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 08:54:11	ga_ls7e_ard_3-2-0_096083_2021-09-17_final
2021-09-20 08:41:15	ga_ls7e_ard_3-2-0_094082_2021-09-19_final
2021-09-20 10:14:08	ga_ls7e_ard_3-2-0_110067_2021-09-20_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-09-20 10:20:31	ga_ls7e_ard_3-2-0_110083_2021-09-20_final
2021-11-17 09:10:13	ga_ls7e_ard_3-2-1_100075_2021-11-16_final
2021-11-20 08:03:33	ga_ls7e_ard_3-2-1_089079_2021-11-19_final
2021-11-25 09:56:29	ga_ls7e_ard_3-2-1_108069_2021-11-25_final
2021-11-28 08:49:49	ga_ls7e_ard_3-2-1_097073_2021-11-27_final
2021-11-28 08:51:25	ga_ls7e_ard_3-2-1_097077_2021-11-27_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-29 09:34:59	ga_ls7e_ard_3-2-1_104078_2021-11-29_final
2021-12-05 10:37:25	ga_ls7e_ard_3-2-1_114081_2021-12-05_final
2021-12-06 09:37:43	ga_ls7e_ard_3-2-1_105071_2021-12-06_final
2021-12-07 10:22:53	ga_ls7e_ard_3-2-1_112076_2021-12-07_final
2021-12-08 09:24:46	ga_ls7e_ard_3-2-1_103070_2021-12-07_final
2021-12-08 09:27:34	ga_ls7e_ard_3-2-1_103077_2021-12-07_final
2021-12-09 08:33:27	ga_ls7e_ard_3-2-1_094081_2021-12-08_final
2021-12-10 09:13:01	ga_ls7e_ard_3-2-1_101072_2021-12-09_final
2021-12-10 09:13:25	ga_ls7e_ard_3-2-1_101073_2021-12-09_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-11 09:58:59	ga_ls7e_ard_3-2-1_108079_2021-12-11_final
2021-12-16 10:13:51	ga_ls7e_ard_3-2-1_111071_2021-12-16_final
2021-12-19 09:08:22	ga_ls7e_ard_3-2-1_100078_2021-12-18_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-19 09:09:10	ga_ls7e_ard_3-2-1_100080_2021-12-18_final
2021-12-23 08:41:40	ga_ls7e_ard_3-2-1_096074_2021-12-22_final
2021-12-23 08:42:51	ga_ls7e_ard_3-2-1_096077_2021-12-22_final
2021-12-23 08:43:39	ga_ls7e_ard_3-2-1_096079_2021-12-22_final
2021-12-25 08:33:06	ga_ls7e_ard_3-2-1_094084_2021-12-24_final
2021-12-29 08:05:35	ga_ls7e_ard_3-2-1_090078_2021-12-28_final
2021-12-31 09:28:18	ga_ls7e_ard_3-2-1_104069_2021-12-30_final
2022-01-01 08:34:34	ga_ls7e_ard_3-2-1_095074_2021-12-31_final
2022-01-05 08:15:50	ga_ls7e_ard_3-2-1_091090_2022-01-04_final
2022-01-06 10:33:05	ga_ls7e_ard_3-2-1_114078_2022-01-06_final
2022-01-07 09:34:59	ga_ls7e_ard_3-2-1_105072_2022-01-07_final
2022-01-08 08:39:16	ga_ls7e_ard_3-2-1_096072_2022-01-07_final
2022-01-08 08:39:40	ga_ls7e_ard_3-2-1_096073_2022-01-07_final
2022-01-10 08:31:55	ga_ls7e_ard_3-2-1_094085_2022-01-09_final
2022-01-10 10:10:23	ga_ls7e_ard_3-2-1_110084_2022-01-10_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-12 09:53:27	ga_ls7e_ard_3-2-1_108073_2022-01-12_final
2022-01-12 09:57:03	ga_ls7e_ard_3-2-1_108082_2022-01-12_final
2022-01-13 09:01:20	ga_ls7e_ard_3-2-1_099082_2022-01-12_final
2022-01-13 10:37:49	ga_ls7e_ard_3-2-1_115076_2022-01-13_final
2022-01-14 09:43:42	ga_ls7e_ard_3-2-1_106080_2022-01-14_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-18 09:16:12	ga_ls7e_ard_3-2-1_102074_2022-01-17_final
2022-01-20 09:06:27	ga_ls7e_ard_3-2-1_100081_2022-01-19_final
