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
2021-08-22 09:15:05	ga_ls7e_ard_3-2-0_099083_2021-08-21_final
2021-08-23 08:17:47	ga_ls7e_ard_3-2-0_090079_2021-08-22_final
2021-08-23 08:18:59	ga_ls7e_ard_3-2-0_090082_2021-08-22_final
2021-08-24 09:01:45	ga_ls7e_ard_3-2-0_097081_2021-08-23_final
2021-08-24 10:41:02	ga_ls7e_ard_3-2-0_113082_2021-08-24_final
2021-09-06 08:28:32	ga_ls7e_ard_3-2-0_092078_2021-09-05_final
2021-09-10 09:38:45	ga_ls7e_ard_3-2-0_104069_2021-09-10_final
2021-09-23 09:07:29	ga_ls7e_ard_3-2-0_099071_2021-09-22_final
2021-10-02 09:03:42	ga_ls7e_ard_3-2-0_098079_2021-10-01_final
2021-10-04 08:51:10	ga_ls7e_ard_3-2-0_096079_2021-10-03_final
2021-10-06 10:14:19	ga_ls7e_ard_3-2-0_110071_2021-10-06_final
2021-10-06 10:15:31	ga_ls7e_ard_3-2-0_110074_2021-10-06_final
2021-10-08 08:28:05	ga_ls7e_ard_3-2-0_092084_2021-10-07_final
2021-10-09 09:09:40	ga_ls7e_ard_3-2-0_099080_2021-10-08_final
2021-10-11 10:35:36	ga_ls7e_ard_3-2-0_113079_2021-10-11_final
2021-10-14 09:24:34	ga_ls7e_ard_3-2-0_102072_2021-10-13_final
2021-10-14 09:24:58	ga_ls7e_ard_3-2-0_102073_2021-10-13_final
2021-10-15 08:34:27	ga_ls7e_ard_3-2-0_093086_2021-10-14_final
2021-10-18 08:57:54	ga_ls7e_ard_3-2-0_098068_2021-10-17_final
2021-10-31 10:11:04	ga_ls7e_ard_3-2-0_109084_2021-10-31_final
2021-11-03 10:39:41	ga_ls7e_ard_3-2-0_114079_2021-11-03_final
2021-11-07 10:13:23	ga_ls7e_ard_3-2-0_110076_2021-11-07_final
2021-11-11 09:47:29	ga_ls7e_ard_3-2-0_106074_2021-11-11_final
2021-11-12 10:31:27	ga_ls7e_ard_3-2-1_113076_2021-11-12_final
2021-11-14 08:42:00	ga_ls7e_ard_3-2-1_095081_2021-11-13_final
2021-11-16 10:06:20	ga_ls7e_ard_3-2-1_109076_2021-11-16_final
2021-11-19 08:54:28	ga_ls7e_ard_3-2-1_098067_2021-11-18_final
2021-11-19 10:37:20	ga_ls7e_ard_3-2-1_114077_2021-11-19_final
2021-11-21 08:43:07	ga_ls7e_ard_3-2-1_096070_2021-11-20_final
2021-11-21 10:23:59	ga_ls7e_ard_3-2-1_112075_2021-11-21_final
2021-11-23 08:33:45	ga_ls7e_ard_3-2-1_094078_2021-11-22_final
2021-11-23 10:14:13	ga_ls7e_ard_3-2-1_110082_2021-11-23_final
2021-11-26 09:03:34	ga_ls7e_ard_3-2-1_099076_2021-11-25_final
2021-11-27 09:47:32	ga_ls7e_ard_3-2-1_106078_2021-11-27_final
2021-11-28 08:51:49	ga_ls7e_ard_3-2-1_097078_2021-11-27_final
2021-11-30 10:15:22	ga_ls7e_ard_3-2-1_111071_2021-11-30_final
2021-11-30 10:16:09	ga_ls7e_ard_3-2-1_111073_2021-11-30_final
2021-12-02 10:02:25	ga_ls7e_ard_3-2-1_109070_2021-12-02_final
2021-12-02 10:05:12	ga_ls7e_ard_3-2-1_109077_2021-12-02_final
2021-12-05 10:37:25	ga_ls7e_ard_3-2-1_114081_2021-12-05_final
2021-12-09 10:11:08	ga_ls7e_ard_3-2-1_110078_2021-12-09_final
2021-12-10 09:15:49	ga_ls7e_ard_3-2-1_101079_2021-12-09_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-13 09:42:02	ga_ls7e_ard_3-2-1_106068_2021-12-13_final
2021-12-16 10:16:14	ga_ls7e_ard_3-2-1_111077_2021-12-16_final
2021-12-17 09:18:56	ga_ls7e_ard_3-2-1_102073_2021-12-16_final
