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 08:55:23	ga_ls7e_ard_3-2-0_096086_2021-09-17_final
2021-09-24 09:50:15	ga_ls7e_ard_3-2-0_106070_2021-09-24_final
2021-09-26 09:41:42	ga_ls7e_ard_3-2-0_104080_2021-09-26_final
2021-10-09 09:09:40	ga_ls7e_ard_3-2-0_099080_2021-10-08_final
2021-10-09 10:46:33	ga_ls7e_ard_3-2-0_115075_2021-10-09_final
2021-10-10 08:17:09	ga_ls7e_ard_3-2-0_090088_2021-10-09_final
2021-10-11 08:58:43	ga_ls7e_ard_3-2-0_097084_2021-10-10_final
2021-10-24 08:23:04	ga_ls7e_ard_3-2-0_092075_2021-10-23_final
2021-10-24 08:27:03	ga_ls7e_ard_3-2-0_092085_2021-10-23_final
2021-10-24 08:27:27	ga_ls7e_ard_3-2-0_092086_2021-10-23_final
2021-10-25 09:05:02	ga_ls7e_ard_3-2-0_099072_2021-10-24_final
2021-10-25 09:06:38	ga_ls7e_ard_3-2-0_099076_2021-10-24_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-26 09:49:48	ga_ls7e_ard_3-2-0_106076_2021-10-26_final
2021-10-30 09:27:06	ga_ls7e_ard_3-2-0_102082_2021-10-29_final
2021-11-02 09:55:43	ga_ls7e_ard_3-2-0_107077_2021-11-02_final
2021-11-02 09:58:31	ga_ls7e_ard_3-2-0_107084_2021-11-02_final
2021-11-03 09:00:49	ga_ls7e_ard_3-2-0_098079_2021-11-02_final
2021-11-07 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-08 09:15:41	ga_ls7e_ard_3-2-0_101071_2021-11-07_final
2021-11-10 09:03:31	ga_ls7e_ard_3-2-0_099072_2021-11-09_final
2021-11-11 08:13:24	ga_ls7e_ard_3-2-0_090086_2021-11-10_final
2021-11-15 09:21:35	ga_ls7e_ard_3-2-1_102072_2021-11-14_final
2021-11-16 10:07:56	ga_ls7e_ard_3-2-1_109080_2021-11-16_final
2021-11-18 08:19:18	ga_ls7e_ard_3-2-1_091087_2021-11-17_final
2021-11-28 10:29:54	ga_ls7e_ard_3-2-1_113076_2021-11-28_final
2021-12-04 08:16:35	ga_ls7e_ard_3-2-1_091084_2021-12-03_final
2021-12-04 08:16:59	ga_ls7e_ard_3-2-1_091085_2021-12-03_final
2021-12-04 08:18:34	ga_ls7e_ard_3-2-1_091089_2021-12-03_final
2021-12-04 09:51:28	ga_ls7e_ard_3-2-1_107074_2021-12-04_final
2021-12-05 10:35:50	ga_ls7e_ard_3-2-1_114077_2021-12-05_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-11 08:18:54	ga_ls7e_ard_3-2-1_092076_2021-12-10_final
2021-12-11 09:55:23	ga_ls7e_ard_3-2-1_108070_2021-12-11_final
2021-12-14 10:30:47	ga_ls7e_ard_3-2-1_113082_2021-12-14_final
2021-12-17 09:17:20	ga_ls7e_ard_3-2-1_102069_2021-12-16_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-20 08:15:03	ga_ls7e_ard_3-2-1_091084_2021-12-19_final
2021-12-22 08:02:06	ga_ls7e_ard_3-2-1_089083_2021-12-21_final
2021-12-23 10:21:44	ga_ls7e_ard_3-2-1_112077_2021-12-23_final
2021-12-25 08:32:42	ga_ls7e_ard_3-2-1_094083_2021-12-24_final
2021-12-25 10:06:47	ga_ls7e_ard_3-2-1_110071_2021-12-25_final
2021-12-27 09:55:01	ga_ls7e_ard_3-2-1_108073_2021-12-27_final
2021-12-28 10:38:35	ga_ls7e_ard_3-2-1_115074_2021-12-28_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2021-12-30 10:29:12	ga_ls7e_ard_3-2-1_113082_2021-12-30_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-06 08:53:25	ga_ls7e_ard_3-2-1_098076_2022-01-05_final
2022-01-06 08:55:00	ga_ls7e_ard_3-2-1_098080_2022-01-05_final
