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 10:32:16	ga_ls7e_ard_3-2-0_112081_2021-09-18_final
2021-09-20 08:41:15	ga_ls7e_ard_3-2-0_094082_2021-09-19_final
2021-09-20 10:17:44	ga_ls7e_ard_3-2-0_110076_2021-09-20_final
2021-10-26 09:48:12	ga_ls7e_ard_3-2-0_106072_2021-10-26_final
2021-11-14 08:39:13	ga_ls7e_ard_3-2-1_095074_2021-11-13_final
2021-11-15 09:21:11	ga_ls7e_ard_3-2-1_102071_2021-11-14_final
2021-11-30 08:42:28	ga_ls7e_ard_3-2-1_095086_2021-11-29_final
2021-11-30 10:18:09	ga_ls7e_ard_3-2-1_111078_2021-11-30_final
2021-12-08 09:28:46	ga_ls7e_ard_3-2-1_103080_2021-12-07_final
2021-12-09 10:07:56	ga_ls7e_ard_3-2-1_110070_2021-12-09_final
2021-12-10 09:14:37	ga_ls7e_ard_3-2-1_101076_2021-12-09_final
2021-12-11 08:20:06	ga_ls7e_ard_3-2-1_092079_2021-12-10_final
2021-12-11 09:58:11	ga_ls7e_ard_3-2-1_108077_2021-12-11_final
2021-12-12 09:04:04	ga_ls7e_ard_3-2-1_099081_2021-12-11_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
2021-12-18 10:04:53	ga_ls7e_ard_3-2-1_109080_2021-12-18_final
2021-12-19 09:08:22	ga_ls7e_ard_3-2-1_100078_2021-12-18_final
2021-12-22 09:36:59	ga_ls7e_ard_3-2-1_105073_2021-12-22_final
2021-12-23 08:40:52	ga_ls7e_ard_3-2-1_096072_2021-12-22_final
2021-12-23 08:41:40	ga_ls7e_ard_3-2-1_096074_2021-12-22_final
2021-12-23 08:42:04	ga_ls7e_ard_3-2-1_096075_2021-12-22_final
2021-12-23 08:42:51	ga_ls7e_ard_3-2-1_096077_2021-12-22_final
2021-12-23 08:43:15	ga_ls7e_ard_3-2-1_096078_2021-12-22_final
2021-12-24 09:26:25	ga_ls7e_ard_3-2-1_103078_2021-12-23_final
2021-12-25 08:30:42	ga_ls7e_ard_3-2-1_094078_2021-12-24_final
2021-12-25 10:10:22	ga_ls7e_ard_3-2-1_110080_2021-12-25_final
2021-12-27 09:54:37	ga_ls7e_ard_3-2-1_108072_2021-12-27_final
2021-12-28 09:03:41	ga_ls7e_ard_3-2-1_099084_2021-12-27_final
2021-12-28 10:40:10	ga_ls7e_ard_3-2-1_115078_2021-12-28_final
2021-12-29 08:08:22	ga_ls7e_ard_3-2-1_090085_2021-12-28_final
2021-12-29 09:41:16	ga_ls7e_ard_3-2-1_106070_2021-12-29_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-30 10:28:01	ga_ls7e_ard_3-2-1_113079_2021-12-30_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2022-01-08 08:38:28	ga_ls7e_ard_3-2-1_096070_2022-01-07_final
2022-01-08 08:40:52	ga_ls7e_ard_3-2-1_096076_2022-01-07_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 08:28:19	ga_ls7e_ard_3-2-1_094076_2022-01-09_final
2022-01-10 08:29:07	ga_ls7e_ard_3-2-1_094078_2022-01-09_final
2022-01-10 08:29:31	ga_ls7e_ard_3-2-1_094079_2022-01-09_final
2022-01-12 09:52:39	ga_ls7e_ard_3-2-1_108071_2022-01-12_final
2022-01-12 09:55:03	ga_ls7e_ard_3-2-1_108077_2022-01-12_final
2022-01-15 08:47:59	ga_ls7e_ard_3-2-1_097080_2022-01-14_final
2022-01-19 10:02:10	ga_ls7e_ard_3-2-1_109081_2022-01-19_final
2022-01-19 10:02:34	ga_ls7e_ard_3-2-1_109082_2022-01-19_final
2022-01-19 10:02:58	ga_ls7e_ard_3-2-1_109083_2022-01-19_final
2022-01-22 08:51:30	ga_ls7e_ard_3-2-1_098075_2022-01-21_final
