Search ga_ls7e_ard_3 across February 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
2018-02-19 10:10:37	ga_ls7e_ard_3-0-0_099067_2018-02-19_final
2018-02-19 10:11:00	ga_ls7e_ard_3-0-0_099068_2018-02-19_final
2018-02-19 10:11:24	ga_ls7e_ard_3-0-0_099069_2018-02-19_final
2018-02-19 10:11:48	ga_ls7e_ard_3-0-0_099070_2018-02-19_final
2018-02-19 10:12:12	ga_ls7e_ard_3-0-0_099071_2018-02-19_final
2018-02-19 10:12:36	ga_ls7e_ard_3-0-0_099072_2018-02-19_final
2018-02-20 09:20:10	ga_ls7e_ard_3-0-0_090080_2018-02-19_final
2018-02-20 09:20:34	ga_ls7e_ard_3-0-0_090081_2018-02-19_final
2018-02-20 09:21:46	ga_ls7e_ard_3-0-0_090084_2018-02-19_final
2018-02-20 09:22:10	ga_ls7e_ard_3-1-0_090085_2018-02-19_final
2018-02-20 09:23:21	ga_ls7e_ard_3-0-0_090088_2018-02-19_final
2018-02-20 09:23:45	ga_ls7e_ard_3-0-0_090089_2018-02-19_final
2018-02-20 09:24:09	ga_ls7e_ard_3-0-0_090090_2018-02-19_final
2018-02-21 09:59:02	ga_ls7e_ard_3-0-0_097069_2018-02-21_final
2018-02-21 09:59:25	ga_ls7e_ard_3-0-0_097070_2018-02-21_final
2018-02-21 09:59:49	ga_ls7e_ard_3-0-0_097071_2018-02-21_final
2018-02-21 10:00:13	ga_ls7e_ard_3-0-0_097072_2018-02-21_final
2018-02-21 10:00:37	ga_ls7e_ard_3-0-0_097073_2018-02-21_final
2018-02-21 10:01:01	ga_ls7e_ard_3-0-0_097074_2018-02-21_final
2018-02-21 10:01:25	ga_ls7e_ard_3-0-0_097075_2018-02-21_final
2018-02-21 10:01:49	ga_ls7e_ard_3-1-0_097076_2018-02-21_final
2018-02-21 10:02:13	ga_ls7e_ard_3-0-0_097077_2018-02-21_final
2018-02-21 10:02:37	ga_ls7e_ard_3-0-0_097078_2018-02-21_final
2018-02-21 10:03:01	ga_ls7e_ard_3-0-0_097079_2018-02-21_final
2018-02-21 10:03:25	ga_ls7e_ard_3-0-0_097080_2018-02-21_final
2018-02-21 10:03:49	ga_ls7e_ard_3-0-0_097081_2018-02-21_final
2018-02-21 10:04:13	ga_ls7e_ard_3-0-0_097082_2018-02-21_final
2018-02-23 09:47:50	ga_ls7e_ard_3-0-0_095072_2018-02-23_final
2018-02-23 09:48:14	ga_ls7e_ard_3-1-0_095073_2018-02-23_final
2018-02-23 09:49:26	ga_ls7e_ard_3-0-0_095076_2018-02-23_final
2018-02-23 09:49:50	ga_ls7e_ard_3-0-0_095077_2018-02-23_final
2018-02-23 09:50:14	ga_ls7e_ard_3-0-0_095078_2018-02-23_final
2018-02-23 09:50:38	ga_ls7e_ard_3-1-0_095079_2018-02-23_final
2018-02-23 09:51:02	ga_ls7e_ard_3-0-0_095080_2018-02-23_final
2018-02-23 09:51:26	ga_ls7e_ard_3-0-0_095081_2018-02-23_final
2018-02-23 09:51:50	ga_ls7e_ard_3-0-0_095082_2018-02-23_final
2018-02-23 09:52:14	ga_ls7e_ard_3-0-0_095083_2018-02-23_final
2018-02-23 09:52:38	ga_ls7e_ard_3-0-0_095084_2018-02-23_final
2018-02-23 09:53:02	ga_ls7e_ard_3-0-0_095085_2018-02-23_final
2018-02-23 09:53:26	ga_ls7e_ard_3-0-0_095086_2018-02-23_final
2018-02-23 11:24:44	ga_ls7e_ard_3-0-0_111067_2018-02-23_final
2018-02-23 11:25:08	ga_ls7e_ard_3-0-0_111068_2018-02-23_final
2018-02-23 11:26:43	ga_ls7e_ard_3-0-0_111072_2018-02-23_final
2018-02-23 11:27:07	ga_ls7e_ard_3-0-0_111073_2018-02-23_final
2018-02-23 11:27:31	ga_ls7e_ard_3-0-0_111074_2018-02-23_final
2018-02-23 11:27:55	ga_ls7e_ard_3-0-0_111075_2018-02-23_final
2018-02-23 11:28:19	ga_ls7e_ard_3-0-0_111076_2018-02-23_final
2018-02-23 11:28:43	ga_ls7e_ard_3-0-0_111077_2018-02-23_final
2018-02-23 11:29:07	ga_ls7e_ard_3-0-0_111078_2018-02-23_final
2018-02-23 11:29:31	ga_ls7e_ard_3-0-0_111079_2018-02-23_final
