Search ga_ls7e_ard_3 across September 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:

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First 100 results (query limit)

Time (local)	Label
2020-09-03 08:56:10	ga_ls7e_ard_3-1-0_092076_2020-09-02_final
2020-09-03 08:56:34	ga_ls7e_ard_3-1-0_092077_2020-09-02_final
2020-09-03 08:56:58	ga_ls7e_ard_3-1-0_092078_2020-09-02_final
2020-09-03 08:57:22	ga_ls7e_ard_3-1-0_092079_2020-09-02_final
2020-09-03 08:57:46	ga_ls7e_ard_3-1-0_092080_2020-09-02_final
2020-09-03 08:58:10	ga_ls7e_ard_3-1-0_092081_2020-09-02_final
2020-09-03 08:58:34	ga_ls7e_ard_3-1-0_092082_2020-09-02_final
2020-09-12 08:54:59	ga_ls7e_ard_3-1-0_091090_2020-09-11_final
2020-09-12 10:25:53	ga_ls7e_ard_3-1-0_107070_2020-09-12_final
2020-09-12 10:26:17	ga_ls7e_ard_3-1-0_107071_2020-09-12_final
2020-09-12 10:26:41	ga_ls7e_ard_3-1-0_107072_2020-09-12_final
2020-09-12 10:27:05	ga_ls7e_ard_3-1-0_107073_2020-09-12_final
2020-09-12 10:27:29	ga_ls7e_ard_3-1-0_107074_2020-09-12_final
2020-09-12 10:27:53	ga_ls7e_ard_3-1-0_107075_2020-09-12_final
2020-09-12 10:28:17	ga_ls7e_ard_3-1-0_107076_2020-09-12_final
2020-09-12 10:28:41	ga_ls7e_ard_3-1-0_107077_2020-09-12_final
2020-09-12 10:29:05	ga_ls7e_ard_3-1-0_107078_2020-09-12_final
2020-09-12 10:29:28	ga_ls7e_ard_3-1-0_107079_2020-09-12_final
2020-09-12 10:29:52	ga_ls7e_ard_3-1-0_107080_2020-09-12_final
2020-09-12 10:31:04	ga_ls7e_ard_3-1-0_107083_2020-09-12_final
2020-09-12 10:31:28	ga_ls7e_ard_3-1-0_107084_2020-09-12_final
2020-09-13 09:29:00	ga_ls7e_ard_3-1-0_098067_2020-09-12_final
2020-09-13 09:29:24	ga_ls7e_ard_3-1-0_098068_2020-09-12_final
2020-09-13 09:30:36	ga_ls7e_ard_3-1-0_098071_2020-09-13_final
2020-09-13 09:31:00	ga_ls7e_ard_3-1-0_098072_2020-09-13_final
2020-09-13 09:31:24	ga_ls7e_ard_3-1-0_098073_2020-09-13_final
2020-09-13 09:31:48	ga_ls7e_ard_3-1-0_098074_2020-09-13_final
2020-09-13 09:32:12	ga_ls7e_ard_3-1-0_098075_2020-09-13_final
2020-09-13 09:32:35	ga_ls7e_ard_3-1-0_098076_2020-09-13_final
2020-09-13 09:32:59	ga_ls7e_ard_3-1-0_098077_2020-09-13_final
2020-09-13 09:33:23	ga_ls7e_ard_3-1-0_098078_2020-09-13_final
2020-09-13 09:33:47	ga_ls7e_ard_3-1-0_098079_2020-09-13_final
2020-09-13 09:34:11	ga_ls7e_ard_3-1-0_098080_2020-09-13_final
2020-09-13 09:34:35	ga_ls7e_ard_3-1-0_098081_2020-09-13_final
2020-09-13 09:34:59	ga_ls7e_ard_3-1-0_098082_2020-09-13_final
2020-09-13 09:35:23	ga_ls7e_ard_3-1-0_098083_2020-09-13_final
2020-09-13 09:35:47	ga_ls7e_ard_3-1-0_098084_2020-09-13_final
2020-09-13 09:36:11	ga_ls7e_ard_3-1-0_098085_2020-09-13_final
2020-09-13 11:07:53	ga_ls7e_ard_3-1-0_114067_2020-09-13_final
2020-09-13 11:10:40	ga_ls7e_ard_3-1-0_114074_2020-09-13_final
2020-09-13 11:11:04	ga_ls7e_ard_3-1-0_114075_2020-09-13_final
2020-09-13 11:11:28	ga_ls7e_ard_3-1-0_114076_2020-09-13_final
2020-09-13 11:11:52	ga_ls7e_ard_3-1-0_114077_2020-09-13_final
2020-09-13 11:12:16	ga_ls7e_ard_3-1-0_114078_2020-09-13_final
2020-09-13 11:12:40	ga_ls7e_ard_3-1-0_114079_2020-09-13_final
2020-09-13 11:13:04	ga_ls7e_ard_3-1-0_114080_2020-09-13_final
2020-09-13 11:13:28	ga_ls7e_ard_3-1-0_114081_2020-09-13_final
2020-09-14 08:37:42	ga_ls7e_ard_3-1-0_089078_2020-09-13_final
2020-09-14 08:38:06	ga_ls7e_ard_3-1-0_089079_2020-09-13_final
