Search ga_ls7e_ard_3 across April 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
2019-04-01 09:27:37	ga_ls7e_ard_3-0-0_093075_2019-03-31_final
2019-04-01 09:28:01	ga_ls7e_ard_3-0-0_093076_2019-03-31_final
2019-04-01 09:28:25	ga_ls7e_ard_3-0-0_093077_2019-03-31_final
2019-04-01 09:28:49	ga_ls7e_ard_3-0-0_093078_2019-03-31_final
2019-04-01 09:29:13	ga_ls7e_ard_3-0-0_093079_2019-03-31_final
2019-04-01 09:29:37	ga_ls7e_ard_3-0-0_093080_2019-03-31_final
2019-04-01 09:30:25	ga_ls7e_ard_3-0-0_093082_2019-04-01_final
2019-04-01 09:30:49	ga_ls7e_ard_3-0-0_093083_2019-04-01_final
2019-04-01 09:31:13	ga_ls7e_ard_3-0-0_093084_2019-04-01_final
2019-04-01 09:31:37	ga_ls7e_ard_3-0-0_093085_2019-04-01_final
2019-04-01 09:32:01	ga_ls7e_ard_3-0-0_093086_2019-04-01_final
2019-04-01 11:04:30	ga_ls7e_ard_3-0-0_109070_2019-04-01_final
2019-04-01 11:04:54	ga_ls7e_ard_3-0-0_109071_2019-04-01_final
2019-04-01 11:05:18	ga_ls7e_ard_3-0-0_109072_2019-04-01_final
2019-04-01 11:05:42	ga_ls7e_ard_3-0-0_109073_2019-04-01_final
2019-04-01 11:06:06	ga_ls7e_ard_3-0-0_109074_2019-04-01_final
2019-04-01 11:06:30	ga_ls7e_ard_3-0-0_109075_2019-04-01_final
2019-04-01 11:06:54	ga_ls7e_ard_3-0-0_109076_2019-04-01_final
2019-04-01 11:07:18	ga_ls7e_ard_3-0-0_109077_2019-04-01_final
2019-04-01 11:07:42	ga_ls7e_ard_3-0-0_109078_2019-04-01_final
2019-04-01 11:08:06	ga_ls7e_ard_3-0-0_109079_2019-04-01_final
2019-04-01 11:08:30	ga_ls7e_ard_3-0-0_109080_2019-04-01_final
2019-04-01 11:08:54	ga_ls7e_ard_3-1-0_109081_2019-04-01_final
2019-04-01 11:09:18	ga_ls7e_ard_3-0-0_109082_2019-04-01_final
2019-04-01 11:09:42	ga_ls7e_ard_3-0-0_109083_2019-04-01_final
2019-04-01 11:10:06	ga_ls7e_ard_3-0-0_109084_2019-04-01_final
2019-04-02 10:09:15	ga_ls7e_ard_3-0-0_100071_2019-04-02_final
2019-04-02 10:09:39	ga_ls7e_ard_3-0-0_100072_2019-04-02_final
2019-04-02 10:10:03	ga_ls7e_ard_3-0-0_100073_2019-04-02_final
2019-04-02 10:10:27	ga_ls7e_ard_3-0-0_100074_2019-04-02_final
2019-04-02 10:10:51	ga_ls7e_ard_3-0-0_100075_2019-04-02_final
2019-04-02 10:11:15	ga_ls7e_ard_3-0-0_100076_2019-04-02_final
2019-04-02 10:11:39	ga_ls7e_ard_3-0-0_100077_2019-04-02_final
2019-04-02 10:12:03	ga_ls7e_ard_3-0-0_100078_2019-04-02_final
2019-04-02 10:12:27	ga_ls7e_ard_3-0-0_100079_2019-04-02_final
2019-04-02 10:12:50	ga_ls7e_ard_3-0-0_100080_2019-04-02_final
2019-04-02 10:13:14	ga_ls7e_ard_3-1-0_100081_2019-04-02_final
2019-04-02 10:13:38	ga_ls7e_ard_3-0-0_100082_2019-04-02_final
2019-04-02 10:14:02	ga_ls7e_ard_3-0-0_100083_2019-04-02_final
2019-04-02 10:14:26	ga_ls7e_ard_3-0-0_100084_2019-04-02_final
2019-04-03 09:15:35	ga_ls7e_ard_3-0-0_091076_2019-04-02_final
2019-04-03 09:15:59	ga_ls7e_ard_3-0-0_091077_2019-04-02_final
2019-04-03 09:16:23	ga_ls7e_ard_3-0-0_091078_2019-04-02_final
2019-04-03 09:16:47	ga_ls7e_ard_3-0-0_091079_2019-04-02_final
2019-04-03 09:17:11	ga_ls7e_ard_3-0-0_091080_2019-04-02_final
2019-04-03 09:17:35	ga_ls7e_ard_3-0-0_091081_2019-04-02_final
2019-04-03 09:17:59	ga_ls7e_ard_3-0-0_091082_2019-04-02_final
2019-04-03 09:18:23	ga_ls7e_ard_3-0-0_091083_2019-04-02_final
2019-04-03 09:18:47	ga_ls7e_ard_3-0-0_091084_2019-04-02_final
2019-04-03 09:19:11	ga_ls7e_ard_3-0-0_091085_2019-04-02_final
