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 08:42:50	ga_ls7e_ard_3-2-0_094086_2021-09-19_final
2021-10-26 09:47:00	ga_ls7e_ard_3-2-0_106069_2021-10-26_final
2021-11-02 08:18:27	ga_ls7e_ard_3-2-0_091081_2021-11-01_final
2021-11-02 09:58:31	ga_ls7e_ard_3-2-0_107084_2021-11-02_final
2021-11-04 09:41:59	ga_ls7e_ard_3-2-0_105074_2021-11-04_final
2021-11-16 10:07:08	ga_ls7e_ard_3-2-1_109078_2021-11-16_final
2021-11-25 09:58:05	ga_ls7e_ard_3-2-1_108073_2021-11-25_final
2021-11-25 10:00:52	ga_ls7e_ard_3-2-1_108080_2021-11-25_final
2021-11-26 10:41:39	ga_ls7e_ard_3-2-1_115074_2021-11-26_final
2021-11-30 10:17:45	ga_ls7e_ard_3-2-1_111077_2021-11-30_final
2021-11-30 10:19:21	ga_ls7e_ard_3-2-1_111081_2021-11-30_final
2021-12-01 09:22:03	ga_ls7e_ard_3-2-1_102077_2021-11-30_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-04 08:17:47	ga_ls7e_ard_3-2-1_091087_2021-12-03_final
2021-12-04 08:18:34	ga_ls7e_ard_3-2-1_091089_2021-12-03_final
2021-12-06 09:36:31	ga_ls7e_ard_3-2-1_105068_2021-12-06_final
2021-12-08 09:24:46	ga_ls7e_ard_3-2-1_103070_2021-12-07_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-11 09:57:47	ga_ls7e_ard_3-2-1_108076_2021-12-11_final
2021-12-12 09:00:52	ga_ls7e_ard_3-2-1_099073_2021-12-11_final
2021-12-13 08:11:08	ga_ls7e_ard_3-2-1_090088_2021-12-12_final
2021-12-14 08:48:43	ga_ls7e_ard_3-2-1_097074_2021-12-13_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-16 08:40:33	ga_ls7e_ard_3-2-1_095085_2021-12-15_final
2021-12-20 09:51:56	ga_ls7e_ard_3-2-1_107079_2021-12-20_final
2021-12-23 10:22:08	ga_ls7e_ard_3-2-1_112078_2021-12-23_final
2021-12-25 08:30:18	ga_ls7e_ard_3-2-1_094077_2021-12-24_final
2021-12-25 10:09:35	ga_ls7e_ard_3-2-1_110078_2021-12-25_final
2021-12-27 09:54:13	ga_ls7e_ard_3-2-1_108071_2021-12-27_final
2021-12-29 09:41:16	ga_ls7e_ard_3-2-1_106070_2021-12-29_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 10:29:12	ga_ls7e_ard_3-2-1_113082_2021-12-30_final
2022-01-03 10:03:17	ga_ls7e_ard_3-2-1_109080_2022-01-03_final
2022-01-05 09:47:55	ga_ls7e_ard_3-2-1_107073_2022-01-05_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-06 10:31:53	ga_ls7e_ard_3-2-1_114075_2022-01-06_final
2022-01-07 09:34:35	ga_ls7e_ard_3-2-1_105071_2022-01-07_final
2022-01-15 08:46:47	ga_ls7e_ard_3-2-1_097077_2022-01-14_final
2022-01-15 10:26:52	ga_ls7e_ard_3-2-1_113080_2022-01-15_final
2022-01-17 10:11:31	ga_ls7e_ard_3-2-1_111073_2022-01-17_final
2022-01-18 09:17:48	ga_ls7e_ard_3-2-1_102078_2022-01-17_final
2022-01-21 08:10:20	ga_ls7e_ard_3-2-1_091080_2022-01-20_final
2022-01-21 08:10:44	ga_ls7e_ard_3-2-1_091081_2022-01-20_final
2022-01-23 07:56:59	ga_ls7e_ard_3-2-1_089078_2022-01-22_final
2022-01-26 08:26:23	ga_ls7e_ard_3-2-1_094075_2022-01-25_final
2022-01-26 10:04:52	ga_ls7e_ard_3-2-1_110074_2022-01-26_final
2022-01-28 08:14:14	ga_ls7e_ard_3-2-1_092076_2022-01-27_final
2022-01-29 10:37:04	ga_ls7e_ard_3-2-1_115078_2022-01-29_final
2022-02-02 10:11:33	ga_ls7e_ard_3-2-1_111077_2022-02-02_final
2022-02-03 09:14:38	ga_ls7e_ard_3-2-1_102074_2022-02-02_final
2022-02-07 10:28:23	ga_ls7e_ard_3-2-1_114074_2022-02-07_final
2022-02-08 09:35:51	ga_ls7e_ard_3-2-1_105082_2022-02-08_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-12 09:09:31	ga_ls7e_ard_3-2-1_101079_2022-02-11_final
2022-02-14 08:54:09	ga_ls7e_ard_3-2-1_099072_2022-02-13_final
2022-02-14 08:58:33	ga_ls7e_ard_3-2-1_099083_2022-02-13_final
2022-02-14 10:33:50	ga_ls7e_ard_3-2-1_115074_2022-02-14_final
2022-02-15 09:36:31	ga_ls7e_ard_3-2-1_106070_2022-02-15_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-23 08:47:55	ga_ls7e_ard_3-2-1_098074_2022-02-22_final
2022-02-23 08:50:42	ga_ls7e_ard_3-2-1_098081_2022-02-22_final
2022-02-23 10:29:11	ga_ls7e_ard_3-2-1_114080_2022-02-23_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-03-04 08:38:52	ga_ls7e_ard_3-2-1_097069_2022-03-03_final
2022-03-04 08:39:16	ga_ls7e_ard_3-2-1_097070_2022-03-03_final
2022-03-04 10:21:44	ga_ls7e_ard_3-2-1_113079_2022-03-04_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-08 09:58:13	ga_ls7e_ard_3-2-1_109083_2022-03-08_final
2022-03-09 08:58:54	ga_ls7e_ard_3-2-1_100074_2022-03-08_final
2022-03-10 08:07:59	ga_ls7e_ard_3-2-1_091086_2022-03-09_final
2022-03-10 09:45:39	ga_ls7e_ard_3-2-1_107083_2022-03-10_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-15 10:03:41	ga_ls7e_ard_3-2-1_110083_2022-03-15_final
2022-03-17 09:45:56	ga_ls7e_ard_3-2-1_108070_2022-03-17_final
2022-03-18 08:52:36	ga_ls7e_ard_3-2-1_099076_2022-03-17_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-19 09:33:47	ga_ls7e_ard_3-2-1_106071_2022-03-19_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-23 09:11:53	ga_ls7e_ard_3-2-1_102079_2022-03-22_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-24 09:57:03	ga_ls7e_ard_3-2-1_109084_2022-03-24_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-28 09:25:34	ga_ls7e_ard_3-2-1_105068_2022-03-27_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-29 08:37:02	ga_ls7e_ard_3-2-1_096086_2022-03-28_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-01 09:06:27	ga_ls7e_ard_3-2-1_101083_2022-03-31_final
2022-04-02 09:44:01	ga_ls7e_ard_3-2-1_108069_2022-04-02_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_2022-04-02_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_2022-04-02_final
2022-04-04 07:58:10	ga_ls7e_ard_3-2-1_090083_2022-04-03_final
2022-04-05 08:39:44	ga_ls7e_ard_3-2-1_097079_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