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
2021-09-13 10:09:47	ga_ls7e_ard_3-2-0_109070_2021-09-13_final
2021-10-03 09:45:40	ga_ls7e_ard_3-2-0_105076_2021-10-03_final
2021-10-06 10:16:42	ga_ls7e_ard_3-2-0_110077_2021-10-06_final
2021-10-08 08:27:17	ga_ls7e_ard_3-2-0_092082_2021-10-07_final
2021-10-08 08:28:05	ga_ls7e_ard_3-2-0_092084_2021-10-07_final
2021-10-09 09:06:28	ga_ls7e_ard_3-2-0_099072_2021-10-08_final
2021-10-09 09:09:40	ga_ls7e_ard_3-2-0_099080_2021-10-08_final
2021-10-12 09:41:06	ga_ls7e_ard_3-2-0_104082_2021-10-12_final
2021-10-17 08:17:55	ga_ls7e_ard_3-2-0_091076_2021-10-16_final
2021-10-18 10:39:58	ga_ls7e_ard_3-2-0_114076_2021-10-18_final
2021-10-24 08:23:28	ga_ls7e_ard_3-2-0_092076_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 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-26 08:12:07	ga_ls7e_ard_3-2-0_090079_2021-10-25_final
2021-10-28 09:34:27	ga_ls7e_ard_3-2-0_104069_2021-10-28_final
2021-11-02 09:53:20	ga_ls7e_ard_3-2-0_107071_2021-11-02_final
2021-11-03 09:00:49	ga_ls7e_ard_3-2-0_098079_2021-11-02_final
2021-11-04 09:41:59	ga_ls7e_ard_3-2-0_105074_2021-11-04_final
2021-11-09 08:26:21	ga_ls7e_ard_3-2-0_092087_2021-11-08_final
2021-11-09 09:58:50	ga_ls7e_ard_3-2-0_108071_2021-11-09_final
2021-11-11 08:12:36	ga_ls7e_ard_3-2-0_090084_2021-11-10_final
2021-11-11 08:13:24	ga_ls7e_ard_3-2-0_090086_2021-11-10_final
2021-11-12 08:50:10	ga_ls7e_ard_3-2-0_097070_2021-11-11_final
2021-11-12 08:50:58	ga_ls7e_ard_3-2-0_097072_2021-11-11_final
2021-11-12 10:34:14	ga_ls7e_ard_3-2-1_113083_2021-11-12_final
2021-11-15 09:21:35	ga_ls7e_ard_3-2-1_102072_2021-11-14_final
2021-11-21 10:23:59	ga_ls7e_ard_3-2-1_112075_2021-11-21_final
2021-11-23 10:11:01	ga_ls7e_ard_3-2-1_110074_2021-11-23_final
2021-12-01 09:19:15	ga_ls7e_ard_3-2-1_102070_2021-11-30_final
2021-12-02 08:25:08	ga_ls7e_ard_3-2-1_093074_2021-12-01_final
2021-12-02 08:25:56	ga_ls7e_ard_3-2-1_093076_2021-12-01_final
2021-12-02 10:03:37	ga_ls7e_ard_3-2-1_109073_2021-12-02_final
2021-12-04 08:16:59	ga_ls7e_ard_3-2-1_091085_2021-12-03_final
2021-12-05 10:37:25	ga_ls7e_ard_3-2-1_114081_2021-12-05_final
2021-12-08 09:24:46	ga_ls7e_ard_3-2-1_103070_2021-12-07_final
2021-12-10 09:12:37	ga_ls7e_ard_3-2-1_101071_2021-12-09_final
2021-12-12 10:41:44	ga_ls7e_ard_3-2-1_115078_2021-12-12_final
2021-12-13 09:42:26	ga_ls7e_ard_3-2-1_106069_2021-12-13_final
2021-12-14 08:47:07	ga_ls7e_ard_3-2-1_097070_2021-12-13_final
2021-12-14 10:28:00	ga_ls7e_ard_3-2-1_113075_2021-12-14_final
2021-12-20 08:11:51	ga_ls7e_ard_3-2-1_091076_2021-12-19_final
2021-12-20 08:12:15	ga_ls7e_ard_3-2-1_091077_2021-12-19_final
2021-12-21 10:35:29	ga_ls7e_ard_3-2-1_114080_2021-12-21_final
2021-12-22 08:00:54	ga_ls7e_ard_3-2-1_089080_2021-12-21_final
2021-12-23 08:40:04	ga_ls7e_ard_3-2-1_096070_2021-12-22_final
2021-12-27 09:57:49	ga_ls7e_ard_3-2-1_108080_2021-12-27_final
2021-12-28 09:03:17	ga_ls7e_ard_3-2-1_099083_2021-12-27_final
2022-01-01 10:12:15	ga_ls7e_ard_3-2-1_111071_2022-01-01_final
2022-01-02 09:18:56	ga_ls7e_ard_3-2-1_102077_2022-01-01_final
