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 08:54:35	ga_ls7e_ard_3-2-0_096084_2021-09-17_final
2021-09-18 08:55:23	ga_ls7e_ard_3-2-0_096086_2021-09-17_final
2021-09-20 10:15:20	ga_ls7e_ard_3-2-0_110070_2021-09-20_final
2021-11-02 08:20:50	ga_ls7e_ard_3-2-0_091087_2021-11-01_final
2021-11-02 08:21:14	ga_ls7e_ard_3-2-0_091088_2021-11-01_final
2021-11-03 10:39:41	ga_ls7e_ard_3-2-0_114079_2021-11-03_final
2021-11-07 10:12:59	ga_ls7e_ard_3-2-0_110075_2021-11-07_final
2021-11-08 09:16:05	ga_ls7e_ard_3-2-0_101072_2021-11-07_final
2021-11-09 08:25:57	ga_ls7e_ard_3-2-0_092086_2021-11-08_final
2021-11-14 08:38:49	ga_ls7e_ard_3-2-1_095073_2021-11-13_final
2021-11-15 09:22:23	ga_ls7e_ard_3-2-1_102074_2021-11-14_final
2021-11-16 10:06:44	ga_ls7e_ard_3-2-1_109077_2021-11-16_final
2021-11-19 08:56:28	ga_ls7e_ard_3-2-1_098072_2021-11-18_final
2021-11-22 09:25:52	ga_ls7e_ard_3-2-1_103069_2021-11-21_final
2021-11-22 09:27:28	ga_ls7e_ard_3-2-1_103073_2021-11-21_final
2021-11-27 09:47:56	ga_ls7e_ard_3-2-1_106079_2021-11-27_final
2021-11-27 09:48:20	ga_ls7e_ard_3-2-1_106080_2021-11-27_final
2021-11-28 08:49:26	ga_ls7e_ard_3-2-1_097072_2021-11-27_final
2021-11-28 08:50:13	ga_ls7e_ard_3-2-1_097074_2021-11-27_final
2021-11-28 08:53:25	ga_ls7e_ard_3-2-1_097082_2021-11-27_final
2021-12-02 10:04:01	ga_ls7e_ard_3-2-1_109074_2021-12-02_final
2021-12-08 09:27:10	ga_ls7e_ard_3-2-1_103076_2021-12-07_final
2021-12-09 10:09:08	ga_ls7e_ard_3-2-1_110073_2021-12-09_final
2021-12-10 09:17:01	ga_ls7e_ard_3-2-1_101082_2021-12-09_final
2021-12-12 09:04:51	ga_ls7e_ard_3-2-1_099083_2021-12-11_final
2021-12-13 09:42:50	ga_ls7e_ard_3-2-1_106070_2021-12-13_final
2021-12-13 09:44:02	ga_ls7e_ard_3-2-1_106073_2021-12-13_final
2021-12-13 09:45:38	ga_ls7e_ard_3-2-1_106077_2021-12-13_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-16 08:36:10	ga_ls7e_ard_3-2-1_095074_2021-12-15_final
2021-12-20 09:49:56	ga_ls7e_ard_3-2-1_107074_2021-12-20_final
2021-12-20 09:51:56	ga_ls7e_ard_3-2-1_107079_2021-12-20_final
2021-12-23 10:24:08	ga_ls7e_ard_3-2-1_112083_2021-12-23_final
2021-12-27 09:56:13	ga_ls7e_ard_3-2-1_108076_2021-12-27_final
2021-12-27 09:58:37	ga_ls7e_ard_3-2-1_108082_2021-12-27_final
2021-12-28 09:00:30	ga_ls7e_ard_3-2-1_099076_2021-12-27_final
2021-12-29 08:07:58	ga_ls7e_ard_3-2-1_090084_2021-12-28_final
2021-12-30 08:45:33	ga_ls7e_ard_3-2-1_097070_2021-12-29_final
2021-12-30 08:49:32	ga_ls7e_ard_3-2-1_097080_2021-12-29_final
2021-12-30 08:51:08	ga_ls7e_ard_3-2-1_097084_2021-12-29_final
2022-01-01 10:16:15	ga_ls7e_ard_3-2-1_111081_2022-01-01_final
2022-01-03 08:27:12	ga_ls7e_ard_3-2-1_093087_2022-01-02_final
2022-01-07 09:34:59	ga_ls7e_ard_3-2-1_105072_2022-01-07_final
2022-01-07 09:35:23	ga_ls7e_ard_3-2-1_105073_2022-01-07_final
2022-01-08 08:39:16	ga_ls7e_ard_3-2-1_096072_2022-01-07_final
2022-01-08 10:22:32	ga_ls7e_ard_3-2-1_112083_2022-01-08_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-15 08:44:24	ga_ls7e_ard_3-2-1_097071_2022-01-14_final
