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
2021-09-18 08:54:35	ga_ls7e_ard_3-2-0_096084_2021-09-17_final
2021-09-18 08:54:59	ga_ls7e_ard_3-2-0_096085_2021-09-17_final
2021-10-25 09:04:14	ga_ls7e_ard_3-2-0_099070_2021-10-24_final
2021-10-25 10:45:06	ga_ls7e_ard_3-2-0_115075_2021-10-25_final
2021-10-25 10:46:18	ga_ls7e_ard_3-2-0_115078_2021-10-25_final
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-10-26 09:48:36	ga_ls7e_ard_3-2-0_106073_2021-10-26_final
2021-12-18 10:05:41	ga_ls7e_ard_3-2-1_109082_2021-12-18_final
2021-12-21 08:53:49	ga_ls7e_ard_3-2-1_098073_2021-12-20_final
2021-12-21 08:55:01	ga_ls7e_ard_3-2-1_098076_2021-12-20_final
2021-12-26 09:13:27	ga_ls7e_ard_3-2-1_101077_2021-12-25_final
2021-12-26 09:15:03	ga_ls7e_ard_3-2-1_101081_2021-12-25_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-28 09:00:06	ga_ls7e_ard_3-2-1_099075_2021-12-27_final
2021-12-29 08:09:58	ga_ls7e_ard_3-2-1_090089_2021-12-28_final
2022-01-01 08:36:58	ga_ls7e_ard_3-2-1_095080_2021-12-31_final
2022-01-01 10:16:39	ga_ls7e_ard_3-2-1_111082_2022-01-01_final
2022-01-04 09:05:58	ga_ls7e_ard_3-2-1_100076_2022-01-03_final
2022-01-04 09:08:45	ga_ls7e_ard_3-2-1_100083_2022-01-03_final
2022-01-08 08:43:16	ga_ls7e_ard_3-2-1_096082_2022-01-07_final
2022-01-08 10:19:45	ga_ls7e_ard_3-2-1_112076_2022-01-08_final
2022-01-08 10:20:09	ga_ls7e_ard_3-2-1_112077_2022-01-08_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 08:30:43	ga_ls7e_ard_3-2-1_094082_2022-01-09_final
2022-01-10 08:31:55	ga_ls7e_ard_3-2-1_094085_2022-01-09_final
2022-01-12 08:15:46	ga_ls7e_ard_3-2-1_092076_2022-01-11_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-13 09:01:44	ga_ls7e_ard_3-2-1_099083_2022-01-12_final
2022-01-13 10:38:37	ga_ls7e_ard_3-2-1_115078_2022-01-13_final
2022-01-15 08:47:11	ga_ls7e_ard_3-2-1_097078_2022-01-14_final
2022-01-15 08:47:59	ga_ls7e_ard_3-2-1_097080_2022-01-14_final
2022-01-15 08:48:47	ga_ls7e_ard_3-2-1_097082_2022-01-14_final
2022-01-16 09:26:46	ga_ls7e_ard_3-2-1_104069_2022-01-15_final
2022-01-18 09:16:12	ga_ls7e_ard_3-2-1_102074_2022-01-17_final
2022-01-19 10:02:34	ga_ls7e_ard_3-2-1_109082_2022-01-19_final
2022-01-20 09:04:27	ga_ls7e_ard_3-2-1_100076_2022-01-19_final
2022-01-20 09:05:39	ga_ls7e_ard_3-2-1_100079_2022-01-19_final
2022-01-21 08:11:32	ga_ls7e_ard_3-2-1_091083_2022-01-20_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-21 09:50:48	ga_ls7e_ard_3-2-1_107084_2022-01-21_final
2022-01-22 08:51:30	ga_ls7e_ard_3-2-1_098075_2022-01-21_final
2022-01-24 08:37:21	ga_ls7e_ard_3-2-1_096071_2022-01-23_final
2022-01-24 08:40:56	ga_ls7e_ard_3-2-1_096080_2022-01-23_final
2022-01-25 09:24:06	ga_ls7e_ard_3-2-1_103080_2022-01-24_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-29 10:37:04	ga_ls7e_ard_3-2-1_115078_2022-01-29_final