2021-12-22 09:38:34	ga_ls7e_ard_3-2-1_105077_2021-12-22_final
2021-12-25 10:07:11	ga_ls7e_ard_3-2-1_110072_2021-12-25_final
2021-12-27 09:54:37	ga_ls7e_ard_3-2-1_108072_2021-12-27_final
2022-01-05 08:11:26	ga_ls7e_ard_3-2-1_091079_2022-01-04_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-12 09:51:52	ga_ls7e_ard_3-2-1_108069_2022-01-12_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-15 10:25:40	ga_ls7e_ard_3-2-1_113077_2022-01-15_final
2022-01-15 10:26:28	ga_ls7e_ard_3-2-1_113079_2022-01-15_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-20 09:07:15	ga_ls7e_ard_3-2-1_100083_2022-01-19_final
2022-01-21 08:13:32	ga_ls7e_ard_3-2-1_091088_2022-01-20_final
2022-01-23 07:56:35	ga_ls7e_ard_3-2-1_089077_2022-01-22_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-25 09:22:54	ga_ls7e_ard_3-2-1_103077_2022-01-24_final
2022-01-26 10:04:28	ga_ls7e_ard_3-2-1_110073_2022-01-26_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-02-03 09:16:14	ga_ls7e_ard_3-2-1_102078_2022-02-02_final
2022-02-04 10:01:23	ga_ls7e_ard_3-2-1_109083_2022-02-04_final
2022-02-09 10:15:49	ga_ls7e_ard_3-2-1_112074_2022-02-09_final
2022-02-13 09:51:29	ga_ls7e_ard_3-2-1_108076_2022-02-13_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-17 09:25:09	ga_ls7e_ard_3-2-1_104073_2022-02-16_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-19 09:14:36	ga_ls7e_ard_3-2-1_102078_2022-02-18_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-02-25 08:38:57	ga_ls7e_ard_3-2-1_096083_2022-02-24_final
2022-02-25 10:14:14	ga_ls7e_ard_3-2-1_112074_2022-02-25_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-04 08:40:52	ga_ls7e_ard_3-2-1_097074_2022-03-03_final
2022-03-08 08:21:20	ga_ls7e_ard_3-2-1_093088_2022-03-07_final
2022-03-10 08:04:23	ga_ls7e_ard_3-2-1_091077_2022-03-09_final
2022-03-11 08:49:08	ga_ls7e_ard_3-2-1_098081_2022-03-10_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-13 08:33:47	ga_ls7e_ard_3-2-1_096074_2022-03-12_final
2022-03-15 09:59:18	ga_ls7e_ard_3-2-1_110072_2022-03-15_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-17 08:13:26	ga_ls7e_ard_3-2-1_092086_2022-03-16_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-19 08:02:05	ga_ls7e_ard_3-2-1_090089_2022-03-18_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-20 08:42:04	ga_ls7e_ard_3-2-1_097081_2022-03-19_final
2022-03-20 10:18:09	ga_ls7e_ard_3-2-1_113074_2022-03-20_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_final
2022-03-26 08:06:49	ga_ls7e_ard_3-2-1_091087_2022-03-25_final
2022-03-27 08:43:36	ga_ls7e_ard_3-2-1_098071_2022-03-26_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-27 08:46:47	ga_ls7e_ard_3-2-1_098079_2022-03-26_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-04-03 08:52:17	ga_ls7e_ard_3-2-1_099079_2022-04-02_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years