2019-04-03 09:19:35	ga_ls7e_ard_3-1-0_091086_2019-04-02_final
2019-04-03 09:19:59	ga_ls7e_ard_3-0-0_091087_2019-04-02_final
2019-04-03 09:20:23	ga_ls7e_ard_3-0-0_091088_2019-04-02_final
2019-04-03 09:21:11	ga_ls7e_ard_3-0-0_091090_2019-04-02_final
2019-04-03 10:52:05	ga_ls7e_ard_3-0-0_107070_2019-04-03_final
2019-04-03 10:52:29	ga_ls7e_ard_3-0-0_107071_2019-04-03_final
2019-04-03 10:52:53	ga_ls7e_ard_3-0-0_107072_2019-04-03_final
2019-04-03 10:53:16	ga_ls7e_ard_3-0-0_107073_2019-04-03_final
2019-04-03 10:53:40	ga_ls7e_ard_3-0-0_107074_2019-04-03_final
2019-04-03 10:54:04	ga_ls7e_ard_3-0-0_107075_2019-04-03_final
2019-04-03 10:54:28	ga_ls7e_ard_3-0-0_107076_2019-04-03_final
2019-04-03 10:54:52	ga_ls7e_ard_3-0-0_107077_2019-04-03_final
2019-04-03 10:55:16	ga_ls7e_ard_3-0-0_107078_2019-04-03_final
2019-04-03 10:55:40	ga_ls7e_ard_3-0-0_107079_2019-04-03_final
2019-04-03 10:56:04	ga_ls7e_ard_3-0-0_107080_2019-04-03_final
2019-04-03 10:56:28	ga_ls7e_ard_3-0-0_107081_2019-04-03_final
2019-04-04 09:56:25	ga_ls7e_ard_3-0-0_098070_2019-04-04_final
2019-04-04 09:56:49	ga_ls7e_ard_3-0-0_098071_2019-04-04_final
2019-04-04 09:57:13	ga_ls7e_ard_3-0-0_098072_2019-04-04_final
2019-04-04 09:57:37	ga_ls7e_ard_3-0-0_098073_2019-04-04_final
2019-04-04 09:58:01	ga_ls7e_ard_3-0-0_098074_2019-04-04_final
2019-04-04 09:58:25	ga_ls7e_ard_3-0-0_098075_2019-04-04_final
2019-04-04 09:58:49	ga_ls7e_ard_3-0-0_098076_2019-04-04_final
2019-04-04 09:59:13	ga_ls7e_ard_3-0-0_098077_2019-04-04_final
2019-04-04 09:59:37	ga_ls7e_ard_3-0-0_098078_2019-04-04_final
2019-04-04 10:00:01	ga_ls7e_ard_3-0-0_098079_2019-04-04_final
2019-04-04 10:00:25	ga_ls7e_ard_3-1-0_098080_2019-04-04_final
2019-04-04 10:00:49	ga_ls7e_ard_3-0-0_098081_2019-04-04_final
2019-04-04 10:01:13	ga_ls7e_ard_3-0-0_098082_2019-04-04_final
2019-04-04 10:01:37	ga_ls7e_ard_3-0-0_098083_2019-04-04_final
2019-04-04 10:02:00	ga_ls7e_ard_3-0-0_098084_2019-04-04_final
2019-04-04 10:02:24	ga_ls7e_ard_3-0-0_098085_2019-04-04_final
2019-04-04 11:34:06	ga_ls7e_ard_3-0-0_114067_2019-04-04_final
2019-04-21 09:04:35	ga_ls7e_ard_3-1-0_089081_2019-04-20_final
2019-04-21 10:43:04	ga_ls7e_ard_3-1-0_105080_2019-04-21_final
2019-04-22 09:49:48	ga_ls7e_ard_3-1-0_096086_2019-04-22_final
2019-04-24 09:29:47	ga_ls7e_ard_3-1-0_094067_2019-04-23_final
2019-04-24 09:33:46	ga_ls7e_ard_3-0-0_094077_2019-04-24_final
2019-04-29 11:29:49	ga_ls7e_ard_3-0-0_113074_2019-04-29_final
2019-04-29 11:30:13	ga_ls7e_ard_3-0-0_113075_2019-04-29_final
2019-04-29 11:30:36	ga_ls7e_ard_3-0-0_113076_2019-04-29_final
2019-04-29 11:31:00	ga_ls7e_ard_3-0-0_113077_2019-04-29_final
2019-04-29 11:31:24	ga_ls7e_ard_3-0-0_113078_2019-04-29_final
2019-04-29 11:31:48	ga_ls7e_ard_3-0-0_113079_2019-04-29_final
2019-04-29 11:33:24	ga_ls7e_ard_3-0-0_113083_2019-04-29_final
2019-04-30 10:31:45	ga_ls7e_ard_3-0-0_104068_2019-04-30_final
2019-04-30 10:32:09	ga_ls7e_ard_3-0-0_104069_2019-04-30_final
2019-04-30 10:32:33	ga_ls7e_ard_3-1-0_104070_2019-04-30_final
2019-04-30 10:32:57	ga_ls7e_ard_3-0-0_104071_2019-04-30_final
2019-04-30 10:33:21	ga_ls7e_ard_3-0-0_104072_2019-04-30_final

Return to ga_ls7e_ard_3 across April 2019 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

2019

April

All days