2022-01-30 08:04:28	ga_ls7e_ard_3-2-1_090083_2022-01-29_final
2022-01-30 08:07:16	ga_ls7e_ard_3-2-1_090090_2022-01-29_final
2022-01-31 08:44:02	ga_ls7e_ard_3-2-1_097074_2022-01-30_final
2022-01-31 08:45:38	ga_ls7e_ard_3-2-1_097078_2022-01-30_final
2022-02-01 09:25:12	ga_ls7e_ard_3-2-1_104069_2022-01-31_final
2022-02-08 07:56:59	ga_ls7e_ard_3-2-1_089082_2022-02-07_final
2022-02-08 09:32:16	ga_ls7e_ard_3-2-1_105073_2022-02-08_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-09 10:16:13	ga_ls7e_ard_3-2-1_112075_2022-02-09_final
2022-02-10 09:23:17	ga_ls7e_ard_3-2-1_103082_2022-02-09_final
2022-02-11 08:27:10	ga_ls7e_ard_3-2-1_094081_2022-02-10_final
2022-02-13 09:49:05	ga_ls7e_ard_3-2-1_108070_2022-02-13_final
2022-02-14 08:58:09	ga_ls7e_ard_3-2-1_099082_2022-02-13_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-15 08:05:13	ga_ls7e_ard_3-2-1_090089_2022-02-14_final
2022-02-15 09:37:43	ga_ls7e_ard_3-2-1_106073_2022-02-15_final
2022-02-15 09:39:42	ga_ls7e_ard_3-2-1_106078_2022-02-15_final
2022-02-16 08:41:11	ga_ls7e_ard_3-2-1_097071_2022-02-15_final
2022-02-16 08:44:23	ga_ls7e_ard_3-2-1_097079_2022-02-15_final
2022-02-20 08:22:05	ga_ls7e_ard_3-2-1_093086_2022-02-19_final
2022-02-22 09:46:25	ga_ls7e_ard_3-2-1_107081_2022-02-22_final
2022-02-23 08:52:18	ga_ls7e_ard_3-2-1_098085_2022-02-22_final
2022-02-25 08:38:57	ga_ls7e_ard_3-2-1_096083_2022-02-24_final
2022-02-26 09:20:55	ga_ls7e_ard_3-2-1_103080_2022-02-25_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-03-01 09:49:56	ga_ls7e_ard_3-2-1_108076_2022-03-01_final
2022-03-02 10:32:42	ga_ls7e_ard_3-2-1_115075_2022-03-02_final
2022-03-03 08:00:06	ga_ls7e_ard_3-2-1_090080_2022-03-02_final
2022-03-03 08:04:05	ga_ls7e_ard_3-2-1_090090_2022-03-02_final
2022-03-06 08:28:18	ga_ls7e_ard_3-2-1_095074_2022-03-05_final
2022-03-07 09:09:28	ga_ls7e_ard_3-2-1_102069_2022-03-06_final
2022-03-07 09:12:16	ga_ls7e_ard_3-2-1_102076_2022-03-06_final
2022-03-11 10:25:37	ga_ls7e_ard_3-2-1_114075_2022-03-11_final
2022-03-12 07:52:37	ga_ls7e_ard_3-2-1_089079_2022-03-11_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_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 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-26 09:42:54	ga_ls7e_ard_3-2-1_107080_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-03-27 08:49:11	ga_ls7e_ard_3-2-1_098085_2022-03-26_final
2022-03-28 07:52:40	ga_ls7e_ard_3-2-1_089083_2022-03-27_final
2022-03-31 08:23:41	ga_ls7e_ard_3-2-1_094084_2022-03-30_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-03-31 09:59:22	ga_ls7e_ard_3-2-1_110076_2022-03-31_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-04-02 08:07:56	ga_ls7e_ard_3-2-1_092076_2022-04-01_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years