2020-09-14 08:38:30	ga_ls7e_ard_3-1-0_089080_2020-09-13_final
2020-09-14 08:38:54	ga_ls7e_ard_3-1-0_089081_2020-09-13_final
2020-09-14 08:39:18	ga_ls7e_ard_3-1-0_089082_2020-09-13_final
2020-09-14 08:39:42	ga_ls7e_ard_3-1-0_089083_2020-09-13_final
2020-09-14 08:40:06	ga_ls7e_ard_3-1-0_089084_2020-09-13_final
2020-09-14 08:40:30	ga_ls7e_ard_3-1-0_089085_2020-09-13_final
2020-09-14 08:40:54	ga_ls7e_ard_3-1-0_089086_2020-09-13_final
2020-09-14 10:12:36	ga_ls7e_ard_3-1-0_105068_2020-09-14_final
2020-09-14 10:13:00	ga_ls7e_ard_3-1-0_105069_2020-09-14_final
2020-09-14 10:13:23	ga_ls7e_ard_3-1-0_105070_2020-09-14_final
2020-09-14 10:13:47	ga_ls7e_ard_3-1-0_105071_2020-09-14_final
2020-09-14 10:14:11	ga_ls7e_ard_3-1-0_105072_2020-09-14_final
2020-09-14 10:14:35	ga_ls7e_ard_3-1-0_105073_2020-09-14_final
2020-09-14 10:14:59	ga_ls7e_ard_3-1-0_105074_2020-09-14_final
2020-09-14 10:15:23	ga_ls7e_ard_3-1-0_105075_2020-09-14_final
2020-09-14 10:15:47	ga_ls7e_ard_3-1-0_105076_2020-09-14_final
2020-09-14 10:16:11	ga_ls7e_ard_3-1-0_105077_2020-09-14_final
2020-09-14 10:16:35	ga_ls7e_ard_3-1-0_105078_2020-09-14_final
2020-09-14 10:16:59	ga_ls7e_ard_3-1-0_105079_2020-09-14_final
2020-09-14 10:17:23	ga_ls7e_ard_3-1-0_105080_2020-09-14_final
2020-09-14 10:17:47	ga_ls7e_ard_3-1-0_105081_2020-09-14_final
2020-09-14 10:18:11	ga_ls7e_ard_3-1-0_105082_2020-09-14_final
2020-09-15 09:16:31	ga_ls7e_ard_3-1-0_096067_2020-09-14_final
2020-09-15 09:17:42	ga_ls7e_ard_3-1-0_096070_2020-09-14_final
2020-09-15 09:18:06	ga_ls7e_ard_3-1-0_096071_2020-09-14_final
2020-09-15 09:18:30	ga_ls7e_ard_3-1-0_096072_2020-09-14_final
2020-09-15 09:18:54	ga_ls7e_ard_3-1-0_096073_2020-09-14_final
2020-09-15 09:19:18	ga_ls7e_ard_3-1-0_096074_2020-09-14_final
2020-09-15 09:19:42	ga_ls7e_ard_3-1-0_096075_2020-09-14_final
2020-09-15 09:20:06	ga_ls7e_ard_3-1-0_096076_2020-09-14_final
2020-09-15 09:20:30	ga_ls7e_ard_3-1-0_096077_2020-09-14_final
2020-09-15 09:20:54	ga_ls7e_ard_3-1-0_096078_2020-09-14_final
2020-09-15 09:21:18	ga_ls7e_ard_3-1-0_096079_2020-09-14_final
2020-09-15 09:21:42	ga_ls7e_ard_3-1-0_096080_2020-09-14_final
2020-09-15 09:22:06	ga_ls7e_ard_3-1-0_096081_2020-09-14_final
2020-09-15 09:22:30	ga_ls7e_ard_3-1-0_096082_2020-09-14_final
2020-09-15 09:22:54	ga_ls7e_ard_3-1-0_096083_2020-09-14_final
2020-09-15 09:23:17	ga_ls7e_ard_3-1-0_096084_2020-09-14_final
2020-09-15 09:23:41	ga_ls7e_ard_3-1-0_096085_2020-09-14_final
2020-09-15 09:24:05	ga_ls7e_ard_3-1-0_096086_2020-09-14_final
2020-09-15 10:55:23	ga_ls7e_ard_3-1-0_112067_2020-09-15_final
2020-09-15 10:58:11	ga_ls7e_ard_3-1-0_112074_2020-09-15_final
2020-09-15 10:58:35	ga_ls7e_ard_3-1-0_112075_2020-09-15_final
2020-09-15 10:58:59	ga_ls7e_ard_3-1-0_112076_2020-09-15_final
2020-09-15 10:59:23	ga_ls7e_ard_3-1-0_112077_2020-09-15_final
2020-09-15 10:59:47	ga_ls7e_ard_3-1-0_112078_2020-09-15_final
2020-09-15 11:00:11	ga_ls7e_ard_3-1-0_112079_2020-09-15_final
2020-09-15 11:00:34	ga_ls7e_ard_3-1-0_112080_2020-09-15_final
2020-09-15 11:00:58	ga_ls7e_ard_3-1-0_112081_2020-09-15_final
2020-09-15 11:01:22	ga_ls7e_ard_3-1-0_112082_2020-09-15_final
2020-09-15 11:01:46	ga_ls7e_ard_3-1-0_112083_2020-09-15_final

Return to ga_ls7e_ard_3 across September 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

September

All days