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
2020-10-06 09:37:17	ga_ls7e_ard_3-2-0_099076_2020-10-06_final
2021-09-11 08:45:02	ga_ls7e_ard_3-2-0_095074_2021-09-10_final
2021-09-11 08:46:14	ga_ls7e_ard_3-2-0_095077_2021-09-10_final
2021-09-11 10:24:19	ga_ls7e_ard_3-2-0_111075_2021-09-11_final
2021-09-11 10:25:30	ga_ls7e_ard_3-2-0_111078_2021-09-11_final
2021-09-12 09:27:24	ga_ls7e_ard_3-2-0_102072_2021-09-11_final
2021-09-18 10:32:40	ga_ls7e_ard_3-2-0_112082_2021-09-18_final
2021-09-20 10:18:32	ga_ls7e_ard_3-2-0_110078_2021-09-20_final
2021-09-24 08:14:58	ga_ls7e_ard_3-2-0_090079_2021-09-23_final
2021-09-30 09:13:02	ga_ls7e_ard_3-2-0_100071_2021-09-29_final
2021-10-10 08:17:09	ga_ls7e_ard_3-2-0_090088_2021-10-09_final
2021-10-10 09:51:14	ga_ls7e_ard_3-2-0_106076_2021-10-10_final
2021-10-14 09:24:34	ga_ls7e_ard_3-2-0_102072_2021-10-13_final
2021-10-16 09:16:25	ga_ls7e_ard_3-2-0_100083_2021-10-15_final
2021-10-17 09:57:59	ga_ls7e_ard_3-2-0_107079_2021-10-17_final
2021-10-20 10:27:25	ga_ls7e_ard_3-2-0_112076_2021-10-20_final
2021-10-25 09:08:13	ga_ls7e_ard_3-2-0_099080_2021-10-24_final
2021-10-26 09:47:00	ga_ls7e_ard_3-2-0_106069_2021-10-26_final
2021-10-28 09:34:51	ga_ls7e_ard_3-2-0_104070_2021-10-28_final
2021-10-28 09:39:15	ga_ls7e_ard_3-2-0_104081_2021-10-28_final
2021-11-02 09:58:31	ga_ls7e_ard_3-2-0_107084_2021-11-02_final
2021-11-05 10:25:09	ga_ls7e_ard_3-2-0_112074_2021-11-05_final
2021-11-07 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-14 08:38:49	ga_ls7e_ard_3-2-1_095073_2021-11-13_final
2021-11-14 10:21:17	ga_ls7e_ard_3-2-1_111082_2021-11-14_final
2021-11-15 09:23:58	ga_ls7e_ard_3-2-1_102078_2021-11-14_final
2021-11-16 10:07:32	ga_ls7e_ard_3-2-1_109079_2021-11-16_final
2021-11-18 08:18:54	ga_ls7e_ard_3-2-1_091086_2021-11-17_final
2021-11-20 08:03:33	ga_ls7e_ard_3-2-1_089079_2021-11-19_final
2021-11-20 09:40:49	ga_ls7e_ard_3-2-1_105075_2021-11-20_final
2021-11-23 08:33:45	ga_ls7e_ard_3-2-1_094078_2021-11-22_final
2021-11-28 10:30:42	ga_ls7e_ard_3-2-1_113078_2021-11-28_final
2021-11-30 10:19:21	ga_ls7e_ard_3-2-1_111081_2021-11-30_final
2021-12-01 09:22:26	ga_ls7e_ard_3-2-1_102078_2021-11-30_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-04 08:18:10	ga_ls7e_ard_3-2-1_091088_2021-12-03_final
2021-12-12 10:40:57	ga_ls7e_ard_3-2-1_115076_2021-12-12_final
2021-12-13 09:46:02	ga_ls7e_ard_3-2-1_106078_2021-12-13_final
2021-12-14 10:29:11	ga_ls7e_ard_3-2-1_113078_2021-12-14_final
2021-12-17 09:19:20	ga_ls7e_ard_3-2-1_102074_2021-12-16_final
2021-12-18 10:03:17	ga_ls7e_ard_3-2-1_109076_2021-12-18_final
2021-12-18 10:04:05	ga_ls7e_ard_3-2-1_109078_2021-12-18_final
2021-12-20 08:14:15	ga_ls7e_ard_3-2-1_091082_2021-12-19_final
2021-12-21 08:53:49	ga_ls7e_ard_3-2-1_098073_2021-12-20_final
2021-12-23 08:45:39	ga_ls7e_ard_3-2-1_096084_2021-12-22_final
