Search ga_ls7e_ard_3 across March 2022

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
2022-03-01 08:10:39	ga_ls7e_ard_3-2-1_092075_2022-02-28_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-01 08:11:27	ga_ls7e_ard_3-2-1_092077_2022-02-28_final
2022-03-01 08:11:51	ga_ls7e_ard_3-2-1_092078_2022-02-28_final
2022-03-01 08:12:15	ga_ls7e_ard_3-2-1_092079_2022-02-28_final
2022-03-01 08:12:39	ga_ls7e_ard_3-2-1_092080_2022-02-28_final
2022-03-01 08:13:03	ga_ls7e_ard_3-2-1_092081_2022-02-28_final
2022-03-01 08:13:27	ga_ls7e_ard_3-2-1_092082_2022-02-28_final
2022-03-01 08:13:51	ga_ls7e_ard_3-2-1_092083_2022-02-28_final
2022-03-01 08:14:39	ga_ls7e_ard_3-2-1_092085_2022-02-28_final
2022-03-01 08:15:03	ga_ls7e_ard_3-2-1_092086_2022-02-28_final
2022-03-01 08:16:15	ga_ls7e_ard_3-2-1_092089_2022-02-28_final
2022-03-01 09:48:20	ga_ls7e_ard_3-2-1_108072_2022-03-01_final
2022-03-01 09:49:32	ga_ls7e_ard_3-2-1_108075_2022-03-01_final
2022-03-01 09:49:56	ga_ls7e_ard_3-2-1_108076_2022-03-01_final
2022-03-01 09:50:20	ga_ls7e_ard_3-2-1_108077_2022-03-01_final
2022-03-01 09:50:44	ga_ls7e_ard_3-2-1_108078_2022-03-01_final
2022-03-01 09:51:08	ga_ls7e_ard_3-2-1_108079_2022-03-01_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-01 09:51:56	ga_ls7e_ard_3-2-1_108081_2022-03-01_final
2022-03-01 09:52:20	ga_ls7e_ard_3-2-1_108082_2022-03-01_final
2022-03-01 09:52:43	ga_ls7e_ard_3-2-1_108083_2022-03-01_final
2022-03-01 09:53:07	ga_ls7e_ard_3-2-1_108084_2022-03-01_final
2022-03-02 08:50:38	ga_ls7e_ard_3-2-1_099067_2022-03-01_final
2022-03-02 08:51:01	ga_ls7e_ard_3-2-1_099068_2022-03-01_final
2022-03-02 08:51:25	ga_ls7e_ard_3-2-1_099069_2022-03-01_final
2022-03-02 08:51:49	ga_ls7e_ard_3-2-1_099070_2022-03-01_final
2022-03-02 08:52:13	ga_ls7e_ard_3-2-1_099071_2022-03-01_final
2022-03-02 08:52:37	ga_ls7e_ard_3-2-1_099072_2022-03-01_final
2022-03-02 08:53:01	ga_ls7e_ard_3-2-1_099073_2022-03-01_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-02 08:54:13	ga_ls7e_ard_3-2-1_099076_2022-03-01_final
2022-03-02 08:54:37	ga_ls7e_ard_3-2-1_099077_2022-03-01_final
2022-03-02 08:55:01	ga_ls7e_ard_3-2-1_099078_2022-03-01_final
2022-03-02 08:55:25	ga_ls7e_ard_3-2-1_099079_2022-03-01_final
2022-03-02 08:55:49	ga_ls7e_ard_3-2-1_099080_2022-03-01_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-02 08:56:37	ga_ls7e_ard_3-2-1_099082_2022-03-01_final
2022-03-02 08:57:01	ga_ls7e_ard_3-2-1_099083_2022-03-01_final
2022-03-02 08:57:24	ga_ls7e_ard_3-2-1_099084_2022-03-01_final
2022-03-02 10:32:18	ga_ls7e_ard_3-2-1_115074_2022-03-02_final
2022-03-02 10:32:42	ga_ls7e_ard_3-2-1_115075_2022-03-02_final
2022-03-02 10:33:06	ga_ls7e_ard_3-2-1_115076_2022-03-02_final
2022-03-02 10:33:30	ga_ls7e_ard_3-2-1_115077_2022-03-02_final
2022-03-02 10:33:53	ga_ls7e_ard_3-2-1_115078_2022-03-02_final
2022-03-02 10:34:17	ga_ls7e_ard_3-2-1_115079_2022-03-02_final
2022-03-02 10:34:41	ga_ls7e_ard_3-2-1_115080_2022-03-02_final
2022-03-03 07:58:06	ga_ls7e_ard_3-2-1_090075_2022-03-02_final
2022-03-03 07:58:30	ga_ls7e_ard_3-2-1_090076_2022-03-02_final
2022-03-03 07:58:54	ga_ls7e_ard_3-2-1_090077_2022-03-02_final
