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
2021-03-25 08:24:47	ga_ls7e_ard_3-2-0_089080_2021-03-24_final
2021-09-18 08:49:48	ga_ls7e_ard_3-2-0_096072_2021-09-17_final
2021-09-18 10:31:28	ga_ls7e_ard_3-2-0_112079_2021-09-18_final
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-11-20 09:41:37	ga_ls7e_ard_3-2-1_105077_2021-11-20_final
2021-11-21 08:45:06	ga_ls7e_ard_3-2-1_096075_2021-11-20_final
2021-11-22 09:25:52	ga_ls7e_ard_3-2-1_103069_2021-11-21_final
2021-11-23 08:32:33	ga_ls7e_ard_3-2-1_094075_2021-11-22_final
2021-11-29 09:36:11	ga_ls7e_ard_3-2-1_104081_2021-11-29_final
2021-12-02 10:06:48	ga_ls7e_ard_3-2-1_109081_2021-12-02_final
2021-12-04 08:18:10	ga_ls7e_ard_3-2-1_091088_2021-12-03_final
2021-12-04 09:51:04	ga_ls7e_ard_3-2-1_107073_2021-12-04_final
2021-12-06 09:39:19	ga_ls7e_ard_3-2-1_105075_2021-12-06_final
2021-12-19 09:09:58	ga_ls7e_ard_3-2-1_100082_2021-12-18_final
2021-12-20 09:49:32	ga_ls7e_ard_3-2-1_107073_2021-12-20_final
2021-12-23 10:20:56	ga_ls7e_ard_3-2-1_112075_2021-12-23_final
2021-12-25 10:10:22	ga_ls7e_ard_3-2-1_110080_2021-12-25_final
2021-12-28 09:02:54	ga_ls7e_ard_3-2-1_099082_2021-12-27_final
2021-12-29 08:10:22	ga_ls7e_ard_3-2-1_090090_2021-12-28_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2021-12-30 08:51:08	ga_ls7e_ard_3-2-1_097084_2021-12-29_final
2021-12-30 08:51:32	ga_ls7e_ard_3-2-1_097085_2021-12-29_final
2022-01-01 08:36:10	ga_ls7e_ard_3-2-1_095078_2021-12-31_final
2022-01-01 10:14:39	ga_ls7e_ard_3-2-1_111077_2022-01-01_final
2022-01-02 09:17:44	ga_ls7e_ard_3-2-1_102074_2022-01-01_final
2022-01-07 09:37:22	ga_ls7e_ard_3-2-1_105078_2022-01-07_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-08 10:20:32	ga_ls7e_ard_3-2-1_112078_2022-01-08_final
2022-01-09 09:20:50	ga_ls7e_ard_3-2-1_103068_2022-01-08_final
2022-01-11 09:13:05	ga_ls7e_ard_3-2-1_101080_2022-01-10_final
2022-01-14 08:03:38	ga_ls7e_ard_3-2-1_090077_2022-01-13_final
2022-01-17 08:35:02	ga_ls7e_ard_3-2-1_095079_2022-01-16_final
2022-01-17 10:13:31	ga_ls7e_ard_3-2-1_111078_2022-01-17_final
2022-01-18 09:16:12	ga_ls7e_ard_3-2-1_102074_2022-01-17_final
2022-01-18 09:17:24	ga_ls7e_ard_3-2-1_102077_2022-01-17_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-24 10:17:49	ga_ls7e_ard_3-2-1_112075_2022-01-24_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-02-03 09:13:02	ga_ls7e_ard_3-2-1_102070_2022-02-02_final
2022-02-03 09:13:50	ga_ls7e_ard_3-2-1_102072_2022-02-02_final
2022-02-03 09:16:38	ga_ls7e_ard_3-2-1_102079_2022-02-02_final
2022-02-04 08:21:43	ga_ls7e_ard_3-2-1_093081_2022-02-03_final
2022-02-04 08:23:42	ga_ls7e_ard_3-2-1_093086_2022-02-03_final
2022-02-05 09:04:52	ga_ls7e_ard_3-2-1_100081_2022-02-04_final
2022-02-06 08:09:57	ga_ls7e_ard_3-2-1_091083_2022-02-05_final
2022-02-06 09:48:25	ga_ls7e_ard_3-2-1_107082_2022-02-06_final
2022-02-07 08:52:18	ga_ls7e_ard_3-2-1_098081_2022-02-06_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-09 08:36:09	ga_ls7e_ard_3-2-1_096072_2022-02-08_final
