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 08:39:39	ga_ls7e_ard_3-2-0_094078_2021-09-19_final
2021-09-20 08:40:03	ga_ls7e_ard_3-2-0_094079_2021-09-19_final
2021-09-20 08:41:15	ga_ls7e_ard_3-2-0_094082_2021-09-19_final
2021-09-20 08:42:03	ga_ls7e_ard_3-2-0_094084_2021-09-19_final
2021-09-20 10:17:44	ga_ls7e_ard_3-2-0_110076_2021-09-20_final
2021-10-26 08:13:43	ga_ls7e_ard_3-2-0_090083_2021-10-25_final
2021-11-13 09:33:44	ga_ls7e_ard_3-2-1_104071_2021-11-13_final
2021-11-15 09:23:10	ga_ls7e_ard_3-2-1_102076_2021-11-14_final
2021-11-21 08:48:18	ga_ls7e_ard_3-2-1_096083_2021-11-20_final
2021-11-21 08:48:42	ga_ls7e_ard_3-2-1_096084_2021-11-20_final
2021-11-27 08:09:27	ga_ls7e_ard_3-2-1_090080_2021-11-26_final
2021-11-30 10:20:09	ga_ls7e_ard_3-2-1_111083_2021-11-30_final
2021-12-04 08:14:59	ga_ls7e_ard_3-2-1_091080_2021-12-03_final
2021-12-10 09:13:49	ga_ls7e_ard_3-2-1_101074_2021-12-09_final
2021-12-11 08:20:06	ga_ls7e_ard_3-2-1_092079_2021-12-10_final
2021-12-12 10:41:44	ga_ls7e_ard_3-2-1_115078_2021-12-12_final
2021-12-13 09:43:14	ga_ls7e_ard_3-2-1_106071_2021-12-13_final
2021-12-13 09:45:38	ga_ls7e_ard_3-2-1_106077_2021-12-13_final
2021-12-18 10:01:17	ga_ls7e_ard_3-2-1_109071_2021-12-18_final
2021-12-18 10:04:29	ga_ls7e_ard_3-2-1_109079_2021-12-18_final
2021-12-23 08:44:27	ga_ls7e_ard_3-2-1_096081_2021-12-22_final
2021-12-23 10:22:56	ga_ls7e_ard_3-2-1_112080_2021-12-23_final
2021-12-27 08:18:56	ga_ls7e_ard_3-2-1_092080_2021-12-26_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-27 08:20:08	ga_ls7e_ard_3-2-1_092083_2021-12-26_final
2021-12-27 08:20:32	ga_ls7e_ard_3-2-1_092084_2021-12-26_final
2022-01-01 08:34:34	ga_ls7e_ard_3-2-1_095074_2021-12-31_final
2022-01-03 08:24:48	ga_ls7e_ard_3-2-1_093081_2022-01-02_final
2022-01-03 10:03:41	ga_ls7e_ard_3-2-1_109081_2022-01-03_final
2022-01-05 09:47:31	ga_ls7e_ard_3-2-1_107072_2022-01-05_final
2022-01-09 09:25:38	ga_ls7e_ard_3-2-1_103080_2022-01-08_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-12 09:57:27	ga_ls7e_ard_3-2-1_108083_2022-01-12_final
2022-01-14 08:06:01	ga_ls7e_ard_3-2-1_090083_2022-01-13_final
2022-01-15 08:45:12	ga_ls7e_ard_3-2-1_097073_2022-01-14_final
2022-01-16 09:26:22	ga_ls7e_ard_3-2-1_104068_2022-01-15_final
2022-01-17 08:35:50	ga_ls7e_ard_3-2-1_095081_2022-01-16_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-18 09:13:49	ga_ls7e_ard_3-2-1_102068_2022-01-17_final
2022-01-18 09:16:36	ga_ls7e_ard_3-2-1_102075_2022-01-17_final
2022-01-19 10:01:46	ga_ls7e_ard_3-2-1_109080_2022-01-19_final
2022-01-20 09:04:03	ga_ls7e_ard_3-2-1_100075_2022-01-19_final
2022-01-20 09:05:39	ga_ls7e_ard_3-2-1_100079_2022-01-19_final
2022-01-21 09:48:25	ga_ls7e_ard_3-2-1_107078_2022-01-21_final
2022-01-23 07:57:47	ga_ls7e_ard_3-2-1_089080_2022-01-22_final
2022-01-24 08:40:09	ga_ls7e_ard_3-2-1_096078_2022-01-23_final
2022-01-24 10:19:01	ga_ls7e_ard_3-2-1_112078_2022-01-24_final
2022-01-25 09:23:42	ga_ls7e_ard_3-2-1_103079_2022-01-24_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-28 08:15:50	ga_ls7e_ard_3-2-1_092080_2022-01-27_final
