Search ga_ls7e_ard_3 across March 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
2019-03-18 10:57:01	ga_ls7e_ard_3-1-0_107081_2019-03-18_final
2019-03-18 10:57:25	ga_ls7e_ard_3-1-0_107082_2019-03-18_final
2019-03-18 10:57:48	ga_ls7e_ard_3-1-0_107083_2019-03-18_final
2019-03-18 10:58:12	ga_ls7e_ard_3-1-0_107084_2019-03-18_final
2019-03-19 09:56:58	ga_ls7e_ard_3-1-0_098070_2019-03-19_final
2019-03-19 09:57:22	ga_ls7e_ard_3-1-0_098071_2019-03-19_final
2019-03-19 09:57:46	ga_ls7e_ard_3-1-0_098072_2019-03-19_final
2019-03-19 09:58:10	ga_ls7e_ard_3-1-0_098073_2019-03-19_final
2019-03-19 09:58:34	ga_ls7e_ard_3-1-0_098074_2019-03-19_final
2019-03-19 09:58:58	ga_ls7e_ard_3-1-0_098075_2019-03-19_final
2019-03-19 09:59:22	ga_ls7e_ard_3-1-0_098076_2019-03-19_final
2019-03-19 09:59:46	ga_ls7e_ard_3-1-0_098077_2019-03-19_final
2019-03-19 10:00:10	ga_ls7e_ard_3-1-0_098078_2019-03-19_final
2019-03-19 10:00:33	ga_ls7e_ard_3-1-0_098079_2019-03-19_final
2019-03-19 10:00:57	ga_ls7e_ard_3-1-0_098080_2019-03-19_final
2019-03-19 10:01:21	ga_ls7e_ard_3-1-0_098081_2019-03-19_final
2019-03-19 10:01:45	ga_ls7e_ard_3-1-0_098082_2019-03-19_final
2019-03-19 10:02:09	ga_ls7e_ard_3-1-0_098083_2019-03-19_final
2019-03-19 10:02:33	ga_ls7e_ard_3-1-0_098084_2019-03-19_final
2019-03-19 10:02:57	ga_ls7e_ard_3-1-0_098085_2019-03-19_final
2019-03-19 11:37:27	ga_ls7e_ard_3-1-0_114074_2019-03-19_final
2019-03-19 11:37:51	ga_ls7e_ard_3-1-0_114075_2019-03-19_final
2019-03-19 11:38:15	ga_ls7e_ard_3-1-0_114076_2019-03-19_final
2019-03-19 11:38:39	ga_ls7e_ard_3-1-0_114077_2019-03-19_final
2019-03-19 11:39:02	ga_ls7e_ard_3-1-0_114078_2019-03-19_final
2019-03-19 11:39:26	ga_ls7e_ard_3-1-0_114079_2019-03-19_final
2019-03-19 11:39:50	ga_ls7e_ard_3-1-0_114080_2019-03-19_final
2019-03-19 11:40:14	ga_ls7e_ard_3-1-0_114081_2019-03-19_final
2019-03-20 09:04:06	ga_ls7e_ard_3-1-0_089077_2019-03-19_final
2019-03-20 09:04:30	ga_ls7e_ard_3-1-0_089078_2019-03-19_final
2019-03-20 09:04:54	ga_ls7e_ard_3-1-0_089079_2019-03-19_final
2019-03-20 09:05:18	ga_ls7e_ard_3-1-0_089080_2019-03-19_final
2019-03-20 09:05:42	ga_ls7e_ard_3-1-0_089081_2019-03-19_final
2019-03-20 09:06:06	ga_ls7e_ard_3-1-0_089082_2019-03-19_final
2019-03-20 09:06:30	ga_ls7e_ard_3-1-0_089083_2019-03-19_final
2019-03-20 09:06:54	ga_ls7e_ard_3-1-0_089084_2019-03-19_final
2019-03-20 09:07:18	ga_ls7e_ard_3-1-0_089085_2019-03-19_final
2019-03-20 10:39:24	ga_ls7e_ard_3-1-0_105068_2019-03-20_final
2019-03-20 10:39:48	ga_ls7e_ard_3-1-0_105069_2019-03-20_final
2019-03-20 10:40:12	ga_ls7e_ard_3-1-0_105070_2019-03-20_final
2019-03-20 10:40:36	ga_ls7e_ard_3-1-0_105071_2019-03-20_final
2019-03-20 10:41:00	ga_ls7e_ard_3-1-0_105072_2019-03-20_final
2019-03-20 10:41:23	ga_ls7e_ard_3-1-0_105073_2019-03-20_final
2019-03-20 10:41:47	ga_ls7e_ard_3-1-0_105074_2019-03-20_final
2019-03-20 10:42:11	ga_ls7e_ard_3-1-0_105075_2019-03-20_final
2019-03-20 10:42:35	ga_ls7e_ard_3-1-0_105076_2019-03-20_final
2019-03-20 10:42:59	ga_ls7e_ard_3-1-0_105077_2019-03-20_final
2019-03-20 10:43:23	ga_ls7e_ard_3-1-0_105078_2019-03-20_final
2019-03-20 10:43:47	ga_ls7e_ard_3-1-0_105079_2019-03-20_final
2019-03-20 10:44:11	ga_ls7e_ard_3-1-0_105080_2019-03-20_final
2019-03-20 10:44:35	ga_ls7e_ard_3-1-0_105081_2019-03-20_final
