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
2021-11-02 09:55:43	ga_ls7e_ard_3-2-0_107077_2021-11-02_final
2021-11-05 10:27:56	ga_ls7e_ard_3-2-0_112081_2021-11-05_final
2021-11-06 09:29:02	ga_ls7e_ard_3-2-0_103073_2021-11-05_final
2021-11-07 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-09 08:23:33	ga_ls7e_ard_3-2-0_092080_2021-11-08_final
2021-11-10 10:44:00	ga_ls7e_ard_3-2-0_115076_2021-11-10_final
2021-11-11 09:45:53	ga_ls7e_ard_3-2-0_106070_2021-11-11_final
2021-11-11 09:48:17	ga_ls7e_ard_3-2-0_106076_2021-11-11_final
2021-11-12 08:50:58	ga_ls7e_ard_3-2-0_097072_2021-11-11_final
2021-11-12 10:32:15	ga_ls7e_ard_3-2-1_113078_2021-11-12_final
2021-11-15 09:22:23	ga_ls7e_ard_3-2-1_102074_2021-11-14_final
2021-11-17 09:10:13	ga_ls7e_ard_3-2-1_100075_2021-11-16_final
2021-11-19 08:57:40	ga_ls7e_ard_3-2-1_098075_2021-11-18_final
2021-11-28 08:51:01	ga_ls7e_ard_3-2-1_097076_2021-11-27_final
2021-11-29 09:33:23	ga_ls7e_ard_3-2-1_104074_2021-11-29_final
2021-12-02 08:30:19	ga_ls7e_ard_3-2-1_093087_2021-12-01_final
2021-12-04 08:15:23	ga_ls7e_ard_3-2-1_091081_2021-12-03_final
2021-12-04 09:51:28	ga_ls7e_ard_3-2-1_107074_2021-12-04_final
2021-12-05 08:56:33	ga_ls7e_ard_3-2-1_098076_2021-12-04_final
2021-12-05 10:36:37	ga_ls7e_ard_3-2-1_114079_2021-12-05_final
2021-12-09 08:33:27	ga_ls7e_ard_3-2-1_094081_2021-12-08_final
2021-12-09 10:11:55	ga_ls7e_ard_3-2-1_110080_2021-12-09_final
2021-12-11 09:57:47	ga_ls7e_ard_3-2-1_108076_2021-12-11_final
2021-12-14 10:28:47	ga_ls7e_ard_3-2-1_113077_2021-12-14_final
2021-12-16 08:35:46	ga_ls7e_ard_3-2-1_095073_2021-12-15_final
2021-12-16 10:19:02	ga_ls7e_ard_3-2-1_111084_2021-12-16_final
2021-12-25 08:33:30	ga_ls7e_ard_3-2-1_094085_2021-12-24_final
2021-12-25 10:06:47	ga_ls7e_ard_3-2-1_110071_2021-12-25_final
2021-12-26 09:15:51	ga_ls7e_ard_3-2-1_101083_2021-12-25_final
2021-12-28 09:03:17	ga_ls7e_ard_3-2-1_099083_2021-12-27_final
2021-12-29 08:07:10	ga_ls7e_ard_3-2-1_090082_2021-12-28_final
2021-12-30 10:29:36	ga_ls7e_ard_3-2-1_113083_2021-12-30_final
2022-01-04 09:06:46	ga_ls7e_ard_3-2-1_100078_2022-01-03_final
2022-01-08 10:22:32	ga_ls7e_ard_3-2-1_112083_2022-01-08_final
2022-01-11 09:11:53	ga_ls7e_ard_3-2-1_101077_2022-01-10_final
2022-01-12 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-13 08:58:08	ga_ls7e_ard_3-2-1_099074_2022-01-12_final
2022-01-13 10:37:49	ga_ls7e_ard_3-2-1_115076_2022-01-13_final
2022-01-14 08:08:01	ga_ls7e_ard_3-2-1_090088_2022-01-13_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-19 10:03:22	ga_ls7e_ard_3-2-1_109084_2022-01-19_final
2022-01-21 09:46:49	ga_ls7e_ard_3-2-1_107074_2022-01-21_final
2022-01-22 08:50:42	ga_ls7e_ard_3-2-1_098073_2022-01-21_final
2022-01-25 09:22:54	ga_ls7e_ard_3-2-1_103077_2022-01-24_final
2022-01-29 08:58:11	ga_ls7e_ard_3-2-1_099078_2022-01-28_final
