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
2021-09-20 08:40:51	ga_ls7e_ard_3-2-0_094081_2021-09-19_final
2021-10-08 10:03:22	ga_ls7e_ard_3-2-0_108075_2021-10-08_final
2021-10-11 08:57:08	ga_ls7e_ard_3-2-0_097080_2021-10-10_final
2021-10-11 10:33:37	ga_ls7e_ard_3-2-0_113074_2021-10-11_final
2021-10-16 09:11:38	ga_ls7e_ard_3-2-0_100071_2021-10-15_final
2021-10-17 08:22:18	ga_ls7e_ard_3-2-0_091087_2021-10-16_final
2021-10-17 09:56:48	ga_ls7e_ard_3-2-0_107076_2021-10-17_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-26 09:49:00	ga_ls7e_ard_3-2-0_106074_2021-10-26_final
2021-10-28 09:39:39	ga_ls7e_ard_3-2-0_104082_2021-10-28_final
2021-10-31 10:07:04	ga_ls7e_ard_3-2-0_109074_2021-10-31_final
2021-11-03 08:56:49	ga_ls7e_ard_3-2-0_098069_2021-11-02_final
2021-11-10 09:03:31	ga_ls7e_ard_3-2-0_099072_2021-11-09_final
2021-11-13 09:35:44	ga_ls7e_ard_3-2-1_104076_2021-11-13_final
2021-11-16 10:04:20	ga_ls7e_ard_3-2-1_109071_2021-11-16_final
2021-11-16 10:06:20	ga_ls7e_ard_3-2-1_109076_2021-11-16_final
2021-11-19 10:37:44	ga_ls7e_ard_3-2-1_114078_2021-11-19_final
2021-11-19 10:38:56	ga_ls7e_ard_3-2-1_114081_2021-11-19_final
2021-11-26 10:42:03	ga_ls7e_ard_3-2-1_115075_2021-11-26_final
2021-11-27 09:46:44	ga_ls7e_ard_3-2-1_106076_2021-11-27_final
2021-11-28 08:54:13	ga_ls7e_ard_3-2-1_097084_2021-11-27_final
2021-11-28 08:54:37	ga_ls7e_ard_3-2-1_097085_2021-11-27_final
2021-11-28 10:29:06	ga_ls7e_ard_3-2-1_113074_2021-11-28_final
2021-11-30 10:15:46	ga_ls7e_ard_3-2-1_111072_2021-11-30_final
2021-12-01 09:20:03	ga_ls7e_ard_3-2-1_102072_2021-11-30_final
2021-12-02 08:25:32	ga_ls7e_ard_3-2-1_093075_2021-12-01_final
2021-12-05 09:00:08	ga_ls7e_ard_3-2-1_098085_2021-12-04_final
2021-12-11 09:55:23	ga_ls7e_ard_3-2-1_108070_2021-12-11_final
2021-12-13 08:07:57	ga_ls7e_ard_3-2-1_090080_2021-12-12_final
2021-12-13 08:08:21	ga_ls7e_ard_3-2-1_090081_2021-12-12_final
2021-12-13 09:44:26	ga_ls7e_ard_3-2-1_106074_2021-12-13_final
2021-12-18 10:01:17	ga_ls7e_ard_3-2-1_109071_2021-12-18_final
2021-12-20 08:13:27	ga_ls7e_ard_3-2-1_091080_2021-12-19_final
2021-12-20 08:15:03	ga_ls7e_ard_3-2-1_091084_2021-12-19_final
2021-12-20 08:15:51	ga_ls7e_ard_3-2-1_091086_2021-12-19_final
2021-12-21 08:57:49	ga_ls7e_ard_3-2-1_098083_2021-12-20_final
2021-12-21 10:33:30	ga_ls7e_ard_3-2-1_114075_2021-12-21_final
2021-12-24 09:23:37	ga_ls7e_ard_3-2-1_103071_2021-12-23_final
2021-12-28 09:02:30	ga_ls7e_ard_3-2-1_099081_2021-12-27_final
2021-12-31 09:28:42	ga_ls7e_ard_3-2-1_104070_2021-12-30_final
2022-01-03 10:00:29	ga_ls7e_ard_3-2-1_109073_2022-01-03_final
2022-01-05 08:15:50	ga_ls7e_ard_3-2-1_091090_2022-01-04_final
2022-01-06 08:53:25	ga_ls7e_ard_3-2-1_098076_2022-01-05_final
2022-01-08 10:22:56	ga_ls7e_ard_3-2-1_112084_2022-01-08_final
2022-01-12 08:15:22	ga_ls7e_ard_3-2-1_092075_2022-01-11_final
2022-01-15 10:26:04	ga_ls7e_ard_3-2-1_113078_2022-01-15_final
2022-01-16 09:27:58	ga_ls7e_ard_3-2-1_104072_2022-01-15_final
2022-01-19 10:03:22	ga_ls7e_ard_3-2-1_109084_2022-01-19_final
