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
2021-10-25 09:06:38	ga_ls7e_ard_3-2-0_099076_2021-10-24_final
2021-10-26 08:11:43	ga_ls7e_ard_3-2-0_090078_2021-10-25_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-11-04 09:41:11	ga_ls7e_ard_3-2-0_105072_2021-11-04_final
2021-11-05 08:45:52	ga_ls7e_ard_3-2-0_096073_2021-11-04_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-06 09:30:14	ga_ls7e_ard_3-2-0_103076_2021-11-06_final
2021-11-08 09:16:29	ga_ls7e_ard_3-2-0_101073_2021-11-07_final
2021-11-08 09:18:04	ga_ls7e_ard_3-2-0_101077_2021-11-07_final
2021-11-21 08:43:55	ga_ls7e_ard_3-2-1_096072_2021-11-20_final
2021-11-21 08:44:18	ga_ls7e_ard_3-2-1_096073_2021-11-20_final
2021-11-26 10:42:51	ga_ls7e_ard_3-2-1_115077_2021-11-26_final
2021-12-01 09:20:51	ga_ls7e_ard_3-2-1_102074_2021-11-30_final
2021-12-02 08:28:43	ga_ls7e_ard_3-2-1_093083_2021-12-01_final
2021-12-02 10:03:13	ga_ls7e_ard_3-2-1_109072_2021-12-02_final
2021-12-24 09:24:49	ga_ls7e_ard_3-2-1_103074_2021-12-23_final
2021-12-27 09:57:25	ga_ls7e_ard_3-2-1_108079_2021-12-27_final
2021-12-29 08:06:22	ga_ls7e_ard_3-2-1_090080_2021-12-28_final
2021-12-29 08:07:34	ga_ls7e_ard_3-2-1_090083_2021-12-28_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2022-01-01 08:36:58	ga_ls7e_ard_3-2-1_095080_2021-12-31_final
2022-01-02 09:17:44	ga_ls7e_ard_3-2-1_102074_2022-01-01_final
2022-01-03 08:26:24	ga_ls7e_ard_3-2-1_093085_2022-01-02_final
2022-01-04 09:05:34	ga_ls7e_ard_3-2-1_100075_2022-01-03_final
2022-01-06 10:32:41	ga_ls7e_ard_3-2-1_114077_2022-01-06_final
2022-01-07 09:38:10	ga_ls7e_ard_3-2-1_105080_2022-01-07_final
2022-01-08 08:40:04	ga_ls7e_ard_3-2-1_096074_2022-01-07_final
2022-01-08 08:42:28	ga_ls7e_ard_3-2-1_096080_2022-01-07_final
2022-01-08 08:43:16	ga_ls7e_ard_3-2-1_096082_2022-01-07_final
2022-01-09 09:21:38	ga_ls7e_ard_3-2-1_103070_2022-01-08_final
2022-01-10 08:30:19	ga_ls7e_ard_3-2-1_094081_2022-01-09_final
2022-01-11 09:13:29	ga_ls7e_ard_3-2-1_101081_2022-01-10_final
2022-01-12 08:18:58	ga_ls7e_ard_3-2-1_092084_2022-01-11_final
2022-01-15 08:48:47	ga_ls7e_ard_3-2-1_097082_2022-01-14_final
2022-01-15 08:49:11	ga_ls7e_ard_3-2-1_097083_2022-01-14_final
2022-01-15 10:27:40	ga_ls7e_ard_3-2-1_113082_2022-01-15_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-21 09:46:25	ga_ls7e_ard_3-2-1_107073_2022-01-21_final
2022-01-22 10:31:35	ga_ls7e_ard_3-2-1_114078_2022-01-22_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-03 09:16:38	ga_ls7e_ard_3-2-1_102079_2022-02-02_final
2022-02-06 08:09:09	ga_ls7e_ard_3-2-1_091081_2022-02-05_final
2022-02-06 08:10:44	ga_ls7e_ard_3-2-1_091085_2022-02-05_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-12 09:08:19	ga_ls7e_ard_3-2-1_101076_2022-02-11_final
2022-02-13 09:49:29	ga_ls7e_ard_3-2-1_108071_2022-02-13_final
2022-02-16 08:42:23	ga_ls7e_ard_3-2-1_097074_2022-02-15_final
2022-02-16 10:24:04	ga_ls7e_ard_3-2-1_113081_2022-02-16_final
