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
2021-11-13 09:32:56	ga_ls7e_ard_3-2-1_104069_2021-11-13_final
2021-11-14 08:41:37	ga_ls7e_ard_3-2-1_095080_2021-11-13_final
2021-11-17 09:12:37	ga_ls7e_ard_3-2-1_100081_2021-11-16_final
2021-11-20 09:40:01	ga_ls7e_ard_3-2-1_105073_2021-11-20_final
2021-11-21 08:45:06	ga_ls7e_ard_3-2-1_096075_2021-11-20_final
2021-11-21 08:47:54	ga_ls7e_ard_3-2-1_096082_2021-11-20_final
2021-11-22 09:29:04	ga_ls7e_ard_3-2-1_103077_2021-11-21_final
2021-11-23 10:12:37	ga_ls7e_ard_3-2-1_110078_2021-11-23_final
2021-11-28 08:53:25	ga_ls7e_ard_3-2-1_097082_2021-11-27_final
2021-12-04 09:51:04	ga_ls7e_ard_3-2-1_107073_2021-12-04_final
2021-12-06 09:39:19	ga_ls7e_ard_3-2-1_105075_2021-12-06_final
2021-12-06 09:40:07	ga_ls7e_ard_3-2-1_105077_2021-12-06_final
2021-12-07 08:42:24	ga_ls7e_ard_3-2-1_096072_2021-12-06_final
2021-12-07 10:23:41	ga_ls7e_ard_3-2-1_112078_2021-12-07_final
2021-12-18 10:04:29	ga_ls7e_ard_3-2-1_109079_2021-12-18_final
2021-12-22 09:35:23	ga_ls7e_ard_3-2-1_105069_2021-12-22_final
2021-12-22 09:38:34	ga_ls7e_ard_3-2-1_105077_2021-12-22_final
2021-12-27 09:54:37	ga_ls7e_ard_3-2-1_108072_2021-12-27_final
2021-12-29 09:40:52	ga_ls7e_ard_3-2-1_106069_2021-12-29_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2021-12-31 09:28:18	ga_ls7e_ard_3-2-1_104069_2021-12-30_final
2022-01-02 09:19:20	ga_ls7e_ard_3-2-1_102078_2022-01-01_final
2022-01-03 10:03:41	ga_ls7e_ard_3-2-1_109081_2022-01-03_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-05 09:50:19	ga_ls7e_ard_3-2-1_107079_2022-01-05_final
2022-01-07 09:34:35	ga_ls7e_ard_3-2-1_105071_2022-01-07_final
2022-01-07 09:35:23	ga_ls7e_ard_3-2-1_105073_2022-01-07_final
2022-01-08 08:42:52	ga_ls7e_ard_3-2-1_096081_2022-01-07_final
2022-01-10 08:29:07	ga_ls7e_ard_3-2-1_094078_2022-01-09_final
2022-01-10 10:05:12	ga_ls7e_ard_3-2-1_110071_2022-01-10_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-13 09:01:20	ga_ls7e_ard_3-2-1_099082_2022-01-12_final
2022-01-14 09:43:18	ga_ls7e_ard_3-2-1_106079_2022-01-14_final
2022-01-15 08:46:47	ga_ls7e_ard_3-2-1_097077_2022-01-14_final
2022-01-15 10:26:28	ga_ls7e_ard_3-2-1_113079_2022-01-15_final
2022-01-17 08:34:38	ga_ls7e_ard_3-2-1_095078_2022-01-16_final
2022-01-21 08:11:08	ga_ls7e_ard_3-2-1_091082_2022-01-20_final
2022-01-21 09:45:37	ga_ls7e_ard_3-2-1_107071_2022-01-21_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-30 09:41:45	ga_ls7e_ard_3-2-1_106079_2022-01-30_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-02-02 10:12:21	ga_ls7e_ard_3-2-1_111079_2022-02-02_final
2022-02-04 08:24:30	ga_ls7e_ard_3-2-1_093088_2022-02-03_final
2022-02-04 09:59:47	ga_ls7e_ard_3-2-1_109079_2022-02-04_final
2022-02-08 09:30:16	ga_ls7e_ard_3-2-1_105068_2022-02-08_final
2022-02-09 10:18:13	ga_ls7e_ard_3-2-1_112080_2022-02-09_final