2022-01-24 08:37:21	ga_ls7e_ard_3-2-1_096071_2022-01-23_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-24 10:20:37	ga_ls7e_ard_3-2-1_112082_2022-01-24_final
2022-01-28 08:15:26	ga_ls7e_ard_3-2-1_092079_2022-01-27_final
2022-01-28 09:53:55	ga_ls7e_ard_3-2-1_108078_2022-01-28_final
2022-01-30 08:02:52	ga_ls7e_ard_3-2-1_090079_2022-01-29_final
2022-01-30 09:43:21	ga_ls7e_ard_3-2-1_106083_2022-01-30_final
2022-02-05 09:04:52	ga_ls7e_ard_3-2-1_100081_2022-02-04_final
2022-02-05 09:06:04	ga_ls7e_ard_3-2-1_100084_2022-02-04_final
2022-02-06 09:48:01	ga_ls7e_ard_3-2-1_107081_2022-02-06_final
2022-02-08 07:56:11	ga_ls7e_ard_3-2-1_089080_2022-02-07_final
2022-02-09 08:35:45	ga_ls7e_ard_3-2-1_096071_2022-02-08_final
2022-02-09 08:38:32	ga_ls7e_ard_3-2-1_096078_2022-02-08_final
2022-02-09 10:15:49	ga_ls7e_ard_3-2-1_112074_2022-02-09_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-10 09:21:41	ga_ls7e_ard_3-2-1_103078_2022-02-09_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-12 09:07:32	ga_ls7e_ard_3-2-1_101074_2022-02-11_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-14 10:35:26	ga_ls7e_ard_3-2-1_115078_2022-02-14_final
2022-02-18 08:33:26	ga_ls7e_ard_3-2-1_095083_2022-02-17_final
2022-02-22 09:43:13	ga_ls7e_ard_3-2-1_107073_2022-02-22_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-24 09:30:40	ga_ls7e_ard_3-2-1_105073_2022-02-24_final
2022-02-25 08:38:33	ga_ls7e_ard_3-2-1_096082_2022-02-24_final
2022-02-25 10:17:02	ga_ls7e_ard_3-2-1_112081_2022-02-25_final
2022-02-27 08:22:49	ga_ls7e_ard_3-2-1_094074_2022-02-26_final
2022-02-27 08:25:36	ga_ls7e_ard_3-2-1_094081_2022-02-26_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-03-06 08:29:30	ga_ls7e_ard_3-2-1_095077_2022-03-05_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-10 09:46:03	ga_ls7e_ard_3-2-1_107084_2022-03-10_final
2022-03-13 08:36:35	ga_ls7e_ard_3-2-1_096081_2022-03-12_final
2022-03-13 08:37:23	ga_ls7e_ard_3-2-1_096083_2022-03-12_final
2022-03-13 10:14:15	ga_ls7e_ard_3-2-1_112078_2022-03-13_final
2022-03-13 10:14:39	ga_ls7e_ard_3-2-1_112079_2022-03-13_final
2022-03-15 08:23:37	ga_ls7e_ard_3-2-1_094080_2022-03-14_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-20 08:42:51	ga_ls7e_ard_3-2-1_097083_2022-03-19_final
2022-03-20 10:20:56	ga_ls7e_ard_3-2-1_113081_2022-03-20_final
2022-03-22 08:26:19	ga_ls7e_ard_3-2-1_095073_2022-03-21_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-24 08:17:22	ga_ls7e_ard_3-2-1_093082_2022-03-23_final
2022-03-24 08:17:46	ga_ls7e_ard_3-2-1_093083_2022-03-23_final
2022-03-29 08:33:02	ga_ls7e_ard_3-2-1_096076_2022-03-28_final
2022-03-29 08:35:02	ga_ls7e_ard_3-2-1_096081_2022-03-28_final
2022-03-29 10:11:55	ga_ls7e_ard_3-2-1_112076_2022-03-29_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_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