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
2021-09-18 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-18 10:30:16	ga_ls7e_ard_3-2-0_112076_2021-09-18_final
2021-12-19 09:09:10	ga_ls7e_ard_3-2-1_100080_2021-12-18_final
2021-12-25 10:06:47	ga_ls7e_ard_3-2-1_110071_2021-12-25_final
2021-12-25 10:11:10	ga_ls7e_ard_3-2-1_110082_2021-12-25_final
2021-12-29 08:10:22	ga_ls7e_ard_3-2-1_090090_2021-12-28_final
2021-12-30 08:47:56	ga_ls7e_ard_3-2-1_097076_2021-12-29_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-01 08:34:34	ga_ls7e_ard_3-2-1_095074_2021-12-31_final
2022-01-02 09:17:44	ga_ls7e_ard_3-2-1_102074_2022-01-01_final
2022-01-03 08:24:48	ga_ls7e_ard_3-2-1_093081_2022-01-02_final
2022-01-03 08:25:12	ga_ls7e_ard_3-2-1_093082_2022-01-02_final
2022-01-04 09:05:10	ga_ls7e_ard_3-2-1_100074_2022-01-03_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-06 10:33:53	ga_ls7e_ard_3-2-1_114080_2022-01-06_final
2022-01-08 08:38:28	ga_ls7e_ard_3-2-1_096070_2022-01-07_final
2022-01-08 08:40:04	ga_ls7e_ard_3-2-1_096074_2022-01-07_final
2022-01-09 09:21:38	ga_ls7e_ard_3-2-1_103070_2022-01-08_final
2022-01-10 08:27:55	ga_ls7e_ard_3-2-1_094075_2022-01-09_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-12 08:19:22	ga_ls7e_ard_3-2-1_092085_2022-01-11_final
2022-01-12 09:57:03	ga_ls7e_ard_3-2-1_108082_2022-01-12_final
2022-01-13 10:39:01	ga_ls7e_ard_3-2-1_115079_2022-01-13_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-15 08:49:59	ga_ls7e_ard_3-2-1_097085_2022-01-14_final
2022-01-21 08:12:44	ga_ls7e_ard_3-2-1_091086_2022-01-20_final
2022-01-21 09:46:25	ga_ls7e_ard_3-2-1_107073_2022-01-21_final
2022-01-21 09:47:13	ga_ls7e_ard_3-2-1_107075_2022-01-21_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-28 08:17:02	ga_ls7e_ard_3-2-1_092083_2022-01-27_final
2022-01-28 09:54:42	ga_ls7e_ard_3-2-1_108080_2022-01-28_final
2022-01-28 09:55:30	ga_ls7e_ard_3-2-1_108082_2022-01-28_final
2022-02-02 08:33:04	ga_ls7e_ard_3-2-1_095078_2022-02-01_final
2022-02-02 10:07:58	ga_ls7e_ard_3-2-1_111068_2022-02-02_final
2022-02-05 09:04:28	ga_ls7e_ard_3-2-1_100080_2022-02-04_final
2022-02-06 08:07:33	ga_ls7e_ard_3-2-1_091077_2022-02-05_final
2022-02-06 08:08:45	ga_ls7e_ard_3-2-1_091080_2022-02-05_final
2022-02-06 09:46:25	ga_ls7e_ard_3-2-1_107077_2022-02-06_final
2022-02-08 07:56:35	ga_ls7e_ard_3-2-1_089081_2022-02-07_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-10 09:18:54	ga_ls7e_ard_3-2-1_103071_2022-02-09_final
2022-02-11 08:28:46	ga_ls7e_ard_3-2-1_094085_2022-02-10_final
2022-02-11 10:06:27	ga_ls7e_ard_3-2-1_110082_2022-02-11_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-15 08:02:49	ga_ls7e_ard_3-2-1_090083_2022-02-14_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-16 08:42:47	ga_ls7e_ard_3-2-1_097075_2022-02-15_final
2022-02-16 08:43:11	ga_ls7e_ard_3-2-1_097076_2022-02-15_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-17 09:25:33	ga_ls7e_ard_3-2-1_104074_2022-02-16_final
2022-02-17 09:26:45	ga_ls7e_ard_3-2-1_104077_2022-02-16_final
2022-02-18 08:33:02	ga_ls7e_ard_3-2-1_095082_2022-02-17_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-20 09:58:58	ga_ls7e_ard_3-2-1_109081_2022-02-20_final
2022-02-21 09:01:15	ga_ls7e_ard_3-2-1_100076_2022-02-20_final
2022-02-22 08:05:57	ga_ls7e_ard_3-2-1_091077_2022-02-21_final
2022-02-22 09:46:49	ga_ls7e_ard_3-2-1_107082_2022-02-22_final
2022-02-26 09:16:56	ga_ls7e_ard_3-2-1_103070_2022-02-25_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-02-28 09:07:34	ga_ls7e_ard_3-2-1_101078_2022-02-27_final
2022-02-28 09:08:46	ga_ls7e_ard_3-2-1_101081_2022-02-27_final
2022-03-02 10:32:18	ga_ls7e_ard_3-2-1_115074_2022-03-02_final
2022-03-02 10:33:06	ga_ls7e_ard_3-2-1_115076_2022-03-02_final
2022-03-03 09:36:11	ga_ls7e_ard_3-2-1_106073_2022-03-03_final
2022-03-03 09:40:10	ga_ls7e_ard_3-2-1_106083_2022-03-03_final
2022-03-05 09:25:37	ga_ls7e_ard_3-2-1_104078_2022-03-04_final
2022-03-06 08:28:42	ga_ls7e_ard_3-2-1_095075_2022-03-05_final
2022-03-06 10:10:23	ga_ls7e_ard_3-2-1_111082_2022-03-06_final
2022-03-07 09:11:52	ga_ls7e_ard_3-2-1_102075_2022-03-06_final
2022-03-07 09:13:52	ga_ls7e_ard_3-2-1_102080_2022-03-06_final
2022-03-08 08:18:56	ga_ls7e_ard_3-2-1_093082_2022-03-07_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-10 08:04:23	ga_ls7e_ard_3-2-1_091077_2022-03-09_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-15 08:21:13	ga_ls7e_ard_3-2-1_094074_2022-03-14_final
2022-03-17 09:45:56	ga_ls7e_ard_3-2-1_108070_2022-03-17_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-24 09:54:15	ga_ls7e_ard_3-2-1_109077_2022-03-24_final
2022-03-25 09:00:32	ga_ls7e_ard_3-2-1_100082_2022-03-24_final
2022-03-27 08:43:36	ga_ls7e_ard_3-2-1_098071_2022-03-26_final
2022-03-27 08:45:11	ga_ls7e_ard_3-2-1_098075_2022-03-26_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-27 10:25:40	ga_ls7e_ard_3-2-1_114079_2022-03-27_final
2022-03-28 09:26:22	ga_ls7e_ard_3-2-1_105070_2022-03-27_final
2022-04-01 09:05:39	ga_ls7e_ard_3-2-1_101081_2022-03-31_final
2022-04-02 09:44:25	ga_ls7e_ard_3-2-1_108070_2022-04-02_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_2022-04-04_final
2022-04-04 09:35:27	ga_ls7e_ard_3-2-1_106079_2022-04-04_final
2022-04-05 08:35:44	ga_ls7e_ard_3-2-1_097069_2022-04-04_final
2022-04-05 08:39:44	ga_ls7e_ard_3-2-1_097079_2022-04-04_final
2022-04-05 08:40:55	ga_ls7e_ard_3-2-1_097082_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