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 08:49:00	ga_ls7e_ard_3-2-0_096070_2021-09-17_final
2021-09-20 08:38:51	ga_ls7e_ard_3-2-0_094076_2021-09-19_final
2021-09-20 08:41:39	ga_ls7e_ard_3-2-0_094083_2021-09-19_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-10-26 09:48:36	ga_ls7e_ard_3-2-0_106073_2021-10-26_final
2021-11-04 09:43:58	ga_ls7e_ard_3-2-0_105079_2021-11-04_final
2021-11-05 10:28:20	ga_ls7e_ard_3-2-0_112082_2021-11-05_final
2021-11-08 09:17:40	ga_ls7e_ard_3-2-0_101076_2021-11-07_final
2021-11-10 10:43:36	ga_ls7e_ard_3-2-0_115075_2021-11-10_final
2021-11-18 09:53:47	ga_ls7e_ard_3-2-1_107076_2021-11-18_final
2021-11-19 08:57:40	ga_ls7e_ard_3-2-1_098075_2021-11-18_final
2021-11-27 09:48:20	ga_ls7e_ard_3-2-1_106080_2021-11-27_final
2021-11-28 08:51:01	ga_ls7e_ard_3-2-1_097076_2021-11-27_final
2021-11-30 10:15:46	ga_ls7e_ard_3-2-1_111072_2021-11-30_final
2021-11-30 10:19:45	ga_ls7e_ard_3-2-1_111082_2021-11-30_final
2021-12-03 09:10:18	ga_ls7e_ard_3-2-1_100079_2021-12-02_final
2021-12-05 08:54:33	ga_ls7e_ard_3-2-1_098071_2021-12-04_final
2021-12-07 10:24:28	ga_ls7e_ard_3-2-1_112080_2021-12-07_final
2021-12-08 09:29:10	ga_ls7e_ard_3-2-1_103081_2021-12-07_final
2021-12-10 09:16:13	ga_ls7e_ard_3-2-1_101080_2021-12-09_final
2021-12-12 09:00:52	ga_ls7e_ard_3-2-1_099073_2021-12-11_final
2021-12-14 10:28:47	ga_ls7e_ard_3-2-1_113077_2021-12-14_final
2021-12-18 10:01:41	ga_ls7e_ard_3-2-1_109072_2021-12-18_final
2021-12-18 10:02:05	ga_ls7e_ard_3-2-1_109073_2021-12-18_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-19 09:09:34	ga_ls7e_ard_3-2-1_100081_2021-12-18_final
2021-12-23 10:20:56	ga_ls7e_ard_3-2-1_112075_2021-12-23_final
2021-12-27 09:56:13	ga_ls7e_ard_3-2-1_108076_2021-12-27_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2022-01-01 08:35:22	ga_ls7e_ard_3-2-1_095076_2021-12-31_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-03 10:00:05	ga_ls7e_ard_3-2-1_109072_2022-01-03_final
2022-01-05 09:47:55	ga_ls7e_ard_3-2-1_107073_2022-01-05_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-08 08:38:28	ga_ls7e_ard_3-2-1_096070_2022-01-07_final
2022-01-08 08:42:52	ga_ls7e_ard_3-2-1_096081_2022-01-07_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-12 08:18:58	ga_ls7e_ard_3-2-1_092084_2022-01-11_final
2022-01-13 10:38:37	ga_ls7e_ard_3-2-1_115078_2022-01-13_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-15 08:46:23	ga_ls7e_ard_3-2-1_097076_2022-01-14_final
2022-01-15 08:47:11	ga_ls7e_ard_3-2-1_097078_2022-01-14_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-17 10:13:31	ga_ls7e_ard_3-2-1_111078_2022-01-17_final
2022-01-18 09:19:24	ga_ls7e_ard_3-2-1_102082_2022-01-17_final
2022-01-20 09:04:27	ga_ls7e_ard_3-2-1_100076_2022-01-19_final
2022-01-22 08:51:06	ga_ls7e_ard_3-2-1_098074_2022-01-21_final
2022-01-22 08:51:30	ga_ls7e_ard_3-2-1_098075_2022-01-21_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-30 08:02:52	ga_ls7e_ard_3-2-1_090079_2022-01-29_final
2022-01-31 08:45:14	ga_ls7e_ard_3-2-1_097077_2022-01-30_final
2022-02-02 10:11:57	ga_ls7e_ard_3-2-1_111078_2022-02-02_final
2022-02-05 09:02:28	ga_ls7e_ard_3-2-1_100075_2022-02-04_final
2022-02-07 08:49:30	ga_ls7e_ard_3-2-1_098074_2022-02-06_final
2022-02-07 08:49:54	ga_ls7e_ard_3-2-1_098075_2022-02-06_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-11 08:24:46	ga_ls7e_ard_3-2-1_094075_2022-02-10_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-16 08:44:47	ga_ls7e_ard_3-2-1_097080_2022-02-15_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-18 08:32:14	ga_ls7e_ard_3-2-1_095080_2022-02-17_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-18 10:11:31	ga_ls7e_ard_3-2-1_111081_2022-02-18_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-20 09:56:10	ga_ls7e_ard_3-2-1_109074_2022-02-20_final
2022-02-23 08:48:19	ga_ls7e_ard_3-2-1_098075_2022-02-22_final
2022-02-23 08:49:54	ga_ls7e_ard_3-2-1_098079_2022-02-22_final
2022-02-24 09:31:04	ga_ls7e_ard_3-2-1_105074_2022-02-24_final
2022-02-25 08:40:09	ga_ls7e_ard_3-2-1_096086_2022-02-24_final
2022-02-26 09:18:55	ga_ls7e_ard_3-2-1_103075_2022-02-25_final
2022-03-02 08:54:13	ga_ls7e_ard_3-2-1_099076_2022-03-01_final
2022-03-06 10:10:47	ga_ls7e_ard_3-2-1_111083_2022-03-06_final
2022-03-10 08:06:47	ga_ls7e_ard_3-2-1_091083_2022-03-09_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-12 07:54:37	ga_ls7e_ard_3-2-1_089084_2022-03-11_final
2022-03-12 09:30:18	ga_ls7e_ard_3-2-1_105076_2022-03-12_final
2022-03-13 08:36:35	ga_ls7e_ard_3-2-1_096081_2022-03-12_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-18 08:50:37	ga_ls7e_ard_3-2-1_099071_2022-03-17_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-20 08:39:16	ga_ls7e_ard_3-2-1_097074_2022-03-19_final
2022-03-20 10:18:56	ga_ls7e_ard_3-2-1_113076_2022-03-20_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-21 09:24:26	ga_ls7e_ard_3-2-1_104079_2022-03-20_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-28 09:25:34	ga_ls7e_ard_3-2-1_105068_2022-03-27_final
2022-03-28 09:26:22	ga_ls7e_ard_3-2-1_105070_2022-03-27_final
2022-03-30 09:13:49	ga_ls7e_ard_3-2-1_103070_2022-03-29_final
2022-04-01 09:02:03	ga_ls7e_ard_3-2-1_101072_2022-03-31_final
2022-04-01 09:03:15	ga_ls7e_ard_3-2-1_101075_2022-03-31_final
2022-04-02 09:49:12	ga_ls7e_ard_3-2-1_108082_2022-04-02_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_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