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 10:03:40	ga_ls7e_ard_3-2-0_105080_2021-03-25_final
2021-09-18 10:30:16	ga_ls7e_ard_3-2-0_112076_2021-09-18_final
2021-09-18 10:30:40	ga_ls7e_ard_3-2-0_112077_2021-09-18_final
2021-09-20 08:40:27	ga_ls7e_ard_3-2-0_094080_2021-09-19_final
2021-09-20 10:19:19	ga_ls7e_ard_3-2-0_110080_2021-09-20_final
2021-10-26 08:13:19	ga_ls7e_ard_3-2-0_090082_2021-10-25_final
2021-10-26 09:50:59	ga_ls7e_ard_3-2-0_106079_2021-10-26_final
2021-12-17 09:22:31	ga_ls7e_ard_3-2-1_102082_2021-12-16_final
2021-12-19 09:09:34	ga_ls7e_ard_3-2-1_100081_2021-12-18_final
2021-12-22 09:38:11	ga_ls7e_ard_3-2-1_105076_2021-12-22_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-23 08:42:51	ga_ls7e_ard_3-2-1_096077_2021-12-22_final
2021-12-27 09:55:01	ga_ls7e_ard_3-2-1_108073_2021-12-27_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-27 09:57:01	ga_ls7e_ard_3-2-1_108078_2021-12-27_final
2021-12-27 09:57:25	ga_ls7e_ard_3-2-1_108079_2021-12-27_final
2021-12-28 08:59:42	ga_ls7e_ard_3-2-1_099074_2021-12-27_final
2021-12-29 09:42:51	ga_ls7e_ard_3-2-1_106074_2021-12-29_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2021-12-31 09:30:18	ga_ls7e_ard_3-2-1_104074_2021-12-31_final
2022-01-01 10:13:51	ga_ls7e_ard_3-2-1_111075_2022-01-01_final
2022-01-02 09:18:32	ga_ls7e_ard_3-2-1_102076_2022-01-01_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-03 10:00:05	ga_ls7e_ard_3-2-1_109072_2022-01-03_final
2022-01-08 08:38:52	ga_ls7e_ard_3-2-1_096071_2022-01-07_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-10 08:27:55	ga_ls7e_ard_3-2-1_094075_2022-01-09_final
2022-01-10 10:06:00	ga_ls7e_ard_3-2-1_110073_2022-01-10_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-12 08:15:22	ga_ls7e_ard_3-2-1_092075_2022-01-11_final
2022-01-13 10:37:01	ga_ls7e_ard_3-2-1_115074_2022-01-13_final
2022-01-13 10:38:37	ga_ls7e_ard_3-2-1_115078_2022-01-13_final
2022-01-15 08:48:23	ga_ls7e_ard_3-2-1_097081_2022-01-14_final
2022-01-17 08:32:15	ga_ls7e_ard_3-2-1_095072_2022-01-16_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-24 08:36:57	ga_ls7e_ard_3-2-1_096070_2022-01-23_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-26 08:29:59	ga_ls7e_ard_3-2-1_094084_2022-01-25_final
2022-01-29 10:37:04	ga_ls7e_ard_3-2-1_115078_2022-01-29_final
2022-01-30 09:41:45	ga_ls7e_ard_3-2-1_106079_2022-01-30_final
2022-02-02 08:31:29	ga_ls7e_ard_3-2-1_095074_2022-02-01_final
2022-02-02 08:36:16	ga_ls7e_ard_3-2-1_095086_2022-02-01_final
2022-02-02 10:11:33	ga_ls7e_ard_3-2-1_111077_2022-02-02_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-06 09:43:38	ga_ls7e_ard_3-2-1_107070_2022-02-06_final
2022-02-06 09:44:02	ga_ls7e_ard_3-2-1_107071_2022-02-06_final
2022-02-07 08:53:06	ga_ls7e_ard_3-2-1_098083_2022-02-06_final
