Search ga_ls7e_ard_3 across June 2015

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
2015-06-01 10:22:36	ga_ls7e_ard_3-0-0_101071_2015-06-01_final
2015-06-01 10:23:00	ga_ls7e_ard_3-0-0_101072_2015-06-01_final
2015-06-01 10:23:48	ga_ls7e_ard_3-0-0_101074_2015-06-01_final
2015-06-01 10:24:12	ga_ls7e_ard_3-1-0_101075_2015-06-01_final
2015-06-01 10:24:36	ga_ls7e_ard_3-0-0_101076_2015-06-01_final
2015-06-01 10:25:24	ga_ls7e_ard_3-0-0_101078_2015-06-01_final
2015-06-01 10:25:48	ga_ls7e_ard_3-0-0_101079_2015-06-01_final
2015-06-01 10:26:12	ga_ls7e_ard_3-0-0_101080_2015-06-01_final
2015-06-01 10:26:35	ga_ls7e_ard_3-0-0_101081_2015-06-01_final
2015-06-01 10:26:59	ga_ls7e_ard_3-0-0_101082_2015-06-01_final
2015-06-01 10:27:23	ga_ls7e_ard_3-0-0_101083_2015-06-01_final
2015-06-02 09:28:35	ga_ls7e_ard_3-0-0_092075_2015-06-01_final
2015-06-02 09:28:59	ga_ls7e_ard_3-0-0_092076_2015-06-01_final
2015-06-02 09:29:23	ga_ls7e_ard_3-0-0_092077_2015-06-01_final
2015-06-02 09:29:47	ga_ls7e_ard_3-1-0_092078_2015-06-01_final
2015-06-02 09:30:11	ga_ls7e_ard_3-1-0_092079_2015-06-02_final
2015-06-02 09:30:35	ga_ls7e_ard_3-0-0_092080_2015-06-02_final
2015-06-02 09:30:59	ga_ls7e_ard_3-0-0_092081_2015-06-02_final
2015-06-02 09:31:23	ga_ls7e_ard_3-0-0_092082_2015-06-02_final
2015-06-02 09:31:47	ga_ls7e_ard_3-0-0_092083_2015-06-02_final
2015-06-02 09:32:11	ga_ls7e_ard_3-0-0_092084_2015-06-02_final
2015-06-02 09:32:35	ga_ls7e_ard_3-0-0_092085_2015-06-02_final
2015-06-02 09:32:59	ga_ls7e_ard_3-0-0_092086_2015-06-02_final
2015-06-05 09:57:07	ga_ls7e_ard_3-0-0_097069_2015-06-05_final
2015-06-05 09:57:31	ga_ls7e_ard_3-0-0_097070_2015-06-05_final
2015-06-12 10:02:33	ga_ls7e_ard_3-0-0_098067_2015-06-12_final
2015-06-12 10:02:57	ga_ls7e_ard_3-0-0_098068_2015-06-12_final
2015-06-12 10:03:21	ga_ls7e_ard_3-0-0_098069_2015-06-12_final
2015-06-12 10:03:45	ga_ls7e_ard_3-0-0_098070_2015-06-12_final
2015-06-12 10:04:09	ga_ls7e_ard_3-0-0_098071_2015-06-12_final
2015-06-12 10:04:33	ga_ls7e_ard_3-0-0_098072_2015-06-12_final
2015-06-12 10:06:08	ga_ls7e_ard_3-0-0_098076_2015-06-12_final
2015-06-12 10:06:32	ga_ls7e_ard_3-0-0_098077_2015-06-12_final
2015-06-12 10:07:20	ga_ls7e_ard_3-0-0_098079_2015-06-12_final
2015-06-12 10:07:44	ga_ls7e_ard_3-0-0_098080_2015-06-12_final
2015-06-12 10:08:08	ga_ls7e_ard_3-0-0_098081_2015-06-12_final
2015-06-12 10:08:32	ga_ls7e_ard_3-0-0_098082_2015-06-12_final
2015-06-12 10:08:56	ga_ls7e_ard_3-0-0_098083_2015-06-12_final
2015-06-12 10:09:20	ga_ls7e_ard_3-0-0_098084_2015-06-12_final
2015-06-12 10:09:44	ga_ls7e_ard_3-0-0_098085_2015-06-12_final
2015-06-12 11:41:26	ga_ls7e_ard_3-0-0_114067_2015-06-12_final
2015-06-12 11:44:14	ga_ls7e_ard_3-0-0_114074_2015-06-12_final
2015-06-12 11:44:38	ga_ls7e_ard_3-0-0_114075_2015-06-12_final
2015-06-12 11:45:02	ga_ls7e_ard_3-0-0_114076_2015-06-12_final
2015-06-12 11:45:25	ga_ls7e_ard_3-0-0_114077_2015-06-12_final
2015-06-12 11:45:49	ga_ls7e_ard_3-0-0_114078_2015-06-12_final
2015-06-12 11:46:13	ga_ls7e_ard_3-0-0_114079_2015-06-12_final
2015-06-13 09:15:43	ga_ls7e_ard_3-0-0_089089_2015-06-12_final
2015-06-13 09:16:07	ga_ls7e_ard_3-0-0_089090_2015-06-12_final
2015-06-13 10:49:00	ga_ls7e_ard_3-0-0_105075_2015-06-13_final
