Search ga_ls7e_ard_3 across November 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
2020-11-05 09:45:41	ga_ls7e_ard_3-1-0_101071_2020-11-05_final
2020-11-05 09:46:05	ga_ls7e_ard_3-1-0_101072_2020-11-05_final
2020-11-05 09:46:28	ga_ls7e_ard_3-1-0_101073_2020-11-05_final
2020-11-05 09:46:52	ga_ls7e_ard_3-1-0_101074_2020-11-05_final
2020-11-05 09:47:16	ga_ls7e_ard_3-1-0_101075_2020-11-05_final
2020-11-05 09:47:40	ga_ls7e_ard_3-1-0_101076_2020-11-05_final
2020-11-05 09:48:04	ga_ls7e_ard_3-1-0_101077_2020-11-05_final
2020-11-05 09:48:28	ga_ls7e_ard_3-1-0_101078_2020-11-05_final
2020-11-05 09:48:52	ga_ls7e_ard_3-1-0_101079_2020-11-05_final
2020-11-05 09:49:16	ga_ls7e_ard_3-1-0_101080_2020-11-05_final
2020-11-05 09:49:40	ga_ls7e_ard_3-1-0_101081_2020-11-05_final
2020-11-05 09:50:04	ga_ls7e_ard_3-1-0_101082_2020-11-05_final
2020-11-05 09:50:28	ga_ls7e_ard_3-1-0_101083_2020-11-05_final
2020-11-06 08:51:35	ga_ls7e_ard_3-1-0_092075_2020-11-05_final
2020-11-06 08:51:59	ga_ls7e_ard_3-1-0_092076_2020-11-05_final
2020-11-06 08:52:23	ga_ls7e_ard_3-1-0_092077_2020-11-05_final
2020-11-06 08:52:47	ga_ls7e_ard_3-1-0_092078_2020-11-05_final
2020-11-06 08:53:11	ga_ls7e_ard_3-1-0_092079_2020-11-05_final
2020-11-06 08:53:35	ga_ls7e_ard_3-1-0_092080_2020-11-05_final
2020-11-06 08:53:59	ga_ls7e_ard_3-1-0_092081_2020-11-05_final
2020-11-06 08:54:23	ga_ls7e_ard_3-1-0_092082_2020-11-05_final
2020-11-06 08:54:47	ga_ls7e_ard_3-1-0_092083_2020-11-05_final
2020-11-06 08:55:11	ga_ls7e_ard_3-1-0_092084_2020-11-05_final
2020-11-06 08:55:35	ga_ls7e_ard_3-1-0_092085_2020-11-05_final
2020-11-06 08:56:22	ga_ls7e_ard_3-1-0_092087_2020-11-05_final
2020-11-06 08:56:46	ga_ls7e_ard_3-1-0_092088_2020-11-05_final
2020-11-06 10:28:04	ga_ls7e_ard_3-1-0_108069_2020-11-06_final
2020-11-06 10:28:28	ga_ls7e_ard_3-1-0_108070_2020-11-06_final
2020-11-06 10:28:52	ga_ls7e_ard_3-1-0_108071_2020-11-06_final
2020-11-06 10:29:16	ga_ls7e_ard_3-1-0_108072_2020-11-06_final
2020-11-06 10:29:40	ga_ls7e_ard_3-1-0_108073_2020-11-06_final
2020-11-06 10:30:04	ga_ls7e_ard_3-1-0_108074_2020-11-06_final
2020-11-06 10:31:16	ga_ls7e_ard_3-1-0_108077_2020-11-06_final
2020-11-06 10:31:40	ga_ls7e_ard_3-1-0_108078_2020-11-06_final
2020-11-06 10:32:04	ga_ls7e_ard_3-1-0_108079_2020-11-06_final
2020-11-06 10:32:28	ga_ls7e_ard_3-1-0_108080_2020-11-06_final
2020-11-06 10:32:51	ga_ls7e_ard_3-1-0_108081_2020-11-06_final
2020-11-06 10:33:15	ga_ls7e_ard_3-1-0_108082_2020-11-06_final
2020-11-06 10:33:39	ga_ls7e_ard_3-1-0_108083_2020-11-06_final
2020-11-06 10:34:03	ga_ls7e_ard_3-1-0_108084_2020-11-06_final
2020-11-07 09:31:35	ga_ls7e_ard_3-1-0_099067_2020-11-07_final
2020-11-07 09:31:59	ga_ls7e_ard_3-1-0_099068_2020-11-07_final
2020-11-07 09:32:23	ga_ls7e_ard_3-1-0_099069_2020-11-07_final
2020-11-07 09:32:47	ga_ls7e_ard_3-1-0_099070_2020-11-07_final
2020-11-07 09:33:11	ga_ls7e_ard_3-1-0_099071_2020-11-07_final
2020-11-07 09:33:35	ga_ls7e_ard_3-1-0_099072_2020-11-07_final
2020-11-07 09:33:59	ga_ls7e_ard_3-1-0_099073_2020-11-07_final
2020-11-07 09:34:23	ga_ls7e_ard_3-1-0_099074_2020-11-07_final
2020-11-07 09:34:47	ga_ls7e_ard_3-1-0_099075_2020-11-07_final
2020-11-07 09:35:10	ga_ls7e_ard_3-1-0_099076_2020-11-07_final
