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 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-20 10:19:19	ga_ls7e_ard_3-2-0_110080_2021-09-20_final
2021-10-26 08:12:55	ga_ls7e_ard_3-2-0_090081_2021-10-25_final
2021-10-26 09:52:11	ga_ls7e_ard_3-2-0_106082_2021-10-26_final
2021-11-15 09:23:10	ga_ls7e_ard_3-2-1_102076_2021-11-14_final
2021-11-30 08:40:28	ga_ls7e_ard_3-2-1_095081_2021-11-29_final
2021-12-07 08:46:00	ga_ls7e_ard_3-2-1_096081_2021-12-06_final
2021-12-08 09:29:34	ga_ls7e_ard_3-2-1_103082_2021-12-07_final
2021-12-09 08:31:03	ga_ls7e_ard_3-2-1_094075_2021-12-08_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-14 08:48:43	ga_ls7e_ard_3-2-1_097074_2021-12-13_final
2021-12-16 10:16:38	ga_ls7e_ard_3-2-1_111078_2021-12-16_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-20 09:53:08	ga_ls7e_ard_3-2-1_107082_2021-12-20_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-26 09:13:04	ga_ls7e_ard_3-2-1_101076_2021-12-25_final
2021-12-30 08:48:20	ga_ls7e_ard_3-2-1_097077_2021-12-29_final
2021-12-30 08:50:44	ga_ls7e_ard_3-2-1_097083_2021-12-29_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-01 10:14:15	ga_ls7e_ard_3-2-1_111076_2022-01-01_final
2022-01-01 10:15:27	ga_ls7e_ard_3-2-1_111079_2022-01-01_final
2022-01-03 08:24:00	ga_ls7e_ard_3-2-1_093079_2022-01-02_final
2022-01-03 10:02:29	ga_ls7e_ard_3-2-1_109078_2022-01-03_final
2022-01-03 10:02:53	ga_ls7e_ard_3-2-1_109079_2022-01-03_final
2022-01-04 09:05:10	ga_ls7e_ard_3-2-1_100074_2022-01-03_final
2022-01-05 08:11:02	ga_ls7e_ard_3-2-1_091078_2022-01-04_final
2022-01-05 08:12:38	ga_ls7e_ard_3-2-1_091082_2022-01-04_final
2022-01-05 09:47:55	ga_ls7e_ard_3-2-1_107073_2022-01-05_final
2022-01-07 09:37:22	ga_ls7e_ard_3-2-1_105078_2022-01-07_final
2022-01-08 08:41:16	ga_ls7e_ard_3-2-1_096077_2022-01-07_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-12 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-12 09:55:27	ga_ls7e_ard_3-2-1_108078_2022-01-12_final
2022-01-13 10:38:13	ga_ls7e_ard_3-2-1_115077_2022-01-13_final
2022-01-14 09:43:18	ga_ls7e_ard_3-2-1_106079_2022-01-14_final
2022-01-17 10:13:31	ga_ls7e_ard_3-2-1_111078_2022-01-17_final
2022-01-17 10:15:07	ga_ls7e_ard_3-2-1_111082_2022-01-17_final
2022-01-21 09:48:01	ga_ls7e_ard_3-2-1_107077_2022-01-21_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-26 08:26:47	ga_ls7e_ard_3-2-1_094076_2022-01-25_final
2022-01-26 10:05:16	ga_ls7e_ard_3-2-1_110075_2022-01-26_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-27 09:11:33	ga_ls7e_ard_3-2-1_101080_2022-01-26_final
2022-02-02 10:11:33	ga_ls7e_ard_3-2-1_111077_2022-02-02_final
2022-02-03 09:17:02	ga_ls7e_ard_3-2-1_102080_2022-02-02_final
2022-02-04 08:21:43	ga_ls7e_ard_3-2-1_093081_2022-02-03_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-10 09:22:05	ga_ls7e_ard_3-2-1_103079_2022-02-09_final
2022-02-11 08:26:22	ga_ls7e_ard_3-2-1_094079_2022-02-10_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-16 08:43:11	ga_ls7e_ard_3-2-1_097076_2022-02-15_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 10:09:55	ga_ls7e_ard_3-2-1_111077_2022-02-18_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-26 09:19:19	ga_ls7e_ard_3-2-1_103076_2022-02-25_final
2022-02-26 09:20:31	ga_ls7e_ard_3-2-1_103079_2022-02-25_final
2022-02-27 08:24:00	ga_ls7e_ard_3-2-1_094077_2022-02-26_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-03-01 08:13:03	ga_ls7e_ard_3-2-1_092081_2022-02-28_final
2022-03-01 08:13:27	ga_ls7e_ard_3-2-1_092082_2022-02-28_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-05 09:24:49	ga_ls7e_ard_3-2-1_104076_2022-03-04_final
2022-03-06 10:09:59	ga_ls7e_ard_3-2-1_111081_2022-03-06_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-08 08:17:45	ga_ls7e_ard_3-2-1_093079_2022-03-07_final
2022-03-10 09:43:16	ga_ls7e_ard_3-2-1_107077_2022-03-10_final
2022-03-10 09:43:40	ga_ls7e_ard_3-2-1_107078_2022-03-10_final
2022-03-11 08:47:09	ga_ls7e_ard_3-2-1_098076_2022-03-10_final
2022-03-11 08:48:44	ga_ls7e_ard_3-2-1_098080_2022-03-10_final
2022-03-12 09:28:42	ga_ls7e_ard_3-2-1_105072_2022-03-11_final
2022-03-13 08:35:47	ga_ls7e_ard_3-2-1_096079_2022-03-12_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-15 08:23:37	ga_ls7e_ard_3-2-1_094080_2022-03-14_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-19 07:58:30	ga_ls7e_ard_3-2-1_090080_2022-03-18_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-21 09:25:13	ga_ls7e_ard_3-2-1_104081_2022-03-20_final
2022-03-22 08:29:07	ga_ls7e_ard_3-2-1_095080_2022-03-21_final
2022-03-23 09:09:53	ga_ls7e_ard_3-2-1_102074_2022-03-22_final
2022-03-24 09:55:03	ga_ls7e_ard_3-2-1_109079_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-27 08:44:24	ga_ls7e_ard_3-2-1_098073_2022-03-26_final
2022-03-29 08:31:27	ga_ls7e_ard_3-2-1_096072_2022-03-28_final
2022-03-29 08:35:02	ga_ls7e_ard_3-2-1_096081_2022-03-28_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-29 10:11:55	ga_ls7e_ard_3-2-1_112076_2022-03-29_final
2022-03-30 09:15:00	ga_ls7e_ard_3-2-1_103073_2022-03-29_final
2022-03-30 09:15:24	ga_ls7e_ard_3-2-1_103074_2022-03-29_final
2022-03-31 08:21:41	ga_ls7e_ard_3-2-1_094079_2022-03-30_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-04-01 09:02:03	ga_ls7e_ard_3-2-1_101072_2022-03-31_final
2022-04-02 09:46:49	ga_ls7e_ard_3-2-1_108076_2022-04-02_final
2022-04-03 08:50:41	ga_ls7e_ard_3-2-1_099075_2022-04-02_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