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 08:50:12	ga_ls7e_ard_3-2-0_096073_2021-09-17_final
2021-09-18 10:30:16	ga_ls7e_ard_3-2-0_112076_2021-09-18_final
2021-10-23 09:19:10	ga_ls7e_ard_3-2-0_101076_2021-10-22_final
2021-10-24 10:02:44	ga_ls7e_ard_3-2-0_108077_2021-10-24_final
2021-10-27 08:54:05	ga_ls7e_ard_3-2-0_097076_2021-10-26_final
2021-10-27 08:57:17	ga_ls7e_ard_3-2-0_097084_2021-10-26_final
2021-10-27 10:33:46	ga_ls7e_ard_3-2-0_113078_2021-10-27_final
2021-10-30 09:24:18	ga_ls7e_ard_3-2-0_102075_2021-10-29_final
2021-11-02 08:22:02	ga_ls7e_ard_3-2-0_091090_2021-11-01_final
2021-11-02 09:54:08	ga_ls7e_ard_3-2-0_107073_2021-11-02_final
2021-11-02 09:56:07	ga_ls7e_ard_3-2-0_107078_2021-11-02_final
2021-11-03 08:57:37	ga_ls7e_ard_3-2-0_098071_2021-11-02_final
2021-11-03 10:37:42	ga_ls7e_ard_3-2-0_114074_2021-11-03_final
2021-11-03 10:40:05	ga_ls7e_ard_3-2-0_114080_2021-11-03_final
2021-11-05 08:48:16	ga_ls7e_ard_3-2-0_096079_2021-11-04_final
2021-11-05 08:51:03	ga_ls7e_ard_3-2-0_096086_2021-11-04_final
2021-11-07 08:35:43	ga_ls7e_ard_3-2-0_094079_2021-11-06_final
2021-11-07 10:14:35	ga_ls7e_ard_3-2-0_110079_2021-11-07_final
2021-11-10 09:07:07	ga_ls7e_ard_3-2-0_099081_2021-11-09_final
2021-11-11 08:14:12	ga_ls7e_ard_3-2-0_090088_2021-11-10_final
2021-11-14 08:40:25	ga_ls7e_ard_3-2-1_095077_2021-11-13_final
2021-11-14 08:44:00	ga_ls7e_ard_3-2-1_095086_2021-11-13_final
2021-11-14 10:21:17	ga_ls7e_ard_3-2-1_111082_2021-11-14_final
2021-11-23 10:13:49	ga_ls7e_ard_3-2-1_110081_2021-11-23_final
2021-11-26 10:43:38	ga_ls7e_ard_3-2-1_115079_2021-11-26_final
2021-11-30 08:40:04	ga_ls7e_ard_3-2-1_095080_2021-11-29_final
2021-11-30 10:18:57	ga_ls7e_ard_3-2-1_111080_2021-11-30_final
2021-12-02 10:03:13	ga_ls7e_ard_3-2-1_109072_2021-12-02_final
2021-12-02 10:06:24	ga_ls7e_ard_3-2-1_109080_2021-12-02_final
2021-12-05 08:55:45	ga_ls7e_ard_3-2-1_098074_2021-12-04_final
2021-12-05 08:58:57	ga_ls7e_ard_3-2-1_098082_2021-12-04_final
2021-12-07 10:26:04	ga_ls7e_ard_3-2-1_112084_2021-12-07_final
2021-12-10 09:16:37	ga_ls7e_ard_3-2-1_101081_2021-12-09_final
2021-12-11 08:22:54	ga_ls7e_ard_3-2-1_092086_2021-12-10_final
2021-12-11 10:00:34	ga_ls7e_ard_3-2-1_108083_2021-12-11_final
2021-12-14 10:29:35	ga_ls7e_ard_3-2-1_113079_2021-12-14_final
2021-12-16 08:37:46	ga_ls7e_ard_3-2-1_095078_2021-12-15_final
2021-12-17 09:17:20	ga_ls7e_ard_3-2-1_102069_2021-12-16_final
2021-12-17 09:17:44	ga_ls7e_ard_3-2-1_102070_2021-12-16_final
2021-12-18 10:01:41	ga_ls7e_ard_3-2-1_109072_2021-12-18_final
2021-12-19 09:09:34	ga_ls7e_ard_3-2-1_100081_2021-12-18_final
2021-12-21 10:34:41	ga_ls7e_ard_3-2-1_114078_2021-12-21_final
2021-12-23 08:44:51	ga_ls7e_ard_3-2-1_096082_2021-12-22_final
2021-12-25 08:30:18	ga_ls7e_ard_3-2-1_094077_2021-12-24_final
2021-12-26 09:15:27	ga_ls7e_ard_3-2-1_101082_2021-12-25_final
2021-12-26 09:15:51	ga_ls7e_ard_3-2-1_101083_2021-12-25_final