2015-06-13 10:49:48	ga_ls7e_ard_3-0-0_105077_2015-06-13_final
2015-06-13 10:50:12	ga_ls7e_ard_3-0-0_105078_2015-06-13_final
2015-06-13 10:50:36	ga_ls7e_ard_3-0-0_105079_2015-06-13_final
2015-06-13 10:51:00	ga_ls7e_ard_3-1-0_105080_2015-06-13_final
2015-06-13 10:51:24	ga_ls7e_ard_3-0-0_105081_2015-06-13_final
2015-06-13 10:51:48	ga_ls7e_ard_3-0-0_105082_2015-06-13_final
2015-06-14 09:50:12	ga_ls7e_ard_3-0-0_096067_2015-06-14_final
2015-06-14 09:51:24	ga_ls7e_ard_3-0-0_096070_2015-06-14_final
2015-06-14 09:51:48	ga_ls7e_ard_3-0-0_096071_2015-06-14_final
2015-06-14 09:52:11	ga_ls7e_ard_3-0-0_096072_2015-06-14_final
2015-06-14 09:52:35	ga_ls7e_ard_3-0-0_096073_2015-06-14_final
2015-06-14 09:52:59	ga_ls7e_ard_3-0-0_096074_2015-06-14_final
2015-06-14 09:53:23	ga_ls7e_ard_3-0-0_096075_2015-06-14_final
2015-06-14 09:53:47	ga_ls7e_ard_3-0-0_096076_2015-06-14_final
2015-06-14 09:54:11	ga_ls7e_ard_3-0-0_096077_2015-06-14_final
2015-06-14 09:54:35	ga_ls7e_ard_3-0-0_096078_2015-06-14_final
2015-06-14 09:54:59	ga_ls7e_ard_3-0-0_096079_2015-06-14_final
2015-06-14 09:55:23	ga_ls7e_ard_3-0-0_096080_2015-06-14_final
2015-06-14 09:55:47	ga_ls7e_ard_3-0-0_096081_2015-06-14_final
2015-06-14 09:56:11	ga_ls7e_ard_3-0-0_096082_2015-06-14_final
2015-06-14 09:56:35	ga_ls7e_ard_3-0-0_096083_2015-06-14_final
2015-06-14 09:56:59	ga_ls7e_ard_3-0-0_096084_2015-06-14_final
2015-06-14 09:57:23	ga_ls7e_ard_3-0-0_096085_2015-06-14_final
2015-06-14 11:29:05	ga_ls7e_ard_3-0-0_112067_2015-06-14_final
2015-06-14 11:31:52	ga_ls7e_ard_3-0-0_112074_2015-06-14_final
2015-06-14 11:32:16	ga_ls7e_ard_3-0-0_112075_2015-06-14_final
2015-06-14 11:32:40	ga_ls7e_ard_3-0-0_112076_2015-06-14_final
2015-06-14 11:33:04	ga_ls7e_ard_3-0-0_112077_2015-06-14_final
2015-06-14 11:33:28	ga_ls7e_ard_3-0-0_112078_2015-06-14_final
2015-06-14 11:33:52	ga_ls7e_ard_3-0-0_112079_2015-06-14_final
2015-06-14 11:34:16	ga_ls7e_ard_3-0-0_112080_2015-06-14_final
2015-06-14 11:34:40	ga_ls7e_ard_3-0-0_112081_2015-06-14_final
2015-06-14 11:35:04	ga_ls7e_ard_3-0-0_112082_2015-06-14_final
2015-06-14 11:35:28	ga_ls7e_ard_3-0-0_112083_2015-06-14_final
2015-06-14 11:35:52	ga_ls7e_ard_3-0-0_112084_2015-06-14_final
2015-06-15 10:33:52	ga_ls7e_ard_3-0-0_103068_2015-06-15_final
2015-06-15 10:34:16	ga_ls7e_ard_3-0-0_103069_2015-06-15_final
2015-06-15 10:34:39	ga_ls7e_ard_3-0-0_103070_2015-06-15_final
2015-06-15 10:35:03	ga_ls7e_ard_3-0-0_103071_2015-06-15_final
2015-06-15 10:35:27	ga_ls7e_ard_3-0-0_103072_2015-06-15_final
2015-06-15 10:35:51	ga_ls7e_ard_3-0-0_103073_2015-06-15_final
2015-06-15 10:36:15	ga_ls7e_ard_3-0-0_103074_2015-06-15_final
2015-06-15 10:36:39	ga_ls7e_ard_3-0-0_103075_2015-06-15_final
2015-06-15 10:37:03	ga_ls7e_ard_3-0-0_103076_2015-06-15_final
2015-06-15 10:37:27	ga_ls7e_ard_3-0-0_103077_2015-06-15_final
2015-06-15 10:38:15	ga_ls7e_ard_3-0-0_103079_2015-06-15_final
2015-06-15 10:38:39	ga_ls7e_ard_3-0-0_103080_2015-06-15_final
2015-06-15 10:39:03	ga_ls7e_ard_3-0-0_103081_2015-06-15_final
2015-06-16 09:40:14	ga_ls7e_ard_3-0-0_094073_2015-06-16_final
2015-06-16 09:40:38	ga_ls7e_ard_3-0-0_094074_2015-06-16_final

Return to ga_ls7e_ard_3 across June 2015 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

2015

June

All days