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
2021-09-12 09:28:12	ga_ls7e_ard_3-2-0_102074_2021-09-11_final
2021-09-18 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-18 08:54:11	ga_ls7e_ard_3-2-0_096083_2021-09-17_final
2021-09-20 08:41:39	ga_ls7e_ard_3-2-0_094083_2021-09-19_final
2021-09-25 08:55:21	ga_ls7e_ard_3-2-0_097072_2021-09-24_final
2021-09-25 08:59:20	ga_ls7e_ard_3-2-0_097082_2021-09-24_final
2021-09-26 09:38:31	ga_ls7e_ard_3-2-0_104072_2021-09-26_final
2021-09-30 09:16:14	ga_ls7e_ard_3-2-0_100079_2021-09-29_final
2021-10-06 10:16:18	ga_ls7e_ard_3-2-0_110076_2021-10-06_final
2021-10-08 08:27:17	ga_ls7e_ard_3-2-0_092082_2021-10-07_final
2021-10-08 10:04:58	ga_ls7e_ard_3-2-0_108079_2021-10-08_final
2021-10-08 10:05:22	ga_ls7e_ard_3-2-0_108080_2021-10-08_final
2021-10-10 08:13:09	ga_ls7e_ard_3-2-0_090078_2021-10-09_final
2021-10-19 09:41:52	ga_ls7e_ard_3-2-0_105070_2021-10-19_final
2021-10-19 09:42:39	ga_ls7e_ard_3-2-0_105072_2021-10-19_final
2021-10-20 08:51:20	ga_ls7e_ard_3-2-0_096083_2021-10-19_final
2021-10-23 09:19:34	ga_ls7e_ard_3-2-0_101077_2021-10-22_final
2021-10-24 08:25:27	ga_ls7e_ard_3-2-0_092081_2021-10-23_final
2021-10-24 10:03:32	ga_ls7e_ard_3-2-0_108079_2021-10-24_final
2021-10-26 09:50:36	ga_ls7e_ard_3-2-0_106078_2021-10-26_final
2021-10-29 10:20:01	ga_ls7e_ard_3-2-0_111075_2021-10-29_final
2021-10-30 09:23:07	ga_ls7e_ard_3-2-0_102072_2021-10-29_final
2021-10-31 08:30:35	ga_ls7e_ard_3-2-0_093080_2021-10-30_final
2021-10-31 10:06:17	ga_ls7e_ard_3-2-0_109072_2021-10-31_final
2021-10-31 10:09:52	ga_ls7e_ard_3-2-0_109081_2021-10-31_final
2021-11-02 09:54:08	ga_ls7e_ard_3-2-0_107073_2021-11-02_final
2021-11-04 09:43:34	ga_ls7e_ard_3-2-0_105078_2021-11-04_final
2021-11-09 08:23:57	ga_ls7e_ard_3-2-0_092081_2021-11-08_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-12 08:52:58	ga_ls7e_ard_3-2-0_097077_2021-11-11_final
2021-11-13 09:34:32	ga_ls7e_ard_3-2-1_104073_2021-11-13_final
2021-11-16 10:04:44	ga_ls7e_ard_3-2-1_109072_2021-11-16_final
2021-11-19 10:37:20	ga_ls7e_ard_3-2-1_114077_2021-11-19_final
2021-11-21 08:45:30	ga_ls7e_ard_3-2-1_096076_2021-11-20_final
2021-11-21 08:47:54	ga_ls7e_ard_3-2-1_096082_2021-11-20_final
2021-11-23 10:12:37	ga_ls7e_ard_3-2-1_110078_2021-11-23_final
2021-11-29 09:34:35	ga_ls7e_ard_3-2-1_104077_2021-11-29_final
2021-12-02 08:27:56	ga_ls7e_ard_3-2-1_093081_2021-12-01_final
2021-12-06 09:40:31	ga_ls7e_ard_3-2-1_105078_2021-12-06_final
2021-12-07 08:42:24	ga_ls7e_ard_3-2-1_096072_2021-12-06_final
2021-12-07 08:44:48	ga_ls7e_ard_3-2-1_096078_2021-12-06_final
2021-12-18 10:03:41	ga_ls7e_ard_3-2-1_109077_2021-12-18_final
2021-12-23 08:42:51	ga_ls7e_ard_3-2-1_096077_2021-12-22_final
2021-12-24 09:26:49	ga_ls7e_ard_3-2-1_103079_2021-12-23_final
