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
2021-09-20 08:40:51	ga_ls7e_ard_3-2-0_094081_2021-09-19_final
2021-09-20 10:19:19	ga_ls7e_ard_3-2-0_110080_2021-09-20_final
2021-11-20 09:42:01	ga_ls7e_ard_3-2-1_105078_2021-11-20_final
2021-11-21 08:48:18	ga_ls7e_ard_3-2-1_096083_2021-11-20_final
2021-12-01 09:22:26	ga_ls7e_ard_3-2-1_102078_2021-11-30_final
2021-12-10 09:14:13	ga_ls7e_ard_3-2-1_101075_2021-12-09_final
2021-12-12 09:00:52	ga_ls7e_ard_3-2-1_099073_2021-12-11_final
2021-12-13 08:11:56	ga_ls7e_ard_3-2-1_090090_2021-12-12_final
2021-12-14 08:50:43	ga_ls7e_ard_3-2-1_097079_2021-12-13_final
2021-12-19 09:09:10	ga_ls7e_ard_3-2-1_100080_2021-12-18_final
2021-12-20 09:52:20	ga_ls7e_ard_3-2-1_107080_2021-12-20_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-21 08:56:37	ga_ls7e_ard_3-2-1_098080_2021-12-20_final
2021-12-21 08:57:49	ga_ls7e_ard_3-2-1_098083_2021-12-20_final
2021-12-23 08:42:04	ga_ls7e_ard_3-2-1_096075_2021-12-22_final
2021-12-23 08:44:27	ga_ls7e_ard_3-2-1_096081_2021-12-22_final
2021-12-23 08:45:15	ga_ls7e_ard_3-2-1_096083_2021-12-22_final
2021-12-26 09:13:51	ga_ls7e_ard_3-2-1_101078_2021-12-25_final
2021-12-27 08:20:32	ga_ls7e_ard_3-2-1_092084_2021-12-26_final
2021-12-27 09:55:01	ga_ls7e_ard_3-2-1_108073_2021-12-27_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-30 08:49:08	ga_ls7e_ard_3-2-1_097079_2021-12-29_final
2021-12-30 08:50:44	ga_ls7e_ard_3-2-1_097083_2021-12-29_final
2022-01-01 08:35:46	ga_ls7e_ard_3-2-1_095077_2021-12-31_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-01 10:13:27	ga_ls7e_ard_3-2-1_111074_2022-01-01_final
2022-01-01 10:13:51	ga_ls7e_ard_3-2-1_111075_2022-01-01_final
2022-01-01 10:15:51	ga_ls7e_ard_3-2-1_111080_2022-01-01_final
2022-01-02 09:18:56	ga_ls7e_ard_3-2-1_102077_2022-01-01_final
2022-01-06 08:54:36	ga_ls7e_ard_3-2-1_098079_2022-01-05_final
2022-01-08 08:39:40	ga_ls7e_ard_3-2-1_096073_2022-01-07_final
2022-01-09 09:21:14	ga_ls7e_ard_3-2-1_103069_2022-01-08_final
2022-01-10 10:08:00	ga_ls7e_ard_3-2-1_110078_2022-01-10_final
2022-01-11 09:12:41	ga_ls7e_ard_3-2-1_101079_2022-01-10_final
2022-01-11 09:13:05	ga_ls7e_ard_3-2-1_101080_2022-01-10_final
2022-01-11 09:13:29	ga_ls7e_ard_3-2-1_101081_2022-01-10_final
2022-01-17 10:13:07	ga_ls7e_ard_3-2-1_111077_2022-01-17_final
2022-01-19 10:01:46	ga_ls7e_ard_3-2-1_109080_2022-01-19_final
2022-01-21 08:12:44	ga_ls7e_ard_3-2-1_091086_2022-01-20_final
2022-01-22 10:31:58	ga_ls7e_ard_3-2-1_114079_2022-01-22_final
2022-01-25 09:22:54	ga_ls7e_ard_3-2-1_103077_2022-01-24_final
2022-01-31 08:45:14	ga_ls7e_ard_3-2-1_097077_2022-01-30_final
2022-02-03 09:15:50	ga_ls7e_ard_3-2-1_102077_2022-02-02_final
2022-02-04 08:20:31	ga_ls7e_ard_3-2-1_093078_2022-02-03_final
2022-02-04 08:22:30	ga_ls7e_ard_3-2-1_093083_2022-02-03_final
2022-02-04 10:00:35	ga_ls7e_ard_3-2-1_109081_2022-02-04_final