2022-01-22 08:50:18	ga_ls7e_ard_3-2-1_098072_2022-01-21_final
2022-01-24 08:37:45	ga_ls7e_ard_3-2-1_096072_2022-01-23_final
2022-01-25 09:22:06	ga_ls7e_ard_3-2-1_103075_2022-01-24_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-30 08:04:52	ga_ls7e_ard_3-2-1_090084_2022-01-29_final
2022-01-31 08:45:38	ga_ls7e_ard_3-2-1_097078_2022-01-30_final
2022-01-31 10:24:31	ga_ls7e_ard_3-2-1_113078_2022-01-31_final
2022-02-06 08:10:44	ga_ls7e_ard_3-2-1_091085_2022-02-05_final
2022-02-07 08:49:07	ga_ls7e_ard_3-2-1_098073_2022-02-06_final
2022-02-07 08:53:30	ga_ls7e_ard_3-2-1_098084_2022-02-06_final
2022-02-07 10:29:59	ga_ls7e_ard_3-2-1_114078_2022-02-07_final
2022-02-10 09:21:18	ga_ls7e_ard_3-2-1_103077_2022-02-09_final
2022-02-11 10:06:50	ga_ls7e_ard_3-2-1_110083_2022-02-11_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-15 09:37:43	ga_ls7e_ard_3-2-1_106073_2022-02-15_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-17 09:27:09	ga_ls7e_ard_3-2-1_104078_2022-02-16_final
2022-02-21 08:59:40	ga_ls7e_ard_3-2-1_100072_2022-02-20_final
2022-02-22 08:10:44	ga_ls7e_ard_3-2-1_091089_2022-02-21_final
2022-02-23 08:48:42	ga_ls7e_ard_3-2-1_098076_2022-02-22_final
2022-02-27 08:22:49	ga_ls7e_ard_3-2-1_094074_2022-02-26_final
2022-02-27 08:27:12	ga_ls7e_ard_3-2-1_094085_2022-02-26_final
2022-02-28 09:07:10	ga_ls7e_ard_3-2-1_101077_2022-02-27_final
2022-03-02 08:55:25	ga_ls7e_ard_3-2-1_099079_2022-03-01_final
2022-03-04 10:20:08	ga_ls7e_ard_3-2-1_113075_2022-03-04_final
2022-03-07 09:09:52	ga_ls7e_ard_3-2-1_102070_2022-03-06_final
2022-03-08 08:17:21	ga_ls7e_ard_3-2-1_093078_2022-03-07_final
2022-03-09 09:02:30	ga_ls7e_ard_3-2-1_100083_2022-03-08_final
2022-03-10 08:05:35	ga_ls7e_ard_3-2-1_091080_2022-03-09_final
2022-03-10 08:07:59	ga_ls7e_ard_3-2-1_091086_2022-03-09_final
2022-03-10 08:08:47	ga_ls7e_ard_3-2-1_091088_2022-03-09_final
2022-03-11 10:27:13	ga_ls7e_ard_3-2-1_114079_2022-03-11_final
2022-03-12 09:27:07	ga_ls7e_ard_3-2-1_105068_2022-03-11_final
2022-03-13 08:33:23	ga_ls7e_ard_3-2-1_096073_2022-03-12_final
2022-03-15 09:59:18	ga_ls7e_ard_3-2-1_110072_2022-03-15_final
2022-03-15 10:03:41	ga_ls7e_ard_3-2-1_110083_2022-03-15_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-19 09:33:47	ga_ls7e_ard_3-2-1_106071_2022-03-19_final
2022-03-19 09:34:35	ga_ls7e_ard_3-2-1_106073_2022-03-19_final
2022-03-23 09:08:41	ga_ls7e_ard_3-2-1_102071_2022-03-22_final
2022-03-24 08:19:22	ga_ls7e_ard_3-2-1_093087_2022-03-23_final
2022-03-25 08:57:20	ga_ls7e_ard_3-2-1_100074_2022-03-24_final
2022-03-26 08:06:49	ga_ls7e_ard_3-2-1_091087_2022-03-25_final
2022-03-26 08:07:37	ga_ls7e_ard_3-2-1_091089_2022-03-25_final
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-29 10:14:43	ga_ls7e_ard_3-2-1_112083_2022-03-29_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_final
2022-04-02 08:10:20	ga_ls7e_ard_3-2-1_092082_2022-04-01_final
2022-04-02 09:46:25	ga_ls7e_ard_3-2-1_108075_2022-04-02_final
2022-04-04 07:58:34	ga_ls7e_ard_3-2-1_090084_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years