Search ga_ls7e_ard_3 across January 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
2020-01-06 10:03:43	ga_ls7e_ard_3-1-0_101071_2020-01-06_final
2020-01-06 10:04:07	ga_ls7e_ard_3-1-0_101072_2020-01-06_final
2020-01-06 10:04:31	ga_ls7e_ard_3-1-0_101073_2020-01-06_final
2020-01-06 10:04:55	ga_ls7e_ard_3-1-0_101074_2020-01-06_final
2020-01-06 10:05:19	ga_ls7e_ard_3-1-0_101075_2020-01-06_final
2020-01-06 10:05:43	ga_ls7e_ard_3-1-0_101076_2020-01-06_final
2020-01-06 10:06:07	ga_ls7e_ard_3-1-0_101077_2020-01-06_final
2020-01-06 10:06:31	ga_ls7e_ard_3-1-0_101078_2020-01-06_final
2020-01-06 10:06:55	ga_ls7e_ard_3-1-0_101079_2020-01-06_final
2020-01-06 10:07:19	ga_ls7e_ard_3-1-0_101080_2020-01-06_final
2020-01-06 10:07:43	ga_ls7e_ard_3-1-0_101081_2020-01-06_final
2020-01-06 10:08:06	ga_ls7e_ard_3-1-0_101082_2020-01-06_final
2020-01-06 10:08:30	ga_ls7e_ard_3-1-0_101083_2020-01-06_final
2020-01-07 09:09:38	ga_ls7e_ard_3-1-0_092075_2020-01-06_final
2020-01-07 09:10:50	ga_ls7e_ard_3-1-0_092078_2020-01-06_final
2020-01-07 09:11:14	ga_ls7e_ard_3-1-0_092079_2020-01-06_final
2020-01-07 09:11:38	ga_ls7e_ard_3-1-0_092080_2020-01-06_final
2020-01-07 09:12:02	ga_ls7e_ard_3-1-0_092081_2020-01-06_final
2020-01-07 09:12:26	ga_ls7e_ard_3-1-0_092082_2020-01-06_final
2020-01-07 09:12:50	ga_ls7e_ard_3-1-0_092083_2020-01-06_final
2020-01-07 09:13:14	ga_ls7e_ard_3-1-0_092084_2020-01-06_final
2020-01-07 09:13:38	ga_ls7e_ard_3-1-0_092085_2020-01-06_final
2020-01-07 09:14:02	ga_ls7e_ard_3-1-0_092086_2020-01-06_final
2020-01-07 10:46:32	ga_ls7e_ard_3-1-0_108070_2020-01-07_final
2020-01-07 10:49:43	ga_ls7e_ard_3-1-0_108078_2020-01-07_final
2020-01-07 10:50:07	ga_ls7e_ard_3-1-0_108079_2020-01-07_final
2020-01-07 10:50:31	ga_ls7e_ard_3-1-0_108080_2020-01-07_final
2020-01-07 10:50:55	ga_ls7e_ard_3-1-0_108081_2020-01-07_final
2020-01-07 10:51:19	ga_ls7e_ard_3-1-0_108082_2020-01-07_final
2020-01-07 10:51:43	ga_ls7e_ard_3-1-0_108083_2020-01-07_final
2020-01-07 10:52:07	ga_ls7e_ard_3-1-0_108084_2020-01-07_final
2020-01-08 09:50:27	ga_ls7e_ard_3-1-0_099069_2020-01-08_final
2020-01-08 09:50:51	ga_ls7e_ard_3-1-0_099070_2020-01-08_final
2020-01-08 09:51:15	ga_ls7e_ard_3-1-0_099071_2020-01-08_final
2020-01-08 09:51:39	ga_ls7e_ard_3-1-0_099072_2020-01-08_final
2020-01-08 09:52:03	ga_ls7e_ard_3-1-0_099073_2020-01-08_final
2020-01-08 09:52:27	ga_ls7e_ard_3-1-0_099074_2020-01-08_final
2020-01-08 09:52:51	ga_ls7e_ard_3-1-0_099075_2020-01-08_final
2020-01-08 09:53:15	ga_ls7e_ard_3-1-0_099076_2020-01-08_final
2020-01-08 09:53:39	ga_ls7e_ard_3-1-0_099077_2020-01-08_final
2020-01-08 09:54:03	ga_ls7e_ard_3-1-0_099078_2020-01-08_final
2020-01-08 09:54:27	ga_ls7e_ard_3-1-0_099079_2020-01-08_final
2020-01-08 09:54:51	ga_ls7e_ard_3-1-0_099080_2020-01-08_final
2020-01-08 09:55:15	ga_ls7e_ard_3-1-0_099081_2020-01-08_final
2020-01-08 09:55:39	ga_ls7e_ard_3-1-0_099082_2020-01-08_final
2020-01-08 09:56:03	ga_ls7e_ard_3-1-0_099083_2020-01-08_final
2020-01-08 09:56:26	ga_ls7e_ard_3-1-0_099084_2020-01-08_final
2020-01-08 11:31:20	ga_ls7e_ard_3-1-0_115074_2020-01-08_final
2020-01-08 11:31:44	ga_ls7e_ard_3-1-0_115075_2020-01-08_final
2020-01-08 11:32:08	ga_ls7e_ard_3-1-0_115076_2020-01-08_final
