Search ga_ls7e_ard_3 across March 2018

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
2018-03-17 09:12:54	ga_ls7e_ard_3-0-0_089078_2018-03-16_final
2018-03-17 09:13:18	ga_ls7e_ard_3-0-0_089079_2018-03-16_final
2018-03-17 09:13:42	ga_ls7e_ard_3-0-0_089080_2018-03-16_final
2018-03-17 09:14:06	ga_ls7e_ard_3-1-0_089081_2018-03-16_final
2018-03-17 09:14:30	ga_ls7e_ard_3-0-0_089082_2018-03-16_final
2018-03-17 09:14:54	ga_ls7e_ard_3-0-0_089083_2018-03-16_final
2018-03-17 09:15:17	ga_ls7e_ard_3-0-0_089084_2018-03-16_final
2018-03-17 09:15:41	ga_ls7e_ard_3-0-0_089085_2018-03-16_final
2018-03-17 09:16:05	ga_ls7e_ard_3-0-0_089086_2018-03-16_final
2018-03-18 09:53:21	ga_ls7e_ard_3-0-0_096071_2018-03-18_final
2018-03-18 09:53:45	ga_ls7e_ard_3-0-0_096072_2018-03-18_final
2018-03-18 09:54:09	ga_ls7e_ard_3-0-0_096073_2018-03-18_final
2018-03-18 09:54:33	ga_ls7e_ard_3-0-0_096074_2018-03-18_final
2018-03-18 09:54:57	ga_ls7e_ard_3-0-0_096075_2018-03-18_final
2018-03-18 09:55:21	ga_ls7e_ard_3-0-0_096076_2018-03-18_final
2018-03-18 09:55:45	ga_ls7e_ard_3-0-0_096077_2018-03-18_final
2018-03-18 09:56:09	ga_ls7e_ard_3-0-0_096078_2018-03-18_final
2018-03-18 09:56:33	ga_ls7e_ard_3-0-0_096079_2018-03-18_final
2018-03-28 10:29:06	ga_ls7e_ard_3-0-0_102068_2018-03-28_final
2018-03-28 10:29:30	ga_ls7e_ard_3-0-0_102069_2018-03-28_final
2018-03-28 10:29:54	ga_ls7e_ard_3-0-0_102070_2018-03-28_final
2018-03-28 10:30:18	ga_ls7e_ard_3-0-0_102071_2018-03-28_final
2018-03-28 10:30:42	ga_ls7e_ard_3-0-0_102072_2018-03-28_final
2018-03-28 10:31:05	ga_ls7e_ard_3-0-0_102073_2018-03-28_final
2018-03-28 10:31:53	ga_ls7e_ard_3-0-0_102075_2018-03-28_final
2018-03-28 10:32:17	ga_ls7e_ard_3-0-0_102076_2018-03-28_final
2018-03-28 10:32:41	ga_ls7e_ard_3-0-0_102077_2018-03-28_final
2018-03-28 10:33:05	ga_ls7e_ard_3-0-0_102078_2018-03-28_final
2018-03-28 10:33:29	ga_ls7e_ard_3-0-0_102079_2018-03-28_final
2018-03-28 10:33:53	ga_ls7e_ard_3-0-0_102080_2018-03-28_final
2018-03-28 10:34:17	ga_ls7e_ard_3-0-0_102081_2018-03-28_final
2018-03-28 10:34:41	ga_ls7e_ard_3-0-0_102082_2018-03-28_final
2018-03-29 09:35:51	ga_ls7e_ard_3-0-0_093074_2018-03-29_final
2018-03-29 09:36:15	ga_ls7e_ard_3-0-0_093075_2018-03-29_final
2018-03-29 09:36:39	ga_ls7e_ard_3-0-0_093076_2018-03-29_final
2018-03-29 09:37:03	ga_ls7e_ard_3-0-0_093077_2018-03-29_final
2018-03-29 09:37:27	ga_ls7e_ard_3-0-0_093078_2018-03-29_final
2018-03-29 09:37:51	ga_ls7e_ard_3-0-0_093079_2018-03-29_final
2018-03-29 09:38:15	ga_ls7e_ard_3-0-0_093080_2018-03-29_final
2018-03-29 09:38:39	ga_ls7e_ard_3-0-0_093081_2018-03-29_final
2018-03-29 09:39:03	ga_ls7e_ard_3-0-0_093082_2018-03-29_final
2018-03-29 09:39:27	ga_ls7e_ard_3-0-0_093083_2018-03-29_final
2018-03-29 09:39:51	ga_ls7e_ard_3-0-0_093084_2018-03-29_final
2018-03-29 09:40:15	ga_ls7e_ard_3-0-0_093085_2018-03-29_final
2018-03-29 09:40:39	ga_ls7e_ard_3-0-0_093086_2018-03-29_final
2018-03-29 09:41:03	ga_ls7e_ard_3-1-0_093087_2018-03-29_final
2018-03-29 11:13:08	ga_ls7e_ard_3-0-0_109070_2018-03-29_final
2018-03-29 11:13:32	ga_ls7e_ard_3-0-0_109071_2018-03-29_final
2018-03-29 11:14:20	ga_ls7e_ard_3-0-0_109073_2018-03-29_final
2018-03-29 11:14:44	ga_ls7e_ard_3-0-0_109074_2018-03-29_final
