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
2019-03-02 09:16:39	ga_ls7e_ard_3-1-0_091076_2019-03-01_final
2019-03-02 09:17:03	ga_ls7e_ard_3-1-0_091077_2019-03-01_final
2019-03-02 09:17:51	ga_ls7e_ard_3-1-0_091079_2019-03-01_final
2019-03-02 09:18:15	ga_ls7e_ard_3-1-0_091080_2019-03-01_final
2019-03-02 09:18:39	ga_ls7e_ard_3-1-0_091081_2019-03-01_final
2019-03-02 09:19:03	ga_ls7e_ard_3-1-0_091082_2019-03-01_final
2019-03-04 09:05:26	ga_ls7e_ard_3-1-0_089079_2019-03-03_final
2019-03-04 09:05:49	ga_ls7e_ard_3-1-0_089080_2019-03-03_final
2019-03-04 09:06:13	ga_ls7e_ard_3-1-0_089081_2019-03-03_final
2019-03-04 09:06:37	ga_ls7e_ard_3-1-0_089082_2019-03-03_final
2019-03-04 09:07:01	ga_ls7e_ard_3-1-0_089083_2019-03-03_final
2019-03-04 09:07:25	ga_ls7e_ard_3-1-0_089084_2019-03-03_final
2019-03-04 09:07:49	ga_ls7e_ard_3-1-0_089085_2019-03-03_final
2019-03-04 09:08:13	ga_ls7e_ard_3-1-0_089086_2019-03-03_final
2019-03-05 09:45:04	ga_ls7e_ard_3-1-0_096070_2019-03-05_final
2019-03-05 09:45:28	ga_ls7e_ard_3-1-0_096071_2019-03-05_final
2019-03-05 09:45:52	ga_ls7e_ard_3-1-0_096072_2019-03-05_final
2019-03-05 09:46:16	ga_ls7e_ard_3-1-0_096073_2019-03-05_final
2019-03-05 09:46:40	ga_ls7e_ard_3-1-0_096074_2019-03-05_final
2019-03-05 09:47:03	ga_ls7e_ard_3-1-0_096075_2019-03-05_final
2019-03-05 09:47:27	ga_ls7e_ard_3-1-0_096076_2019-03-05_final
2019-03-05 09:47:51	ga_ls7e_ard_3-1-0_096077_2019-03-05_final
2019-03-05 09:48:15	ga_ls7e_ard_3-1-0_096078_2019-03-05_final
2019-03-05 09:48:39	ga_ls7e_ard_3-1-0_096079_2019-03-05_final
2019-03-05 09:49:03	ga_ls7e_ard_3-1-0_096080_2019-03-05_final
2019-03-05 09:49:27	ga_ls7e_ard_3-1-0_096081_2019-03-05_final
2019-03-05 09:49:51	ga_ls7e_ard_3-1-0_096082_2019-03-05_final
2019-03-05 09:50:15	ga_ls7e_ard_3-1-0_096083_2019-03-05_final
2019-03-05 09:50:39	ga_ls7e_ard_3-1-0_096084_2019-03-05_final
2019-03-05 09:51:03	ga_ls7e_ard_3-1-0_096085_2019-03-05_final
2019-03-05 11:22:45	ga_ls7e_ard_3-1-0_112067_2019-03-05_final
2019-03-05 11:25:32	ga_ls7e_ard_3-1-0_112074_2019-03-05_final
2019-03-05 11:25:56	ga_ls7e_ard_3-1-0_112075_2019-03-05_final
2019-03-05 11:26:20	ga_ls7e_ard_3-1-0_112076_2019-03-05_final
2019-03-05 11:26:44	ga_ls7e_ard_3-1-0_112077_2019-03-05_final
2019-03-05 11:27:08	ga_ls7e_ard_3-1-0_112078_2019-03-05_final
2019-03-05 11:27:56	ga_ls7e_ard_3-1-0_112080_2019-03-05_final
2019-03-05 11:28:20	ga_ls7e_ard_3-1-0_112081_2019-03-05_final
2019-03-05 11:28:44	ga_ls7e_ard_3-1-0_112082_2019-03-05_final
2019-03-05 11:29:08	ga_ls7e_ard_3-1-0_112083_2019-03-05_final
2019-03-05 11:29:32	ga_ls7e_ard_3-1-0_112084_2019-03-05_final
2019-03-06 10:27:30	ga_ls7e_ard_3-1-0_103068_2019-03-06_final
2019-03-06 10:28:18	ga_ls7e_ard_3-1-0_103070_2019-03-06_final
2019-03-06 10:28:41	ga_ls7e_ard_3-1-0_103071_2019-03-06_final
2019-03-06 10:29:05	ga_ls7e_ard_3-1-0_103072_2019-03-06_final
2019-03-06 10:29:29	ga_ls7e_ard_3-1-0_103073_2019-03-06_final
2019-03-06 10:29:53	ga_ls7e_ard_3-1-0_103074_2019-03-06_final
2019-03-06 10:30:17	ga_ls7e_ard_3-1-0_103075_2019-03-06_final
2019-03-06 10:30:41	ga_ls7e_ard_3-1-0_103076_2019-03-06_final
2019-03-06 10:31:05	ga_ls7e_ard_3-1-0_103077_2019-03-06_final
2019-03-06 10:31:29	ga_ls7e_ard_3-1-0_103078_2019-03-06_final
