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
2021-09-18 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 08:50:35	ga_ls7e_ard_3-2-0_096074_2021-09-17_final
2021-09-20 08:40:27	ga_ls7e_ard_3-2-0_094080_2021-09-19_final
2021-09-25 08:56:56	ga_ls7e_ard_3-2-0_097076_2021-09-24_final
2021-09-26 09:40:06	ga_ls7e_ard_3-2-0_104076_2021-09-26_final
2021-09-28 09:28:46	ga_ls7e_ard_3-2-0_102079_2021-09-27_final
2021-10-08 10:04:34	ga_ls7e_ard_3-2-0_108078_2021-10-08_final
2021-10-10 09:52:02	ga_ls7e_ard_3-2-0_106078_2021-10-10_final
2021-10-12 09:36:42	ga_ls7e_ard_3-2-0_104071_2021-10-12_final
2021-10-12 09:39:30	ga_ls7e_ard_3-2-0_104078_2021-10-12_final
2021-10-13 08:45:23	ga_ls7e_ard_3-2-0_095082_2021-10-12_final
2021-10-13 10:22:16	ga_ls7e_ard_3-2-0_111077_2021-10-13_final
2021-10-15 10:11:44	ga_ls7e_ard_3-2-0_109082_2021-10-15_final
2021-10-17 09:55:36	ga_ls7e_ard_3-2-0_107073_2021-10-17_final
2021-10-25 09:05:26	ga_ls7e_ard_3-2-0_099073_2021-10-24_final
2021-10-25 09:08:37	ga_ls7e_ard_3-2-0_099081_2021-10-24_final
2021-10-26 08:12:55	ga_ls7e_ard_3-2-0_090081_2021-10-25_final
2021-10-28 09:36:51	ga_ls7e_ard_3-2-0_104075_2021-10-28_final
2021-10-29 10:20:49	ga_ls7e_ard_3-2-0_111077_2021-10-29_final
2021-10-30 09:23:07	ga_ls7e_ard_3-2-0_102072_2021-10-29_final
2021-10-31 08:29:00	ga_ls7e_ard_3-2-0_093076_2021-10-30_final
2021-10-31 10:10:16	ga_ls7e_ard_3-2-0_109082_2021-10-31_final
2021-11-12 10:32:15	ga_ls7e_ard_3-2-1_113078_2021-11-12_final
2021-11-14 08:41:37	ga_ls7e_ard_3-2-1_095080_2021-11-13_final
2021-11-17 09:12:37	ga_ls7e_ard_3-2-1_100081_2021-11-16_final
2021-11-20 09:39:14	ga_ls7e_ard_3-2-1_105071_2021-11-20_final
2021-11-23 08:32:57	ga_ls7e_ard_3-2-1_094076_2021-11-22_final
2021-11-30 10:17:45	ga_ls7e_ard_3-2-1_111077_2021-11-30_final
2021-12-03 09:10:18	ga_ls7e_ard_3-2-1_100079_2021-12-02_final
2021-12-05 08:55:21	ga_ls7e_ard_3-2-1_098073_2021-12-04_final
2021-12-06 09:41:43	ga_ls7e_ard_3-2-1_105081_2021-12-06_final
2021-12-07 08:43:36	ga_ls7e_ard_3-2-1_096075_2021-12-06_final
2021-12-09 10:11:08	ga_ls7e_ard_3-2-1_110078_2021-12-09_final
2021-12-10 09:14:37	ga_ls7e_ard_3-2-1_101076_2021-12-09_final
2021-12-12 09:00:52	ga_ls7e_ard_3-2-1_099073_2021-12-11_final
2021-12-12 09:02:04	ga_ls7e_ard_3-2-1_099076_2021-12-11_final
2021-12-13 09:46:02	ga_ls7e_ard_3-2-1_106078_2021-12-13_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-14 10:28:47	ga_ls7e_ard_3-2-1_113077_2021-12-14_final
2021-12-16 10:16:38	ga_ls7e_ard_3-2-1_111078_2021-12-16_final
2021-12-18 10:04:53	ga_ls7e_ard_3-2-1_109080_2021-12-18_final
2021-12-19 09:07:10	ga_ls7e_ard_3-2-1_100075_2021-12-18_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-22 09:36:59	ga_ls7e_ard_3-2-1_105073_2021-12-22_final
2021-12-23 08:42:28	ga_ls7e_ard_3-2-1_096076_2021-12-22_final
2021-12-23 10:22:56	ga_ls7e_ard_3-2-1_112080_2021-12-23_final
2021-12-25 08:31:06	ga_ls7e_ard_3-2-1_094079_2021-12-24_final
2021-12-25 10:10:46	ga_ls7e_ard_3-2-1_110081_2021-12-25_final
2021-12-30 08:48:20	ga_ls7e_ard_3-2-1_097077_2021-12-29_final
2022-01-01 08:35:22	ga_ls7e_ard_3-2-1_095076_2021-12-31_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-05 08:11:26	ga_ls7e_ard_3-2-1_091079_2022-01-04_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-09 09:24:50	ga_ls7e_ard_3-2-1_103078_2022-01-08_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-14 08:04:01	ga_ls7e_ard_3-2-1_090078_2022-01-13_final
2022-01-17 08:35:02	ga_ls7e_ard_3-2-1_095079_2022-01-16_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-21 09:48:25	ga_ls7e_ard_3-2-1_107078_2022-01-21_final
2022-01-24 10:18:13	ga_ls7e_ard_3-2-1_112076_2022-01-24_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-27 09:11:09	ga_ls7e_ard_3-2-1_101079_2022-01-26_final
2022-02-07 10:29:35	ga_ls7e_ard_3-2-1_114077_2022-02-07_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-11 08:26:22	ga_ls7e_ard_3-2-1_094079_2022-02-10_final
2022-02-11 08:26:46	ga_ls7e_ard_3-2-1_094080_2022-02-10_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-19 09:15:24	ga_ls7e_ard_3-2-1_102080_2022-02-18_final
2022-02-21 09:00:04	ga_ls7e_ard_3-2-1_100073_2022-02-20_final
2022-02-22 08:06:21	ga_ls7e_ard_3-2-1_091078_2022-02-21_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-24 09:32:40	ga_ls7e_ard_3-2-1_105078_2022-02-24_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-01 08:11:51	ga_ls7e_ard_3-2-1_092078_2022-02-28_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-06 08:28:42	ga_ls7e_ard_3-2-1_095075_2022-03-05_final
2022-03-11 10:26:25	ga_ls7e_ard_3-2-1_114077_2022-03-11_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-17 09:49:55	ga_ls7e_ard_3-2-1_108080_2022-03-17_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-25 09:00:08	ga_ls7e_ard_3-2-1_100081_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-26 09:41:42	ga_ls7e_ard_3-2-1_107077_2022-03-26_final
2022-03-26 09:42:30	ga_ls7e_ard_3-2-1_107079_2022-03-26_final
2022-04-03 08:49:54	ga_ls7e_ard_3-2-1_099073_2022-04-02_final
2022-04-05 10:18:12	ga_ls7e_ard_3-2-1_113078_2022-04-05_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