2019-03-20 10:44:59	ga_ls7e_ard_3-1-0_105082_2019-03-20_final
2019-03-20 10:45:23	ga_ls7e_ard_3-1-0_105083_2019-03-20_final
2019-03-21 09:45:44	ga_ls7e_ard_3-1-0_096073_2019-03-21_final
2019-03-21 09:46:08	ga_ls7e_ard_3-1-0_096074_2019-03-21_final
2019-03-21 09:46:32	ga_ls7e_ard_3-1-0_096075_2019-03-21_final
2019-03-21 09:46:56	ga_ls7e_ard_3-1-0_096076_2019-03-21_final
2019-03-21 09:47:20	ga_ls7e_ard_3-1-0_096077_2019-03-21_final
2019-03-21 09:47:44	ga_ls7e_ard_3-1-0_096078_2019-03-21_final
2019-03-21 09:48:08	ga_ls7e_ard_3-1-0_096079_2019-03-21_final
2019-03-21 09:48:32	ga_ls7e_ard_3-1-0_096080_2019-03-21_final
2019-03-21 09:48:56	ga_ls7e_ard_3-1-0_096081_2019-03-21_final
2019-03-21 09:49:20	ga_ls7e_ard_3-1-0_096082_2019-03-21_final
2019-03-21 09:49:44	ga_ls7e_ard_3-1-0_096083_2019-03-21_final
2019-03-21 09:50:08	ga_ls7e_ard_3-1-0_096084_2019-03-21_final
2019-03-21 09:50:32	ga_ls7e_ard_3-1-0_096085_2019-03-21_final
2019-03-21 11:22:14	ga_ls7e_ard_3-1-0_112067_2019-03-21_final
2019-03-21 11:25:25	ga_ls7e_ard_3-1-0_112075_2019-03-21_final
2019-03-21 11:25:49	ga_ls7e_ard_3-1-0_112076_2019-03-21_final
2019-03-21 11:26:13	ga_ls7e_ard_3-1-0_112077_2019-03-21_final
2019-03-21 11:26:37	ga_ls7e_ard_3-1-0_112078_2019-03-21_final
2019-03-21 11:28:13	ga_ls7e_ard_3-1-0_112082_2019-03-21_final
2019-03-21 11:28:37	ga_ls7e_ard_3-1-0_112083_2019-03-21_final
2019-03-21 11:29:01	ga_ls7e_ard_3-1-0_112084_2019-03-21_final
2019-03-29 10:32:55	ga_ls7e_ard_3-1-0_104068_2019-03-29_final
2019-03-29 10:33:19	ga_ls7e_ard_3-1-0_104069_2019-03-29_final
2019-03-29 10:33:43	ga_ls7e_ard_3-1-0_104070_2019-03-29_final
2019-03-29 10:34:06	ga_ls7e_ard_3-1-0_104071_2019-03-29_final
2019-03-29 10:34:30	ga_ls7e_ard_3-1-0_104072_2019-03-29_final
2019-03-29 10:34:54	ga_ls7e_ard_3-1-0_104073_2019-03-29_final
2019-03-29 10:35:18	ga_ls7e_ard_3-1-0_104074_2019-03-29_final
2019-03-29 10:35:42	ga_ls7e_ard_3-1-0_104075_2019-03-29_final
2019-03-29 10:36:06	ga_ls7e_ard_3-1-0_104076_2019-03-29_final
2019-03-29 10:36:30	ga_ls7e_ard_3-1-0_104077_2019-03-29_final
2019-03-29 10:36:54	ga_ls7e_ard_3-1-0_104078_2019-03-29_final
2019-03-29 10:37:18	ga_ls7e_ard_3-1-0_104079_2019-03-29_final
2019-03-29 10:37:42	ga_ls7e_ard_3-1-0_104080_2019-03-29_final
2019-03-31 10:20:29	ga_ls7e_ard_3-0-0_102068_2019-03-31_final
2019-03-31 10:20:53	ga_ls7e_ard_3-0-0_102069_2019-03-31_final
2019-03-31 10:21:17	ga_ls7e_ard_3-0-0_102070_2019-03-31_final
2019-03-31 10:21:41	ga_ls7e_ard_3-0-0_102071_2019-03-31_final
2019-03-31 10:22:05	ga_ls7e_ard_3-0-0_102072_2019-03-31_final
2019-03-31 10:22:29	ga_ls7e_ard_3-0-0_102073_2019-03-31_final
2019-03-31 10:22:53	ga_ls7e_ard_3-0-0_102074_2019-03-31_final
2019-03-31 10:23:17	ga_ls7e_ard_3-0-0_102075_2019-03-31_final
2019-03-31 10:23:40	ga_ls7e_ard_3-0-0_102076_2019-03-31_final
2019-03-31 10:24:04	ga_ls7e_ard_3-0-0_102077_2019-03-31_final
2019-03-31 10:24:28	ga_ls7e_ard_3-0-0_102078_2019-03-31_final
2019-03-31 10:24:52	ga_ls7e_ard_3-0-0_102079_2019-03-31_final
2019-03-31 10:25:16	ga_ls7e_ard_3-0-0_102080_2019-03-31_final

Return to ga_ls7e_ard_3 across March 2019 overview

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

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

2019

March

All days