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
2021-07-21 09:13:54	ga_ls7e_ard_3-2-0_099073_2021-07-20_final
2021-07-23 09:04:34	ga_ls7e_ard_3-2-0_097081_2021-07-22_final
2021-07-26 09:31:13	ga_ls7e_ard_3-2-0_102071_2021-07-26_final
2021-08-04 09:25:02	ga_ls7e_ard_3-2-0_101073_2021-08-03_final
2021-08-04 09:25:26	ga_ls7e_ard_3-2-0_101074_2021-08-03_final
2021-08-08 08:59:58	ga_ls7e_ard_3-2-0_097073_2021-08-07_final
2021-08-12 08:36:05	ga_ls7e_ard_3-2-0_093076_2021-08-11_final
2021-08-23 08:20:34	ga_ls7e_ard_3-2-0_090086_2021-08-22_final
2021-08-28 08:34:42	ga_ls7e_ard_3-2-0_093076_2021-08-27_final
2021-08-30 10:02:38	ga_ls7e_ard_3-2-0_107080_2021-08-30_final
2021-09-01 09:46:31	ga_ls7e_ard_3-2-0_105071_2021-09-01_final
2021-09-03 09:34:47	ga_ls7e_ard_3-2-0_103073_2021-09-03_final
2021-09-04 10:21:32	ga_ls7e_ard_3-2-0_110082_2021-09-04_final
2021-09-04 10:21:56	ga_ls7e_ard_3-2-0_110083_2021-09-04_final
2021-09-06 10:06:37	ga_ls7e_ard_3-2-0_108076_2021-09-06_final
2021-09-09 08:59:58	ga_ls7e_ard_3-2-0_097080_2021-09-08_final
2021-09-13 10:10:59	ga_ls7e_ard_3-2-0_109073_2021-09-13_final
2021-09-15 08:23:33	ga_ls7e_ard_3-2-0_091083_2021-09-14_final
2021-09-15 09:58:26	ga_ls7e_ard_3-2-0_107073_2021-09-15_final
2021-09-18 10:32:40	ga_ls7e_ard_3-2-0_112082_2021-09-18_final
2021-09-19 09:32:34	ga_ls7e_ard_3-2-0_103071_2021-09-19_final
2021-09-20 10:18:08	ga_ls7e_ard_3-2-0_110077_2021-09-20_final
2021-09-23 09:08:17	ga_ls7e_ard_3-2-0_099073_2021-09-22_final
2021-09-23 09:11:52	ga_ls7e_ard_3-2-0_099082_2021-09-22_final
2021-09-24 09:53:27	ga_ls7e_ard_3-2-0_106078_2021-09-24_final
2021-09-28 09:27:34	ga_ls7e_ard_3-2-0_102076_2021-09-27_final
2021-10-02 09:01:18	ga_ls7e_ard_3-2-0_098073_2021-10-01_final
2021-10-03 08:09:35	ga_ls7e_ard_3-2-0_089083_2021-10-02_final
2021-10-03 09:43:41	ga_ls7e_ard_3-2-0_105071_2021-10-03_final
2021-10-06 08:39:26	ga_ls7e_ard_3-2-0_094081_2021-10-05_final
2021-10-08 10:06:10	ga_ls7e_ard_3-2-0_108082_2021-10-08_final
2021-10-09 09:08:04	ga_ls7e_ard_3-2-0_099076_2021-10-08_final
2021-10-13 08:47:23	ga_ls7e_ard_3-2-0_095087_2021-10-12_final
2021-10-17 08:19:31	ga_ls7e_ard_3-2-0_091080_2021-10-16_final
2021-10-18 10:41:10	ga_ls7e_ard_3-2-0_114079_2021-10-18_final
2021-10-22 08:37:36	ga_ls7e_ard_3-2-0_094080_2021-10-21_final
2021-10-23 09:21:34	ga_ls7e_ard_3-2-0_101082_2021-10-22_final
2021-10-24 10:00:44	ga_ls7e_ard_3-2-0_108072_2021-10-24_final
2021-10-28 09:35:39	ga_ls7e_ard_3-2-0_104072_2021-10-28_final
2021-10-29 10:20:49	ga_ls7e_ard_3-2-0_111077_2021-10-29_final
2021-10-30 09:27:06	ga_ls7e_ard_3-2-0_102082_2021-10-29_final
2021-11-08 09:16:53	ga_ls7e_ard_3-2-0_101074_2021-11-07_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-17 09:10:13	ga_ls7e_ard_3-2-1_100075_2021-11-16_final