2018-03-29 11:15:08	ga_ls7e_ard_3-0-0_109075_2018-03-29_final
2018-03-29 11:15:32	ga_ls7e_ard_3-0-0_109076_2018-03-29_final
2018-03-29 11:15:56	ga_ls7e_ard_3-0-0_109077_2018-03-29_final
2018-03-29 11:16:20	ga_ls7e_ard_3-0-0_109078_2018-03-29_final
2018-03-29 11:16:44	ga_ls7e_ard_3-0-0_109079_2018-03-29_final
2018-03-29 11:17:08	ga_ls7e_ard_3-0-0_109080_2018-03-29_final
2018-03-29 11:17:32	ga_ls7e_ard_3-1-0_109081_2018-03-29_final
2018-03-29 11:17:56	ga_ls7e_ard_3-0-0_109082_2018-03-29_final
2018-03-29 11:18:20	ga_ls7e_ard_3-0-0_109083_2018-03-29_final
2018-03-30 10:17:54	ga_ls7e_ard_3-0-0_100071_2018-03-30_final
2018-03-30 10:18:18	ga_ls7e_ard_3-0-0_100072_2018-03-30_final
2018-03-30 10:18:42	ga_ls7e_ard_3-0-0_100073_2018-03-30_final
2018-03-30 10:19:06	ga_ls7e_ard_3-0-0_100074_2018-03-30_final
2018-03-30 10:19:30	ga_ls7e_ard_3-0-0_100075_2018-03-30_final
2018-03-30 10:19:54	ga_ls7e_ard_3-0-0_100076_2018-03-30_final
2018-03-30 10:20:18	ga_ls7e_ard_3-0-0_100077_2018-03-30_final
2018-03-30 10:20:42	ga_ls7e_ard_3-0-0_100078_2018-03-30_final
2018-03-30 10:21:06	ga_ls7e_ard_3-0-0_100079_2018-03-30_final
2018-03-30 10:21:30	ga_ls7e_ard_3-0-0_100080_2018-03-30_final
2018-03-30 10:21:54	ga_ls7e_ard_3-0-0_100081_2018-03-30_final
2018-03-30 10:22:18	ga_ls7e_ard_3-0-0_100082_2018-03-30_final
2018-03-30 10:22:42	ga_ls7e_ard_3-0-0_100083_2018-03-30_final
2018-03-30 10:23:05	ga_ls7e_ard_3-0-0_100084_2018-03-30_final
2018-03-31 09:24:16	ga_ls7e_ard_3-0-0_091076_2018-03-30_final
2018-03-31 09:24:40	ga_ls7e_ard_3-0-0_091077_2018-03-30_final
2018-03-31 09:25:04	ga_ls7e_ard_3-0-0_091078_2018-03-30_final
2018-03-31 09:25:28	ga_ls7e_ard_3-0-0_091079_2018-03-30_final
2018-03-31 09:25:51	ga_ls7e_ard_3-0-0_091080_2018-03-30_final
2018-03-31 09:26:15	ga_ls7e_ard_3-0-0_091081_2018-03-30_final
2018-03-31 09:26:39	ga_ls7e_ard_3-0-0_091082_2018-03-30_final
2018-03-31 09:27:03	ga_ls7e_ard_3-0-0_091083_2018-03-30_final
2018-03-31 09:27:27	ga_ls7e_ard_3-0-0_091084_2018-03-30_final
2018-03-31 09:27:51	ga_ls7e_ard_3-0-0_091085_2018-03-30_final
2018-03-31 09:28:15	ga_ls7e_ard_3-1-0_091086_2018-03-30_final
2018-03-31 09:28:39	ga_ls7e_ard_3-0-0_091087_2018-03-30_final
2018-03-31 09:29:03	ga_ls7e_ard_3-0-0_091088_2018-03-30_final
2018-03-31 09:29:27	ga_ls7e_ard_3-0-0_091089_2018-03-30_final
2018-03-31 11:00:45	ga_ls7e_ard_3-0-0_107070_2018-03-31_final
2018-03-31 11:01:09	ga_ls7e_ard_3-0-0_107071_2018-03-31_final
2018-03-31 11:01:33	ga_ls7e_ard_3-0-0_107072_2018-03-31_final
2018-03-31 11:01:57	ga_ls7e_ard_3-0-0_107073_2018-03-31_final
2018-03-31 11:02:21	ga_ls7e_ard_3-0-0_107074_2018-03-31_final
2018-03-31 11:02:45	ga_ls7e_ard_3-0-0_107075_2018-03-31_final
2018-03-31 11:03:09	ga_ls7e_ard_3-0-0_107076_2018-03-31_final
2018-03-31 11:03:33	ga_ls7e_ard_3-0-0_107077_2018-03-31_final
2018-03-31 11:03:57	ga_ls7e_ard_3-0-0_107078_2018-03-31_final
2018-03-31 11:04:20	ga_ls7e_ard_3-0-0_107079_2018-03-31_final
2018-03-31 11:04:44	ga_ls7e_ard_3-0-0_107080_2018-03-31_final
2018-03-31 11:05:32	ga_ls7e_ard_3-0-0_107082_2018-03-31_final
2018-03-31 11:05:56	ga_ls7e_ard_3-0-0_107083_2018-03-31_final

Return to ga_ls7e_ard_3 across March 2018 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2018

March

All days