Search ga_ls7e_ard_3 across August 2019

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
2019-08-22 10:15:00	ga_ls7e_ard_3-0-0_102068_2019-08-22_final
2019-08-22 10:15:24	ga_ls7e_ard_3-0-0_102069_2019-08-22_final
2019-08-22 10:15:48	ga_ls7e_ard_3-0-0_102070_2019-08-22_final
2019-08-22 10:16:12	ga_ls7e_ard_3-0-0_102071_2019-08-22_final
2019-08-22 10:16:35	ga_ls7e_ard_3-0-0_102072_2019-08-22_final
2019-08-22 10:16:59	ga_ls7e_ard_3-0-0_102073_2019-08-22_final
2019-08-22 10:17:23	ga_ls7e_ard_3-0-0_102074_2019-08-22_final
2019-08-22 10:17:47	ga_ls7e_ard_3-0-0_102075_2019-08-22_final
2019-08-22 10:18:11	ga_ls7e_ard_3-0-0_102076_2019-08-22_final
2019-08-22 10:18:35	ga_ls7e_ard_3-0-0_102077_2019-08-22_final
2019-08-22 10:18:59	ga_ls7e_ard_3-0-0_102078_2019-08-22_final
2019-08-22 10:19:23	ga_ls7e_ard_3-0-0_102079_2019-08-22_final
2019-08-22 10:19:47	ga_ls7e_ard_3-0-0_102080_2019-08-22_final
2019-08-22 10:20:11	ga_ls7e_ard_3-0-0_102081_2019-08-22_final
2019-08-22 10:20:35	ga_ls7e_ard_3-0-0_102082_2019-08-22_final
2019-08-23 09:21:44	ga_ls7e_ard_3-0-0_093074_2019-08-22_final
2019-08-23 09:22:07	ga_ls7e_ard_3-0-0_093075_2019-08-22_final
2019-08-23 09:22:31	ga_ls7e_ard_3-0-0_093076_2019-08-22_final
2019-08-23 09:22:55	ga_ls7e_ard_3-0-0_093077_2019-08-22_final
2019-08-23 09:23:19	ga_ls7e_ard_3-0-0_093078_2019-08-22_final
2019-08-23 09:23:43	ga_ls7e_ard_3-0-0_093079_2019-08-22_final
2019-08-23 09:24:07	ga_ls7e_ard_3-0-0_093080_2019-08-22_final
2019-08-23 09:24:31	ga_ls7e_ard_3-0-0_093081_2019-08-22_final
2019-08-23 09:24:55	ga_ls7e_ard_3-0-0_093082_2019-08-22_final
2019-08-23 09:25:19	ga_ls7e_ard_3-0-0_093083_2019-08-22_final
2019-08-23 09:25:43	ga_ls7e_ard_3-0-0_093084_2019-08-22_final
2019-08-23 09:26:07	ga_ls7e_ard_3-0-0_093085_2019-08-22_final
2019-08-23 09:26:31	ga_ls7e_ard_3-0-0_093086_2019-08-22_final
2019-08-23 09:26:55	ga_ls7e_ard_3-1-0_093087_2019-08-22_final
2019-08-23 10:59:01	ga_ls7e_ard_3-1-0_109070_2019-08-23_final
2019-08-23 10:59:25	ga_ls7e_ard_3-1-0_109071_2019-08-23_final
2019-08-23 10:59:49	ga_ls7e_ard_3-1-0_109072_2019-08-23_final
2019-08-23 11:00:12	ga_ls7e_ard_3-1-0_109073_2019-08-23_final
2019-08-23 11:00:36	ga_ls7e_ard_3-1-0_109074_2019-08-23_final
2019-08-23 11:01:00	ga_ls7e_ard_3-1-0_109075_2019-08-23_final
2019-08-23 11:01:24	ga_ls7e_ard_3-1-0_109076_2019-08-23_final
2019-08-23 11:01:48	ga_ls7e_ard_3-1-0_109077_2019-08-23_final
2019-08-23 11:02:12	ga_ls7e_ard_3-1-0_109078_2019-08-23_final
2019-08-23 11:02:36	ga_ls7e_ard_3-1-0_109079_2019-08-23_final
2019-08-23 11:03:00	ga_ls7e_ard_3-1-0_109080_2019-08-23_final
2019-08-24 10:03:45	ga_ls7e_ard_3-1-0_100071_2019-08-24_final
2019-08-24 10:04:09	ga_ls7e_ard_3-1-0_100072_2019-08-24_final
2019-08-24 10:04:33	ga_ls7e_ard_3-1-0_100073_2019-08-24_final
2019-08-24 10:04:57	ga_ls7e_ard_3-1-0_100074_2019-08-24_final
2019-08-24 10:05:21	ga_ls7e_ard_3-1-0_100075_2019-08-24_final
2019-08-24 10:05:44	ga_ls7e_ard_3-1-0_100076_2019-08-24_final
2019-08-24 10:06:08	ga_ls7e_ard_3-1-0_100077_2019-08-24_final
2019-08-24 10:06:32	ga_ls7e_ard_3-1-0_100078_2019-08-24_final
2019-08-24 10:06:56	ga_ls7e_ard_3-1-0_100079_2019-08-24_final
2019-08-24 10:07:20	ga_ls7e_ard_3-1-0_100080_2019-08-24_final
