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:

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First 100 results (query limit)

Time (local)	Label
2021-09-18 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 08:51:47	ga_ls7e_ard_3-2-0_096077_2021-09-17_final
2021-09-18 10:31:52	ga_ls7e_ard_3-2-0_112080_2021-09-18_final
2021-09-20 08:40:03	ga_ls7e_ard_3-2-0_094079_2021-09-19_final
2021-09-20 08:43:14	ga_ls7e_ard_3-2-0_094087_2021-09-19_final
2021-09-20 10:20:31	ga_ls7e_ard_3-2-0_110083_2021-09-20_final
2021-11-14 08:40:49	ga_ls7e_ard_3-2-1_095078_2021-11-13_final
2021-11-14 10:19:17	ga_ls7e_ard_3-2-1_111077_2021-11-14_final
2021-11-14 10:20:05	ga_ls7e_ard_3-2-1_111079_2021-11-14_final
2021-11-19 10:38:08	ga_ls7e_ard_3-2-1_114079_2021-11-19_final
2021-11-22 09:28:16	ga_ls7e_ard_3-2-1_103075_2021-11-21_final
2021-11-23 10:13:25	ga_ls7e_ard_3-2-1_110080_2021-11-23_final
2021-11-26 09:01:10	ga_ls7e_ard_3-2-1_099070_2021-11-25_final
2021-11-26 09:02:22	ga_ls7e_ard_3-2-1_099073_2021-11-25_final
2021-11-30 10:19:21	ga_ls7e_ard_3-2-1_111081_2021-11-30_final
2021-12-07 08:45:36	ga_ls7e_ard_3-2-1_096080_2021-12-06_final
2021-12-08 09:25:10	ga_ls7e_ard_3-2-1_103071_2021-12-07_final
2021-12-11 08:20:06	ga_ls7e_ard_3-2-1_092079_2021-12-10_final
2021-12-12 09:04:28	ga_ls7e_ard_3-2-1_099082_2021-12-11_final
2021-12-13 09:47:37	ga_ls7e_ard_3-2-1_106082_2021-12-13_final
2021-12-14 08:51:54	ga_ls7e_ard_3-2-1_097082_2021-12-13_final
2021-12-21 08:54:37	ga_ls7e_ard_3-2-1_098075_2021-12-20_final
2021-12-22 08:02:06	ga_ls7e_ard_3-2-1_089083_2021-12-21_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-25 10:09:58	ga_ls7e_ard_3-2-1_110079_2021-12-25_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-28 09:00:06	ga_ls7e_ard_3-2-1_099075_2021-12-27_final
2021-12-29 09:43:15	ga_ls7e_ard_3-2-1_106075_2021-12-29_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2021-12-30 10:27:13	ga_ls7e_ard_3-2-1_113077_2021-12-30_final
2022-01-01 08:36:10	ga_ls7e_ard_3-2-1_095078_2021-12-31_final
2022-01-02 09:17:20	ga_ls7e_ard_3-2-1_102073_2022-01-01_final
2022-01-02 09:20:07	ga_ls7e_ard_3-2-1_102080_2022-01-01_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-06 08:52:13	ga_ls7e_ard_3-2-1_098073_2022-01-05_final
2022-01-07 09:35:47	ga_ls7e_ard_3-2-1_105074_2022-01-07_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-09 09:22:02	ga_ls7e_ard_3-2-1_103071_2022-01-08_final
2022-01-12 08:18:34	ga_ls7e_ard_3-2-1_092083_2022-01-11_final
2022-01-13 08:58:32	ga_ls7e_ard_3-2-1_099075_2022-01-12_final
2022-01-14 09:38:55	ga_ls7e_ard_3-2-1_106068_2022-01-14_final
2022-01-15 08:44:48	ga_ls7e_ard_3-2-1_097072_2022-01-14_final
2022-01-19 10:02:34	ga_ls7e_ard_3-2-1_109082_2022-01-19_final
2022-01-21 09:46:01	ga_ls7e_ard_3-2-1_107072_2022-01-21_final
2022-01-21 09:48:25	ga_ls7e_ard_3-2-1_107078_2022-01-21_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-27 09:11:09	ga_ls7e_ard_3-2-1_101079_2022-01-26_final
2022-01-29 10:37:28	ga_ls7e_ard_3-2-1_115079_2022-01-29_final