2022-01-07 09:36:58	ga_ls7e_ard_3-2-1_105077_2022-01-07_final
2022-01-10 08:27:31	ga_ls7e_ard_3-2-1_094074_2022-01-09_final
2022-01-10 10:06:48	ga_ls7e_ard_3-2-1_110075_2022-01-10_final
2022-01-13 10:38:13	ga_ls7e_ard_3-2-1_115077_2022-01-13_final
2022-01-14 09:41:18	ga_ls7e_ard_3-2-1_106074_2022-01-14_final
2022-01-17 08:37:50	ga_ls7e_ard_3-2-1_095086_2022-01-16_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-21 08:11:32	ga_ls7e_ard_3-2-1_091083_2022-01-20_final
2022-01-22 10:30:23	ga_ls7e_ard_3-2-1_114075_2022-01-22_final
2022-01-22 10:31:11	ga_ls7e_ard_3-2-1_114077_2022-01-22_final
2022-01-23 07:58:11	ga_ls7e_ard_3-2-1_089081_2022-01-22_final
2022-01-24 08:37:45	ga_ls7e_ard_3-2-1_096072_2022-01-23_final
2022-01-29 08:57:24	ga_ls7e_ard_3-2-1_099076_2022-01-28_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-01-31 10:25:19	ga_ls7e_ard_3-2-1_113080_2022-01-31_final
2022-02-01 09:26:24	ga_ls7e_ard_3-2-1_104072_2022-01-31_final
2022-02-02 10:14:21	ga_ls7e_ard_3-2-1_111084_2022-02-02_final
2022-02-03 09:13:50	ga_ls7e_ard_3-2-1_102072_2022-02-02_final
2022-02-03 09:17:50	ga_ls7e_ard_3-2-1_102082_2022-02-02_final
2022-02-06 08:08:45	ga_ls7e_ard_3-2-1_091080_2022-02-05_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-06 09:49:13	ga_ls7e_ard_3-2-1_107084_2022-02-06_final
2022-02-07 08:48:43	ga_ls7e_ard_3-2-1_098072_2022-02-06_final
2022-02-08 09:32:16	ga_ls7e_ard_3-2-1_105073_2022-02-08_final
2022-02-09 10:16:13	ga_ls7e_ard_3-2-1_112075_2022-02-09_final
2022-02-19 09:10:37	ga_ls7e_ard_3-2-1_102068_2022-02-18_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-20 09:56:10	ga_ls7e_ard_3-2-1_109074_2022-02-20_final
2022-02-21 08:59:40	ga_ls7e_ard_3-2-1_100072_2022-02-20_final
2022-02-22 08:05:33	ga_ls7e_ard_3-2-1_091076_2022-02-21_final
2022-02-22 08:08:20	ga_ls7e_ard_3-2-1_091083_2022-02-21_final
2022-02-23 08:49:54	ga_ls7e_ard_3-2-1_098079_2022-02-22_final
2022-02-27 08:27:12	ga_ls7e_ard_3-2-1_094085_2022-02-26_final
2022-03-02 10:32:18	ga_ls7e_ard_3-2-1_115074_2022-03-02_final
2022-03-02 10:33:30	ga_ls7e_ard_3-2-1_115077_2022-03-02_final
2022-03-04 10:20:08	ga_ls7e_ard_3-2-1_113075_2022-03-04_final
2022-03-04 10:23:20	ga_ls7e_ard_3-2-1_113083_2022-03-04_final
2022-03-05 09:21:38	ga_ls7e_ard_3-2-1_104068_2022-03-04_final
2022-03-07 09:09:52	ga_ls7e_ard_3-2-1_102070_2022-03-06_final
2022-03-08 09:55:25	ga_ls7e_ard_3-2-1_109076_2022-03-08_final
2022-03-09 09:02:06	ga_ls7e_ard_3-2-1_100082_2022-03-08_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-10 08:04:23	ga_ls7e_ard_3-2-1_091077_2022-03-09_final
2022-03-11 10:25:37	ga_ls7e_ard_3-2-1_114075_2022-03-11_final
2022-03-12 07:55:25	ga_ls7e_ard_3-2-1_089086_2022-03-11_final
2022-03-18 10:31:29	ga_ls7e_ard_3-2-1_115076_2022-03-18_final
2022-03-24 08:18:10	ga_ls7e_ard_3-2-1_093084_2022-03-23_final
2022-03-26 09:44:06	ga_ls7e_ard_3-2-1_107083_2022-03-26_final
2022-04-02 08:07:56	ga_ls7e_ard_3-2-1_092076_2022-04-01_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