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
2021-03-25 08:24:23	ga_ls7e_ard_3-2-0_089079_2021-03-24_final
2021-10-26 08:13:19	ga_ls7e_ard_3-2-0_090082_2021-10-25_final
2021-10-26 08:14:54	ga_ls7e_ard_3-2-0_090086_2021-10-25_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-26 09:52:35	ga_ls7e_ard_3-2-0_106083_2021-10-26_final
2021-11-14 10:17:18	ga_ls7e_ard_3-2-1_111072_2021-11-14_final
2021-11-14 10:18:29	ga_ls7e_ard_3-2-1_111075_2021-11-14_final
2021-11-17 09:09:01	ga_ls7e_ard_3-2-1_100072_2021-11-16_final
2021-11-18 09:52:59	ga_ls7e_ard_3-2-1_107074_2021-11-18_final
2021-11-23 10:10:38	ga_ls7e_ard_3-2-1_110073_2021-11-23_final
2021-11-27 09:44:44	ga_ls7e_ard_3-2-1_106071_2021-11-27_final
2021-11-28 08:51:49	ga_ls7e_ard_3-2-1_097078_2021-11-27_final
2021-11-29 09:31:48	ga_ls7e_ard_3-2-1_104070_2021-11-29_final
2021-11-30 08:41:16	ga_ls7e_ard_3-2-1_095083_2021-11-29_final
2021-11-30 10:19:45	ga_ls7e_ard_3-2-1_111082_2021-11-30_final
2021-12-02 10:05:36	ga_ls7e_ard_3-2-1_109078_2021-12-02_final
2021-12-03 09:07:54	ga_ls7e_ard_3-2-1_100073_2021-12-02_final
2021-12-05 08:53:21	ga_ls7e_ard_3-2-1_098068_2021-12-04_final
2021-12-06 09:40:55	ga_ls7e_ard_3-2-1_105079_2021-12-06_final
2021-12-20 09:53:32	ga_ls7e_ard_3-2-1_107083_2021-12-20_final
2021-12-22 09:36:11	ga_ls7e_ard_3-2-1_105071_2021-12-22_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-29 09:41:16	ga_ls7e_ard_3-2-1_106070_2021-12-29_final
2021-12-29 09:42:51	ga_ls7e_ard_3-2-1_106074_2021-12-29_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2022-01-01 10:17:03	ga_ls7e_ard_3-2-1_111083_2022-01-01_final
2022-01-02 09:16:32	ga_ls7e_ard_3-2-1_102071_2022-01-01_final
2022-01-03 08:23:12	ga_ls7e_ard_3-2-1_093077_2022-01-02_final
2022-01-03 09:59:41	ga_ls7e_ard_3-2-1_109071_2022-01-03_final
2022-01-08 08:38:52	ga_ls7e_ard_3-2-1_096071_2022-01-07_final
2022-01-08 10:22:08	ga_ls7e_ard_3-2-1_112082_2022-01-08_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-14 09:44:06	ga_ls7e_ard_3-2-1_106081_2022-01-14_final
2022-01-15 10:24:52	ga_ls7e_ard_3-2-1_113075_2022-01-15_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-17 10:11:31	ga_ls7e_ard_3-2-1_111073_2022-01-17_final
2022-01-19 08:22:05	ga_ls7e_ard_3-2-1_093078_2022-01-18_final
2022-01-21 08:13:56	ga_ls7e_ard_3-2-1_091089_2022-01-20_final
2022-01-23 07:57:23	ga_ls7e_ard_3-2-1_089079_2022-01-22_final
2022-01-23 09:36:15	ga_ls7e_ard_3-2-1_105079_2022-01-23_final
2022-01-24 08:36:57	ga_ls7e_ard_3-2-1_096070_2022-01-23_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-25 09:20:07	ga_ls7e_ard_3-2-1_103070_2022-01-24_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-03 09:12:38	ga_ls7e_ard_3-2-1_102069_2022-02-02_final
2022-02-04 08:19:43	ga_ls7e_ard_3-2-1_093076_2022-02-03_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-05 09:05:16	ga_ls7e_ard_3-2-1_100082_2022-02-04_final