2022-02-09 08:38:32	ga_ls7e_ard_3-2-1_096078_2022-02-08_final
2022-02-09 10:17:49	ga_ls7e_ard_3-2-1_112079_2022-02-09_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-10 09:21:41	ga_ls7e_ard_3-2-1_103078_2022-02-09_final
2022-02-10 09:22:05	ga_ls7e_ard_3-2-1_103079_2022-02-09_final
2022-02-14 08:57:45	ga_ls7e_ard_3-2-1_099081_2022-02-13_final
2022-02-18 10:11:07	ga_ls7e_ard_3-2-1_111080_2022-02-18_final
2022-02-18 10:12:43	ga_ls7e_ard_3-2-1_111084_2022-02-18_final
2022-02-20 08:20:05	ga_ls7e_ard_3-2-1_093081_2022-02-19_final
2022-02-20 09:58:58	ga_ls7e_ard_3-2-1_109081_2022-02-20_final
2022-02-22 09:44:01	ga_ls7e_ard_3-2-1_107075_2022-02-22_final
2022-02-22 09:44:25	ga_ls7e_ard_3-2-1_107076_2022-02-22_final
2022-02-22 09:44:49	ga_ls7e_ard_3-2-1_107077_2022-02-22_final
2022-02-22 09:46:49	ga_ls7e_ard_3-2-1_107082_2022-02-22_final
2022-02-24 09:30:40	ga_ls7e_ard_3-2-1_105073_2022-02-24_final
2022-02-25 10:15:02	ga_ls7e_ard_3-2-1_112076_2022-02-25_final
2022-02-25 10:17:02	ga_ls7e_ard_3-2-1_112081_2022-02-25_final
2022-02-27 08:22:25	ga_ls7e_ard_3-2-1_094073_2022-02-26_final
2022-02-28 09:06:22	ga_ls7e_ard_3-2-1_101075_2022-02-27_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-02 08:57:01	ga_ls7e_ard_3-2-1_099083_2022-03-01_final
2022-03-05 09:22:02	ga_ls7e_ard_3-2-1_104069_2022-03-04_final
2022-03-05 09:26:01	ga_ls7e_ard_3-2-1_104079_2022-03-04_final
2022-03-06 08:30:18	ga_ls7e_ard_3-2-1_095079_2022-03-05_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-07 09:14:16	ga_ls7e_ard_3-2-1_102081_2022-03-06_final
2022-03-07 09:14:40	ga_ls7e_ard_3-2-1_102082_2022-03-06_final
2022-03-09 08:57:43	ga_ls7e_ard_3-2-1_100071_2022-03-08_final
2022-03-11 08:49:32	ga_ls7e_ard_3-2-1_098082_2022-03-10_final
2022-03-13 08:35:47	ga_ls7e_ard_3-2-1_096079_2022-03-12_final
2022-03-13 10:13:04	ga_ls7e_ard_3-2-1_112075_2022-03-13_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-18 08:50:37	ga_ls7e_ard_3-2-1_099071_2022-03-17_final
2022-03-19 07:57:18	ga_ls7e_ard_3-2-1_090077_2022-03-18_final
2022-03-22 10:06:24	ga_ls7e_ard_3-2-1_111076_2022-03-22_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-25 09:00:08	ga_ls7e_ard_3-2-1_100081_2022-03-24_final
2022-03-25 09:00:56	ga_ls7e_ard_3-2-1_100083_2022-03-24_final
2022-03-26 08:02:49	ga_ls7e_ard_3-2-1_091077_2022-03-25_final
2022-03-26 08:07:13	ga_ls7e_ard_3-2-1_091088_2022-03-25_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-29 08:33:02	ga_ls7e_ard_3-2-1_096076_2022-03-28_final
2022-03-29 08:34:14	ga_ls7e_ard_3-2-1_096079_2022-03-28_final
2022-03-30 09:17:24	ga_ls7e_ard_3-2-1_103079_2022-03-29_final
2022-03-31 08:20:29	ga_ls7e_ard_3-2-1_094076_2022-03-30_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_final
2022-03-31 08:22:53	ga_ls7e_ard_3-2-1_094082_2022-03-30_final
2022-04-03 08:53:53	ga_ls7e_ard_3-2-1_099083_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