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
2021-08-01 08:57:12	ga_ls7e_ard_3-2-0_096080_2021-07-31_final
2021-08-07 08:19:59	ga_ls7e_ard_3-2-0_090081_2021-08-06_final
2021-08-26 10:28:06	ga_ls7e_ard_3-2-0_111081_2021-08-26_final
2021-08-30 08:24:09	ga_ls7e_ard_3-2-0_091081_2021-08-29_final
2021-08-30 10:00:14	ga_ls7e_ard_3-2-0_107074_2021-08-30_final
2021-08-31 10:44:37	ga_ls7e_ard_3-2-0_114077_2021-08-31_final
2021-09-08 08:15:36	ga_ls7e_ard_3-2-0_090077_2021-09-07_final
2021-09-12 09:25:49	ga_ls7e_ard_3-2-0_102068_2021-09-11_final
2021-09-13 08:38:05	ga_ls7e_ard_3-2-0_093088_2021-09-12_final
2021-09-14 09:18:28	ga_ls7e_ard_3-2-0_100081_2021-09-13_final
2021-09-16 09:04:44	ga_ls7e_ard_3-2-0_098078_2021-09-15_final
2021-09-19 09:33:22	ga_ls7e_ard_3-2-0_103073_2021-09-19_final
2021-09-22 10:05:11	ga_ls7e_ard_3-2-0_108076_2021-09-22_final
2021-09-24 08:19:22	ga_ls7e_ard_3-2-0_090090_2021-09-23_final
2021-09-24 09:49:27	ga_ls7e_ard_3-2-0_106068_2021-09-24_final
2021-10-01 08:20:31	ga_ls7e_ard_3-2-0_091079_2021-09-30_final
2021-10-09 10:46:33	ga_ls7e_ard_3-2-0_115075_2021-10-09_final
2021-10-10 09:52:02	ga_ls7e_ard_3-2-0_106078_2021-10-10_final
2021-10-12 09:37:54	ga_ls7e_ard_3-2-0_104074_2021-10-12_final
2021-10-17 08:20:19	ga_ls7e_ard_3-2-0_091082_2021-10-16_final
2021-10-19 09:43:27	ga_ls7e_ard_3-2-0_105074_2021-10-19_final
2021-10-23 09:18:22	ga_ls7e_ard_3-2-0_101074_2021-10-22_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-11-02 08:17:15	ga_ls7e_ard_3-2-0_091078_2021-11-01_final
2021-11-02 09:57:43	ga_ls7e_ard_3-2-0_107082_2021-11-02_final
2021-11-03 09:01:36	ga_ls7e_ard_3-2-0_098081_2021-11-02_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-10 10:43:36	ga_ls7e_ard_3-2-0_115075_2021-11-10_final
2021-11-11 09:48:17	ga_ls7e_ard_3-2-0_106076_2021-11-11_final
2021-11-13 09:34:32	ga_ls7e_ard_3-2-1_104073_2021-11-13_final
2021-11-14 10:21:41	ga_ls7e_ard_3-2-1_111083_2021-11-14_final
2021-11-23 10:11:01	ga_ls7e_ard_3-2-1_110074_2021-11-23_final
2021-11-23 10:11:49	ga_ls7e_ard_3-2-1_110076_2021-11-23_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-30 08:39:40	ga_ls7e_ard_3-2-1_095079_2021-11-29_final
2021-12-03 09:09:06	ga_ls7e_ard_3-2-1_100076_2021-12-02_final
2021-12-05 10:36:14	ga_ls7e_ard_3-2-1_114078_2021-12-05_final
2021-12-05 10:36:37	ga_ls7e_ard_3-2-1_114079_2021-12-05_final
2021-12-06 09:40:55	ga_ls7e_ard_3-2-1_105079_2021-12-06_final
2021-12-08 09:27:10	ga_ls7e_ard_3-2-1_103076_2021-12-07_final
2021-12-11 09:56:11	ga_ls7e_ard_3-2-1_108072_2021-12-11_final
2021-12-12 09:01:40	ga_ls7e_ard_3-2-1_099075_2021-12-11_final
2021-12-20 08:12:15	ga_ls7e_ard_3-2-1_091077_2021-12-19_final
2021-12-21 10:34:41	ga_ls7e_ard_3-2-1_114078_2021-12-21_final
2021-12-21 10:35:29	ga_ls7e_ard_3-2-1_114080_2021-12-21_final
2021-12-23 10:21:44	ga_ls7e_ard_3-2-1_112077_2021-12-23_final
2021-12-24 09:28:01	ga_ls7e_ard_3-2-1_103082_2021-12-23_final
2021-12-26 09:12:40	ga_ls7e_ard_3-2-1_101075_2021-12-25_final