2022-01-03 10:04:29	ga_ls7e_ard_3-2-1_109083_2022-01-03_final
2022-01-05 09:48:19	ga_ls7e_ard_3-2-1_107074_2022-01-05_final
2022-01-06 10:31:29	ga_ls7e_ard_3-2-1_114074_2022-01-06_final
2022-01-10 10:09:59	ga_ls7e_ard_3-2-1_110083_2022-01-10_final
2022-01-11 09:10:17	ga_ls7e_ard_3-2-1_101073_2022-01-10_final
2022-01-13 08:57:45	ga_ls7e_ard_3-2-1_099073_2022-01-12_final
2022-01-13 09:02:08	ga_ls7e_ard_3-2-1_099084_2022-01-12_final
2022-01-17 10:11:07	ga_ls7e_ard_3-2-1_111072_2022-01-17_final
2022-01-19 08:20:30	ga_ls7e_ard_3-2-1_093074_2022-01-18_final
2022-01-22 08:51:54	ga_ls7e_ard_3-2-1_098076_2022-01-21_final
2022-01-30 08:07:16	ga_ls7e_ard_3-2-1_090090_2022-01-29_final
2022-01-31 10:22:55	ga_ls7e_ard_3-2-1_113074_2022-01-31_final
2022-02-03 09:17:26	ga_ls7e_ard_3-2-1_102081_2022-02-02_final
2022-02-07 08:47:07	ga_ls7e_ard_3-2-1_098068_2022-02-06_final
2022-02-08 07:56:35	ga_ls7e_ard_3-2-1_089081_2022-02-07_final
2022-02-08 09:32:16	ga_ls7e_ard_3-2-1_105073_2022-02-08_final
2022-02-12 09:11:07	ga_ls7e_ard_3-2-1_101083_2022-02-11_final
2022-02-15 09:36:07	ga_ls7e_ard_3-2-1_106069_2022-02-15_final
2022-02-16 10:23:16	ga_ls7e_ard_3-2-1_113079_2022-02-16_final
2022-02-16 10:24:27	ga_ls7e_ard_3-2-1_113082_2022-02-16_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-23 10:27:59	ga_ls7e_ard_3-2-1_114077_2022-02-23_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-24 09:31:52	ga_ls7e_ard_3-2-1_105076_2022-02-24_final
2022-02-27 08:22:25	ga_ls7e_ard_3-2-1_094073_2022-02-26_final
2022-03-01 08:10:39	ga_ls7e_ard_3-2-1_092075_2022-02-28_final
2022-03-02 08:53:01	ga_ls7e_ard_3-2-1_099073_2022-03-01_final
2022-03-04 08:38:52	ga_ls7e_ard_3-2-1_097069_2022-03-03_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-07 09:14:40	ga_ls7e_ard_3-2-1_102082_2022-03-06_final
2022-03-10 08:05:11	ga_ls7e_ard_3-2-1_091079_2022-03-09_final
2022-03-11 08:47:09	ga_ls7e_ard_3-2-1_098076_2022-03-10_final
2022-03-11 10:26:49	ga_ls7e_ard_3-2-1_114078_2022-03-11_final
2022-03-12 07:52:37	ga_ls7e_ard_3-2-1_089079_2022-03-11_final
2022-03-13 10:16:39	ga_ls7e_ard_3-2-1_112084_2022-03-13_final
2022-03-17 08:12:39	ga_ls7e_ard_3-2-1_092084_2022-03-16_final
2022-03-17 09:45:56	ga_ls7e_ard_3-2-1_108070_2022-03-17_final
2022-03-18 08:55:48	ga_ls7e_ard_3-2-1_099084_2022-03-17_final
2022-03-20 10:21:44	ga_ls7e_ard_3-2-1_113083_2022-03-20_final
2022-03-22 08:26:19	ga_ls7e_ard_3-2-1_095073_2022-03-21_final
2022-03-22 10:04:48	ga_ls7e_ard_3-2-1_111072_2022-03-22_final
2022-03-27 08:46:47	ga_ls7e_ard_3-2-1_098079_2022-03-26_final
2022-03-27 10:25:16	ga_ls7e_ard_3-2-1_114078_2022-03-27_final
2022-03-27 10:25:40	ga_ls7e_ard_3-2-1_114079_2022-03-27_final
2022-04-01 09:01:39	ga_ls7e_ard_3-2-1_101071_2022-03-31_final
2022-04-02 08:07:56	ga_ls7e_ard_3-2-1_092076_2022-04-01_final
2022-04-02 09:44:25	ga_ls7e_ard_3-2-1_108070_2022-04-02_final
2022-04-03 08:52:41	ga_ls7e_ard_3-2-1_099080_2022-04-02_final
2022-04-03 08:53:29	ga_ls7e_ard_3-2-1_099082_2022-04-02_final
2022-04-04 09:31:51	ga_ls7e_ard_3-2-1_106070_2022-04-04_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