_ard_3 across May 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

May

All days