2021-12-28 09:03:17	ga_ls7e_ard_3-2-1_099083_2021-12-27_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-04 09:06:46	ga_ls7e_ard_3-2-1_100078_2022-01-03_final
2022-01-05 08:11:50	ga_ls7e_ard_3-2-1_091080_2022-01-04_final
2022-01-07 09:35:47	ga_ls7e_ard_3-2-1_105074_2022-01-07_final
2022-01-08 08:40:04	ga_ls7e_ard_3-2-1_096074_2022-01-07_final
2022-01-12 09:52:15	ga_ls7e_ard_3-2-1_108070_2022-01-12_final
2022-01-21 08:13:56	ga_ls7e_ard_3-2-1_091089_2022-01-20_final
2022-01-23 09:32:16	ga_ls7e_ard_3-2-1_105069_2022-01-23_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-31 10:25:42	ga_ls7e_ard_3-2-1_113081_2022-01-31_final
2022-02-07 08:50:18	ga_ls7e_ard_3-2-1_098076_2022-02-06_final
2022-02-08 09:30:16	ga_ls7e_ard_3-2-1_105068_2022-02-08_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
2022-02-11 10:02:27	ga_ls7e_ard_3-2-1_110072_2022-02-11_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-16 08:42:23	ga_ls7e_ard_3-2-1_097074_2022-02-15_final
2022-02-16 10:22:28	ga_ls7e_ard_3-2-1_113077_2022-02-16_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-17 09:27:09	ga_ls7e_ard_3-2-1_104078_2022-02-16_final
2022-02-22 08:07:08	ga_ls7e_ard_3-2-1_091080_2022-02-21_final
2022-02-23 10:27:59	ga_ls7e_ard_3-2-1_114077_2022-02-23_final
2022-02-27 10:02:53	ga_ls7e_ard_3-2-1_110077_2022-02-27_final
2022-02-27 10:04:29	ga_ls7e_ard_3-2-1_110081_2022-02-27_final
2022-03-02 10:34:17	ga_ls7e_ard_3-2-1_115079_2022-03-02_final
2022-03-04 08:39:40	ga_ls7e_ard_3-2-1_097071_2022-03-03_final
2022-03-04 10:20:08	ga_ls7e_ard_3-2-1_113075_2022-03-04_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-04 10:21:20	ga_ls7e_ard_3-2-1_113078_2022-03-04_final
2022-03-04 10:22:08	ga_ls7e_ard_3-2-1_113080_2022-03-04_final
2022-03-06 10:09:59	ga_ls7e_ard_3-2-1_111081_2022-03-06_final
2022-03-09 09:02:30	ga_ls7e_ard_3-2-1_100083_2022-03-08_final
2022-03-11 08:47:33	ga_ls7e_ard_3-2-1_098077_2022-03-10_final
2022-03-11 08:47:57	ga_ls7e_ard_3-2-1_098078_2022-03-10_final
2022-03-13 10:16:39	ga_ls7e_ard_3-2-1_112084_2022-03-13_final
2022-03-18 08:49:25	ga_ls7e_ard_3-2-1_099068_2022-03-17_final
2022-03-18 08:51:01	ga_ls7e_ard_3-2-1_099072_2022-03-17_final
2022-03-18 10:33:05	ga_ls7e_ard_3-2-1_115080_2022-03-18_final
2022-03-19 09:34:11	ga_ls7e_ard_3-2-1_106072_2022-03-19_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-23 09:09:05	ga_ls7e_ard_3-2-1_102072_2022-03-22_final
2022-03-24 09:51:03	ga_ls7e_ard_3-2-1_109069_2022-03-24_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-25 09:01:20	ga_ls7e_ard_3-2-1_100084_2022-03-24_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-30 09:14:36	ga_ls7e_ard_3-2-1_103072_2022-03-29_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_final
2022-04-04 07:57:22	ga_ls7e_ard_3-2-1_090081_2022-04-03_final
2022-04-05 08:36:32	ga_ls7e_ard_3-2-1_097071_2022-04-04_final
2022-04-05 08:37:44	ga_ls7e_ard_3-2-1_097074_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