2021-11-20 08:03:56	ga_ls7e_ard_3-2-1_089080_2021-11-19_final
2021-11-20 09:38:50	ga_ls7e_ard_3-2-1_105070_2021-11-20_final
2021-11-26 09:02:22	ga_ls7e_ard_3-2-1_099073_2021-11-25_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-04 08:14:35	ga_ls7e_ard_3-2-1_091079_2021-12-03_final
2021-12-06 09:38:07	ga_ls7e_ard_3-2-1_105072_2021-12-06_final
2021-12-07 08:46:24	ga_ls7e_ard_3-2-1_096082_2021-12-06_final
2021-12-08 09:28:46	ga_ls7e_ard_3-2-1_103080_2021-12-07_final
2021-12-11 09:58:59	ga_ls7e_ard_3-2-1_108079_2021-12-11_final
2021-12-11 10:00:10	ga_ls7e_ard_3-2-1_108082_2021-12-11_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-17 09:22:31	ga_ls7e_ard_3-2-1_102082_2021-12-16_final
2021-12-18 08:26:24	ga_ls7e_ard_3-2-1_093081_2021-12-17_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-23 08:46:03	ga_ls7e_ard_3-2-1_096085_2021-12-22_final
2021-12-27 09:54:37	ga_ls7e_ard_3-2-1_108072_2021-12-27_final
2021-12-27 09:56:13	ga_ls7e_ard_3-2-1_108076_2021-12-27_final
2021-12-29 08:10:22	ga_ls7e_ard_3-2-1_090090_2021-12-28_final
2022-01-01 10:14:39	ga_ls7e_ard_3-2-1_111077_2022-01-01_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-05 09:50:43	ga_ls7e_ard_3-2-1_107080_2022-01-05_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-07 09:38:34	ga_ls7e_ard_3-2-1_105081_2022-01-07_final
2022-01-08 10:21:44	ga_ls7e_ard_3-2-1_112081_2022-01-08_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-12 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-21 08:12:44	ga_ls7e_ard_3-2-1_091086_2022-01-20_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-02-04 08:21:19	ga_ls7e_ard_3-2-1_093080_2022-02-03_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-14 08:58:09	ga_ls7e_ard_3-2-1_099082_2022-02-13_final
2022-02-17 09:26:45	ga_ls7e_ard_3-2-1_104077_2022-02-16_final
2022-02-18 08:33:26	ga_ls7e_ard_3-2-1_095083_2022-02-17_final
2022-02-25 08:35:22	ga_ls7e_ard_3-2-1_096074_2022-02-24_final
2022-02-25 08:38:57	ga_ls7e_ard_3-2-1_096083_2022-02-24_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-01 09:52:20	ga_ls7e_ard_3-2-1_108082_2022-03-01_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-04 10:23:20	ga_ls7e_ard_3-2-1_113083_2022-03-04_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-13 08:33:47	ga_ls7e_ard_3-2-1_096074_2022-03-12_final
2022-03-17 08:11:27	ga_ls7e_ard_3-2-1_092081_2022-03-16_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-21 09:20:26	ga_ls7e_ard_3-2-1_104069_2022-03-20_final
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-22 10:05:36	ga_ls7e_ard_3-2-1_111074_2022-03-22_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-25 08:59:44	ga_ls7e_ard_3-2-1_100080_2022-03-24_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_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