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
2021-09-20 10:18:32	ga_ls7e_ard_3-2-0_110078_2021-09-20_final
2021-10-26 08:13:19	ga_ls7e_ard_3-2-0_090082_2021-10-25_final
2021-11-02 08:20:02	ga_ls7e_ard_3-2-0_091085_2021-11-01_final
2021-11-03 10:37:42	ga_ls7e_ard_3-2-0_114074_2021-11-03_final
2021-11-04 08:06:18	ga_ls7e_ard_3-2-0_089082_2021-11-03_final
2021-11-04 09:43:34	ga_ls7e_ard_3-2-0_105078_2021-11-04_final
2021-11-05 08:48:16	ga_ls7e_ard_3-2-0_096079_2021-11-04_final
2021-11-06 09:28:14	ga_ls7e_ard_3-2-0_103071_2021-11-05_final
2021-11-07 08:36:06	ga_ls7e_ard_3-2-0_094080_2021-11-06_final
2021-11-07 10:14:11	ga_ls7e_ard_3-2-0_110078_2021-11-07_final
2021-11-08 09:17:40	ga_ls7e_ard_3-2-0_101076_2021-11-07_final
2021-11-09 09:58:03	ga_ls7e_ard_3-2-0_108069_2021-11-09_final
2021-11-12 10:32:39	ga_ls7e_ard_3-2-1_113079_2021-11-12_final
2021-11-16 10:07:08	ga_ls7e_ard_3-2-1_109078_2021-11-16_final
2021-11-19 08:57:16	ga_ls7e_ard_3-2-1_098074_2021-11-18_final
2021-11-23 08:33:45	ga_ls7e_ard_3-2-1_094078_2021-11-22_final
2021-11-30 10:19:21	ga_ls7e_ard_3-2-1_111081_2021-11-30_final
2021-12-01 09:20:51	ga_ls7e_ard_3-2-1_102074_2021-11-30_final
2021-12-02 10:03:13	ga_ls7e_ard_3-2-1_109072_2021-12-02_final
2021-12-02 10:06:24	ga_ls7e_ard_3-2-1_109080_2021-12-02_final
2021-12-05 08:56:33	ga_ls7e_ard_3-2-1_098076_2021-12-04_final
2021-12-07 08:44:48	ga_ls7e_ard_3-2-1_096078_2021-12-06_final
2021-12-12 09:04:28	ga_ls7e_ard_3-2-1_099082_2021-12-11_final
2021-12-14 08:47:55	ga_ls7e_ard_3-2-1_097072_2021-12-13_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-14 10:29:11	ga_ls7e_ard_3-2-1_113078_2021-12-14_final
2021-12-16 08:38:10	ga_ls7e_ard_3-2-1_095079_2021-12-15_final
2021-12-16 08:38:33	ga_ls7e_ard_3-2-1_095080_2021-12-15_final
2021-12-16 08:38:57	ga_ls7e_ard_3-2-1_095081_2021-12-15_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-18 10:05:41	ga_ls7e_ard_3-2-1_109082_2021-12-18_final
2021-12-18 10:06:05	ga_ls7e_ard_3-2-1_109083_2021-12-18_final
2021-12-20 09:52:44	ga_ls7e_ard_3-2-1_107081_2021-12-20_final
2021-12-26 09:13:51	ga_ls7e_ard_3-2-1_101078_2021-12-25_final
2021-12-28 09:02:54	ga_ls7e_ard_3-2-1_099082_2021-12-27_final
2021-12-29 08:06:46	ga_ls7e_ard_3-2-1_090081_2021-12-28_final
2021-12-30 08:49:08	ga_ls7e_ard_3-2-1_097079_2021-12-29_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-01 10:16:39	ga_ls7e_ard_3-2-1_111082_2022-01-01_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-05 08:11:26	ga_ls7e_ard_3-2-1_091079_2022-01-04_final
2022-01-05 09:51:07	ga_ls7e_ard_3-2-1_107081_2022-01-05_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 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-14 08:04:49	ga_ls7e_ard_3-2-1_090080_2022-01-13_final
2022-01-15 08:46:23	ga_ls7e_ard_3-2-1_097076_2022-01-14_final
2022-01-18 09:14:13	ga_ls7e_ard_3-2-1_102069_2022-01-17_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-25 09:20:07	ga_ls7e_ard_3-2-1_103070_2022-01-24_final
2022-01-25 09:24:06	ga_ls7e_ard_3-2-1_103080_2022-01-24_final
2022-01-26 08:26:47	ga_ls7e_ard_3-2-1_094076_2022-01-25_final
2022-01-28 08:15:50	ga_ls7e_ard_3-2-1_092080_2022-01-27_final
2022-01-28 08:17:50	ga_ls7e_ard_3-2-1_092085_2022-01-27_final
2022-01-28 09:54:18	ga_ls7e_ard_3-2-1_108079_2022-01-28_final
2022-01-29 10:35:28	ga_ls7e_ard_3-2-1_115074_2022-01-29_final
2022-01-30 08:02:05	ga_ls7e_ard_3-2-1_090077_2022-01-29_final
2022-01-30 09:41:21	ga_ls7e_ard_3-2-1_106078_2022-01-30_final
2022-01-31 08:44:02	ga_ls7e_ard_3-2-1_097074_2022-01-30_final
2022-02-02 08:32:17	ga_ls7e_ard_3-2-1_095076_2022-02-01_final
2022-02-02 10:13:33	ga_ls7e_ard_3-2-1_111082_2022-02-02_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-11 10:03:39	ga_ls7e_ard_3-2-1_110075_2022-02-11_final
2022-02-12 09:07:32	ga_ls7e_ard_3-2-1_101074_2022-02-11_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-16 08:41:35	ga_ls7e_ard_3-2-1_097072_2022-02-15_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-20 08:22:05	ga_ls7e_ard_3-2-1_093086_2022-02-19_final
2022-02-22 08:09:08	ga_ls7e_ard_3-2-1_091085_2022-02-21_final
2022-02-25 08:35:22	ga_ls7e_ard_3-2-1_096074_2022-02-24_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-03 08:00:06	ga_ls7e_ard_3-2-1_090080_2022-03-02_final
2022-03-04 08:42:51	ga_ls7e_ard_3-2-1_097079_2022-03-03_final
2022-03-05 09:25:37	ga_ls7e_ard_3-2-1_104078_2022-03-04_final
2022-03-07 09:10:16	ga_ls7e_ard_3-2-1_102071_2022-03-06_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-08 08:15:45	ga_ls7e_ard_3-2-1_093074_2022-03-07_final
2022-03-09 09:00:54	ga_ls7e_ard_3-2-1_100079_2022-03-08_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-20 08:41:40	ga_ls7e_ard_3-2-1_097080_2022-03-19_final
2022-03-20 08:42:04	ga_ls7e_ard_3-2-1_097081_2022-03-19_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-25 09:00:32	ga_ls7e_ard_3-2-1_100082_2022-03-24_final
2022-03-27 08:49:11	ga_ls7e_ard_3-2-1_098085_2022-03-26_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-30 09:17:00	ga_ls7e_ard_3-2-1_103078_2022-03-29_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_final
2022-04-02 08:08:20	ga_ls7e_ard_3-2-1_092077_2022-04-01_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years