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 08:50:35	ga_ls7e_ard_3-2-0_096074_2021-09-17_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-10-26 08:12:55	ga_ls7e_ard_3-2-0_090081_2021-10-25_final
2021-10-26 09:50:59	ga_ls7e_ard_3-2-0_106079_2021-10-26_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-20 09:52:44	ga_ls7e_ard_3-2-1_107081_2021-12-20_final
2021-12-23 10:23:44	ga_ls7e_ard_3-2-1_112082_2021-12-23_final
2021-12-29 08:06:22	ga_ls7e_ard_3-2-1_090080_2021-12-28_final
2022-01-01 08:35:22	ga_ls7e_ard_3-2-1_095076_2021-12-31_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-04 09:04:46	ga_ls7e_ard_3-2-1_100073_2022-01-03_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-06 10:32:17	ga_ls7e_ard_3-2-1_114076_2022-01-06_final
2022-01-07 09:37:22	ga_ls7e_ard_3-2-1_105078_2022-01-07_final
2022-01-07 09:37:46	ga_ls7e_ard_3-2-1_105079_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 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-10 10:09:36	ga_ls7e_ard_3-2-1_110082_2022-01-10_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-13 08:57:45	ga_ls7e_ard_3-2-1_099073_2022-01-12_final
2022-01-14 08:04:25	ga_ls7e_ard_3-2-1_090079_2022-01-13_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_2022-01-13_final
2022-01-19 08:21:41	ga_ls7e_ard_3-2-1_093077_2022-01-18_final
2022-01-19 09:58:34	ga_ls7e_ard_3-2-1_109072_2022-01-19_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-21 09:48:25	ga_ls7e_ard_3-2-1_107078_2022-01-21_final
2022-01-23 09:35:52	ga_ls7e_ard_3-2-1_105078_2022-01-23_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-25 09:22:54	ga_ls7e_ard_3-2-1_103077_2022-01-24_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-26 10:07:40	ga_ls7e_ard_3-2-1_110081_2022-01-26_final
2022-01-29 08:59:23	ga_ls7e_ard_3-2-1_099081_2022-01-28_final
2022-01-30 08:03:16	ga_ls7e_ard_3-2-1_090080_2022-01-29_final
2022-01-30 09:43:21	ga_ls7e_ard_3-2-1_106083_2022-01-30_final
2022-02-03 09:17:02	ga_ls7e_ard_3-2-1_102080_2022-02-02_final
2022-02-05 09:01:40	ga_ls7e_ard_3-2-1_100073_2022-02-04_final
2022-02-05 09:02:28	ga_ls7e_ard_3-2-1_100075_2022-02-04_final
2022-02-06 08:08:21	ga_ls7e_ard_3-2-1_091079_2022-02-05_final
2022-02-06 09:47:37	ga_ls7e_ard_3-2-1_107080_2022-02-06_final
2022-02-06 09:48:25	ga_ls7e_ard_3-2-1_107082_2022-02-06_final
2022-02-08 09:31:28	ga_ls7e_ard_3-2-1_105071_2022-02-08_final
2022-02-10 09:21:41	ga_ls7e_ard_3-2-1_103078_2022-02-09_final
2022-02-11 10:02:51	ga_ls7e_ard_3-2-1_110073_2022-02-11_final
2022-02-12 09:06:44	ga_ls7e_ard_3-2-1_101072_2022-02-11_final
2022-02-13 09:49:29	ga_ls7e_ard_3-2-1_108071_2022-02-13_final
2022-02-14 08:57:45	ga_ls7e_ard_3-2-1_099081_2022-02-13_final
2022-02-14 10:33:50	ga_ls7e_ard_3-2-1_115074_2022-02-14_final
2022-02-15 08:01:14	ga_ls7e_ard_3-2-1_090079_2022-02-14_final
2022-02-18 08:29:51	ga_ls7e_ard_3-2-1_095074_2022-02-17_final
