Search ga_ls7e_ard_3 whole collection

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
2017-11-03 11:29:31	ga_ls7e_ard_3-1-0_111076_2017-11-03_final
2020-05-21 10:47:16	ga_ls7e_ard_3-1-0_109075_2020-05-21_final
2020-05-21 10:47:40	ga_ls7e_ard_3-1-0_109076_2020-05-21_final
2020-05-21 10:48:04	ga_ls7e_ard_3-1-0_109077_2020-05-21_final
2020-05-21 10:48:28	ga_ls7e_ard_3-1-0_109078_2020-05-21_final
2020-05-23 10:32:47	ga_ls7e_ard_3-1-0_107070_2020-05-23_final
2020-05-23 10:33:11	ga_ls7e_ard_3-1-0_107071_2020-05-23_final
2020-05-23 10:33:35	ga_ls7e_ard_3-1-0_107072_2020-05-23_final
2020-05-23 10:34:47	ga_ls7e_ard_3-1-0_107075_2020-05-23_final
2020-05-23 10:35:11	ga_ls7e_ard_3-1-0_107076_2020-05-23_final
2020-05-23 10:35:59	ga_ls7e_ard_3-1-0_107078_2020-05-23_final
2020-05-23 10:36:47	ga_ls7e_ard_3-1-0_107080_2020-05-23_final
2020-05-23 10:37:11	ga_ls7e_ard_3-1-0_107081_2020-05-23_final
2020-05-23 10:37:35	ga_ls7e_ard_3-1-0_107082_2020-05-23_final
2020-05-23 10:37:58	ga_ls7e_ard_3-1-0_107083_2020-05-23_final
2020-05-26 11:06:41	ga_ls7e_ard_3-1-0_112078_2020-05-26_final
2020-05-28 10:52:37	ga_ls7e_ard_3-1-0_110074_2020-05-28_final
2020-05-28 10:53:25	ga_ls7e_ard_3-1-0_110076_2020-05-28_final
2020-05-28 10:54:13	ga_ls7e_ard_3-1-0_110078_2020-05-28_final
2020-05-28 10:55:25	ga_ls7e_ard_3-1-0_110081_2020-05-28_final
2020-05-30 09:02:52	ga_ls7e_ard_3-1-0_092078_2020-05-29_final
2020-05-30 09:06:03	ga_ls7e_ard_3-1-0_092086_2020-05-29_final
2020-05-30 10:38:57	ga_ls7e_ard_3-1-0_108071_2020-05-30_final
2020-05-30 10:39:21	ga_ls7e_ard_3-1-0_108072_2020-05-30_final
2020-05-30 10:40:33	ga_ls7e_ard_3-1-0_108075_2020-05-30_final
2020-05-30 10:40:57	ga_ls7e_ard_3-1-0_108076_2020-05-30_final
2020-05-30 10:41:20	ga_ls7e_ard_3-1-0_108077_2020-05-30_final
2020-05-30 10:41:44	ga_ls7e_ard_3-1-0_108078_2020-05-30_final
2020-05-30 10:42:56	ga_ls7e_ard_3-1-0_108081_2020-05-30_final
2020-05-31 09:43:16	ga_ls7e_ard_3-1-0_099071_2020-05-31_final
2020-05-31 09:43:40	ga_ls7e_ard_3-1-0_099072_2020-05-31_final
2020-05-31 09:46:28	ga_ls7e_ard_3-1-0_099079_2020-05-31_final
2020-05-31 09:47:16	ga_ls7e_ard_3-1-0_099081_2020-05-31_final
2020-06-01 08:52:47	ga_ls7e_ard_3-1-0_090084_2020-05-31_final
2020-06-01 08:53:11	ga_ls7e_ard_3-1-0_090085_2020-05-31_final
2020-06-01 08:54:23	ga_ls7e_ard_3-1-0_090088_2020-05-31_final
2020-06-01 08:55:11	ga_ls7e_ard_3-1-0_090090_2020-05-31_final
2020-06-01 10:25:17	ga_ls7e_ard_3-1-0_106068_2020-06-01_final
2020-06-01 10:26:28	ga_ls7e_ard_3-1-0_106071_2020-06-01_final
2020-06-01 10:26:52	ga_ls7e_ard_3-1-0_106072_2020-06-01_final
2020-06-01 10:27:16	ga_ls7e_ard_3-1-0_106073_2020-06-01_final
2020-06-01 10:28:04	ga_ls7e_ard_3-1-0_106075_2020-06-01_final
2020-06-01 10:29:40	ga_ls7e_ard_3-1-0_106079_2020-06-01_final
2020-06-01 10:30:28	ga_ls7e_ard_3-1-0_106081_2020-06-01_final
2020-06-01 10:30:52	ga_ls7e_ard_3-1-0_106082_2020-06-01_final
2020-06-01 10:31:16	ga_ls7e_ard_3-1-0_106083_2020-06-01_final
2020-06-02 09:30:24	ga_ls7e_ard_3-1-0_097070_2020-06-02_final
2020-06-02 09:31:12	ga_ls7e_ard_3-1-0_097072_2020-06-02_final
2020-06-02 09:32:00	ga_ls7e_ard_3-1-0_097074_2020-06-02_final
2020-06-02 09:33:59	ga_ls7e_ard_3-1-0_097079_2020-06-02_final