2022-01-30 08:03:40	ga_ls7e_ard_3-2-1_090081_2022-01-29_final
2022-01-31 08:44:26	ga_ls7e_ard_3-2-1_097075_2022-01-30_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-04 08:21:43	ga_ls7e_ard_3-2-1_093081_2022-02-03_final
2022-02-04 08:22:54	ga_ls7e_ard_3-2-1_093084_2022-02-03_final
2022-02-09 08:37:44	ga_ls7e_ard_3-2-1_096076_2022-02-08_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-10 09:22:29	ga_ls7e_ard_3-2-1_103080_2022-02-09_final
2022-02-15 08:03:13	ga_ls7e_ard_3-2-1_090084_2022-02-14_final
2022-02-16 10:23:16	ga_ls7e_ard_3-2-1_113079_2022-02-16_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-18 08:30:14	ga_ls7e_ard_3-2-1_095075_2022-02-17_final
2022-02-18 08:30:38	ga_ls7e_ard_3-2-1_095076_2022-02-17_final
2022-02-20 08:20:29	ga_ls7e_ard_3-2-1_093082_2022-02-19_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-22 09:47:13	ga_ls7e_ard_3-2-1_107083_2022-02-22_final
2022-02-22 09:47:37	ga_ls7e_ard_3-2-1_107084_2022-02-22_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-23 08:51:06	ga_ls7e_ard_3-2-1_098082_2022-02-22_final
2022-02-23 08:51:30	ga_ls7e_ard_3-2-1_098083_2022-02-22_final
2022-02-27 08:23:36	ga_ls7e_ard_3-2-1_094076_2022-02-26_final
2022-02-27 08:24:48	ga_ls7e_ard_3-2-1_094079_2022-02-26_final
2022-02-27 08:26:24	ga_ls7e_ard_3-2-1_094083_2022-02-26_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-03-02 08:54:37	ga_ls7e_ard_3-2-1_099077_2022-03-01_final
2022-03-04 10:22:08	ga_ls7e_ard_3-2-1_113080_2022-03-04_final
2022-03-06 08:31:06	ga_ls7e_ard_3-2-1_095081_2022-03-05_final
2022-03-09 08:59:18	ga_ls7e_ard_3-2-1_100075_2022-03-08_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-10 09:42:04	ga_ls7e_ard_3-2-1_107074_2022-03-10_final
2022-03-12 09:31:06	ga_ls7e_ard_3-2-1_105078_2022-03-12_final
2022-03-15 08:21:37	ga_ls7e_ard_3-2-1_094075_2022-03-14_final
2022-03-15 08:23:13	ga_ls7e_ard_3-2-1_094079_2022-03-14_final
2022-03-15 09:58:30	ga_ls7e_ard_3-2-1_110070_2022-03-15_final
2022-03-18 10:31:29	ga_ls7e_ard_3-2-1_115076_2022-03-18_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-20 08:39:40	ga_ls7e_ard_3-2-1_097075_2022-03-19_final
2022-03-20 08:40:04	ga_ls7e_ard_3-2-1_097076_2022-03-19_final
2022-03-20 08:43:15	ga_ls7e_ard_3-2-1_097084_2022-03-19_final
2022-03-20 10:20:08	ga_ls7e_ard_3-2-1_113079_2022-03-20_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-21 09:24:50	ga_ls7e_ard_3-2-1_104080_2022-03-20_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-24 08:15:46	ga_ls7e_ard_3-2-1_093078_2022-03-23_final
2022-03-24 08:17:22	ga_ls7e_ard_3-2-1_093082_2022-03-23_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-29 08:31:27	ga_ls7e_ard_3-2-1_096072_2022-03-28_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_final
2022-04-01 09:02:03	ga_ls7e_ard_3-2-1_101072_2022-03-31_final
2022-04-05 08:38:08	ga_ls7e_ard_3-2-1_097075_2022-04-04_final
2022-04-06 09:19:18	ga_ls7e_ard_3-2-1_104070_2022-04-05_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