2022-02-06 09:47:13	ga_ls7e_ard_3-2-1_107079_2022-02-06_final
2022-02-06 09:49:13	ga_ls7e_ard_3-2-1_107084_2022-02-06_final
2022-02-08 07:57:47	ga_ls7e_ard_3-2-1_089084_2022-02-07_final
2022-02-09 08:38:08	ga_ls7e_ard_3-2-1_096077_2022-02-08_final
2022-02-09 08:38:56	ga_ls7e_ard_3-2-1_096079_2022-02-08_final
2022-02-11 08:25:10	ga_ls7e_ard_3-2-1_094076_2022-02-10_final
2022-02-13 09:51:53	ga_ls7e_ard_3-2-1_108077_2022-02-13_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-20 09:58:58	ga_ls7e_ard_3-2-1_109081_2022-02-20_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-25 10:15:26	ga_ls7e_ard_3-2-1_112077_2022-02-25_final
2022-02-25 10:15:50	ga_ls7e_ard_3-2-1_112078_2022-02-25_final
2022-02-25 10:16:14	ga_ls7e_ard_3-2-1_112079_2022-02-25_final
2022-02-26 09:18:55	ga_ls7e_ard_3-2-1_103075_2022-02-25_final
2022-02-26 09:20:31	ga_ls7e_ard_3-2-1_103079_2022-02-25_final
2022-02-27 10:02:53	ga_ls7e_ard_3-2-1_110077_2022-02-27_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-01 09:50:20	ga_ls7e_ard_3-2-1_108077_2022-03-01_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-05 09:21:38	ga_ls7e_ard_3-2-1_104068_2022-03-04_final
2022-03-05 09:26:01	ga_ls7e_ard_3-2-1_104079_2022-03-04_final
2022-03-08 08:20:32	ga_ls7e_ard_3-2-1_093086_2022-03-07_final
2022-03-09 09:00:54	ga_ls7e_ard_3-2-1_100079_2022-03-08_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-13 08:34:59	ga_ls7e_ard_3-2-1_096077_2022-03-12_final
2022-03-14 09:15:45	ga_ls7e_ard_3-2-1_103071_2022-03-13_final
2022-03-14 09:16:56	ga_ls7e_ard_3-2-1_103074_2022-03-13_final
2022-03-14 09:17:20	ga_ls7e_ard_3-2-1_103075_2022-03-13_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-17 09:49:07	ga_ls7e_ard_3-2-1_108078_2022-03-17_final
2022-03-19 09:34:35	ga_ls7e_ard_3-2-1_106073_2022-03-19_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-22 08:26:19	ga_ls7e_ard_3-2-1_095073_2022-03-21_final
2022-03-22 08:27:31	ga_ls7e_ard_3-2-1_095076_2022-03-21_final
2022-03-25 08:56:56	ga_ls7e_ard_3-2-1_100073_2022-03-24_final
2022-03-26 08:02:49	ga_ls7e_ard_3-2-1_091077_2022-03-25_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-26 09:42:30	ga_ls7e_ard_3-2-1_107079_2022-03-26_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-27 08:47:35	ga_ls7e_ard_3-2-1_098081_2022-03-26_final
2022-03-27 08:48:23	ga_ls7e_ard_3-2-1_098083_2022-03-26_final
2022-03-29 08:32:38	ga_ls7e_ard_3-2-1_096075_2022-03-28_final
2022-03-30 09:15:48	ga_ls7e_ard_3-2-1_103075_2022-03-29_final
2022-03-31 08:23:17	ga_ls7e_ard_3-2-1_094083_2022-03-30_final
2022-03-31 08:23:41	ga_ls7e_ard_3-2-1_094084_2022-03-30_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-01 09:03:15	ga_ls7e_ard_3-2-1_101075_2022-03-31_final
2022-04-01 09:04:03	ga_ls7e_ard_3-2-1_101077_2022-03-31_final
2022-04-03 08:49:30	ga_ls7e_ard_3-2-1_099072_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years