2019-03-06 10:31:53	ga_ls7e_ard_3-1-0_103079_2019-03-06_final
2019-03-06 10:32:17	ga_ls7e_ard_3-1-0_103080_2019-03-06_final
2019-03-06 10:32:41	ga_ls7e_ard_3-1-0_103081_2019-03-06_final
2019-03-06 10:33:05	ga_ls7e_ard_3-1-0_103082_2019-03-06_final
2019-03-07 09:31:27	ga_ls7e_ard_3-1-0_094067_2019-03-07_final
2019-03-07 09:33:50	ga_ls7e_ard_3-1-0_094073_2019-03-07_final
2019-03-07 09:34:14	ga_ls7e_ard_3-1-0_094074_2019-03-07_final
2019-03-07 09:34:38	ga_ls7e_ard_3-1-0_094075_2019-03-07_final
2019-03-07 09:35:02	ga_ls7e_ard_3-1-0_094076_2019-03-07_final
2019-03-07 09:35:26	ga_ls7e_ard_3-1-0_094077_2019-03-07_final
2019-03-07 09:35:50	ga_ls7e_ard_3-1-0_094078_2019-03-07_final
2019-03-07 09:36:14	ga_ls7e_ard_3-1-0_094079_2019-03-07_final
2019-03-07 09:36:38	ga_ls7e_ard_3-1-0_094080_2019-03-07_final
2019-03-07 09:37:02	ga_ls7e_ard_3-1-0_094081_2019-03-07_final
2019-03-07 09:37:26	ga_ls7e_ard_3-1-0_094082_2019-03-07_final
2019-03-07 09:37:50	ga_ls7e_ard_3-1-0_094083_2019-03-07_final
2019-03-07 09:38:14	ga_ls7e_ard_3-1-0_094084_2019-03-07_final
2019-03-07 09:38:37	ga_ls7e_ard_3-1-0_094085_2019-03-07_final
2019-03-07 09:39:01	ga_ls7e_ard_3-1-0_094086_2019-03-07_final
2019-03-07 09:39:25	ga_ls7e_ard_3-1-0_094087_2019-03-07_final
2019-03-07 11:10:19	ga_ls7e_ard_3-1-0_110067_2019-03-07_final
2019-03-07 11:11:31	ga_ls7e_ard_3-1-0_110070_2019-03-07_final
2019-03-07 11:11:55	ga_ls7e_ard_3-1-0_110071_2019-03-07_final
2019-03-07 11:12:19	ga_ls7e_ard_3-1-0_110072_2019-03-07_final
2019-03-07 11:12:43	ga_ls7e_ard_3-1-0_110073_2019-03-07_final
2019-03-07 11:13:07	ga_ls7e_ard_3-1-0_110074_2019-03-07_final
2019-03-07 11:13:31	ga_ls7e_ard_3-1-0_110075_2019-03-07_final
2019-03-07 11:13:55	ga_ls7e_ard_3-1-0_110076_2019-03-07_final
2019-03-07 11:14:19	ga_ls7e_ard_3-1-0_110077_2019-03-07_final
2019-03-07 11:14:43	ga_ls7e_ard_3-1-0_110078_2019-03-07_final
2019-03-07 11:15:07	ga_ls7e_ard_3-1-0_110079_2019-03-07_final
2019-03-08 10:16:16	ga_ls7e_ard_3-1-0_101071_2019-03-08_final
2019-03-08 10:16:40	ga_ls7e_ard_3-1-0_101072_2019-03-08_final
2019-03-08 10:17:04	ga_ls7e_ard_3-1-0_101073_2019-03-08_final
2019-03-08 10:17:28	ga_ls7e_ard_3-1-0_101074_2019-03-08_final
2019-03-08 10:17:52	ga_ls7e_ard_3-1-0_101075_2019-03-08_final
2019-03-08 10:18:16	ga_ls7e_ard_3-1-0_101076_2019-03-08_final
2019-03-08 10:18:40	ga_ls7e_ard_3-1-0_101077_2019-03-08_final
2019-03-08 10:19:04	ga_ls7e_ard_3-1-0_101078_2019-03-08_final
2019-03-08 10:19:27	ga_ls7e_ard_3-1-0_101079_2019-03-08_final
2019-03-08 10:19:51	ga_ls7e_ard_3-1-0_101080_2019-03-08_final
2019-03-08 10:20:15	ga_ls7e_ard_3-1-0_101081_2019-03-08_final
2019-03-08 10:21:03	ga_ls7e_ard_3-1-0_101083_2019-03-08_final
2019-03-09 09:22:13	ga_ls7e_ard_3-1-0_092075_2019-03-08_final
2019-03-09 09:23:00	ga_ls7e_ard_3-1-0_092077_2019-03-08_final
2019-03-09 09:23:24	ga_ls7e_ard_3-1-0_092078_2019-03-08_final
2019-03-09 09:23:48	ga_ls7e_ard_3-1-0_092079_2019-03-08_final
2019-03-09 09:24:12	ga_ls7e_ard_3-1-0_092080_2019-03-08_final
2019-03-09 09:24:36	ga_ls7e_ard_3-1-0_092081_2019-03-08_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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2019

March

All days