Search ga_ls7e_ard_3 across February 2017

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
2017-02-14 10:25:49	ga_ls7e_ard_3-0-0_101073_2017-02-14_final
2017-02-14 10:26:13	ga_ls7e_ard_3-0-0_101074_2017-02-14_final
2017-02-14 10:26:37	ga_ls7e_ard_3-1-0_101075_2017-02-14_final
2017-02-14 10:27:01	ga_ls7e_ard_3-0-0_101076_2017-02-14_final
2017-02-14 10:27:25	ga_ls7e_ard_3-0-0_101077_2017-02-14_final
2017-02-14 10:27:49	ga_ls7e_ard_3-0-0_101078_2017-02-14_final
2017-02-14 10:28:13	ga_ls7e_ard_3-0-0_101079_2017-02-14_final
2017-02-14 10:28:37	ga_ls7e_ard_3-0-0_101080_2017-02-14_final
2017-02-14 10:29:01	ga_ls7e_ard_3-0-0_101081_2017-02-14_final
2017-02-14 10:29:25	ga_ls7e_ard_3-0-0_101082_2017-02-14_final
2017-02-14 10:29:49	ga_ls7e_ard_3-0-0_101083_2017-02-14_final
2017-02-15 09:31:01	ga_ls7e_ard_3-0-0_092075_2017-02-15_final
2017-02-15 09:31:25	ga_ls7e_ard_3-0-0_092076_2017-02-15_final
2017-02-15 09:31:48	ga_ls7e_ard_3-0-0_092077_2017-02-15_final
2017-02-15 09:32:12	ga_ls7e_ard_3-0-0_092078_2017-02-15_final
2017-02-15 09:32:36	ga_ls7e_ard_3-0-0_092079_2017-02-15_final
2017-02-15 09:33:00	ga_ls7e_ard_3-0-0_092080_2017-02-15_final
2017-02-15 09:33:24	ga_ls7e_ard_3-0-0_092081_2017-02-15_final
2017-02-15 09:33:48	ga_ls7e_ard_3-0-0_092082_2017-02-15_final
2017-02-15 09:34:12	ga_ls7e_ard_3-0-0_092083_2017-02-15_final
2017-02-15 09:34:36	ga_ls7e_ard_3-0-0_092084_2017-02-15_final
2017-02-15 09:35:00	ga_ls7e_ard_3-0-0_092085_2017-02-15_final
2017-02-15 09:35:24	ga_ls7e_ard_3-0-0_092086_2017-02-15_final
2017-02-15 09:35:48	ga_ls7e_ard_3-0-0_092087_2017-02-15_final
2017-02-15 09:36:12	ga_ls7e_ard_3-0-0_092088_2017-02-15_final
2017-02-15 09:36:36	ga_ls7e_ard_3-0-0_092089_2017-02-15_final
2017-02-15 11:07:54	ga_ls7e_ard_3-0-0_108070_2017-02-15_final
2017-02-15 11:08:18	ga_ls7e_ard_3-0-0_108071_2017-02-15_final
2017-02-15 11:09:30	ga_ls7e_ard_3-0-0_108074_2017-02-15_final
2017-02-15 11:09:54	ga_ls7e_ard_3-1-0_108075_2017-02-15_final
2017-02-15 11:10:18	ga_ls7e_ard_3-0-0_108076_2017-02-15_final
2017-02-15 11:10:42	ga_ls7e_ard_3-0-0_108077_2017-02-15_final
2017-02-15 11:11:05	ga_ls7e_ard_3-0-0_108078_2017-02-15_final
2017-02-16 10:11:05	ga_ls7e_ard_3-0-0_099067_2017-02-16_final
2017-02-16 10:11:29	ga_ls7e_ard_3-0-0_099068_2017-02-16_final
2017-02-16 10:13:05	ga_ls7e_ard_3-0-0_099072_2017-02-16_final
2017-02-16 10:13:29	ga_ls7e_ard_3-0-0_099073_2017-02-16_final
2017-02-16 10:13:53	ga_ls7e_ard_3-0-0_099074_2017-02-16_final
2017-02-16 10:14:17	ga_ls7e_ard_3-0-0_099075_2017-02-16_final
2017-02-16 10:14:41	ga_ls7e_ard_3-0-0_099076_2017-02-16_final
2017-02-16 10:15:05	ga_ls7e_ard_3-0-0_099077_2017-02-16_final
2017-02-16 10:15:29	ga_ls7e_ard_3-0-0_099078_2017-02-16_final
2017-02-16 10:15:53	ga_ls7e_ard_3-0-0_099079_2017-02-16_final
2017-02-16 10:16:17	ga_ls7e_ard_3-0-0_099080_2017-02-16_final
2017-02-16 10:16:41	ga_ls7e_ard_3-0-0_099081_2017-02-16_final
2017-02-16 10:17:05	ga_ls7e_ard_3-0-0_099082_2017-02-16_final
2017-02-16 10:17:28	ga_ls7e_ard_3-0-0_099083_2017-02-16_final
2017-02-16 10:17:52	ga_ls7e_ard_3-0-0_099084_2017-02-16_final
2017-02-17 09:19:28	ga_ls7e_ard_3-0-0_090077_2017-02-16_final
2017-02-17 09:19:52	ga_ls7e_ard_3-0-0_090078_2017-02-16_final