2021-12-23 10:23:20	ga_ls7e_ard_3-2-1_112081_2021-12-23_final
2021-12-24 09:26:25	ga_ls7e_ard_3-2-1_103078_2021-12-23_final
2021-12-27 08:19:44	ga_ls7e_ard_3-2-1_092082_2021-12-26_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-02 09:19:43	ga_ls7e_ard_3-2-1_102079_2022-01-01_final
2022-01-03 08:22:24	ga_ls7e_ard_3-2-1_093075_2022-01-02_final
2022-01-05 08:11:26	ga_ls7e_ard_3-2-1_091079_2022-01-04_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-09 09:23:38	ga_ls7e_ard_3-2-1_103075_2022-01-08_final
2022-01-10 08:32:43	ga_ls7e_ard_3-2-1_094087_2022-01-09_final
2022-01-10 10:07:36	ga_ls7e_ard_3-2-1_110077_2022-01-10_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-15 08:48:47	ga_ls7e_ard_3-2-1_097082_2022-01-14_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-21 08:10:44	ga_ls7e_ard_3-2-1_091081_2022-01-20_final
2022-01-22 10:29:59	ga_ls7e_ard_3-2-1_114074_2022-01-22_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-06 09:47:13	ga_ls7e_ard_3-2-1_107079_2022-02-06_final
2022-02-09 10:15:49	ga_ls7e_ard_3-2-1_112074_2022-02-09_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-11 10:06:50	ga_ls7e_ard_3-2-1_110083_2022-02-11_final
2022-02-13 09:49:29	ga_ls7e_ard_3-2-1_108071_2022-02-13_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-19 09:15:00	ga_ls7e_ard_3-2-1_102079_2022-02-18_final
2022-02-20 09:54:35	ga_ls7e_ard_3-2-1_109070_2022-02-20_final
2022-02-22 09:44:01	ga_ls7e_ard_3-2-1_107075_2022-02-22_final
2022-02-24 09:30:40	ga_ls7e_ard_3-2-1_105073_2022-02-24_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-06 08:29:06	ga_ls7e_ard_3-2-1_095076_2022-03-05_final
2022-03-06 10:09:59	ga_ls7e_ard_3-2-1_111081_2022-03-06_final
2022-03-07 09:13:52	ga_ls7e_ard_3-2-1_102080_2022-03-06_final
2022-03-11 08:44:21	ga_ls7e_ard_3-2-1_098069_2022-03-10_final
2022-03-11 10:26:49	ga_ls7e_ard_3-2-1_114078_2022-03-11_final
2022-03-14 09:14:57	ga_ls7e_ard_3-2-1_103069_2022-03-13_final
2022-03-14 09:16:09	ga_ls7e_ard_3-2-1_103072_2022-03-13_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-18 08:52:12	ga_ls7e_ard_3-2-1_099075_2022-03-17_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-20 08:40:04	ga_ls7e_ard_3-2-1_097076_2022-03-19_final
2022-03-21 09:22:50	ga_ls7e_ard_3-2-1_104075_2022-03-20_final
2022-03-23 09:13:05	ga_ls7e_ard_3-2-1_102082_2022-03-22_final
2022-03-25 08:56:56	ga_ls7e_ard_3-2-1_100073_2022-03-24_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-27 08:45:11	ga_ls7e_ard_3-2-1_098075_2022-03-26_final
2022-03-30 09:14:12	ga_ls7e_ard_3-2-1_103071_2022-03-29_final
2022-03-30 09:15:48	ga_ls7e_ard_3-2-1_103075_2022-03-29_final
2022-03-31 08:20:05	ga_ls7e_ard_3-2-1_094075_2022-03-30_final
2022-04-04 07:58:10	ga_ls7e_ard_3-2-1_090083_2022-04-03_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