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 08:49:48	ga_ls7e_ard_3-2-0_096072_2021-09-17_final
2021-10-26 09:50:36	ga_ls7e_ard_3-2-0_106078_2021-10-26_final
2021-10-26 09:50:59	ga_ls7e_ard_3-2-0_106079_2021-10-26_final
2021-10-31 10:05:29	ga_ls7e_ard_3-2-0_109070_2021-10-31_final
2021-11-03 10:39:41	ga_ls7e_ard_3-2-0_114079_2021-11-03_final
2021-11-03 10:40:05	ga_ls7e_ard_3-2-0_114080_2021-11-03_final
2021-11-05 08:48:40	ga_ls7e_ard_3-2-0_096080_2021-11-04_final
2021-11-14 10:19:17	ga_ls7e_ard_3-2-1_111077_2021-11-14_final
2021-11-17 09:10:37	ga_ls7e_ard_3-2-1_100076_2021-11-16_final
2021-11-18 09:52:11	ga_ls7e_ard_3-2-1_107072_2021-11-18_final
2021-11-18 09:52:35	ga_ls7e_ard_3-2-1_107073_2021-11-18_final
2021-11-25 09:57:41	ga_ls7e_ard_3-2-1_108072_2021-11-25_final
2021-11-30 10:19:21	ga_ls7e_ard_3-2-1_111081_2021-11-30_final
2021-12-03 09:10:18	ga_ls7e_ard_3-2-1_100079_2021-12-02_final
2021-12-05 10:35:26	ga_ls7e_ard_3-2-1_114076_2021-12-05_final
2021-12-09 08:31:51	ga_ls7e_ard_3-2-1_094077_2021-12-08_final
2021-12-09 08:33:03	ga_ls7e_ard_3-2-1_094080_2021-12-08_final
2021-12-11 08:20:30	ga_ls7e_ard_3-2-1_092080_2021-12-10_final
2021-12-13 09:47:37	ga_ls7e_ard_3-2-1_106082_2021-12-13_final
2021-12-16 08:36:10	ga_ls7e_ard_3-2-1_095074_2021-12-15_final
2021-12-16 08:37:46	ga_ls7e_ard_3-2-1_095078_2021-12-15_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-21 08:57:25	ga_ls7e_ard_3-2-1_098082_2021-12-20_final
2021-12-23 08:45:15	ga_ls7e_ard_3-2-1_096083_2021-12-22_final
2021-12-25 10:09:35	ga_ls7e_ard_3-2-1_110078_2021-12-25_final
2021-12-25 10:10:22	ga_ls7e_ard_3-2-1_110080_2021-12-25_final
2021-12-26 09:12:40	ga_ls7e_ard_3-2-1_101075_2021-12-25_final
2021-12-27 08:20:32	ga_ls7e_ard_3-2-1_092084_2021-12-26_final
2021-12-29 09:44:03	ga_ls7e_ard_3-2-1_106077_2021-12-29_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-03 08:26:48	ga_ls7e_ard_3-2-1_093086_2022-01-02_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-05 08:11:26	ga_ls7e_ard_3-2-1_091079_2022-01-04_final
2022-01-06 08:54:36	ga_ls7e_ard_3-2-1_098079_2022-01-05_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-07 09:35:23	ga_ls7e_ard_3-2-1_105073_2022-01-07_final
2022-01-07 09:38:34	ga_ls7e_ard_3-2-1_105081_2022-01-07_final
2022-01-08 10:20:56	ga_ls7e_ard_3-2-1_112079_2022-01-08_final
2022-01-08 10:21:20	ga_ls7e_ard_3-2-1_112080_2022-01-08_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-10 08:31:07	ga_ls7e_ard_3-2-1_094083_2022-01-09_final
2022-01-12 09:55:03	ga_ls7e_ard_3-2-1_108077_2022-01-12_final
2022-01-13 08:58:56	ga_ls7e_ard_3-2-1_099076_2022-01-12_final
2022-01-14 09:42:30	ga_ls7e_ard_3-2-1_106077_2022-01-14_final
2022-01-15 08:46:23	ga_ls7e_ard_3-2-1_097076_2022-01-14_final
