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
2021-07-21 09:17:06	ga_ls7e_ard_3-2-0_099081_2021-07-20_final
2021-07-22 09:59:52	ga_ls7e_ard_3-2-0_106080_2021-07-22_final
2021-07-31 09:53:42	ga_ls7e_ard_3-2-0_105082_2021-07-31_final
2021-08-03 08:39:29	ga_ls7e_ard_3-2-0_094067_2021-08-02_final
2021-08-05 10:11:24	ga_ls7e_ard_3-2-0_108081_2021-08-05_final
2021-08-07 09:58:28	ga_ls7e_ard_3-2-0_106080_2021-08-07_final
2021-08-21 08:31:07	ga_ls7e_ard_3-2-0_092081_2021-08-20_final
2021-08-21 10:11:11	ga_ls7e_ard_3-2-0_108084_2021-08-21_final
2021-08-26 10:29:18	ga_ls7e_ard_3-2-0_111084_2021-08-26_final
2021-08-28 08:38:17	ga_ls7e_ard_3-2-0_093085_2021-08-27_final
2021-08-30 09:59:03	ga_ls7e_ard_3-2-0_107071_2021-08-30_final
2021-09-02 08:56:48	ga_ls7e_ard_3-2-0_096086_2021-09-01_final
2021-09-02 10:34:28	ga_ls7e_ard_3-2-0_112083_2021-09-02_final
2021-09-04 10:22:20	ga_ls7e_ard_3-2-0_110084_2021-09-04_final
2021-09-07 10:50:59	ga_ls7e_ard_3-2-0_115079_2021-09-07_final
2021-09-09 10:33:39	ga_ls7e_ard_3-2-0_113067_2021-09-09_final
2021-09-14 09:18:52	ga_ls7e_ard_3-2-0_100082_2021-09-13_final
2021-09-23 09:12:40	ga_ls7e_ard_3-2-0_099084_2021-09-22_final
2021-09-24 09:51:27	ga_ls7e_ard_3-2-0_106073_2021-09-24_final
2021-10-02 10:42:34	ga_ls7e_ard_3-2-0_114079_2021-10-02_final
2021-10-04 08:47:34	ga_ls7e_ard_3-2-0_096070_2021-10-03_final
2021-10-04 08:52:45	ga_ls7e_ard_3-2-0_096083_2021-10-03_final
2021-10-06 10:15:07	ga_ls7e_ard_3-2-0_110073_2021-10-06_final
2021-10-13 08:41:24	ga_ls7e_ard_3-2-0_095072_2021-10-12_final
2021-10-14 09:24:10	ga_ls7e_ard_3-2-0_102071_2021-10-13_final
2021-10-20 08:46:57	ga_ls7e_ard_3-2-0_096072_2021-10-19_final
2021-10-20 08:52:32	ga_ls7e_ard_3-2-0_096086_2021-10-19_final
2021-10-22 08:38:24	ga_ls7e_ard_3-2-0_094082_2021-10-21_final
2021-10-24 08:27:27	ga_ls7e_ard_3-2-0_092086_2021-10-23_final
2021-10-25 09:06:38	ga_ls7e_ard_3-2-0_099076_2021-10-24_final
2021-10-25 09:09:49	ga_ls7e_ard_3-2-0_099084_2021-10-24_final
2021-10-26 08:14:07	ga_ls7e_ard_3-2-0_090084_2021-10-25_final
2021-10-29 08:40:44	ga_ls7e_ard_3-2-0_095074_2021-10-28_final
2021-10-29 08:43:56	ga_ls7e_ard_3-2-0_095082_2021-10-28_final
2021-10-29 10:22:49	ga_ls7e_ard_3-2-0_111082_2021-10-29_final
2021-11-02 08:21:14	ga_ls7e_ard_3-2-0_091088_2021-11-01_final
2021-11-04 08:05:54	ga_ls7e_ard_3-2-0_089081_2021-11-03_final
2021-11-05 08:51:03	ga_ls7e_ard_3-2-0_096086_2021-11-04_final
2021-11-07 10:11:24	ga_ls7e_ard_3-2-0_110071_2021-11-07_final
2021-11-12 08:50:34	ga_ls7e_ard_3-2-0_097071_2021-11-11_final
2021-11-13 09:32:56	ga_ls7e_ard_3-2-1_104069_2021-11-13_final
2021-11-15 09:20:47	ga_ls7e_ard_3-2-1_102070_2021-11-14_final
2021-11-16 08:27:27	ga_ls7e_ard_3-2-1_093076_2021-11-15_final
2021-11-17 09:09:25	ga_ls7e_ard_3-2-1_100073_2021-11-16_final
2021-11-18 09:53:23	ga_ls7e_ard_3-2-1_107075_2021-11-18_final
2021-11-20 09:39:38	ga_ls7e_ard_3-2-1_105072_2021-11-20_final
2021-11-21 10:26:47	ga_ls7e_ard_3-2-1_112082_2021-11-21_final
2021-11-21 10:27:34	ga_ls7e_ard_3-2-1_112084_2021-11-21_final