2018-02-23 11:29:55	ga_ls7e_ard_3-0-0_111080_2018-02-23_final
2018-02-23 11:30:19	ga_ls7e_ard_3-0-0_111081_2018-02-23_final
2018-02-23 11:30:43	ga_ls7e_ard_3-1-0_111082_2018-02-23_final
2018-02-24 10:29:30	ga_ls7e_ard_3-0-0_102068_2018-02-24_final
2018-02-24 10:29:54	ga_ls7e_ard_3-0-0_102069_2018-02-24_final
2018-02-24 10:30:18	ga_ls7e_ard_3-0-0_102070_2018-02-24_final
2018-02-24 10:31:29	ga_ls7e_ard_3-1-0_102073_2018-02-24_final
2018-02-24 10:31:53	ga_ls7e_ard_3-0-0_102074_2018-02-24_final
2018-02-24 10:32:17	ga_ls7e_ard_3-0-0_102075_2018-02-24_final
2018-02-24 10:32:41	ga_ls7e_ard_3-0-0_102076_2018-02-24_final
2018-02-24 10:33:05	ga_ls7e_ard_3-0-0_102077_2018-02-24_final
2018-02-24 10:33:29	ga_ls7e_ard_3-0-0_102078_2018-02-24_final
2018-02-24 10:33:53	ga_ls7e_ard_3-0-0_102079_2018-02-24_final
2018-02-24 10:34:17	ga_ls7e_ard_3-0-0_102080_2018-02-24_final
2018-02-24 10:34:41	ga_ls7e_ard_3-0-0_102081_2018-02-24_final
2018-02-25 09:36:15	ga_ls7e_ard_3-0-0_093074_2018-02-25_final
2018-02-25 09:37:51	ga_ls7e_ard_3-0-0_093078_2018-02-25_final
2018-02-25 09:38:15	ga_ls7e_ard_3-0-0_093079_2018-02-25_final
2018-02-25 09:38:39	ga_ls7e_ard_3-0-0_093080_2018-02-25_final
2018-02-25 09:39:03	ga_ls7e_ard_3-0-0_093081_2018-02-25_final
2018-02-25 09:39:27	ga_ls7e_ard_3-0-0_093082_2018-02-25_final
2018-02-25 09:39:51	ga_ls7e_ard_3-1-0_093083_2018-02-25_final
2018-02-25 09:40:15	ga_ls7e_ard_3-0-0_093084_2018-02-25_final
2018-02-25 09:40:39	ga_ls7e_ard_3-0-0_093085_2018-02-25_final
2018-02-25 09:41:03	ga_ls7e_ard_3-0-0_093086_2018-02-25_final
2018-02-25 11:13:33	ga_ls7e_ard_3-0-0_109070_2018-02-25_final
2018-02-25 11:13:57	ga_ls7e_ard_3-0-0_109071_2018-02-25_final
2018-02-25 11:14:21	ga_ls7e_ard_3-0-0_109072_2018-02-25_final
2018-02-25 11:14:45	ga_ls7e_ard_3-0-0_109073_2018-02-25_final
2018-02-25 11:15:08	ga_ls7e_ard_3-0-0_109074_2018-02-25_final
2018-02-25 11:15:32	ga_ls7e_ard_3-0-0_109075_2018-02-25_final
2018-02-25 11:15:56	ga_ls7e_ard_3-0-0_109076_2018-02-25_final
2018-02-25 11:16:20	ga_ls7e_ard_3-0-0_109077_2018-02-25_final
2018-02-25 11:16:44	ga_ls7e_ard_3-0-0_109078_2018-02-25_final
2018-02-25 11:18:20	ga_ls7e_ard_3-0-0_109082_2018-02-25_final
2018-02-25 11:18:44	ga_ls7e_ard_3-0-0_109083_2018-02-25_final
2018-02-26 10:18:19	ga_ls7e_ard_3-0-0_100071_2018-02-26_final
2018-02-26 10:18:43	ga_ls7e_ard_3-0-0_100072_2018-02-26_final
2018-02-26 10:19:07	ga_ls7e_ard_3-0-0_100073_2018-02-26_final
2018-02-26 10:19:30	ga_ls7e_ard_3-0-0_100074_2018-02-26_final
2018-02-26 10:19:54	ga_ls7e_ard_3-0-0_100075_2018-02-26_final
2018-02-26 10:20:18	ga_ls7e_ard_3-0-0_100076_2018-02-26_final
2018-02-26 10:20:42	ga_ls7e_ard_3-0-0_100077_2018-02-26_final
2018-02-26 10:21:06	ga_ls7e_ard_3-0-0_100078_2018-02-26_final
2018-02-26 10:21:30	ga_ls7e_ard_3-0-0_100079_2018-02-26_final
2018-02-26 10:21:54	ga_ls7e_ard_3-0-0_100080_2018-02-26_final
2018-02-26 10:22:18	ga_ls7e_ard_3-0-0_100081_2018-02-26_final
2018-02-26 10:22:42	ga_ls7e_ard_3-0-0_100082_2018-02-26_final
2018-02-26 10:23:06	ga_ls7e_ard_3-0-0_100083_2018-02-26_final
2018-02-26 10:23:30	ga_ls7e_ard_3-0-0_100084_2018-02-26_final

Return to ga_ls7e_ard_3 across February 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

February

All days