2022-01-15 10:26:04	ga_ls7e_ard_3-2-1_113078_2022-01-15_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-19 10:00:58	ga_ls7e_ard_3-2-1_109078_2022-01-19_final
2022-01-19 10:02:10	ga_ls7e_ard_3-2-1_109081_2022-01-19_final
2022-01-28 08:15:26	ga_ls7e_ard_3-2-1_092079_2022-01-27_final
2022-01-28 08:16:38	ga_ls7e_ard_3-2-1_092082_2022-01-27_final
2022-01-30 09:41:45	ga_ls7e_ard_3-2-1_106079_2022-01-30_final
2022-01-30 09:42:33	ga_ls7e_ard_3-2-1_106081_2022-01-30_final
2022-01-31 10:26:06	ga_ls7e_ard_3-2-1_113082_2022-01-31_final
2022-02-05 09:04:04	ga_ls7e_ard_3-2-1_100079_2022-02-04_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-12 09:10:19	ga_ls7e_ard_3-2-1_101081_2022-02-11_final
2022-02-13 09:51:29	ga_ls7e_ard_3-2-1_108076_2022-02-13_final
2022-02-18 08:32:14	ga_ls7e_ard_3-2-1_095080_2022-02-17_final
2022-02-18 10:11:31	ga_ls7e_ard_3-2-1_111081_2022-02-18_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-19 09:12:13	ga_ls7e_ard_3-2-1_102072_2022-02-18_final
2022-02-20 08:17:18	ga_ls7e_ard_3-2-1_093074_2022-02-19_final
2022-02-21 09:00:04	ga_ls7e_ard_3-2-1_100073_2022-02-20_final
2022-02-22 08:06:44	ga_ls7e_ard_3-2-1_091079_2022-02-21_final
2022-02-24 09:32:40	ga_ls7e_ard_3-2-1_105078_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 10:16:38	ga_ls7e_ard_3-2-1_112080_2022-02-25_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-01 08:11:27	ga_ls7e_ard_3-2-1_092077_2022-02-28_final
2022-03-01 08:11:51	ga_ls7e_ard_3-2-1_092078_2022-02-28_final
2022-03-02 08:57:01	ga_ls7e_ard_3-2-1_099083_2022-03-01_final
2022-03-03 08:01:18	ga_ls7e_ard_3-2-1_090083_2022-03-02_final
2022-03-04 08:40:52	ga_ls7e_ard_3-2-1_097074_2022-03-03_final
2022-03-07 09:11:28	ga_ls7e_ard_3-2-1_102074_2022-03-06_final
2022-03-11 08:44:21	ga_ls7e_ard_3-2-1_098069_2022-03-10_final
2022-03-12 07:54:37	ga_ls7e_ard_3-2-1_089084_2022-03-11_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-14 09:14:57	ga_ls7e_ard_3-2-1_103069_2022-03-13_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-15 08:22:25	ga_ls7e_ard_3-2-1_094077_2022-03-14_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-17 09:49:55	ga_ls7e_ard_3-2-1_108080_2022-03-17_final
2022-03-18 10:31:53	ga_ls7e_ard_3-2-1_115077_2022-03-18_final
2022-03-21 09:22:26	ga_ls7e_ard_3-2-1_104074_2022-03-20_final
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-23 09:10:17	ga_ls7e_ard_3-2-1_102075_2022-03-22_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-26 08:05:13	ga_ls7e_ard_3-2-1_091083_2022-03-25_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-04-02 08:09:56	ga_ls7e_ard_3-2-1_092081_2022-04-01_final
2022-04-02 08:10:44	ga_ls7e_ard_3-2-1_092083_2022-04-01_final
2022-04-04 09:35:03	ga_ls7e_ard_3-2-1_106078_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years