2022-02-06 08:12:20	ga_ls7e_ard_3-2-1_091089_2022-02-05_final
2022-02-07 08:51:54	ga_ls7e_ard_3-2-1_098080_2022-02-06_final
2022-02-08 07:55:47	ga_ls7e_ard_3-2-1_089079_2022-02-07_final
2022-02-09 08:36:09	ga_ls7e_ard_3-2-1_096072_2022-02-08_final
2022-02-11 10:06:50	ga_ls7e_ard_3-2-1_110083_2022-02-11_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-12 09:07:32	ga_ls7e_ard_3-2-1_101074_2022-02-11_final
2022-02-15 08:05:37	ga_ls7e_ard_3-2-1_090090_2022-02-14_final
2022-02-15 09:36:07	ga_ls7e_ard_3-2-1_106069_2022-02-15_final
2022-02-15 09:36:31	ga_ls7e_ard_3-2-1_106070_2022-02-15_final
2022-02-15 09:37:19	ga_ls7e_ard_3-2-1_106072_2022-02-15_final
2022-02-18 10:09:31	ga_ls7e_ard_3-2-1_111076_2022-02-18_final
2022-02-20 09:59:22	ga_ls7e_ard_3-2-1_109082_2022-02-20_final
2022-02-22 08:07:56	ga_ls7e_ard_3-2-1_091082_2022-02-21_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-23 10:28:47	ga_ls7e_ard_3-2-1_114079_2022-02-23_final
2022-02-23 10:29:11	ga_ls7e_ard_3-2-1_114080_2022-02-23_final
2022-02-24 09:30:40	ga_ls7e_ard_3-2-1_105073_2022-02-24_final
2022-02-27 08:25:36	ga_ls7e_ard_3-2-1_094081_2022-02-26_final
2022-02-28 09:09:34	ga_ls7e_ard_3-2-1_101083_2022-02-27_final
2022-03-02 08:55:49	ga_ls7e_ard_3-2-1_099080_2022-03-01_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-04 08:40:52	ga_ls7e_ard_3-2-1_097074_2022-03-03_final
2022-03-04 10:20:08	ga_ls7e_ard_3-2-1_113075_2022-03-04_final
2022-03-04 10:22:08	ga_ls7e_ard_3-2-1_113080_2022-03-04_final
2022-03-08 09:57:25	ga_ls7e_ard_3-2-1_109081_2022-03-08_final
2022-03-09 08:58:54	ga_ls7e_ard_3-2-1_100074_2022-03-08_final
2022-03-09 08:59:42	ga_ls7e_ard_3-2-1_100076_2022-03-08_final
2022-03-10 08:09:11	ga_ls7e_ard_3-2-1_091089_2022-03-09_final
2022-03-10 09:40:28	ga_ls7e_ard_3-2-1_107070_2022-03-10_final
2022-03-11 08:47:33	ga_ls7e_ard_3-2-1_098077_2022-03-10_final
2022-03-11 08:50:44	ga_ls7e_ard_3-2-1_098085_2022-03-10_final
2022-03-12 07:53:25	ga_ls7e_ard_3-2-1_089081_2022-03-11_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-13 08:36:59	ga_ls7e_ard_3-2-1_096082_2022-03-12_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-15 09:59:42	ga_ls7e_ard_3-2-1_110073_2022-03-15_final
2022-03-15 10:00:30	ga_ls7e_ard_3-2-1_110075_2022-03-15_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-26 08:02:26	ga_ls7e_ard_3-2-1_091076_2022-03-25_final
2022-03-26 09:43:42	ga_ls7e_ard_3-2-1_107082_2022-03-26_final
2022-03-29 08:36:38	ga_ls7e_ard_3-2-1_096085_2022-03-28_final
2022-03-29 10:15:07	ga_ls7e_ard_3-2-1_112084_2022-03-29_final
2022-03-31 08:19:17	ga_ls7e_ard_3-2-1_094073_2022-03-30_final
2022-03-31 08:22:53	ga_ls7e_ard_3-2-1_094082_2022-03-30_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-02 08:11:07	ga_ls7e_ard_3-2-1_092084_2022-04-01_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_final
2022-04-04 09:33:27	ga_ls7e_ard_3-2-1_106074_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