2021-12-25 08:33:53	ga_ls7e_ard_3-2-1_094086_2021-12-24_final
2021-12-26 09:15:03	ga_ls7e_ard_3-2-1_101081_2021-12-25_final
2022-01-02 09:18:56	ga_ls7e_ard_3-2-1_102077_2022-01-01_final
2022-01-04 09:05:10	ga_ls7e_ard_3-2-1_100074_2022-01-03_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-06 08:53:25	ga_ls7e_ard_3-2-1_098076_2022-01-05_final
2022-01-07 09:34:59	ga_ls7e_ard_3-2-1_105072_2022-01-07_final
2022-01-07 09:38:58	ga_ls7e_ard_3-2-1_105082_2022-01-07_final
2022-01-08 08:42:04	ga_ls7e_ard_3-2-1_096079_2022-01-07_final
2022-01-08 10:19:21	ga_ls7e_ard_3-2-1_112075_2022-01-08_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
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-13 10:38:13	ga_ls7e_ard_3-2-1_115077_2022-01-13_final
2022-01-14 09:42:30	ga_ls7e_ard_3-2-1_106077_2022-01-14_final
2022-01-15 08:48:23	ga_ls7e_ard_3-2-1_097081_2022-01-14_final
2022-01-19 08:25:17	ga_ls7e_ard_3-2-1_093086_2022-01-18_final
2022-01-21 08:11:08	ga_ls7e_ard_3-2-1_091082_2022-01-20_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-31 08:47:14	ga_ls7e_ard_3-2-1_097082_2022-01-30_final
2022-02-02 08:35:28	ga_ls7e_ard_3-2-1_095084_2022-02-01_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-11 08:27:58	ga_ls7e_ard_3-2-1_094083_2022-02-10_final
2022-02-16 08:44:47	ga_ls7e_ard_3-2-1_097080_2022-02-15_final
2022-02-16 10:23:16	ga_ls7e_ard_3-2-1_113079_2022-02-16_final
2022-02-17 09:27:57	ga_ls7e_ard_3-2-1_104080_2022-02-16_final
2022-02-18 08:32:14	ga_ls7e_ard_3-2-1_095080_2022-02-17_final
2022-02-24 09:33:28	ga_ls7e_ard_3-2-1_105080_2022-02-24_final
2022-02-26 09:18:07	ga_ls7e_ard_3-2-1_103073_2022-02-25_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-02-27 08:23:36	ga_ls7e_ard_3-2-1_094076_2022-02-26_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-03-02 10:34:41	ga_ls7e_ard_3-2-1_115080_2022-03-02_final
2022-03-08 08:16:09	ga_ls7e_ard_3-2-1_093075_2022-03-07_final
2022-03-08 08:18:09	ga_ls7e_ard_3-2-1_093080_2022-03-07_final
2022-03-08 09:57:01	ga_ls7e_ard_3-2-1_109080_2022-03-08_final
2022-03-10 09:44:04	ga_ls7e_ard_3-2-1_107079_2022-03-10_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-20 08:39:16	ga_ls7e_ard_3-2-1_097074_2022-03-19_final
2022-03-21 09:24:02	ga_ls7e_ard_3-2-1_104078_2022-03-20_final
2022-03-21 09:24:50	ga_ls7e_ard_3-2-1_104080_2022-03-20_final
2022-03-24 08:15:22	ga_ls7e_ard_3-2-1_093077_2022-03-23_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-03-30 09:16:12	ga_ls7e_ard_3-2-1_103076_2022-03-29_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_final
2022-04-01 09:03:39	ga_ls7e_ard_3-2-1_101076_2022-03-31_final
2022-04-02 09:45:13	ga_ls7e_ard_3-2-1_108072_2022-04-02_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