2022-02-18 08:30:14	ga_ls7e_ard_3-2-1_095075_2022-02-17_final
2022-02-18 08:32:38	ga_ls7e_ard_3-2-1_095081_2022-02-17_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-19 09:13:48	ga_ls7e_ard_3-2-1_102076_2022-02-18_final
2022-02-20 08:19:17	ga_ls7e_ard_3-2-1_093079_2022-02-19_final
2022-02-22 08:07:08	ga_ls7e_ard_3-2-1_091080_2022-02-21_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-02-24 09:33:28	ga_ls7e_ard_3-2-1_105080_2022-02-24_final
2022-02-25 08:38:33	ga_ls7e_ard_3-2-1_096082_2022-02-24_final
2022-02-25 10:15:02	ga_ls7e_ard_3-2-1_112076_2022-02-25_final
2022-02-26 09:17:20	ga_ls7e_ard_3-2-1_103071_2022-02-25_final
2022-03-01 09:52:20	ga_ls7e_ard_3-2-1_108082_2022-03-01_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-02 08:54:13	ga_ls7e_ard_3-2-1_099076_2022-03-01_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-03 08:00:30	ga_ls7e_ard_3-2-1_090081_2022-03-02_final
2022-03-04 08:41:40	ga_ls7e_ard_3-2-1_097076_2022-03-03_final
2022-03-04 08:42:51	ga_ls7e_ard_3-2-1_097079_2022-03-03_final
2022-03-05 09:22:50	ga_ls7e_ard_3-2-1_104071_2022-03-04_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-08 08:18:09	ga_ls7e_ard_3-2-1_093080_2022-03-07_final
2022-03-08 09:56:13	ga_ls7e_ard_3-2-1_109078_2022-03-08_final
2022-03-08 09:57:01	ga_ls7e_ard_3-2-1_109080_2022-03-08_final
2022-03-09 09:01:18	ga_ls7e_ard_3-2-1_100080_2022-03-08_final
2022-03-11 08:48:44	ga_ls7e_ard_3-2-1_098080_2022-03-10_final
2022-03-11 10:27:13	ga_ls7e_ard_3-2-1_114079_2022-03-11_final
2022-03-12 09:28:42	ga_ls7e_ard_3-2-1_105072_2022-03-11_final
2022-03-13 08:32:59	ga_ls7e_ard_3-2-1_096072_2022-03-12_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-18 08:51:25	ga_ls7e_ard_3-2-1_099073_2022-03-17_final
2022-03-19 07:58:54	ga_ls7e_ard_3-2-1_090081_2022-03-18_final
2022-03-20 08:40:28	ga_ls7e_ard_3-2-1_097077_2022-03-19_final
2022-03-20 08:42:04	ga_ls7e_ard_3-2-1_097081_2022-03-19_final
2022-03-20 08:42:51	ga_ls7e_ard_3-2-1_097083_2022-03-19_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-23 09:11:29	ga_ls7e_ard_3-2-1_102078_2022-03-22_final
2022-03-24 08:16:58	ga_ls7e_ard_3-2-1_093081_2022-03-23_final
2022-03-24 08:17:46	ga_ls7e_ard_3-2-1_093083_2022-03-23_final
2022-03-28 09:27:09	ga_ls7e_ard_3-2-1_105072_2022-03-27_final
2022-03-28 09:29:09	ga_ls7e_ard_3-2-1_105077_2022-03-27_final
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 08:34:14	ga_ls7e_ard_3-2-1_096079_2022-03-28_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-03-31 08:22:05	ga_ls7e_ard_3-2-1_094080_2022-03-30_final
2022-04-02 08:09:08	ga_ls7e_ard_3-2-1_092079_2022-04-01_final
2022-04-02 09:44:01	ga_ls7e_ard_3-2-1_108069_2022-04-02_final
2022-04-02 09:45:13	ga_ls7e_ard_3-2-1_108072_2022-04-02_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_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