Search ga_ls7e_ard_3 across August 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
2020-08-01 09:51:55	ga_ls7e_ard_3-1-0_101071_2020-08-01_final
2020-08-01 09:52:19	ga_ls7e_ard_3-1-0_101072_2020-08-01_final
2020-08-01 09:52:43	ga_ls7e_ard_3-1-0_101073_2020-08-01_final
2020-08-01 09:53:07	ga_ls7e_ard_3-1-0_101074_2020-08-01_final
2020-08-01 09:53:31	ga_ls7e_ard_3-1-0_101075_2020-08-01_final
2020-08-01 09:53:55	ga_ls7e_ard_3-1-0_101076_2020-08-01_final
2020-08-01 09:54:18	ga_ls7e_ard_3-1-0_101077_2020-08-01_final
2020-08-01 09:54:42	ga_ls7e_ard_3-1-0_101078_2020-08-01_final
2020-08-01 09:55:06	ga_ls7e_ard_3-1-0_101079_2020-08-01_final
2020-08-01 09:55:30	ga_ls7e_ard_3-1-0_101080_2020-08-01_final
2020-08-01 09:55:54	ga_ls7e_ard_3-1-0_101081_2020-08-01_final
2020-08-01 09:56:18	ga_ls7e_ard_3-1-0_101082_2020-08-01_final
2020-08-01 09:56:42	ga_ls7e_ard_3-1-0_101083_2020-08-01_final
2020-08-02 08:57:50	ga_ls7e_ard_3-1-0_092075_2020-08-01_final
2020-08-02 08:58:14	ga_ls7e_ard_3-1-0_092076_2020-08-01_final
2020-08-02 08:58:38	ga_ls7e_ard_3-1-0_092077_2020-08-01_final
2020-08-02 08:59:01	ga_ls7e_ard_3-1-0_092078_2020-08-01_final
2020-08-02 08:59:25	ga_ls7e_ard_3-1-0_092079_2020-08-01_final
2020-08-02 08:59:49	ga_ls7e_ard_3-1-0_092080_2020-08-01_final
2020-08-02 09:00:13	ga_ls7e_ard_3-1-0_092081_2020-08-01_final
2020-08-02 09:00:37	ga_ls7e_ard_3-1-0_092082_2020-08-01_final
2020-08-02 09:01:01	ga_ls7e_ard_3-1-0_092083_2020-08-01_final
2020-08-02 09:01:25	ga_ls7e_ard_3-1-0_092084_2020-08-01_final
2020-08-02 09:01:49	ga_ls7e_ard_3-1-0_092085_2020-08-01_final
2020-08-02 09:02:13	ga_ls7e_ard_3-1-0_092086_2020-08-01_final
2020-08-02 09:02:37	ga_ls7e_ard_3-1-0_092087_2020-08-01_final
2020-08-02 09:03:01	ga_ls7e_ard_3-1-0_092088_2020-08-01_final
2020-08-02 09:03:25	ga_ls7e_ard_3-1-0_092089_2020-08-01_final
2020-08-02 10:34:19	ga_ls7e_ard_3-1-0_108069_2020-08-02_final
2020-08-02 10:34:43	ga_ls7e_ard_3-1-0_108070_2020-08-02_final
2020-08-02 10:35:07	ga_ls7e_ard_3-1-0_108071_2020-08-02_final
2020-08-02 10:35:31	ga_ls7e_ard_3-1-0_108072_2020-08-02_final
2020-08-02 10:35:55	ga_ls7e_ard_3-1-0_108073_2020-08-02_final
2020-08-02 10:36:18	ga_ls7e_ard_3-1-0_108074_2020-08-02_final
2020-08-02 10:36:42	ga_ls7e_ard_3-1-0_108075_2020-08-02_final
2020-08-02 10:37:06	ga_ls7e_ard_3-1-0_108076_2020-08-02_final
2020-08-02 10:37:30	ga_ls7e_ard_3-1-0_108077_2020-08-02_final
2020-08-02 10:37:54	ga_ls7e_ard_3-1-0_108078_2020-08-02_final
2020-08-02 10:38:18	ga_ls7e_ard_3-1-0_108079_2020-08-02_final
2020-08-02 10:38:42	ga_ls7e_ard_3-1-0_108080_2020-08-02_final
2020-08-02 10:39:06	ga_ls7e_ard_3-1-0_108081_2020-08-02_final
2020-08-02 10:39:30	ga_ls7e_ard_3-1-0_108082_2020-08-02_final
2020-08-02 10:39:54	ga_ls7e_ard_3-1-0_108083_2020-08-02_final
2020-08-02 10:40:18	ga_ls7e_ard_3-1-0_108084_2020-08-02_final
2020-08-28 09:30:27	ga_ls7e_ard_3-1-0_098068_2020-08-28_final
2020-08-28 09:30:51	ga_ls7e_ard_3-1-0_098069_2020-08-28_final
2020-08-28 09:31:15	ga_ls7e_ard_3-1-0_098070_2020-08-28_final
2020-08-28 09:31:39	ga_ls7e_ard_3-1-0_098071_2020-08-28_final
2020-08-28 09:32:03	ga_ls7e_ard_3-1-0_098072_2020-08-28_final
2020-08-28 09:32:27	ga_ls7e_ard_3-1-0_098073_2020-08-28_final
