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:

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First 100 results (query limit)

Time (local)	Label
2021-09-20 08:40:51	ga_ls7e_ard_3-2-0_094081_2021-09-19_final
2021-10-02 10:41:46	ga_ls7e_ard_3-2-0_114077_2021-10-02_final
2021-10-10 08:13:57	ga_ls7e_ard_3-2-0_090080_2021-10-09_final
2021-10-11 08:53:32	ga_ls7e_ard_3-2-0_097071_2021-10-10_final
2021-10-13 08:39:24	ga_ls7e_ard_3-2-0_095067_2021-10-12_final
2021-10-13 10:21:28	ga_ls7e_ard_3-2-0_111075_2021-10-13_final
2021-10-15 08:29:39	ga_ls7e_ard_3-2-0_093074_2021-10-14_final
2021-10-17 09:56:24	ga_ls7e_ard_3-2-0_107075_2021-10-17_final
2021-10-26 08:11:43	ga_ls7e_ard_3-2-0_090078_2021-10-25_final
2021-10-27 10:35:45	ga_ls7e_ard_3-2-0_113083_2021-10-27_final
2021-10-30 09:23:54	ga_ls7e_ard_3-2-0_102074_2021-10-29_final
2021-11-01 09:14:33	ga_ls7e_ard_3-2-0_100082_2021-10-31_final
2021-11-02 08:18:50	ga_ls7e_ard_3-2-0_091082_2021-11-01_final
2021-11-02 08:21:38	ga_ls7e_ard_3-2-0_091089_2021-11-01_final
2021-11-02 08:22:02	ga_ls7e_ard_3-2-0_091090_2021-11-01_final
2021-11-04 09:40:23	ga_ls7e_ard_3-2-0_105070_2021-11-04_final
2021-11-04 09:40:47	ga_ls7e_ard_3-2-0_105071_2021-11-04_final
2021-11-04 09:44:22	ga_ls7e_ard_3-2-0_105080_2021-11-04_final
2021-11-05 08:50:39	ga_ls7e_ard_3-2-0_096085_2021-11-04_final
2021-11-07 08:37:42	ga_ls7e_ard_3-2-0_094084_2021-11-06_final
2021-11-07 10:12:35	ga_ls7e_ard_3-2-0_110074_2021-11-07_final
2021-11-14 08:42:24	ga_ls7e_ard_3-2-1_095082_2021-11-13_final
2021-11-15 09:20:23	ga_ls7e_ard_3-2-1_102069_2021-11-14_final
2021-11-16 08:30:39	ga_ls7e_ard_3-2-1_093084_2021-11-15_final
2021-11-18 08:17:18	ga_ls7e_ard_3-2-1_091082_2021-11-17_final
2021-11-21 08:44:18	ga_ls7e_ard_3-2-1_096073_2021-11-20_final
2021-11-21 08:49:06	ga_ls7e_ard_3-2-1_096085_2021-11-20_final
2021-11-23 10:14:13	ga_ls7e_ard_3-2-1_110082_2021-11-23_final
2021-11-27 08:09:27	ga_ls7e_ard_3-2-1_090080_2021-11-26_final
2021-11-27 09:47:56	ga_ls7e_ard_3-2-1_106079_2021-11-27_final
2021-11-29 09:31:24	ga_ls7e_ard_3-2-1_104069_2021-11-29_final
2021-11-29 09:34:59	ga_ls7e_ard_3-2-1_104078_2021-11-29_final
2021-12-04 09:54:39	ga_ls7e_ard_3-2-1_107082_2021-12-04_final
2021-12-07 08:42:48	ga_ls7e_ard_3-2-1_096073_2021-12-06_final
2021-12-07 08:43:12	ga_ls7e_ard_3-2-1_096074_2021-12-06_final
2021-12-09 08:33:51	ga_ls7e_ard_3-2-1_094082_2021-12-08_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-11 09:56:59	ga_ls7e_ard_3-2-1_108074_2021-12-11_final
2021-12-11 10:00:34	ga_ls7e_ard_3-2-1_108083_2021-12-11_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-14 08:51:54	ga_ls7e_ard_3-2-1_097082_2021-12-13_final
2021-12-20 09:49:32	ga_ls7e_ard_3-2-1_107073_2021-12-20_final
2021-12-20 09:51:08	ga_ls7e_ard_3-2-1_107077_2021-12-20_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-25 10:07:59	ga_ls7e_ard_3-2-1_110074_2021-12-25_final
2021-12-30 08:49:56	ga_ls7e_ard_3-2-1_097081_2021-12-29_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2022-01-01 08:37:46	ga_ls7e_ard_3-2-1_095082_2021-12-31_final