2019-08-24 10:07:44	ga_ls7e_ard_3-1-0_100081_2019-08-24_final
2019-08-24 10:08:08	ga_ls7e_ard_3-1-0_100082_2019-08-24_final
2019-08-24 10:08:32	ga_ls7e_ard_3-1-0_100083_2019-08-24_final
2019-08-25 09:10:05	ga_ls7e_ard_3-1-0_091076_2019-08-24_final
2019-08-25 09:10:29	ga_ls7e_ard_3-1-0_091077_2019-08-24_final
2019-08-25 09:10:53	ga_ls7e_ard_3-1-0_091078_2019-08-24_final
2019-08-25 09:11:17	ga_ls7e_ard_3-1-0_091079_2019-08-24_final
2019-08-25 09:11:41	ga_ls7e_ard_3-1-0_091080_2019-08-24_final
2019-08-25 09:12:04	ga_ls7e_ard_3-1-0_091081_2019-08-24_final
2019-08-25 09:12:28	ga_ls7e_ard_3-1-0_091082_2019-08-24_final
2019-08-25 09:12:52	ga_ls7e_ard_3-1-0_091083_2019-08-24_final
2019-08-25 09:13:16	ga_ls7e_ard_3-1-0_091084_2019-08-24_final
2019-08-25 09:13:40	ga_ls7e_ard_3-1-0_091085_2019-08-24_final
2019-08-25 09:14:04	ga_ls7e_ard_3-1-0_091086_2019-08-24_final
2019-08-25 09:14:28	ga_ls7e_ard_3-1-0_091087_2019-08-24_final
2019-08-25 09:14:52	ga_ls7e_ard_3-1-0_091088_2019-08-24_final
2019-08-25 09:15:16	ga_ls7e_ard_3-1-0_091089_2019-08-24_final
2019-08-25 09:15:40	ga_ls7e_ard_3-1-0_091090_2019-08-24_final
2019-08-25 10:46:34	ga_ls7e_ard_3-1-0_107070_2019-08-25_final
2019-08-25 10:46:58	ga_ls7e_ard_3-1-0_107071_2019-08-25_final
2019-08-25 10:47:22	ga_ls7e_ard_3-1-0_107072_2019-08-25_final
2019-08-25 10:47:46	ga_ls7e_ard_3-1-0_107073_2019-08-25_final
2019-08-25 10:48:10	ga_ls7e_ard_3-1-0_107074_2019-08-25_final
2019-08-25 10:48:34	ga_ls7e_ard_3-1-0_107075_2019-08-25_final
2019-08-25 10:48:58	ga_ls7e_ard_3-1-0_107076_2019-08-25_final
2019-08-25 10:49:21	ga_ls7e_ard_3-1-0_107077_2019-08-25_final
2019-08-25 10:49:45	ga_ls7e_ard_3-1-0_107078_2019-08-25_final
2019-08-25 10:50:09	ga_ls7e_ard_3-1-0_107079_2019-08-25_final
2019-08-25 10:50:33	ga_ls7e_ard_3-1-0_107080_2019-08-25_final
2019-08-25 10:50:57	ga_ls7e_ard_3-1-0_107081_2019-08-25_final
2019-08-25 10:51:21	ga_ls7e_ard_3-1-0_107082_2019-08-25_final
2019-08-25 10:51:45	ga_ls7e_ard_3-1-0_107083_2019-08-25_final
2019-08-25 10:52:09	ga_ls7e_ard_3-1-0_107084_2019-08-25_final
2019-08-30 09:27:12	ga_ls7e_ard_3-1-0_094073_2019-08-29_final
2019-08-30 09:27:36	ga_ls7e_ard_3-1-0_094074_2019-08-29_final
2019-08-30 09:28:00	ga_ls7e_ard_3-1-0_094075_2019-08-29_final
2019-08-30 09:28:24	ga_ls7e_ard_3-1-0_094076_2019-08-29_final
2019-08-30 09:28:48	ga_ls7e_ard_3-1-0_094077_2019-08-29_final
2019-08-30 09:29:12	ga_ls7e_ard_3-1-0_094078_2019-08-29_final
2019-08-30 09:29:36	ga_ls7e_ard_3-1-0_094079_2019-08-29_final
2019-08-30 09:30:24	ga_ls7e_ard_3-1-0_094081_2019-08-30_final
2019-08-30 09:30:48	ga_ls7e_ard_3-1-0_094082_2019-08-30_final
2019-08-30 09:31:12	ga_ls7e_ard_3-1-0_094083_2019-08-30_final
2019-08-30 09:31:36	ga_ls7e_ard_3-1-0_094084_2019-08-30_final
2019-08-30 09:32:00	ga_ls7e_ard_3-1-0_094085_2019-08-30_final
2019-08-30 09:32:24	ga_ls7e_ard_3-1-0_094086_2019-08-30_final
2019-08-30 09:32:48	ga_ls7e_ard_3-1-0_094087_2019-08-30_final
2019-08-31 10:09:38	ga_ls7e_ard_3-1-0_101071_2019-08-31_final
2019-08-31 10:10:02	ga_ls7e_ard_3-1-0_101072_2019-08-31_final
2019-08-31 10:10:26	ga_ls7e_ard_3-1-0_101073_2019-08-31_final

Return to ga_ls7e_ard_3 across August 2019 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

2019

August

All days