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
2021-03-20 09:45:07	ga_ls7e_ard_3-2-0_102079_2021-03-20_final
2021-07-26 09:31:37	ga_ls7e_ard_3-2-0_102072_2021-07-26_final
2021-07-27 08:39:06	ga_ls7e_ard_3-2-0_093080_2021-07-26_final
2021-07-28 09:21:52	ga_ls7e_ard_3-2-0_100079_2021-07-27_final
2021-08-05 10:10:12	ga_ls7e_ard_3-2-0_108078_2021-08-05_final
2021-08-24 08:59:21	ga_ls7e_ard_3-2-0_097075_2021-08-23_final
2021-08-24 08:59:45	ga_ls7e_ard_3-2-0_097076_2021-08-23_final
2021-08-26 10:26:30	ga_ls7e_ard_3-2-0_111077_2021-08-26_final
2021-08-26 10:26:54	ga_ls7e_ard_3-2-0_111078_2021-08-26_final
2021-08-29 09:16:40	ga_ls7e_ard_3-2-0_100073_2021-08-28_final
2021-08-29 09:19:28	ga_ls7e_ard_3-2-0_100080_2021-08-28_final
2021-08-31 09:04:56	ga_ls7e_ard_3-2-0_098075_2021-08-30_final
2021-09-01 09:50:06	ga_ls7e_ard_3-2-0_105080_2021-09-01_final
2021-09-02 08:51:12	ga_ls7e_ard_3-2-0_096072_2021-09-01_final
2021-09-02 10:33:17	ga_ls7e_ard_3-2-0_112080_2021-09-02_final
2021-09-04 08:41:04	ga_ls7e_ard_3-2-0_094078_2021-09-03_final
2021-09-08 08:17:12	ga_ls7e_ard_3-2-0_090081_2021-09-07_final
2021-09-08 09:55:16	ga_ls7e_ard_3-2-0_106079_2021-09-08_final
2021-09-09 08:58:22	ga_ls7e_ard_3-2-0_097076_2021-09-08_final
2021-09-09 09:01:10	ga_ls7e_ard_3-2-0_097083_2021-09-08_final
2021-09-10 09:39:33	ga_ls7e_ard_3-2-0_104071_2021-09-10_final
2021-09-10 09:41:08	ga_ls7e_ard_3-2-0_104075_2021-09-10_final
2021-09-11 10:25:54	ga_ls7e_ard_3-2-0_111079_2021-09-11_final
2021-09-13 08:33:18	ga_ls7e_ard_3-2-0_093076_2021-09-12_final
2021-09-13 08:35:17	ga_ls7e_ard_3-2-0_093081_2021-09-12_final
2021-09-15 10:00:50	ga_ls7e_ard_3-2-0_107079_2021-09-15_final
2021-09-16 10:39:13	ga_ls7e_ard_3-2-0_114067_2021-09-16_final
2021-09-18 08:53:23	ga_ls7e_ard_3-2-0_096081_2021-09-17_final
2021-09-22 08:28:18	ga_ls7e_ard_3-2-0_092081_2021-09-21_final
2021-09-22 10:08:23	ga_ls7e_ard_3-2-0_108084_2021-09-22_final
2021-09-24 08:15:22	ga_ls7e_ard_3-2-0_090080_2021-09-23_final
2021-09-24 08:15:46	ga_ls7e_ard_3-2-0_090081_2021-09-23_final
2021-10-01 09:59:00	ga_ls7e_ard_3-2-0_107078_2021-10-01_final
2021-10-02 09:04:30	ga_ls7e_ard_3-2-0_098081_2021-10-01_final
2021-10-04 08:48:46	ga_ls7e_ard_3-2-0_096073_2021-10-03_final
2021-10-04 10:29:38	ga_ls7e_ard_3-2-0_112078_2021-10-04_final
2021-10-06 08:37:02	ga_ls7e_ard_3-2-0_094075_2021-10-05_final
2021-10-06 08:37:26	ga_ls7e_ard_3-2-0_094076_2021-10-05_final
2021-10-06 08:38:14	ga_ls7e_ard_3-2-0_094078_2021-10-05_final
2021-10-11 10:34:48	ga_ls7e_ard_3-2-0_113077_2021-10-11_final
2021-10-12 09:39:54	ga_ls7e_ard_3-2-0_104079_2021-10-12_final
2021-10-14 09:27:22	ga_ls7e_ard_3-2-0_102079_2021-10-13_final
2021-10-15 10:10:32	ga_ls7e_ard_3-2-0_109079_2021-10-15_final
2021-10-18 09:00:17	ga_ls7e_ard_3-2-0_098074_2021-10-17_final
2021-10-20 08:48:09	ga_ls7e_ard_3-2-0_096075_2021-10-19_final
2021-10-20 08:49:20	ga_ls7e_ard_3-2-0_096078_2021-10-19_final
2021-10-21 09:32:55	ga_ls7e_ard_3-2-0_103079_2021-10-21_final
2021-10-29 10:21:37	ga_ls7e_ard_3-2-0_111079_2021-10-29_final
2021-11-15 09:25:34	ga_ls7e_ard_3-2-1_102082_2021-11-14_final
