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 08:52:11	ga_ls7e_ard_3-2-0_096078_2021-09-17_final
2021-09-18 10:29:52	ga_ls7e_ard_3-2-0_112075_2021-09-18_final
2021-09-27 10:23:17	ga_ls7e_ard_3-2-0_111076_2021-09-27_final
2021-09-27 10:23:40	ga_ls7e_ard_3-2-0_111077_2021-09-27_final
2021-09-29 10:11:32	ga_ls7e_ard_3-2-0_109078_2021-09-29_final
2021-09-30 09:16:38	ga_ls7e_ard_3-2-0_100080_2021-09-29_final
2021-10-02 09:01:42	ga_ls7e_ard_3-2-0_098074_2021-10-01_final
2021-10-02 09:02:06	ga_ls7e_ard_3-2-0_098075_2021-10-01_final
2021-10-03 09:44:28	ga_ls7e_ard_3-2-0_105073_2021-10-03_final
2021-10-04 08:49:34	ga_ls7e_ard_3-2-0_096075_2021-10-03_final
2021-10-06 08:38:38	ga_ls7e_ard_3-2-0_094079_2021-10-05_final
2021-10-06 10:16:18	ga_ls7e_ard_3-2-0_110076_2021-10-06_final
2021-10-07 09:22:36	ga_ls7e_ard_3-2-0_101081_2021-10-06_final
2021-10-11 10:34:24	ga_ls7e_ard_3-2-0_113076_2021-10-11_final
2021-10-12 09:40:42	ga_ls7e_ard_3-2-0_104081_2021-10-12_final
2021-10-13 08:44:11	ga_ls7e_ard_3-2-0_095079_2021-10-12_final
2021-10-13 08:44:59	ga_ls7e_ard_3-2-0_095081_2021-10-12_final
2021-10-20 08:50:08	ga_ls7e_ard_3-2-0_096080_2021-10-19_final
2021-10-20 10:27:49	ga_ls7e_ard_3-2-0_112077_2021-10-20_final
2021-10-24 08:24:15	ga_ls7e_ard_3-2-0_092078_2021-10-23_final
2021-10-27 10:34:10	ga_ls7e_ard_3-2-0_113079_2021-10-27_final
2021-11-01 09:13:21	ga_ls7e_ard_3-2-0_100079_2021-10-31_final
2021-11-05 08:49:27	ga_ls7e_ard_3-2-0_096082_2021-11-04_final
2021-11-05 10:26:44	ga_ls7e_ard_3-2-0_112078_2021-11-05_final
2021-11-09 08:24:21	ga_ls7e_ard_3-2-0_092082_2021-11-08_final
2021-11-15 09:22:46	ga_ls7e_ard_3-2-1_102075_2021-11-14_final
2021-11-16 10:07:32	ga_ls7e_ard_3-2-1_109079_2021-11-16_final
2021-11-17 09:12:37	ga_ls7e_ard_3-2-1_100081_2021-11-16_final
2021-11-23 08:34:09	ga_ls7e_ard_3-2-1_094079_2021-11-22_final
2021-11-25 09:56:29	ga_ls7e_ard_3-2-1_108069_2021-11-25_final
2021-11-28 08:50:37	ga_ls7e_ard_3-2-1_097075_2021-11-27_final
2021-11-28 10:30:42	ga_ls7e_ard_3-2-1_113078_2021-11-28_final
2021-11-29 09:35:23	ga_ls7e_ard_3-2-1_104079_2021-11-29_final
2021-11-30 10:18:09	ga_ls7e_ard_3-2-1_111078_2021-11-30_final
2021-12-07 08:43:36	ga_ls7e_ard_3-2-1_096075_2021-12-06_final
2021-12-07 08:44:24	ga_ls7e_ard_3-2-1_096077_2021-12-06_final
2021-12-07 08:45:36	ga_ls7e_ard_3-2-1_096080_2021-12-06_final
2021-12-09 08:31:03	ga_ls7e_ard_3-2-1_094075_2021-12-08_final
2021-12-10 09:14:37	ga_ls7e_ard_3-2-1_101076_2021-12-09_final
2021-12-12 09:01:16	ga_ls7e_ard_3-2-1_099074_2021-12-11_final
2021-12-17 09:19:20	ga_ls7e_ard_3-2-1_102074_2021-12-16_final
2021-12-19 09:07:10	ga_ls7e_ard_3-2-1_100075_2021-12-18_final
2021-12-23 08:44:03	ga_ls7e_ard_3-2-1_096080_2021-12-22_final
2021-12-23 10:23:20	ga_ls7e_ard_3-2-1_112081_2021-12-23_final
2021-12-30 10:27:37	ga_ls7e_ard_3-2-1_113078_2021-12-30_final
2022-01-02 09:19:20	ga_ls7e_ard_3-2-1_102078_2022-01-01_final
2022-01-02 09:19:43	ga_ls7e_ard_3-2-1_102079_2022-01-01_final