2022-01-29 09:00:11	ga_ls7e_ard_3-2-1_099083_2022-01-28_final
2022-01-30 08:02:52	ga_ls7e_ard_3-2-1_090079_2022-01-29_final
2022-01-30 08:04:04	ga_ls7e_ard_3-2-1_090082_2022-01-29_final
2022-02-02 10:13:57	ga_ls7e_ard_3-2-1_111083_2022-02-02_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-07 08:49:54	ga_ls7e_ard_3-2-1_098075_2022-02-06_final
2022-02-08 09:33:04	ga_ls7e_ard_3-2-1_105075_2022-02-08_final
2022-02-08 09:33:28	ga_ls7e_ard_3-2-1_105076_2022-02-08_final
2022-02-09 10:15:49	ga_ls7e_ard_3-2-1_112074_2022-02-09_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-11 08:29:34	ga_ls7e_ard_3-2-1_094087_2022-02-10_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-13 09:50:17	ga_ls7e_ard_3-2-1_108073_2022-02-13_final
2022-02-14 08:54:09	ga_ls7e_ard_3-2-1_099072_2022-02-13_final
2022-02-16 10:22:28	ga_ls7e_ard_3-2-1_113077_2022-02-16_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-21 08:59:40	ga_ls7e_ard_3-2-1_100072_2022-02-20_final
2022-02-22 08:09:32	ga_ls7e_ard_3-2-1_091086_2022-02-21_final
2022-02-22 08:09:56	ga_ls7e_ard_3-2-1_091087_2022-02-21_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-23 10:27:35	ga_ls7e_ard_3-2-1_114076_2022-02-23_final
2022-02-23 10:29:35	ga_ls7e_ard_3-2-1_114081_2022-02-23_final
2022-02-24 09:33:52	ga_ls7e_ard_3-2-1_105081_2022-02-24_final
2022-02-27 10:01:17	ga_ls7e_ard_3-2-1_110073_2022-02-27_final
2022-03-01 09:52:43	ga_ls7e_ard_3-2-1_108083_2022-03-01_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-04 10:21:20	ga_ls7e_ard_3-2-1_113078_2022-03-04_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-06 08:28:18	ga_ls7e_ard_3-2-1_095074_2022-03-05_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-09 08:58:54	ga_ls7e_ard_3-2-1_100074_2022-03-08_final
2022-03-09 08:59:18	ga_ls7e_ard_3-2-1_100075_2022-03-08_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-11 10:27:37	ga_ls7e_ard_3-2-1_114080_2022-03-11_final
2022-03-12 07:53:01	ga_ls7e_ard_3-2-1_089080_2022-03-11_final
2022-03-13 08:33:47	ga_ls7e_ard_3-2-1_096074_2022-03-12_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-15 10:03:41	ga_ls7e_ard_3-2-1_110083_2022-03-15_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-18 08:49:25	ga_ls7e_ard_3-2-1_099068_2022-03-17_final
2022-03-18 08:53:48	ga_ls7e_ard_3-2-1_099079_2022-03-17_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-23 09:08:17	ga_ls7e_ard_3-2-1_102070_2022-03-22_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_final
2022-03-26 08:07:37	ga_ls7e_ard_3-2-1_091089_2022-03-25_final
2022-03-26 08:08:01	ga_ls7e_ard_3-2-1_091090_2022-03-25_final
2022-03-27 10:25:16	ga_ls7e_ard_3-2-1_114078_2022-03-27_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-04-01 09:01:15	ga_ls7e_ard_3-2-1_101070_2022-03-31_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years