2020-11-07 09:35:34	ga_ls7e_ard_3-1-0_099077_2020-11-07_final
2020-11-07 09:35:58	ga_ls7e_ard_3-1-0_099078_2020-11-07_final
2020-11-07 09:36:22	ga_ls7e_ard_3-1-0_099079_2020-11-07_final
2020-11-07 09:36:46	ga_ls7e_ard_3-1-0_099080_2020-11-07_final
2020-11-07 09:37:10	ga_ls7e_ard_3-1-0_099081_2020-11-07_final
2020-11-07 09:37:34	ga_ls7e_ard_3-1-0_099082_2020-11-07_final
2020-11-07 09:37:58	ga_ls7e_ard_3-1-0_099083_2020-11-07_final
2020-11-07 11:13:15	ga_ls7e_ard_3-1-0_115074_2020-11-07_final
2020-11-07 11:13:39	ga_ls7e_ard_3-1-0_115075_2020-11-07_final
2020-11-07 11:14:03	ga_ls7e_ard_3-1-0_115076_2020-11-07_final
2020-11-07 11:14:27	ga_ls7e_ard_3-1-0_115077_2020-11-07_final
2020-11-07 11:14:51	ga_ls7e_ard_3-1-0_115078_2020-11-07_final
2020-11-07 11:15:15	ga_ls7e_ard_3-1-0_115079_2020-11-07_final
2020-11-08 08:39:53	ga_ls7e_ard_3-1-0_090077_2020-11-07_final
2020-11-08 08:41:05	ga_ls7e_ard_3-1-0_090080_2020-11-07_final
2020-11-08 08:41:29	ga_ls7e_ard_3-1-0_090081_2020-11-07_final
2020-11-08 08:41:53	ga_ls7e_ard_3-1-0_090082_2020-11-07_final
2020-11-08 08:42:17	ga_ls7e_ard_3-1-0_090083_2020-11-07_final
2020-11-08 08:42:41	ga_ls7e_ard_3-1-0_090084_2020-11-07_final
2020-11-08 08:43:05	ga_ls7e_ard_3-1-0_090085_2020-11-07_final
2020-11-08 08:43:29	ga_ls7e_ard_3-1-0_090086_2020-11-07_final
2020-11-08 08:44:17	ga_ls7e_ard_3-1-0_090088_2020-11-07_final
2020-11-08 08:44:41	ga_ls7e_ard_3-1-0_090089_2020-11-07_final
2020-11-08 08:45:05	ga_ls7e_ard_3-1-0_090090_2020-11-07_final
2020-11-08 10:15:10	ga_ls7e_ard_3-1-0_106068_2020-11-08_final
2020-11-08 10:15:34	ga_ls7e_ard_3-1-0_106069_2020-11-08_final
2020-11-08 10:15:58	ga_ls7e_ard_3-1-0_106070_2020-11-08_final
2020-11-08 10:16:22	ga_ls7e_ard_3-1-0_106071_2020-11-08_final
2020-11-08 10:16:46	ga_ls7e_ard_3-1-0_106072_2020-11-08_final
2020-11-08 10:17:10	ga_ls7e_ard_3-1-0_106073_2020-11-08_final
2020-11-08 10:17:34	ga_ls7e_ard_3-1-0_106074_2020-11-08_final
2020-11-08 10:17:58	ga_ls7e_ard_3-1-0_106075_2020-11-08_final
2020-11-08 10:18:22	ga_ls7e_ard_3-1-0_106076_2020-11-08_final
2020-11-08 10:18:46	ga_ls7e_ard_3-1-0_106077_2020-11-08_final
2020-11-08 10:19:10	ga_ls7e_ard_3-1-0_106078_2020-11-08_final
2020-11-08 10:19:34	ga_ls7e_ard_3-1-0_106079_2020-11-08_final
2020-11-08 10:19:58	ga_ls7e_ard_3-1-0_106080_2020-11-08_final
2020-11-08 10:20:22	ga_ls7e_ard_3-1-0_106081_2020-11-08_final
2020-11-08 10:20:46	ga_ls7e_ard_3-1-0_106082_2020-11-08_final
2020-11-08 10:21:10	ga_ls7e_ard_3-1-0_106083_2020-11-08_final
2020-11-09 09:20:41	ga_ls7e_ard_3-1-0_097071_2020-11-08_final
2020-11-09 09:21:05	ga_ls7e_ard_3-1-0_097072_2020-11-08_final
2020-11-09 09:21:29	ga_ls7e_ard_3-1-0_097073_2020-11-08_final
2020-11-09 09:21:53	ga_ls7e_ard_3-1-0_097074_2020-11-08_final
2020-11-09 09:22:17	ga_ls7e_ard_3-1-0_097075_2020-11-08_final
2020-11-09 09:22:41	ga_ls7e_ard_3-1-0_097076_2020-11-08_final
2020-11-09 09:23:05	ga_ls7e_ard_3-1-0_097077_2020-11-08_final
2020-11-09 09:23:29	ga_ls7e_ard_3-1-0_097078_2020-11-08_final
2020-11-09 09:23:53	ga_ls7e_ard_3-1-0_097079_2020-11-08_final
2020-11-09 09:24:16	ga_ls7e_ard_3-1-0_097080_2020-11-08_final

Return to ga_ls7e_ard_3 across November 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

November

All days