2022-01-03 08:25:12	ga_ls7e_ard_3-2-1_093082_2022-01-02_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-05 09:47:55	ga_ls7e_ard_3-2-1_107073_2022-01-05_final
2022-01-06 08:55:24	ga_ls7e_ard_3-2-1_098081_2022-01-05_final
2022-01-07 09:37:22	ga_ls7e_ard_3-2-1_105078_2022-01-07_final
2022-01-09 09:23:38	ga_ls7e_ard_3-2-1_103075_2022-01-08_final
2022-01-10 10:09:12	ga_ls7e_ard_3-2-1_110081_2022-01-10_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-13 08:58:08	ga_ls7e_ard_3-2-1_099074_2022-01-12_final
2022-01-17 08:35:02	ga_ls7e_ard_3-2-1_095079_2022-01-16_final
2022-01-17 10:13:31	ga_ls7e_ard_3-2-1_111078_2022-01-17_final
2022-01-17 10:15:07	ga_ls7e_ard_3-2-1_111082_2022-01-17_final
2022-01-21 08:14:20	ga_ls7e_ard_3-2-1_091090_2022-01-20_final
2022-01-31 08:46:26	ga_ls7e_ard_3-2-1_097080_2022-01-30_final
2022-02-04 10:00:35	ga_ls7e_ard_3-2-1_109081_2022-02-04_final
2022-02-05 09:04:52	ga_ls7e_ard_3-2-1_100081_2022-02-04_final
2022-02-09 10:18:13	ga_ls7e_ard_3-2-1_112080_2022-02-09_final
2022-02-12 09:09:55	ga_ls7e_ard_3-2-1_101080_2022-02-11_final
2022-02-13 09:50:41	ga_ls7e_ard_3-2-1_108074_2022-02-13_final
2022-02-13 09:52:17	ga_ls7e_ard_3-2-1_108078_2022-02-13_final
2022-02-17 09:27:33	ga_ls7e_ard_3-2-1_104079_2022-02-16_final
2022-02-18 08:31:26	ga_ls7e_ard_3-2-1_095078_2022-02-17_final
2022-02-20 08:19:41	ga_ls7e_ard_3-2-1_093080_2022-02-19_final
2022-02-20 09:57:46	ga_ls7e_ard_3-2-1_109078_2022-02-20_final
2022-02-22 09:43:13	ga_ls7e_ard_3-2-1_107073_2022-02-22_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-03-04 08:39:40	ga_ls7e_ard_3-2-1_097071_2022-03-03_final
2022-03-06 08:28:42	ga_ls7e_ard_3-2-1_095075_2022-03-05_final
2022-03-08 08:16:57	ga_ls7e_ard_3-2-1_093077_2022-03-07_final
2022-03-10 09:43:40	ga_ls7e_ard_3-2-1_107078_2022-03-10_final
2022-03-12 09:28:42	ga_ls7e_ard_3-2-1_105072_2022-03-11_final
2022-03-15 10:02:05	ga_ls7e_ard_3-2-1_110079_2022-03-15_final
2022-03-17 08:09:51	ga_ls7e_ard_3-2-1_092077_2022-03-16_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-18 08:51:48	ga_ls7e_ard_3-2-1_099074_2022-03-17_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-20 08:40:28	ga_ls7e_ard_3-2-1_097077_2022-03-19_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-25 08:57:44	ga_ls7e_ard_3-2-1_100075_2022-03-24_final
2022-03-25 09:00:08	ga_ls7e_ard_3-2-1_100081_2022-03-24_final
2022-03-26 09:42:30	ga_ls7e_ard_3-2-1_107079_2022-03-26_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
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 08:33:26	ga_ls7e_ard_3-2-1_096077_2022-03-28_final
2022-03-30 09:13:49	ga_ls7e_ard_3-2-1_103070_2022-03-29_final
2022-03-31 08:22:05	ga_ls7e_ard_3-2-1_094080_2022-03-30_final
2022-04-02 09:46:49	ga_ls7e_ard_3-2-1_108076_2022-04-02_final
2022-04-04 07:56:58	ga_ls7e_ard_3-2-1_090080_2022-04-03_final
2022-04-05 08:40:55	ga_ls7e_ard_3-2-1_097082_2022-04-04_final
2022-04-05 10:17:24	ga_ls7e_ard_3-2-1_113076_2022-04-05_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