2017-02-17 09:20:16	ga_ls7e_ard_3-0-0_090079_2017-02-16_final
2017-02-17 09:20:40	ga_ls7e_ard_3-0-0_090080_2017-02-16_final
2017-02-17 09:21:04	ga_ls7e_ard_3-0-0_090081_2017-02-16_final
2017-02-17 09:21:28	ga_ls7e_ard_3-0-0_090082_2017-02-16_final
2017-02-17 09:21:52	ga_ls7e_ard_3-0-0_090083_2017-02-16_final
2017-02-17 09:22:16	ga_ls7e_ard_3-0-0_090084_2017-02-16_final
2017-02-17 09:22:40	ga_ls7e_ard_3-1-0_090085_2017-02-16_final
2017-02-17 09:23:04	ga_ls7e_ard_3-0-0_090086_2017-02-16_final
2017-02-27 09:54:15	ga_ls7e_ard_3-0-0_096071_2017-02-27_final
2017-02-27 09:54:39	ga_ls7e_ard_3-0-0_096072_2017-02-27_final
2017-02-27 09:55:03	ga_ls7e_ard_3-0-0_096073_2017-02-27_final
2017-02-27 09:55:27	ga_ls7e_ard_3-0-0_096074_2017-02-27_final
2017-02-27 09:55:51	ga_ls7e_ard_3-0-0_096075_2017-02-27_final
2017-02-27 09:56:15	ga_ls7e_ard_3-0-0_096076_2017-02-27_final
2017-02-27 09:56:38	ga_ls7e_ard_3-0-0_096077_2017-02-27_final
2017-02-27 09:57:02	ga_ls7e_ard_3-0-0_096078_2017-02-27_final
2017-02-27 09:57:26	ga_ls7e_ard_3-0-0_096079_2017-02-27_final
2017-02-27 09:57:50	ga_ls7e_ard_3-0-0_096080_2017-02-27_final
2017-02-27 09:58:14	ga_ls7e_ard_3-1-0_096081_2017-02-27_final
2017-02-27 09:58:38	ga_ls7e_ard_3-0-0_096082_2017-02-27_final
2017-02-27 09:59:02	ga_ls7e_ard_3-0-0_096083_2017-02-27_final
2017-02-27 09:59:26	ga_ls7e_ard_3-0-0_096084_2017-02-27_final
2017-02-27 09:59:50	ga_ls7e_ard_3-0-0_096085_2017-02-27_final
2017-02-27 10:00:14	ga_ls7e_ard_3-1-0_096086_2017-02-27_final
2017-02-27 11:31:32	ga_ls7e_ard_3-0-0_112067_2017-02-27_final
2017-02-27 11:34:20	ga_ls7e_ard_3-0-0_112074_2017-02-27_final
2017-02-27 11:34:44	ga_ls7e_ard_3-0-0_112075_2017-02-27_final
2017-02-27 11:35:08	ga_ls7e_ard_3-0-0_112076_2017-02-27_final
2017-02-27 11:35:32	ga_ls7e_ard_3-0-0_112077_2017-02-27_final
2017-02-27 11:35:56	ga_ls7e_ard_3-0-0_112078_2017-02-27_final
2017-02-27 11:36:19	ga_ls7e_ard_3-0-0_112079_2017-02-27_final
2017-02-27 11:36:43	ga_ls7e_ard_3-0-0_112080_2017-02-27_final
2017-02-27 11:37:07	ga_ls7e_ard_3-0-0_112081_2017-02-27_final
2017-02-27 11:37:31	ga_ls7e_ard_3-0-0_112082_2017-02-27_final
2017-02-27 11:37:55	ga_ls7e_ard_3-0-0_112083_2017-02-27_final
2017-02-27 11:38:19	ga_ls7e_ard_3-0-0_112084_2017-02-27_final
2017-02-28 10:36:19	ga_ls7e_ard_3-0-0_103068_2017-02-28_final
2017-02-28 10:36:43	ga_ls7e_ard_3-0-0_103069_2017-02-28_final
2017-02-28 10:37:07	ga_ls7e_ard_3-0-0_103070_2017-02-28_final
2017-02-28 10:37:31	ga_ls7e_ard_3-0-0_103071_2017-02-28_final
2017-02-28 10:37:55	ga_ls7e_ard_3-0-0_103072_2017-02-28_final
2017-02-28 10:38:19	ga_ls7e_ard_3-0-0_103073_2017-02-28_final
2017-02-28 10:38:43	ga_ls7e_ard_3-0-0_103074_2017-02-28_final
2017-02-28 10:39:07	ga_ls7e_ard_3-0-0_103075_2017-02-28_final
2017-02-28 10:39:31	ga_ls7e_ard_3-0-0_103076_2017-02-28_final
2017-02-28 10:39:55	ga_ls7e_ard_3-0-0_103077_2017-02-28_final
2017-02-28 10:40:19	ga_ls7e_ard_3-0-0_103078_2017-02-28_final
2017-02-28 10:40:43	ga_ls7e_ard_3-0-0_103079_2017-02-28_final
2017-02-28 10:41:06	ga_ls7e_ard_3-0-0_103080_2017-02-28_final
2017-02-28 10:41:30	ga_ls7e_ard_3-0-0_103081_2017-02-28_final

Return to ga_ls7e_ard_3 across February 2017 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

2017

February

All days