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
2021-05-28 09:59:29	ga_ls7e_ard_3-2-0_105083_2021-05-28_final
2021-07-18 10:25:44	ga_ls7e_ard_3-2-0_110082_2021-07-18_final
2021-07-30 09:09:20	ga_ls7e_ard_3-2-0_098079_2021-07-29_final
2021-08-02 09:37:11	ga_ls7e_ard_3-2-0_103072_2021-08-02_final
2021-08-03 08:45:28	ga_ls7e_ard_3-2-0_094082_2021-08-02_final
2021-08-03 10:20:21	ga_ls7e_ard_3-2-0_110072_2021-08-03_final
2021-08-03 10:20:45	ga_ls7e_ard_3-2-0_110073_2021-08-03_final
2021-08-03 10:25:08	ga_ls7e_ard_3-2-0_110084_2021-08-03_final
2021-08-12 08:40:05	ga_ls7e_ard_3-2-0_093086_2021-08-11_final
2021-08-21 08:32:42	ga_ls7e_ard_3-2-0_092085_2021-08-20_final
2021-08-21 10:07:36	ga_ls7e_ard_3-2-0_108075_2021-08-21_final
2021-08-25 09:40:32	ga_ls7e_ard_3-2-0_104070_2021-08-25_final
2021-08-26 10:28:54	ga_ls7e_ard_3-2-0_111083_2021-08-26_final
2021-08-28 08:38:41	ga_ls7e_ard_3-2-0_093086_2021-08-27_final
2021-09-02 08:50:24	ga_ls7e_ard_3-2-0_096070_2021-09-01_final
2021-09-04 08:44:39	ga_ls7e_ard_3-2-0_094087_2021-09-03_final
2021-09-05 09:23:50	ga_ls7e_ard_3-2-0_101077_2021-09-04_final
2021-09-07 10:50:59	ga_ls7e_ard_3-2-0_115079_2021-09-07_final
2021-09-08 08:20:23	ga_ls7e_ard_3-2-0_090089_2021-09-07_final
2021-09-08 09:54:05	ga_ls7e_ard_3-2-0_106076_2021-09-08_final
2021-09-08 09:56:52	ga_ls7e_ard_3-2-0_106083_2021-09-08_final
2021-09-15 08:23:57	ga_ls7e_ard_3-2-0_091084_2021-09-14_final
2021-09-16 09:00:44	ga_ls7e_ard_3-2-0_098068_2021-09-15_final
2021-09-19 09:34:10	ga_ls7e_ard_3-2-0_103075_2021-09-19_final
2021-09-20 10:17:20	ga_ls7e_ard_3-2-0_110075_2021-09-20_final
2021-10-01 09:55:49	ga_ls7e_ard_3-2-0_107070_2021-10-01_final
2021-10-01 09:59:48	ga_ls7e_ard_3-2-0_107080_2021-10-01_final
2021-10-02 09:03:42	ga_ls7e_ard_3-2-0_098079_2021-10-01_final
2021-10-02 09:04:06	ga_ls7e_ard_3-2-0_098080_2021-10-01_final
2021-10-09 09:09:40	ga_ls7e_ard_3-2-0_099080_2021-10-08_final
2021-10-15 08:32:27	ga_ls7e_ard_3-2-0_093081_2021-10-14_final
2021-10-18 08:58:17	ga_ls7e_ard_3-2-0_098069_2021-10-17_final
2021-10-18 09:04:17	ga_ls7e_ard_3-2-0_098084_2021-10-17_final
2021-10-19 08:07:22	ga_ls7e_ard_3-2-0_089081_2021-10-18_final
2021-10-23 09:17:58	ga_ls7e_ard_3-2-0_101073_2021-10-22_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-26 09:49:00	ga_ls7e_ard_3-2-0_106074_2021-10-26_final
2021-10-29 08:40:44	ga_ls7e_ard_3-2-0_095074_2021-10-28_final
2021-10-31 10:07:04	ga_ls7e_ard_3-2-0_109074_2021-10-31_final
2021-11-01 09:14:57	ga_ls7e_ard_3-2-0_100083_2021-10-31_final
2021-11-03 08:57:37	ga_ls7e_ard_3-2-0_098071_2021-11-02_final
2021-11-03 09:01:12	ga_ls7e_ard_3-2-0_098080_2021-11-02_final
2021-11-04 09:41:59	ga_ls7e_ard_3-2-0_105074_2021-11-04_final
2021-11-08 09:16:05	ga_ls7e_ard_3-2-0_101072_2021-11-07_final
2021-11-10 09:05:07	ga_ls7e_ard_3-2-0_099076_2021-11-09_final
2021-11-15 09:19:59	ga_ls7e_ard_3-2-1_102068_2021-11-14_final
2021-11-16 10:06:44	ga_ls7e_ard_3-2-1_109077_2021-11-16_final
2021-11-18 09:51:47	ga_ls7e_ard_3-2-1_107071_2021-11-18_final
2021-11-23 08:31:45	ga_ls7e_ard_3-2-1_094073_2021-11-22_final