2022-01-03 08:26:00	ga_ls7e_ard_3-2-1_093084_2022-01-02_final
2022-01-05 08:11:02	ga_ls7e_ard_3-2-1_091078_2022-01-04_final
2022-01-10 08:28:43	ga_ls7e_ard_3-2-1_094077_2022-01-09_final
2022-01-12 08:17:46	ga_ls7e_ard_3-2-1_092081_2022-01-11_final
2022-01-12 09:53:27	ga_ls7e_ard_3-2-1_108073_2022-01-12_final
2022-01-14 08:04:01	ga_ls7e_ard_3-2-1_090078_2022-01-13_final
2022-01-15 08:45:36	ga_ls7e_ard_3-2-1_097074_2022-01-14_final
2022-01-15 10:26:52	ga_ls7e_ard_3-2-1_113080_2022-01-15_final
2022-01-21 08:10:20	ga_ls7e_ard_3-2-1_091080_2022-01-20_final
2022-01-21 08:13:32	ga_ls7e_ard_3-2-1_091088_2022-01-20_final
2022-01-21 09:49:13	ga_ls7e_ard_3-2-1_107080_2022-01-21_final
2022-01-22 08:51:30	ga_ls7e_ard_3-2-1_098075_2022-01-21_final
2022-01-25 09:20:07	ga_ls7e_ard_3-2-1_103070_2022-01-24_final
2022-01-27 09:09:33	ga_ls7e_ard_3-2-1_101075_2022-01-26_final
2022-01-27 09:10:45	ga_ls7e_ard_3-2-1_101078_2022-01-26_final
2022-01-28 09:54:18	ga_ls7e_ard_3-2-1_108079_2022-01-28_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-01-29 09:00:11	ga_ls7e_ard_3-2-1_099083_2022-01-28_final
2022-01-30 08:03:40	ga_ls7e_ard_3-2-1_090081_2022-01-29_final
2022-01-30 08:04:28	ga_ls7e_ard_3-2-1_090083_2022-01-29_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-04 10:01:23	ga_ls7e_ard_3-2-1_109083_2022-02-04_final
2022-02-06 08:12:20	ga_ls7e_ard_3-2-1_091089_2022-02-05_final
2022-02-07 08:49:30	ga_ls7e_ard_3-2-1_098074_2022-02-06_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-12 09:10:43	ga_ls7e_ard_3-2-1_101082_2022-02-11_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-26 09:21:43	ga_ls7e_ard_3-2-1_103082_2022-02-25_final
2022-02-28 09:09:34	ga_ls7e_ard_3-2-1_101083_2022-02-27_final
2022-03-01 09:52:20	ga_ls7e_ard_3-2-1_108082_2022-03-01_final
2022-03-03 08:00:54	ga_ls7e_ard_3-2-1_090082_2022-03-02_final
2022-03-04 08:42:51	ga_ls7e_ard_3-2-1_097079_2022-03-03_final
2022-03-06 08:28:18	ga_ls7e_ard_3-2-1_095074_2022-03-05_final
2022-03-07 09:10:16	ga_ls7e_ard_3-2-1_102071_2022-03-06_final
2022-03-08 08:19:44	ga_ls7e_ard_3-2-1_093084_2022-03-07_final
2022-03-11 08:48:21	ga_ls7e_ard_3-2-1_098079_2022-03-10_final
2022-03-12 07:52:13	ga_ls7e_ard_3-2-1_089078_2022-03-11_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-13 08:36:59	ga_ls7e_ard_3-2-1_096082_2022-03-12_final
2022-03-13 10:16:15	ga_ls7e_ard_3-2-1_112083_2022-03-13_final
2022-03-14 09:15:45	ga_ls7e_ard_3-2-1_103071_2022-03-13_final
2022-03-15 10:00:30	ga_ls7e_ard_3-2-1_110075_2022-03-15_final
2022-03-17 08:11:51	ga_ls7e_ard_3-2-1_092082_2022-03-16_final
2022-03-17 09:50:19	ga_ls7e_ard_3-2-1_108081_2022-03-17_final
2022-03-18 10:31:29	ga_ls7e_ard_3-2-1_115076_2022-03-18_final
2022-03-19 09:34:11	ga_ls7e_ard_3-2-1_106072_2022-03-19_final
2022-03-20 08:38:04	ga_ls7e_ard_3-2-1_097071_2022-03-19_final
2022-03-29 10:15:07	ga_ls7e_ard_3-2-1_112084_2022-03-29_final
2022-03-30 09:17:00	ga_ls7e_ard_3-2-1_103078_2022-03-29_final
2022-04-05 08:37:20	ga_ls7e_ard_3-2-1_097073_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years