2022-02-17 09:27:09	ga_ls7e_ard_3-2-1_104078_2022-02-16_final
2022-02-17 09:27:57	ga_ls7e_ard_3-2-1_104080_2022-02-16_final
2022-02-20 08:21:17	ga_ls7e_ard_3-2-1_093084_2022-02-19_final
2022-02-20 09:57:22	ga_ls7e_ard_3-2-1_109077_2022-02-20_final
2022-02-21 09:01:15	ga_ls7e_ard_3-2-1_100076_2022-02-20_final
2022-02-21 09:02:27	ga_ls7e_ard_3-2-1_100079_2022-02-20_final
2022-02-22 08:10:44	ga_ls7e_ard_3-2-1_091089_2022-02-21_final
2022-02-22 09:44:49	ga_ls7e_ard_3-2-1_107077_2022-02-22_final
2022-02-23 08:47:55	ga_ls7e_ard_3-2-1_098074_2022-02-22_final
2022-02-23 08:49:54	ga_ls7e_ard_3-2-1_098079_2022-02-22_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-23 10:27:11	ga_ls7e_ard_3-2-1_114075_2022-02-23_final
2022-02-24 09:29:29	ga_ls7e_ard_3-2-1_105070_2022-02-23_final
2022-02-24 09:33:28	ga_ls7e_ard_3-2-1_105080_2022-02-24_final
2022-02-25 08:36:57	ga_ls7e_ard_3-2-1_096078_2022-02-24_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_final
2022-02-27 10:04:29	ga_ls7e_ard_3-2-1_110081_2022-02-27_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-03-01 08:12:39	ga_ls7e_ard_3-2-1_092080_2022-02-28_final
2022-03-01 09:53:07	ga_ls7e_ard_3-2-1_108084_2022-03-01_final
2022-03-03 09:36:11	ga_ls7e_ard_3-2-1_106073_2022-03-03_final
2022-03-04 08:38:52	ga_ls7e_ard_3-2-1_097069_2022-03-03_final
2022-03-06 10:07:35	ga_ls7e_ard_3-2-1_111075_2022-03-06_final
2022-03-07 09:13:52	ga_ls7e_ard_3-2-1_102080_2022-03-06_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-08 09:56:13	ga_ls7e_ard_3-2-1_109078_2022-03-08_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-10 09:41:40	ga_ls7e_ard_3-2-1_107073_2022-03-10_final
2022-03-11 10:27:13	ga_ls7e_ard_3-2-1_114079_2022-03-11_final
2022-03-13 08:34:11	ga_ls7e_ard_3-2-1_096075_2022-03-12_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-17 08:09:27	ga_ls7e_ard_3-2-1_092076_2022-03-16_final
2022-03-20 08:38:28	ga_ls7e_ard_3-2-1_097072_2022-03-19_final
2022-03-20 08:42:51	ga_ls7e_ard_3-2-1_097083_2022-03-19_final
2022-03-21 09:20:26	ga_ls7e_ard_3-2-1_104069_2022-03-20_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-25 08:58:08	ga_ls7e_ard_3-2-1_100076_2022-03-24_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-27 10:25:16	ga_ls7e_ard_3-2-1_114078_2022-03-27_final
2022-03-28 09:29:33	ga_ls7e_ard_3-2-1_105078_2022-03-27_final
2022-03-29 10:13:07	ga_ls7e_ard_3-2-1_112079_2022-03-29_final
2022-03-30 09:13:25	ga_ls7e_ard_3-2-1_103069_2022-03-29_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_final
2022-04-01 09:04:03	ga_ls7e_ard_3-2-1_101077_2022-03-31_final
2022-04-02 08:07:56	ga_ls7e_ard_3-2-1_092076_2022-04-01_final
2022-04-02 08:08:20	ga_ls7e_ard_3-2-1_092077_2022-04-01_final
2022-04-02 08:09:08	ga_ls7e_ard_3-2-1_092079_2022-04-01_final
2022-04-02 08:09:32	ga_ls7e_ard_3-2-1_092080_2022-04-01_final
2022-04-04 09:33:27	ga_ls7e_ard_3-2-1_106074_2022-04-04_final
2022-04-04 09:34:39	ga_ls7e_ard_3-2-1_106077_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