2022-02-08 07:57:47	ga_ls7e_ard_3-2-1_089084_2022-02-07_final
2022-02-08 07:58:11	ga_ls7e_ard_3-2-1_089085_2022-02-07_final
2022-02-09 08:40:08	ga_ls7e_ard_3-2-1_096082_2022-02-08_final
2022-02-09 10:16:13	ga_ls7e_ard_3-2-1_112075_2022-02-09_final
2022-02-11 10:03:39	ga_ls7e_ard_3-2-1_110075_2022-02-11_final
2022-02-12 09:09:31	ga_ls7e_ard_3-2-1_101079_2022-02-11_final
2022-02-14 10:33:50	ga_ls7e_ard_3-2-1_115074_2022-02-14_final
2022-02-15 09:37:43	ga_ls7e_ard_3-2-1_106073_2022-02-15_final
2022-02-16 08:40:48	ga_ls7e_ard_3-2-1_097070_2022-02-15_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-19 09:15:00	ga_ls7e_ard_3-2-1_102079_2022-02-18_final
2022-02-19 09:15:48	ga_ls7e_ard_3-2-1_102081_2022-02-18_final
2022-02-20 08:22:29	ga_ls7e_ard_3-2-1_093087_2022-02-19_final
2022-02-22 09:42:26	ga_ls7e_ard_3-2-1_107071_2022-02-22_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-25 08:35:22	ga_ls7e_ard_3-2-1_096074_2022-02-24_final
2022-02-25 10:15:50	ga_ls7e_ard_3-2-1_112078_2022-02-25_final
2022-02-26 09:16:56	ga_ls7e_ard_3-2-1_103070_2022-02-25_final
2022-02-27 08:23:12	ga_ls7e_ard_3-2-1_094075_2022-02-26_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-04 10:21:44	ga_ls7e_ard_3-2-1_113079_2022-03-04_final
2022-03-07 09:12:16	ga_ls7e_ard_3-2-1_102076_2022-03-06_final
2022-03-07 09:13:04	ga_ls7e_ard_3-2-1_102078_2022-03-06_final
2022-03-07 09:13:52	ga_ls7e_ard_3-2-1_102080_2022-03-06_final
2022-03-08 08:19:44	ga_ls7e_ard_3-2-1_093084_2022-03-07_final
2022-03-08 08:20:08	ga_ls7e_ard_3-2-1_093085_2022-03-07_final
2022-03-10 08:07:59	ga_ls7e_ard_3-2-1_091086_2022-03-09_final
2022-03-12 09:27:31	ga_ls7e_ard_3-2-1_105069_2022-03-11_final
2022-03-12 09:28:42	ga_ls7e_ard_3-2-1_105072_2022-03-11_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-19 08:02:05	ga_ls7e_ard_3-2-1_090089_2022-03-18_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-22 08:30:43	ga_ls7e_ard_3-2-1_095084_2022-03-21_final
2022-03-23 09:11:53	ga_ls7e_ard_3-2-1_102079_2022-03-22_final
2022-03-24 08:19:22	ga_ls7e_ard_3-2-1_093087_2022-03-23_final
2022-03-26 08:06:49	ga_ls7e_ard_3-2-1_091087_2022-03-25_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-26 09:44:06	ga_ls7e_ard_3-2-1_107083_2022-03-26_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-03-31 08:22:05	ga_ls7e_ard_3-2-1_094080_2022-03-30_final
2022-03-31 08:23:17	ga_ls7e_ard_3-2-1_094083_2022-03-30_final
2022-04-02 08:08:20	ga_ls7e_ard_3-2-1_092077_2022-04-01_final
2022-04-03 08:50:18	ga_ls7e_ard_3-2-1_099074_2022-04-02_final
2022-04-04 09:32:39	ga_ls7e_ard_3-2-1_106072_2022-04-04_final
2022-04-05 08:40:31	ga_ls7e_ard_3-2-1_097081_2022-04-04_final
2022-04-05 10:18:36	ga_ls7e_ard_3-2-1_113079_2022-04-05_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