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 08:24:47	ga_ls7e_ard_3-2-0_089080_2021-03-24_final
2021-09-18 08:49:00	ga_ls7e_ard_3-2-0_096070_2021-09-17_final
2021-09-20 10:16:32	ga_ls7e_ard_3-2-0_110073_2021-09-20_final
2021-09-20 10:19:43	ga_ls7e_ard_3-2-0_110081_2021-09-20_final
2021-10-25 09:03:02	ga_ls7e_ard_3-2-0_099067_2021-10-24_final
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-10-26 09:50:59	ga_ls7e_ard_3-2-0_106079_2021-10-26_final
2021-10-26 09:51:47	ga_ls7e_ard_3-2-0_106081_2021-10-26_final
2021-12-10 09:13:49	ga_ls7e_ard_3-2-1_101074_2021-12-09_final
2021-12-13 08:09:09	ga_ls7e_ard_3-2-1_090083_2021-12-12_final
2021-12-14 08:47:55	ga_ls7e_ard_3-2-1_097072_2021-12-13_final
2021-12-14 10:30:23	ga_ls7e_ard_3-2-1_113081_2021-12-14_final
2021-12-21 08:53:49	ga_ls7e_ard_3-2-1_098073_2021-12-20_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-23 10:22:08	ga_ls7e_ard_3-2-1_112078_2021-12-23_final
2021-12-24 09:24:25	ga_ls7e_ard_3-2-1_103073_2021-12-23_final
2021-12-25 10:09:35	ga_ls7e_ard_3-2-1_110078_2021-12-25_final
2021-12-25 10:11:10	ga_ls7e_ard_3-2-1_110082_2021-12-25_final
2021-12-30 08:46:44	ga_ls7e_ard_3-2-1_097073_2021-12-29_final
2021-12-30 08:49:08	ga_ls7e_ard_3-2-1_097079_2021-12-29_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2021-12-31 09:31:29	ga_ls7e_ard_3-2-1_104077_2021-12-31_final
2022-01-01 08:34:58	ga_ls7e_ard_3-2-1_095075_2021-12-31_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-01 10:14:39	ga_ls7e_ard_3-2-1_111077_2022-01-01_final
2022-01-02 09:18:32	ga_ls7e_ard_3-2-1_102076_2022-01-01_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-10 08:27:31	ga_ls7e_ard_3-2-1_094074_2022-01-09_final
2022-01-10 10:09:36	ga_ls7e_ard_3-2-1_110082_2022-01-10_final
2022-01-12 08:18:58	ga_ls7e_ard_3-2-1_092084_2022-01-11_final
2022-01-12 09:53:51	ga_ls7e_ard_3-2-1_108074_2022-01-12_final
2022-01-14 08:04:01	ga_ls7e_ard_3-2-1_090078_2022-01-13_final
2022-01-15 08:45:12	ga_ls7e_ard_3-2-1_097073_2022-01-14_final
2022-01-15 08:46:47	ga_ls7e_ard_3-2-1_097077_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
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-17 10:13:07	ga_ls7e_ard_3-2-1_111077_2022-01-17_final
2022-01-19 08:25:41	ga_ls7e_ard_3-2-1_093087_2022-01-18_final
2022-01-20 09:05:39	ga_ls7e_ard_3-2-1_100079_2022-01-19_final
2022-01-22 08:51:30	ga_ls7e_ard_3-2-1_098075_2022-01-21_final
2022-01-22 10:32:46	ga_ls7e_ard_3-2-1_114081_2022-01-22_final
2022-01-24 08:40:33	ga_ls7e_ard_3-2-1_096079_2022-01-23_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-25 09:19:43	ga_ls7e_ard_3-2-1_103069_2022-01-24_final
2022-01-26 08:29:59	ga_ls7e_ard_3-2-1_094084_2022-01-25_final
2022-01-27 09:10:45	ga_ls7e_ard_3-2-1_101078_2022-01-26_final
2022-01-29 09:00:11	ga_ls7e_ard_3-2-1_099083_2022-01-28_final
2022-01-31 10:26:06	ga_ls7e_ard_3-2-1_113082_2022-01-31_final
2022-02-01 09:29:35	ga_ls7e_ard_3-2-1_104080_2022-01-31_final
2022-02-03 09:14:38	ga_ls7e_ard_3-2-1_102074_2022-02-02_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-06 08:11:08	ga_ls7e_ard_3-2-1_091086_2022-02-05_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-12 09:09:31	ga_ls7e_ard_3-2-1_101079_2022-02-11_final
2022-02-13 09:49:29	ga_ls7e_ard_3-2-1_108071_2022-02-13_final
2022-02-16 08:41:11	ga_ls7e_ard_3-2-1_097071_2022-02-15_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-18 08:29:51	ga_ls7e_ard_3-2-1_095074_2022-02-17_final
2022-02-20 09:56:10	ga_ls7e_ard_3-2-1_109074_2022-02-20_final
2022-02-22 08:06:44	ga_ls7e_ard_3-2-1_091079_2022-02-21_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-03-01 08:13:51	ga_ls7e_ard_3-2-1_092083_2022-02-28_final
2022-03-01 09:52:43	ga_ls7e_ard_3-2-1_108083_2022-03-01_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_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
2022-03-05 09:25:13	ga_ls7e_ard_3-2-1_104077_2022-03-04_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-10 08:07:35	ga_ls7e_ard_3-2-1_091085_2022-03-09_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-13 08:37:46	ga_ls7e_ard_3-2-1_096084_2022-03-12_final
2022-03-13 08:38:34	ga_ls7e_ard_3-2-1_096086_2022-03-12_final
2022-03-14 09:15:45	ga_ls7e_ard_3-2-1_103071_2022-03-13_final
2022-03-14 09:16:32	ga_ls7e_ard_3-2-1_103073_2022-03-13_final
2022-03-15 08:21:37	ga_ls7e_ard_3-2-1_094075_2022-03-14_final
2022-03-15 08:23:37	ga_ls7e_ard_3-2-1_094080_2022-03-14_final
2022-03-15 10:00:30	ga_ls7e_ard_3-2-1_110075_2022-03-15_final
2022-03-15 10:01:18	ga_ls7e_ard_3-2-1_110077_2022-03-15_final
2022-03-20 08:43:39	ga_ls7e_ard_3-2-1_097085_2022-03-19_final
2022-03-23 09:11:29	ga_ls7e_ard_3-2-1_102078_2022-03-22_final
2022-03-23 09:11:53	ga_ls7e_ard_3-2-1_102079_2022-03-22_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-25 08:59:20	ga_ls7e_ard_3-2-1_100079_2022-03-24_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-27 08:48:23	ga_ls7e_ard_3-2-1_098083_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 10:01:46	ga_ls7e_ard_3-2-1_110082_2022-03-31_final
2022-04-02 08:11:07	ga_ls7e_ard_3-2-1_092084_2022-04-01_final
2022-04-03 08:50:41	ga_ls7e_ard_3-2-1_099075_2022-04-02_final
2022-04-03 08:54:17	ga_ls7e_ard_3-2-1_099084_2022-04-02_final
2022-04-04 07:58:58	ga_ls7e_ard_3-2-1_090085_2022-04-03_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_final
2022-04-05 10:17:00	ga_ls7e_ard_3-2-1_113075_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