2021-11-27 09:44:44	ga_ls7e_ard_3-2-1_106071_2021-11-27_final
2021-11-30 08:40:52	ga_ls7e_ard_3-2-1_095082_2021-11-29_final
2021-12-01 09:20:27	ga_ls7e_ard_3-2-1_102073_2021-11-30_final
2021-12-02 10:07:36	ga_ls7e_ard_3-2-1_109083_2021-12-02_final
2021-12-09 10:12:43	ga_ls7e_ard_3-2-1_110082_2021-12-09_final
2021-12-10 09:13:01	ga_ls7e_ard_3-2-1_101072_2021-12-09_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-11 09:59:46	ga_ls7e_ard_3-2-1_108081_2021-12-11_final
2021-12-12 09:04:51	ga_ls7e_ard_3-2-1_099083_2021-12-11_final
2021-12-12 10:40:57	ga_ls7e_ard_3-2-1_115076_2021-12-12_final
2021-12-19 09:07:34	ga_ls7e_ard_3-2-1_100076_2021-12-18_final
2021-12-20 09:51:08	ga_ls7e_ard_3-2-1_107077_2021-12-20_final
2021-12-21 08:56:37	ga_ls7e_ard_3-2-1_098080_2021-12-20_final
2021-12-29 08:06:46	ga_ls7e_ard_3-2-1_090081_2021-12-28_final
2021-12-29 08:07:34	ga_ls7e_ard_3-2-1_090083_2021-12-28_final
2021-12-30 10:28:48	ga_ls7e_ard_3-2-1_113081_2021-12-30_final
2021-12-31 09:28:18	ga_ls7e_ard_3-2-1_104069_2021-12-30_final
2022-01-01 08:34:34	ga_ls7e_ard_3-2-1_095074_2021-12-31_final
2022-01-02 09:15:44	ga_ls7e_ard_3-2-1_102069_2022-01-01_final
2022-01-09 09:26:26	ga_ls7e_ard_3-2-1_103082_2022-01-08_final
2022-01-12 08:20:58	ga_ls7e_ard_3-2-1_092089_2022-01-11_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-15 08:44:24	ga_ls7e_ard_3-2-1_097071_2022-01-14_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-22 10:32:46	ga_ls7e_ard_3-2-1_114081_2022-01-22_final
2022-01-29 10:37:52	ga_ls7e_ard_3-2-1_115080_2022-01-29_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-01-31 08:47:38	ga_ls7e_ard_3-2-1_097083_2022-01-30_final
2022-02-03 09:15:02	ga_ls7e_ard_3-2-1_102075_2022-02-02_final
2022-02-03 09:15:50	ga_ls7e_ard_3-2-1_102077_2022-02-02_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-06 08:12:44	ga_ls7e_ard_3-2-1_091090_2022-02-05_final
2022-02-07 08:51:54	ga_ls7e_ard_3-2-1_098080_2022-02-06_final
2022-02-14 10:35:02	ga_ls7e_ard_3-2-1_115077_2022-02-14_final
2022-02-14 10:36:14	ga_ls7e_ard_3-2-1_115080_2022-02-14_final
2022-02-15 08:01:14	ga_ls7e_ard_3-2-1_090079_2022-02-14_final
2022-02-15 09:37:43	ga_ls7e_ard_3-2-1_106073_2022-02-15_final
2022-02-16 08:41:11	ga_ls7e_ard_3-2-1_097071_2022-02-15_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-24 09:30:40	ga_ls7e_ard_3-2-1_105073_2022-02-24_final
2022-02-24 09:33:52	ga_ls7e_ard_3-2-1_105081_2022-02-24_final
2022-02-25 08:39:21	ga_ls7e_ard_3-2-1_096084_2022-02-24_final
2022-03-02 10:32:42	ga_ls7e_ard_3-2-1_115075_2022-03-02_final
2022-03-10 08:05:35	ga_ls7e_ard_3-2-1_091080_2022-03-09_final
2022-03-10 09:42:52	ga_ls7e_ard_3-2-1_107076_2022-03-10_final
2022-03-11 08:49:56	ga_ls7e_ard_3-2-1_098083_2022-03-10_final
2022-03-12 07:54:37	ga_ls7e_ard_3-2-1_089084_2022-03-11_final
2022-03-24 08:18:58	ga_ls7e_ard_3-2-1_093086_2022-03-23_final
2022-03-25 08:59:20	ga_ls7e_ard_3-2-1_100079_2022-03-24_final
2022-03-27 08:49:11	ga_ls7e_ard_3-2-1_098085_2022-03-26_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