2020-01-08 11:32:32	ga_ls7e_ard_3-1-0_115077_2020-01-08_final
2020-01-08 11:32:56	ga_ls7e_ard_3-1-0_115078_2020-01-08_final
2020-01-08 11:33:20	ga_ls7e_ard_3-1-0_115079_2020-01-08_final
2020-01-09 08:57:59	ga_ls7e_ard_3-1-0_090077_2020-01-08_final
2020-01-09 08:58:23	ga_ls7e_ard_3-1-0_090078_2020-01-08_final
2020-01-09 08:58:47	ga_ls7e_ard_3-1-0_090079_2020-01-08_final
2020-01-09 08:59:11	ga_ls7e_ard_3-1-0_090080_2020-01-08_final
2020-01-09 08:59:35	ga_ls7e_ard_3-1-0_090081_2020-01-08_final
2020-01-09 08:59:59	ga_ls7e_ard_3-1-0_090082_2020-01-08_final
2020-01-09 09:00:22	ga_ls7e_ard_3-1-0_090083_2020-01-08_final
2020-01-09 09:00:46	ga_ls7e_ard_3-1-0_090084_2020-01-08_final
2020-01-09 09:01:10	ga_ls7e_ard_3-1-0_090085_2020-01-08_final
2020-01-09 09:01:34	ga_ls7e_ard_3-1-0_090086_2020-01-08_final
2020-01-28 09:27:57	ga_ls7e_ard_3-1-0_095077_2020-01-27_final
2020-01-28 09:28:21	ga_ls7e_ard_3-1-0_095078_2020-01-27_final
2020-01-28 09:28:45	ga_ls7e_ard_3-1-0_095079_2020-01-27_final
2020-01-28 09:29:09	ga_ls7e_ard_3-1-0_095080_2020-01-27_final
2020-01-28 09:29:33	ga_ls7e_ard_3-1-0_095081_2020-01-27_final
2020-01-28 09:30:20	ga_ls7e_ard_3-1-0_095083_2020-01-28_final
2020-01-28 09:30:44	ga_ls7e_ard_3-1-0_095084_2020-01-28_final
2020-01-28 09:31:08	ga_ls7e_ard_3-1-0_095085_2020-01-28_final
2020-01-28 09:31:32	ga_ls7e_ard_3-1-0_095086_2020-01-28_final
2020-01-28 09:31:56	ga_ls7e_ard_3-1-0_095087_2020-01-28_final
2020-01-29 10:07:34	ga_ls7e_ard_3-1-0_102068_2020-01-29_final
2020-01-29 10:07:58	ga_ls7e_ard_3-1-0_102069_2020-01-29_final
2020-01-29 10:08:22	ga_ls7e_ard_3-1-0_102070_2020-01-29_final
2020-01-30 09:14:17	ga_ls7e_ard_3-1-0_093074_2020-01-29_final
2020-01-30 09:14:41	ga_ls7e_ard_3-1-0_093075_2020-01-29_final
2020-01-30 09:15:05	ga_ls7e_ard_3-1-0_093076_2020-01-29_final
2020-01-30 09:15:29	ga_ls7e_ard_3-1-0_093077_2020-01-29_final
2020-01-30 09:15:53	ga_ls7e_ard_3-1-0_093078_2020-01-29_final
2020-01-30 09:16:17	ga_ls7e_ard_3-1-0_093079_2020-01-29_final
2020-01-30 09:16:41	ga_ls7e_ard_3-1-0_093080_2020-01-29_final
2020-01-30 09:17:05	ga_ls7e_ard_3-1-0_093081_2020-01-29_final
2020-01-30 09:17:29	ga_ls7e_ard_3-1-0_093082_2020-01-29_final
2020-01-30 09:17:53	ga_ls7e_ard_3-1-0_093083_2020-01-29_final
2020-01-30 09:18:17	ga_ls7e_ard_3-1-0_093084_2020-01-29_final
2020-01-30 09:18:41	ga_ls7e_ard_3-1-0_093085_2020-01-29_final
2020-01-30 09:19:05	ga_ls7e_ard_3-1-0_093086_2020-01-29_final
2020-01-30 09:19:29	ga_ls7e_ard_3-1-0_093087_2020-01-29_final
2020-01-30 09:19:53	ga_ls7e_ard_3-1-0_093088_2020-01-29_final
2020-01-31 09:56:42	ga_ls7e_ard_3-1-0_100072_2020-01-31_final
2020-01-31 09:57:06	ga_ls7e_ard_3-1-0_100073_2020-01-31_final
2020-01-31 09:57:30	ga_ls7e_ard_3-1-0_100074_2020-01-31_final
2020-01-31 09:58:18	ga_ls7e_ard_3-1-0_100076_2020-01-31_final
2020-01-31 09:58:42	ga_ls7e_ard_3-1-0_100077_2020-01-31_final
2020-01-31 09:59:06	ga_ls7e_ard_3-1-0_100078_2020-01-31_final
2020-01-31 09:59:30	ga_ls7e_ard_3-1-0_100079_2020-01-31_final
2020-01-31 09:59:54	ga_ls7e_ard_3-1-0_100080_2020-01-31_final
2020-01-31 10:00:18	ga_ls7e_ard_3-1-0_100081_2020-01-31_final

Return to ga_ls7e_ard_3 across January 2020 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

2020

January

All days