2022-02-10 09:18:30	ga_ls7e_ard_3-2-1_103070_2022-02-09_final
2022-02-15 09:39:42	ga_ls7e_ard_3-2-1_106078_2022-02-15_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-18 08:32:38	ga_ls7e_ard_3-2-1_095081_2022-02-17_final
2022-02-18 08:33:02	ga_ls7e_ard_3-2-1_095082_2022-02-17_final
2022-02-20 08:19:41	ga_ls7e_ard_3-2-1_093080_2022-02-19_final
2022-02-20 08:20:05	ga_ls7e_ard_3-2-1_093081_2022-02-19_final
2022-02-20 09:59:22	ga_ls7e_ard_3-2-1_109082_2022-02-20_final
2022-02-23 08:49:54	ga_ls7e_ard_3-2-1_098079_2022-02-22_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-02-25 08:36:57	ga_ls7e_ard_3-2-1_096078_2022-02-24_final
2022-02-27 08:24:24	ga_ls7e_ard_3-2-1_094078_2022-02-26_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-03 09:35:47	ga_ls7e_ard_3-2-1_106072_2022-03-03_final
2022-03-04 08:44:27	ga_ls7e_ard_3-2-1_097083_2022-03-03_final
2022-03-05 09:22:26	ga_ls7e_ard_3-2-1_104070_2022-03-04_final
2022-03-06 08:29:30	ga_ls7e_ard_3-2-1_095077_2022-03-05_final
2022-03-07 09:13:04	ga_ls7e_ard_3-2-1_102078_2022-03-06_final
2022-03-08 08:17:21	ga_ls7e_ard_3-2-1_093078_2022-03-07_final
2022-03-10 09:43:16	ga_ls7e_ard_3-2-1_107077_2022-03-10_final
2022-03-10 09:43:40	ga_ls7e_ard_3-2-1_107078_2022-03-10_final
2022-03-10 09:45:15	ga_ls7e_ard_3-2-1_107082_2022-03-10_final
2022-03-11 08:45:57	ga_ls7e_ard_3-2-1_098073_2022-03-10_final
2022-03-11 08:47:57	ga_ls7e_ard_3-2-1_098078_2022-03-10_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
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-20 10:18:33	ga_ls7e_ard_3-2-1_113075_2022-03-20_final
2022-03-20 10:18:56	ga_ls7e_ard_3-2-1_113076_2022-03-20_final
2022-03-22 08:25:55	ga_ls7e_ard_3-2-1_095072_2022-03-21_final
2022-03-23 09:07:54	ga_ls7e_ard_3-2-1_102069_2022-03-22_final
2022-03-24 08:18:58	ga_ls7e_ard_3-2-1_093086_2022-03-23_final
2022-03-24 09:54:39	ga_ls7e_ard_3-2-1_109078_2022-03-24_final
2022-03-25 08:59:20	ga_ls7e_ard_3-2-1_100079_2022-03-24_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-27 08:46:47	ga_ls7e_ard_3-2-1_098079_2022-03-26_final
2022-03-27 08:49:11	ga_ls7e_ard_3-2-1_098085_2022-03-26_final
2022-03-27 10:26:28	ga_ls7e_ard_3-2-1_114081_2022-03-27_final
2022-03-28 09:29:09	ga_ls7e_ard_3-2-1_105077_2022-03-27_final
2022-03-29 08:33:26	ga_ls7e_ard_3-2-1_096077_2022-03-28_final
2022-03-29 08:35:02	ga_ls7e_ard_3-2-1_096081_2022-03-28_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_final
2022-03-31 08:24:29	ga_ls7e_ard_3-2-1_094086_2022-03-30_final
2022-04-02 08:10:44	ga_ls7e_ard_3-2-1_092083_2022-04-01_final
2022-04-03 08:53:05	ga_ls7e_ard_3-2-1_099081_2022-04-02_final
2022-04-04 09:35:27	ga_ls7e_ard_3-2-1_106079_2022-04-04_final
2022-04-05 08:36:32	ga_ls7e_ard_3-2-1_097071_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