2021-12-27 08:18:32	ga_ls7e_ard_3-2-1_092079_2021-12-26_final
2021-12-29 09:40:52	ga_ls7e_ard_3-2-1_106069_2021-12-29_final
2021-12-31 09:28:42	ga_ls7e_ard_3-2-1_104070_2021-12-30_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-09 09:22:26	ga_ls7e_ard_3-2-1_103072_2022-01-08_final
2022-01-10 08:28:43	ga_ls7e_ard_3-2-1_094077_2022-01-09_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-15 08:46:47	ga_ls7e_ard_3-2-1_097077_2022-01-14_final
2022-01-15 08:47:11	ga_ls7e_ard_3-2-1_097078_2022-01-14_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-19 08:25:41	ga_ls7e_ard_3-2-1_093087_2022-01-18_final
2022-01-20 09:04:27	ga_ls7e_ard_3-2-1_100076_2022-01-19_final
2022-01-25 09:22:54	ga_ls7e_ard_3-2-1_103077_2022-01-24_final
2022-01-26 08:30:23	ga_ls7e_ard_3-2-1_094085_2022-01-25_final
2022-01-28 09:56:18	ga_ls7e_ard_3-2-1_108084_2022-01-28_final
2022-02-01 09:26:00	ga_ls7e_ard_3-2-1_104071_2022-01-31_final
2022-02-06 09:44:50	ga_ls7e_ard_3-2-1_107073_2022-02-06_final
2022-02-06 09:45:38	ga_ls7e_ard_3-2-1_107075_2022-02-06_final
2022-02-06 09:47:13	ga_ls7e_ard_3-2-1_107079_2022-02-06_final
2022-02-08 09:32:16	ga_ls7e_ard_3-2-1_105073_2022-02-08_final
2022-02-09 08:40:08	ga_ls7e_ard_3-2-1_096082_2022-02-08_final
2022-02-09 08:40:32	ga_ls7e_ard_3-2-1_096083_2022-02-08_final
2022-02-09 10:18:37	ga_ls7e_ard_3-2-1_112081_2022-02-09_final
2022-02-11 08:26:22	ga_ls7e_ard_3-2-1_094079_2022-02-10_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-14 08:56:33	ga_ls7e_ard_3-2-1_099078_2022-02-13_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-18 08:30:14	ga_ls7e_ard_3-2-1_095075_2022-02-17_final
2022-02-18 10:11:55	ga_ls7e_ard_3-2-1_111082_2022-02-18_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-24 09:33:04	ga_ls7e_ard_3-2-1_105079_2022-02-24_final
2022-02-25 10:17:26	ga_ls7e_ard_3-2-1_112082_2022-02-25_final
2022-02-27 10:01:17	ga_ls7e_ard_3-2-1_110073_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-02 08:55:49	ga_ls7e_ard_3-2-1_099080_2022-03-01_final
2022-03-04 08:44:27	ga_ls7e_ard_3-2-1_097083_2022-03-03_final
2022-03-06 08:28:18	ga_ls7e_ard_3-2-1_095074_2022-03-05_final
2022-03-10 08:08:23	ga_ls7e_ard_3-2-1_091087_2022-03-09_final
2022-03-10 09:41:16	ga_ls7e_ard_3-2-1_107072_2022-03-10_final
2022-03-11 08:46:45	ga_ls7e_ard_3-2-1_098075_2022-03-10_final
2022-03-12 07:52:37	ga_ls7e_ard_3-2-1_089079_2022-03-11_final
2022-03-14 09:16:09	ga_ls7e_ard_3-2-1_103072_2022-03-13_final
2022-03-15 08:22:01	ga_ls7e_ard_3-2-1_094076_2022-03-14_final
2022-03-21 09:22:50	ga_ls7e_ard_3-2-1_104075_2022-03-20_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-30 09:15:00	ga_ls7e_ard_3-2-1_103073_2022-03-29_final
2022-03-31 08:20:05	ga_ls7e_ard_3-2-1_094075_2022-03-30_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
2022-04-05 08:39:44	ga_ls7e_ard_3-2-1_097079_2022-04-04_final
2022-04-06 09:21:17	ga_ls7e_ard_3-2-1_104075_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years