2022-01-28 09:54:42	ga_ls7e_ard_3-2-1_108080_2022-01-28_final
2022-01-29 08:59:23	ga_ls7e_ard_3-2-1_099081_2022-01-28_final
2022-01-30 09:42:09	ga_ls7e_ard_3-2-1_106080_2022-01-30_final
2022-01-31 08:46:50	ga_ls7e_ard_3-2-1_097081_2022-01-30_final
2022-02-02 08:35:04	ga_ls7e_ard_3-2-1_095083_2022-02-01_final
2022-02-04 08:20:31	ga_ls7e_ard_3-2-1_093078_2022-02-03_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-06 09:46:49	ga_ls7e_ard_3-2-1_107078_2022-02-06_final
2022-02-07 08:53:54	ga_ls7e_ard_3-2-1_098085_2022-02-06_final
2022-02-09 08:38:56	ga_ls7e_ard_3-2-1_096079_2022-02-08_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-13 09:52:17	ga_ls7e_ard_3-2-1_108078_2022-02-13_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-16 08:41:35	ga_ls7e_ard_3-2-1_097072_2022-02-15_final
2022-02-19 09:13:48	ga_ls7e_ard_3-2-1_102076_2022-02-18_final
2022-02-20 08:19:17	ga_ls7e_ard_3-2-1_093079_2022-02-19_final
2022-02-21 08:59:16	ga_ls7e_ard_3-2-1_100071_2022-02-20_final
2022-02-25 08:37:21	ga_ls7e_ard_3-2-1_096079_2022-02-24_final
2022-02-26 09:17:43	ga_ls7e_ard_3-2-1_103072_2022-02-25_final
2022-02-26 09:20:55	ga_ls7e_ard_3-2-1_103080_2022-02-25_final
2022-02-27 10:03:41	ga_ls7e_ard_3-2-1_110079_2022-02-27_final
2022-02-28 09:04:46	ga_ls7e_ard_3-2-1_101071_2022-02-27_final
2022-02-28 09:09:10	ga_ls7e_ard_3-2-1_101082_2022-02-27_final
2022-03-06 08:31:06	ga_ls7e_ard_3-2-1_095081_2022-03-05_final
2022-03-06 10:11:10	ga_ls7e_ard_3-2-1_111084_2022-03-06_final
2022-03-07 09:12:40	ga_ls7e_ard_3-2-1_102077_2022-03-06_final
2022-03-08 08:17:45	ga_ls7e_ard_3-2-1_093079_2022-03-07_final
2022-03-09 08:58:30	ga_ls7e_ard_3-2-1_100073_2022-03-08_final
2022-03-09 09:01:42	ga_ls7e_ard_3-2-1_100081_2022-03-08_final
2022-03-10 08:07:35	ga_ls7e_ard_3-2-1_091085_2022-03-09_final
2022-03-10 09:43:16	ga_ls7e_ard_3-2-1_107077_2022-03-10_final
2022-03-12 07:55:25	ga_ls7e_ard_3-2-1_089086_2022-03-11_final
2022-03-14 09:17:44	ga_ls7e_ard_3-2-1_103076_2022-03-13_final
2022-03-15 08:22:25	ga_ls7e_ard_3-2-1_094077_2022-03-14_final
2022-03-17 08:09:27	ga_ls7e_ard_3-2-1_092076_2022-03-16_final
2022-03-17 08:09:51	ga_ls7e_ard_3-2-1_092077_2022-03-16_final
2022-03-18 08:53:00	ga_ls7e_ard_3-2-1_099077_2022-03-17_final
2022-03-19 09:37:22	ga_ls7e_ard_3-2-1_106080_2022-03-19_final
2022-03-21 09:25:13	ga_ls7e_ard_3-2-1_104081_2022-03-20_final
2022-03-22 08:28:43	ga_ls7e_ard_3-2-1_095079_2022-03-21_final
2022-03-24 09:54:39	ga_ls7e_ard_3-2-1_109078_2022-03-24_final
2022-03-26 09:41:42	ga_ls7e_ard_3-2-1_107077_2022-03-26_final
2022-03-26 09:44:30	ga_ls7e_ard_3-2-1_107084_2022-03-26_final
2022-03-29 08:33:50	ga_ls7e_ard_3-2-1_096078_2022-03-28_final
2022-03-29 08:36:38	ga_ls7e_ard_3-2-1_096085_2022-03-28_final
2022-03-29 10:11:55	ga_ls7e_ard_3-2-1_112076_2022-03-29_final
2022-03-31 10:01:46	ga_ls7e_ard_3-2-1_110082_2022-03-31_final
2022-04-02 09:49:12	ga_ls7e_ard_3-2-1_108082_2022-04-02_final
2022-04-04 07:56:58	ga_ls7e_ard_3-2-1_090080_2022-04-03_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