2022-03-03 07:59:18	ga_ls7e_ard_3-2-1_090078_2022-03-02_final
2022-03-03 07:59:42	ga_ls7e_ard_3-2-1_090079_2022-03-02_final
2022-03-03 08:00:06	ga_ls7e_ard_3-2-1_090080_2022-03-02_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-03 08:00:54	ga_ls7e_ard_3-2-1_090082_2022-03-02_final
2022-03-03 08:01:18	ga_ls7e_ard_3-2-1_090083_2022-03-02_final
2022-03-03 08:01:42	ga_ls7e_ard_3-2-1_090084_2022-03-02_final
2022-03-03 08:02:06	ga_ls7e_ard_3-2-1_090085_2022-03-02_final
2022-03-03 08:03:17	ga_ls7e_ard_3-2-1_090088_2022-03-02_final
2022-03-03 08:03:41	ga_ls7e_ard_3-2-1_090089_2022-03-02_final
2022-03-03 08:04:05	ga_ls7e_ard_3-2-1_090090_2022-03-02_final
2022-03-03 09:34:11	ga_ls7e_ard_3-2-1_106068_2022-03-03_final
2022-03-03 09:34:35	ga_ls7e_ard_3-2-1_106069_2022-03-03_final
2022-03-03 09:34:59	ga_ls7e_ard_3-2-1_106070_2022-03-03_final
2022-03-03 09:35:23	ga_ls7e_ard_3-2-1_106071_2022-03-03_final
2022-03-03 09:35:47	ga_ls7e_ard_3-2-1_106072_2022-03-03_final
2022-03-03 09:36:11	ga_ls7e_ard_3-2-1_106073_2022-03-03_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-03 09:36:59	ga_ls7e_ard_3-2-1_106075_2022-03-03_final
2022-03-03 09:37:23	ga_ls7e_ard_3-2-1_106076_2022-03-03_final
2022-03-03 09:37:47	ga_ls7e_ard_3-2-1_106077_2022-03-03_final
2022-03-03 09:38:10	ga_ls7e_ard_3-2-1_106078_2022-03-03_final
2022-03-03 09:39:46	ga_ls7e_ard_3-2-1_106082_2022-03-03_final
2022-03-03 09:40:10	ga_ls7e_ard_3-2-1_106083_2022-03-03_final
2022-03-06 10:04:47	ga_ls7e_ard_3-2-1_111068_2022-03-06_final
2022-03-06 10:05:11	ga_ls7e_ard_3-2-1_111069_2022-03-06_final
2022-03-06 10:05:35	ga_ls7e_ard_3-2-1_111070_2022-03-06_final
2022-03-06 10:05:59	ga_ls7e_ard_3-2-1_111071_2022-03-06_final
2022-03-06 10:06:23	ga_ls7e_ard_3-2-1_111072_2022-03-06_final
2022-03-06 10:06:47	ga_ls7e_ard_3-2-1_111073_2022-03-06_final
2022-03-06 10:07:11	ga_ls7e_ard_3-2-1_111074_2022-03-06_final
2022-03-06 10:07:35	ga_ls7e_ard_3-2-1_111075_2022-03-06_final
2022-03-06 10:07:59	ga_ls7e_ard_3-2-1_111076_2022-03-06_final
2022-03-06 10:08:47	ga_ls7e_ard_3-2-1_111078_2022-03-06_final
2022-03-06 10:09:35	ga_ls7e_ard_3-2-1_111080_2022-03-06_final
2022-03-06 10:09:59	ga_ls7e_ard_3-2-1_111081_2022-03-06_final
2022-03-06 10:10:23	ga_ls7e_ard_3-2-1_111082_2022-03-06_final
2022-03-06 10:10:47	ga_ls7e_ard_3-2-1_111083_2022-03-06_final
2022-03-06 10:11:10	ga_ls7e_ard_3-2-1_111084_2022-03-06_final
2022-03-07 09:09:04	ga_ls7e_ard_3-2-1_102068_2022-03-06_final
2022-03-07 09:09:28	ga_ls7e_ard_3-2-1_102069_2022-03-06_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-07 09:11:28	ga_ls7e_ard_3-2-1_102074_2022-03-06_final
2022-03-07 09:11:52	ga_ls7e_ard_3-2-1_102075_2022-03-06_final
2022-03-07 09:12:40	ga_ls7e_ard_3-2-1_102077_2022-03-06_final
2022-03-07 09:13:04	ga_ls7e_ard_3-2-1_102078_2022-03-06_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-07 09:13:52	ga_ls7e_ard_3-2-1_102080_2022-03-06_final
2022-03-07 09:14:16	ga_ls7e_ard_3-2-1_102081_2022-03-06_final

Return to ga_ls7e_ard_3 across March 2022 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

2022

March

All days