2022-01-21 08:14:20	ga_ls7e_ard_3-2-1_091090_2022-01-20_final
2022-01-22 10:32:46	ga_ls7e_ard_3-2-1_114081_2022-01-22_final
2022-01-26 08:30:23	ga_ls7e_ard_3-2-1_094085_2022-01-25_final
2022-01-28 08:14:38	ga_ls7e_ard_3-2-1_092077_2022-01-27_final
2022-01-29 10:35:28	ga_ls7e_ard_3-2-1_115074_2022-01-29_final
2022-01-31 10:23:43	ga_ls7e_ard_3-2-1_113076_2022-01-31_final
2022-02-02 08:31:29	ga_ls7e_ard_3-2-1_095074_2022-02-01_final
2022-02-05 09:01:40	ga_ls7e_ard_3-2-1_100073_2022-02-04_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-06 09:47:37	ga_ls7e_ard_3-2-1_107080_2022-02-06_final
2022-02-11 08:27:58	ga_ls7e_ard_3-2-1_094083_2022-02-10_final
2022-02-11 08:29:10	ga_ls7e_ard_3-2-1_094086_2022-02-10_final
2022-02-11 10:02:03	ga_ls7e_ard_3-2-1_110071_2022-02-11_final
2022-02-12 09:07:32	ga_ls7e_ard_3-2-1_101074_2022-02-11_final
2022-02-14 10:33:50	ga_ls7e_ard_3-2-1_115074_2022-02-14_final
2022-02-16 10:24:27	ga_ls7e_ard_3-2-1_113082_2022-02-16_final
2022-02-22 08:09:08	ga_ls7e_ard_3-2-1_091085_2022-02-21_final
2022-02-24 09:32:16	ga_ls7e_ard_3-2-1_105077_2022-02-24_final
2022-02-26 09:18:07	ga_ls7e_ard_3-2-1_103073_2022-02-25_final
2022-02-27 10:04:05	ga_ls7e_ard_3-2-1_110080_2022-02-27_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-04 10:22:08	ga_ls7e_ard_3-2-1_113080_2022-03-04_final
2022-03-06 08:32:42	ga_ls7e_ard_3-2-1_095085_2022-03-05_final
2022-03-07 09:12:16	ga_ls7e_ard_3-2-1_102076_2022-03-06_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-11 08:47:57	ga_ls7e_ard_3-2-1_098078_2022-03-10_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-12 09:32:18	ga_ls7e_ard_3-2-1_105081_2022-03-12_final
2022-03-14 09:15:21	ga_ls7e_ard_3-2-1_103070_2022-03-13_final
2022-03-14 09:16:32	ga_ls7e_ard_3-2-1_103073_2022-03-13_final
2022-03-14 09:17:44	ga_ls7e_ard_3-2-1_103076_2022-03-13_final
2022-03-14 09:18:08	ga_ls7e_ard_3-2-1_103077_2022-03-13_final
2022-03-18 10:31:29	ga_ls7e_ard_3-2-1_115076_2022-03-18_final
2022-03-18 10:32:41	ga_ls7e_ard_3-2-1_115079_2022-03-18_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-19 09:34:35	ga_ls7e_ard_3-2-1_106073_2022-03-19_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-19 09:37:22	ga_ls7e_ard_3-2-1_106080_2022-03-19_final
2022-03-20 08:40:52	ga_ls7e_ard_3-2-1_097078_2022-03-19_final
2022-03-22 08:29:55	ga_ls7e_ard_3-2-1_095082_2022-03-21_final
2022-03-24 09:55:51	ga_ls7e_ard_3-2-1_109081_2022-03-24_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-27 10:25:40	ga_ls7e_ard_3-2-1_114079_2022-03-27_final
2022-04-02 09:47:12	ga_ls7e_ard_3-2-1_108077_2022-04-02_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_final
2022-04-05 08:36:32	ga_ls7e_ard_3-2-1_097071_2022-04-04_final
2022-04-05 08:40:08	ga_ls7e_ard_3-2-1_097080_2022-04-04_final
2022-04-06 09:20:53	ga_ls7e_ard_3-2-1_104074_2022-04-05_final
2022-04-06 09:22:05	ga_ls7e_ard_3-2-1_104077_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years