2022-01-15 08:45:36	ga_ls7e_ard_3-2-1_097074_2022-01-14_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-17 08:33:03	ga_ls7e_ard_3-2-1_095074_2022-01-16_final
2022-01-18 09:17:48	ga_ls7e_ard_3-2-1_102078_2022-01-17_final
2022-01-19 08:21:41	ga_ls7e_ard_3-2-1_093077_2022-01-18_final
2022-01-21 09:50:48	ga_ls7e_ard_3-2-1_107084_2022-01-21_final
2022-01-26 10:04:04	ga_ls7e_ard_3-2-1_110072_2022-01-26_final
2022-01-26 10:07:40	ga_ls7e_ard_3-2-1_110081_2022-01-26_final
2022-01-27 09:12:21	ga_ls7e_ard_3-2-1_101082_2022-01-26_final
2022-01-29 08:59:23	ga_ls7e_ard_3-2-1_099081_2022-01-28_final
2022-01-30 08:03:16	ga_ls7e_ard_3-2-1_090080_2022-01-29_final
2022-01-31 08:47:38	ga_ls7e_ard_3-2-1_097083_2022-01-30_final
2022-01-31 08:48:02	ga_ls7e_ard_3-2-1_097084_2022-01-30_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-02-06 08:07:33	ga_ls7e_ard_3-2-1_091077_2022-02-05_final
2022-02-06 09:46:02	ga_ls7e_ard_3-2-1_107076_2022-02-06_final
2022-02-07 08:49:30	ga_ls7e_ard_3-2-1_098074_2022-02-06_final
2022-02-07 08:50:18	ga_ls7e_ard_3-2-1_098076_2022-02-06_final
2022-02-10 09:19:18	ga_ls7e_ard_3-2-1_103072_2022-02-09_final
2022-02-11 10:06:03	ga_ls7e_ard_3-2-1_110081_2022-02-11_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-15 08:05:13	ga_ls7e_ard_3-2-1_090089_2022-02-14_final
2022-02-15 09:37:19	ga_ls7e_ard_3-2-1_106072_2022-02-15_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-21 09:00:28	ga_ls7e_ard_3-2-1_100074_2022-02-20_final
2022-02-22 08:09:32	ga_ls7e_ard_3-2-1_091086_2022-02-21_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-25 08:38:57	ga_ls7e_ard_3-2-1_096083_2022-02-24_final
2022-02-25 10:17:50	ga_ls7e_ard_3-2-1_112083_2022-02-25_final
2022-02-26 09:17:43	ga_ls7e_ard_3-2-1_103072_2022-02-25_final
2022-02-28 09:05:34	ga_ls7e_ard_3-2-1_101073_2022-02-27_final
2022-03-02 08:53:49	ga_ls7e_ard_3-2-1_099075_2022-03-01_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-04 10:21:20	ga_ls7e_ard_3-2-1_113078_2022-03-04_final
2022-03-06 08:28:18	ga_ls7e_ard_3-2-1_095074_2022-03-05_final
2022-03-06 10:09:59	ga_ls7e_ard_3-2-1_111081_2022-03-06_final
2022-03-11 08:46:21	ga_ls7e_ard_3-2-1_098074_2022-03-10_final
2022-03-15 08:21:13	ga_ls7e_ard_3-2-1_094074_2022-03-14_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-19 07:57:18	ga_ls7e_ard_3-2-1_090077_2022-03-18_final
2022-03-20 08:38:04	ga_ls7e_ard_3-2-1_097071_2022-03-19_final
2022-03-20 08:40:52	ga_ls7e_ard_3-2-1_097078_2022-03-19_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
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-24 08:14:10	ga_ls7e_ard_3-2-1_093074_2022-03-23_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_final
2022-04-01 09:04:03	ga_ls7e_ard_3-2-1_101077_2022-03-31_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_2022-04-02_final
2022-04-05 08:37:20	ga_ls7e_ard_3-2-1_097073_2022-04-04_final
2022-04-05 10:19:24	ga_ls7e_ard_3-2-1_113081_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