2020-06-02 09:34:47	ga_ls7e_ard_3-1-0_097081_2020-06-02_final
2020-06-03 10:13:12	ga_ls7e_ard_3-1-0_104069_2020-06-03_final
2020-06-03 10:13:36	ga_ls7e_ard_3-1-0_104070_2020-06-03_final
2020-06-03 10:14:24	ga_ls7e_ard_3-1-0_104072_2020-06-03_final
2020-06-03 10:15:12	ga_ls7e_ard_3-1-0_104074_2020-06-03_final
2020-06-03 10:15:36	ga_ls7e_ard_3-1-0_104075_2020-06-03_final
2020-06-03 10:16:00	ga_ls7e_ard_3-1-0_104076_2020-06-03_final
2020-06-03 10:16:24	ga_ls7e_ard_3-1-0_104077_2020-06-03_final
2020-06-03 10:16:47	ga_ls7e_ard_3-1-0_104078_2020-06-03_final
2020-06-03 10:17:35	ga_ls7e_ard_3-1-0_104080_2020-06-03_final
2020-06-04 09:16:44	ga_ls7e_ard_3-1-0_095067_2020-06-03_final
2020-06-04 09:18:43	ga_ls7e_ard_3-1-0_095072_2020-06-03_final
2020-06-04 09:19:07	ga_ls7e_ard_3-1-0_095073_2020-06-03_final
2020-06-04 09:19:55	ga_ls7e_ard_3-1-0_095075_2020-06-03_final
2020-06-04 09:20:43	ga_ls7e_ard_3-1-0_095077_2020-06-03_final
2020-06-04 09:21:07	ga_ls7e_ard_3-1-0_095078_2020-06-03_final
2020-06-04 09:21:55	ga_ls7e_ard_3-1-0_095080_2020-06-03_final
2020-06-04 09:22:43	ga_ls7e_ard_3-1-0_095082_2020-06-03_final
2020-06-04 09:23:31	ga_ls7e_ard_3-1-0_095084_2020-06-03_final
2020-06-04 09:24:18	ga_ls7e_ard_3-1-0_095086_2020-06-03_final
2020-06-04 09:24:42	ga_ls7e_ard_3-1-0_095087_2020-06-03_final
2020-06-05 10:02:43	ga_ls7e_ard_3-1-0_102074_2020-06-05_final
2020-06-05 10:04:43	ga_ls7e_ard_3-1-0_102079_2020-06-05_final
2020-06-05 10:05:07	ga_ls7e_ard_3-1-0_102080_2020-06-05_final
2020-06-05 10:05:31	ga_ls7e_ard_3-1-0_102081_2020-06-05_final
2020-06-05 10:05:55	ga_ls7e_ard_3-1-0_102082_2020-06-05_final
2020-06-06 09:08:14	ga_ls7e_ard_3-1-0_093077_2020-06-05_final
2020-06-06 09:11:26	ga_ls7e_ard_3-1-0_093085_2020-06-05_final
2020-06-06 09:11:50	ga_ls7e_ard_3-1-0_093086_2020-06-05_final
2020-06-06 10:44:44	ga_ls7e_ard_3-1-0_109071_2020-06-06_final
2020-06-06 10:45:08	ga_ls7e_ard_3-1-0_109072_2020-06-06_final
2020-06-06 10:45:55	ga_ls7e_ard_3-1-0_109074_2020-06-06_final
2020-06-06 10:46:43	ga_ls7e_ard_3-1-0_109076_2020-06-06_final
2020-06-06 10:47:07	ga_ls7e_ard_3-1-0_109077_2020-06-06_final
2020-06-06 10:47:31	ga_ls7e_ard_3-1-0_109078_2020-06-06_final
2020-06-06 10:48:19	ga_ls7e_ard_3-1-0_109080_2020-06-06_final
2020-06-06 10:49:31	ga_ls7e_ard_3-1-0_109083_2020-06-06_final
2020-06-07 09:50:15	ga_ls7e_ard_3-1-0_100074_2020-06-07_final
2020-06-07 09:51:27	ga_ls7e_ard_3-1-0_100077_2020-06-07_final
2020-06-07 09:53:50	ga_ls7e_ard_3-1-0_100083_2020-06-07_final
2020-06-08 08:55:22	ga_ls7e_ard_3-1-0_091076_2020-06-07_final
2020-06-08 08:56:10	ga_ls7e_ard_3-1-0_091078_2020-06-07_final
2020-06-08 08:56:58	ga_ls7e_ard_3-1-0_091080_2020-06-07_final
2020-06-08 08:58:34	ga_ls7e_ard_3-1-0_091084_2020-06-07_final
2020-06-08 09:00:09	ga_ls7e_ard_3-1-0_091088_2020-06-07_final
2020-06-08 10:35:03	ga_ls7e_ard_3-1-0_107078_2020-06-08_final
2020-06-08 10:35:51	ga_ls7e_ard_3-1-0_107080_2020-06-08_final
2020-06-08 10:36:14	ga_ls7e_ard_3-1-0_107081_2020-06-08_final
2020-06-08 10:36:38	ga_ls7e_ard_3-1-0_107082_2020-06-08_final
2020-06-08 10:37:02	ga_ls7e_ard_3-1-0_107083_2020-06-08_final

Return to ga_ls7e_ard_3 whole collection 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

All years