2021-11-26 09:03:34	ga_ls7e_ard_3-2-1_099076_2021-11-25_final
2021-11-26 09:05:34	ga_ls7e_ard_3-2-1_099081_2021-11-25_final
2021-11-27 08:13:03	ga_ls7e_ard_3-2-1_090089_2021-11-26_final
2021-12-02 08:26:20	ga_ls7e_ard_3-2-1_093077_2021-12-01_final
2021-12-02 10:04:49	ga_ls7e_ard_3-2-1_109076_2021-12-02_final
2021-12-06 09:37:19	ga_ls7e_ard_3-2-1_105070_2021-12-06_final
2021-12-07 10:22:29	ga_ls7e_ard_3-2-1_112075_2021-12-07_final
2021-12-11 08:22:30	ga_ls7e_ard_3-2-1_092085_2021-12-10_final
2021-12-12 10:40:33	ga_ls7e_ard_3-2-1_115075_2021-12-12_final
2021-12-13 09:45:38	ga_ls7e_ard_3-2-1_106077_2021-12-13_final
2021-12-17 09:17:20	ga_ls7e_ard_3-2-1_102069_2021-12-16_final
2021-12-17 09:18:56	ga_ls7e_ard_3-2-1_102073_2021-12-16_final
2021-12-19 09:07:34	ga_ls7e_ard_3-2-1_100076_2021-12-18_final
2021-12-19 09:10:46	ga_ls7e_ard_3-2-1_100084_2021-12-18_final
2021-12-20 08:16:15	ga_ls7e_ard_3-2-1_091087_2021-12-19_final
2021-12-20 09:52:44	ga_ls7e_ard_3-2-1_107081_2021-12-20_final
2021-12-25 10:08:47	ga_ls7e_ard_3-2-1_110076_2021-12-25_final
2021-12-29 08:07:58	ga_ls7e_ard_3-2-1_090084_2021-12-28_final
2022-01-04 09:04:46	ga_ls7e_ard_3-2-1_100073_2022-01-03_final
2022-01-06 10:32:41	ga_ls7e_ard_3-2-1_114077_2022-01-06_final
2022-01-08 08:38:28	ga_ls7e_ard_3-2-1_096070_2022-01-07_final
2022-01-12 08:15:46	ga_ls7e_ard_3-2-1_092076_2022-01-11_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-15 10:28:04	ga_ls7e_ard_3-2-1_113083_2022-01-15_final
2022-01-24 08:40:09	ga_ls7e_ard_3-2-1_096078_2022-01-23_final
2022-01-24 08:40:33	ga_ls7e_ard_3-2-1_096079_2022-01-23_final
2022-01-26 08:29:11	ga_ls7e_ard_3-2-1_094082_2022-01-25_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-08 07:55:47	ga_ls7e_ard_3-2-1_089079_2022-02-07_final
2022-02-09 08:36:09	ga_ls7e_ard_3-2-1_096072_2022-02-08_final
2022-02-15 09:38:30	ga_ls7e_ard_3-2-1_106075_2022-02-15_final
2022-02-15 09:38:54	ga_ls7e_ard_3-2-1_106076_2022-02-15_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-19 09:11:49	ga_ls7e_ard_3-2-1_102071_2022-02-18_final
2022-02-19 09:14:12	ga_ls7e_ard_3-2-1_102077_2022-02-18_final
2022-02-21 08:59:16	ga_ls7e_ard_3-2-1_100071_2022-02-20_final
2022-02-22 08:09:08	ga_ls7e_ard_3-2-1_091085_2022-02-21_final
2022-02-26 09:17:43	ga_ls7e_ard_3-2-1_103072_2022-02-25_final
2022-03-03 09:37:47	ga_ls7e_ard_3-2-1_106077_2022-03-03_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-08 08:15:45	ga_ls7e_ard_3-2-1_093074_2022-03-07_final
2022-03-09 09:02:06	ga_ls7e_ard_3-2-1_100082_2022-03-08_final
2022-03-10 08:07:59	ga_ls7e_ard_3-2-1_091086_2022-03-09_final
2022-03-12 07:55:25	ga_ls7e_ard_3-2-1_089086_2022-03-11_final
2022-03-12 09:32:42	ga_ls7e_ard_3-2-1_105082_2022-03-12_final
2022-03-15 08:26:01	ga_ls7e_ard_3-2-1_094086_2022-03-14_final
2022-03-17 09:45:56	ga_ls7e_ard_3-2-1_108070_2022-03-17_final
2022-03-19 08:02:05	ga_ls7e_ard_3-2-1_090089_2022-03-18_final
2022-03-20 10:18:09	ga_ls7e_ard_3-2-1_113074_2022-03-20_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-26 08:05:13	ga_ls7e_ard_3-2-1_091083_2022-03-25_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