2021-11-16 08:28:39	ga_ls7e_ard_3-2-1_093079_2021-11-15_final
2021-11-20 09:40:01	ga_ls7e_ard_3-2-1_105073_2021-11-20_final
2021-11-28 10:31:06	ga_ls7e_ard_3-2-1_113079_2021-11-28_final
2021-12-09 08:32:15	ga_ls7e_ard_3-2-1_094078_2021-12-08_final
2021-12-14 10:29:35	ga_ls7e_ard_3-2-1_113079_2021-12-14_final
2022-01-01 08:36:10	ga_ls7e_ard_3-2-1_095078_2021-12-31_final
2022-01-01 10:15:51	ga_ls7e_ard_3-2-1_111080_2022-01-01_final
2022-01-03 10:02:29	ga_ls7e_ard_3-2-1_109078_2022-01-03_final
2022-01-05 09:49:55	ga_ls7e_ard_3-2-1_107078_2022-01-05_final
2022-01-08 08:40:28	ga_ls7e_ard_3-2-1_096075_2022-01-07_final
2022-01-08 08:41:16	ga_ls7e_ard_3-2-1_096077_2022-01-07_final
2022-01-08 10:20:32	ga_ls7e_ard_3-2-1_112078_2022-01-08_final
2022-01-10 08:28:19	ga_ls7e_ard_3-2-1_094076_2022-01-09_final
2022-01-10 08:29:31	ga_ls7e_ard_3-2-1_094079_2022-01-09_final
2022-01-10 10:08:00	ga_ls7e_ard_3-2-1_110078_2022-01-10_final
2022-01-10 10:08:24	ga_ls7e_ard_3-2-1_110079_2022-01-10_final
2022-01-11 09:13:05	ga_ls7e_ard_3-2-1_101080_2022-01-10_final
2022-01-15 08:46:00	ga_ls7e_ard_3-2-1_097075_2022-01-14_final
2022-01-15 08:46:47	ga_ls7e_ard_3-2-1_097077_2022-01-14_final
2022-01-17 08:35:26	ga_ls7e_ard_3-2-1_095080_2022-01-16_final
2022-01-26 10:06:28	ga_ls7e_ard_3-2-1_110078_2022-01-26_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-02-01 09:29:59	ga_ls7e_ard_3-2-1_104081_2022-01-31_final
2022-02-04 10:00:11	ga_ls7e_ard_3-2-1_109080_2022-02-04_final
2022-02-09 08:37:44	ga_ls7e_ard_3-2-1_096076_2022-02-08_final
2022-02-09 10:17:01	ga_ls7e_ard_3-2-1_112077_2022-02-09_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-17 09:25:57	ga_ls7e_ard_3-2-1_104075_2022-02-16_final
2022-02-18 08:30:38	ga_ls7e_ard_3-2-1_095076_2022-02-17_final
2022-02-18 08:31:26	ga_ls7e_ard_3-2-1_095078_2022-02-17_final
2022-02-18 10:10:43	ga_ls7e_ard_3-2-1_111079_2022-02-18_final
2022-02-20 08:20:29	ga_ls7e_ard_3-2-1_093082_2022-02-19_final
2022-02-25 10:15:26	ga_ls7e_ard_3-2-1_112077_2022-02-25_final
2022-02-25 10:15:50	ga_ls7e_ard_3-2-1_112078_2022-02-25_final
2022-02-26 09:18:31	ga_ls7e_ard_3-2-1_103074_2022-02-25_final
2022-02-27 10:03:17	ga_ls7e_ard_3-2-1_110078_2022-02-27_final
2022-03-04 08:43:15	ga_ls7e_ard_3-2-1_097080_2022-03-03_final
2022-03-04 08:44:27	ga_ls7e_ard_3-2-1_097083_2022-03-03_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-13 08:35:23	ga_ls7e_ard_3-2-1_096078_2022-03-12_final
2022-03-13 08:37:23	ga_ls7e_ard_3-2-1_096083_2022-03-12_final
2022-03-17 08:10:15	ga_ls7e_ard_3-2-1_092078_2022-03-16_final
2022-03-17 08:10:39	ga_ls7e_ard_3-2-1_092079_2022-03-16_final
2022-03-18 08:52:36	ga_ls7e_ard_3-2-1_099076_2022-03-17_final
2022-03-22 08:28:43	ga_ls7e_ard_3-2-1_095079_2022-03-21_final
2022-03-22 10:06:48	ga_ls7e_ard_3-2-1_111077_2022-03-22_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-24 08:17:22	ga_ls7e_ard_3-2-1_093082_2022-03-23_final
2022-03-24 09:54:39	ga_ls7e_ard_3-2-1_109078_2022-03-24_final
2022-03-29 10:12:19	ga_ls7e_ard_3-2-1_112077_2022-03-29_final
2022-04-03 08:53:05	ga_ls7e_ard_3-2-1_099081_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years