2020-08-28 09:32:51	ga_ls7e_ard_3-1-0_098074_2020-08-28_final
2020-08-28 09:33:15	ga_ls7e_ard_3-1-0_098075_2020-08-28_final
2020-08-28 09:33:39	ga_ls7e_ard_3-1-0_098076_2020-08-28_final
2020-08-28 09:34:03	ga_ls7e_ard_3-1-0_098077_2020-08-28_final
2020-08-28 09:34:27	ga_ls7e_ard_3-1-0_098078_2020-08-28_final
2020-08-28 09:34:51	ga_ls7e_ard_3-1-0_098079_2020-08-28_final
2020-08-28 09:35:14	ga_ls7e_ard_3-1-0_098080_2020-08-28_final
2020-08-28 09:35:38	ga_ls7e_ard_3-1-0_098081_2020-08-28_final
2020-08-28 09:36:02	ga_ls7e_ard_3-1-0_098082_2020-08-28_final
2020-08-28 09:36:26	ga_ls7e_ard_3-1-0_098083_2020-08-28_final
2020-08-28 09:36:50	ga_ls7e_ard_3-1-0_098084_2020-08-28_final
2020-08-29 08:38:22	ga_ls7e_ard_3-1-0_089077_2020-08-28_final
2020-08-29 08:38:46	ga_ls7e_ard_3-1-0_089078_2020-08-28_final
2020-08-29 08:39:09	ga_ls7e_ard_3-1-0_089079_2020-08-28_final
2020-08-29 08:39:33	ga_ls7e_ard_3-1-0_089080_2020-08-28_final
2020-08-29 08:39:57	ga_ls7e_ard_3-1-0_089081_2020-08-28_final
2020-08-29 08:40:21	ga_ls7e_ard_3-1-0_089082_2020-08-28_final
2020-08-29 08:40:45	ga_ls7e_ard_3-1-0_089083_2020-08-28_final
2020-08-29 08:41:09	ga_ls7e_ard_3-1-0_089084_2020-08-28_final
2020-08-29 08:41:33	ga_ls7e_ard_3-1-0_089085_2020-08-28_final
2020-08-29 08:41:57	ga_ls7e_ard_3-1-0_089086_2020-08-28_final
2020-08-30 09:17:34	ga_ls7e_ard_3-1-0_096067_2020-08-29_final
2020-08-30 09:19:34	ga_ls7e_ard_3-1-0_096072_2020-08-29_final
2020-08-30 09:19:57	ga_ls7e_ard_3-1-0_096073_2020-08-29_final
2020-08-30 09:20:21	ga_ls7e_ard_3-1-0_096074_2020-08-29_final
2020-08-30 09:20:45	ga_ls7e_ard_3-1-0_096075_2020-08-29_final
2020-08-30 09:21:09	ga_ls7e_ard_3-1-0_096076_2020-08-29_final
2020-08-30 09:21:33	ga_ls7e_ard_3-1-0_096077_2020-08-29_final
2020-08-30 09:21:57	ga_ls7e_ard_3-1-0_096078_2020-08-29_final
2020-08-30 09:22:21	ga_ls7e_ard_3-1-0_096079_2020-08-29_final
2020-08-30 09:22:45	ga_ls7e_ard_3-1-0_096080_2020-08-29_final
2020-08-30 09:23:09	ga_ls7e_ard_3-1-0_096081_2020-08-29_final
2020-08-30 09:23:33	ga_ls7e_ard_3-1-0_096082_2020-08-29_final
2020-08-30 09:23:57	ga_ls7e_ard_3-1-0_096083_2020-08-29_final
2020-08-30 09:24:21	ga_ls7e_ard_3-1-0_096084_2020-08-29_final
2020-08-30 09:25:09	ga_ls7e_ard_3-1-0_096086_2020-08-29_final
2020-08-31 10:01:09	ga_ls7e_ard_3-1-0_103068_2020-08-31_final
2020-08-31 10:01:33	ga_ls7e_ard_3-1-0_103069_2020-08-31_final
2020-08-31 10:01:57	ga_ls7e_ard_3-1-0_103070_2020-08-31_final
2020-08-31 10:02:21	ga_ls7e_ard_3-1-0_103071_2020-08-31_final
2020-08-31 10:02:45	ga_ls7e_ard_3-1-0_103072_2020-08-31_final
2020-08-31 10:03:09	ga_ls7e_ard_3-1-0_103073_2020-08-31_final
2020-08-31 10:03:33	ga_ls7e_ard_3-1-0_103074_2020-08-31_final
2020-08-31 10:03:57	ga_ls7e_ard_3-1-0_103075_2020-08-31_final
2020-08-31 10:04:21	ga_ls7e_ard_3-1-0_103076_2020-08-31_final
2020-08-31 10:04:45	ga_ls7e_ard_3-1-0_103077_2020-08-31_final
2020-08-31 10:05:09	ga_ls7e_ard_3-1-0_103078_2020-08-31_final
2020-08-31 10:05:33	ga_ls7e_ard_3-1-0_103079_2020-08-31_final
2020-08-31 10:05:57	ga_ls7e_ard_3-1-0_103080_2020-08-31_final
2020-08-31 10:06:21	ga_ls7e_ard_3-1-0_103081_2020-08-31_final

Return to ga_ls7e_ard_3 across August 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

August

All days