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 08:54:11	ga_ls7e_ard_3-2-0_096083_2021-09-17_final
2021-09-20 10:17:44	ga_ls7e_ard_3-2-0_110076_2021-09-20_final
2021-09-20 10:18:32	ga_ls7e_ard_3-2-0_110078_2021-09-20_final
2021-09-20 10:20:31	ga_ls7e_ard_3-2-0_110083_2021-09-20_final
2021-10-25 09:09:01	ga_ls7e_ard_3-2-0_099082_2021-10-24_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-26 09:14:15	ga_ls7e_ard_3-2-1_101079_2021-12-25_final
2021-12-30 08:49:08	ga_ls7e_ard_3-2-1_097079_2021-12-29_final
2021-12-31 09:28:18	ga_ls7e_ard_3-2-1_104069_2021-12-30_final
2022-01-01 08:34:58	ga_ls7e_ard_3-2-1_095075_2021-12-31_final
2022-01-03 08:22:48	ga_ls7e_ard_3-2-1_093076_2022-01-02_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-11 09:11:05	ga_ls7e_ard_3-2-1_101075_2022-01-10_final
2022-01-11 09:12:17	ga_ls7e_ard_3-2-1_101078_2022-01-10_final
2022-01-13 08:58:08	ga_ls7e_ard_3-2-1_099074_2022-01-12_final
2022-01-15 08:46:23	ga_ls7e_ard_3-2-1_097076_2022-01-14_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-19 08:20:30	ga_ls7e_ard_3-2-1_093074_2022-01-18_final
2022-01-19 08:21:17	ga_ls7e_ard_3-2-1_093076_2022-01-18_final
2022-01-21 09:49:13	ga_ls7e_ard_3-2-1_107080_2022-01-21_final
2022-01-22 08:50:42	ga_ls7e_ard_3-2-1_098073_2022-01-21_final
2022-01-23 07:58:11	ga_ls7e_ard_3-2-1_089081_2022-01-22_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-25 09:21:43	ga_ls7e_ard_3-2-1_103074_2022-01-24_final
2022-01-25 09:22:06	ga_ls7e_ard_3-2-1_103075_2022-01-24_final
2022-01-27 09:10:45	ga_ls7e_ard_3-2-1_101078_2022-01-26_final
2022-01-28 09:54:18	ga_ls7e_ard_3-2-1_108079_2022-01-28_final
2022-01-29 10:37:28	ga_ls7e_ard_3-2-1_115079_2022-01-29_final
2022-02-02 08:31:29	ga_ls7e_ard_3-2-1_095074_2022-02-01_final
2022-02-04 08:24:30	ga_ls7e_ard_3-2-1_093088_2022-02-03_final
2022-02-05 09:02:52	ga_ls7e_ard_3-2-1_100076_2022-02-04_final
2022-02-07 08:51:30	ga_ls7e_ard_3-2-1_098079_2022-02-06_final
2022-02-09 08:40:08	ga_ls7e_ard_3-2-1_096082_2022-02-08_final
2022-02-10 09:21:18	ga_ls7e_ard_3-2-1_103077_2022-02-09_final
2022-02-11 08:24:22	ga_ls7e_ard_3-2-1_094074_2022-02-10_final
2022-02-11 10:04:03	ga_ls7e_ard_3-2-1_110076_2022-02-11_final
2022-02-11 10:05:15	ga_ls7e_ard_3-2-1_110079_2022-02-11_final
2022-02-16 08:45:11	ga_ls7e_ard_3-2-1_097081_2022-02-15_final
2022-02-17 09:27:33	ga_ls7e_ard_3-2-1_104079_2022-02-16_final
2022-02-18 10:07:55	ga_ls7e_ard_3-2-1_111072_2022-02-18_final
2022-02-19 09:12:13	ga_ls7e_ard_3-2-1_102072_2022-02-18_final
2022-02-19 09:14:12	ga_ls7e_ard_3-2-1_102077_2022-02-18_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-21 09:00:51	ga_ls7e_ard_3-2-1_100075_2022-02-20_final
2022-02-21 09:02:51	ga_ls7e_ard_3-2-1_100080_2022-02-20_final
2022-02-22 08:09:32	ga_ls7e_ard_3-2-1_091086_2022-02-21_final
2022-02-22 09:44:49	ga_ls7e_ard_3-2-1_107077_2022-02-22_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-23 08:48:42	ga_ls7e_ard_3-2-1_098076_2022-02-22_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-26 09:17:43	ga_ls7e_ard_3-2-1_103072_2022-02-25_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_final
2022-02-26 09:21:43	ga_ls7e_ard_3-2-1_103082_2022-02-25_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-02 08:55:25	ga_ls7e_ard_3-2-1_099079_2022-03-01_final
2022-03-03 07:59:42	ga_ls7e_ard_3-2-1_090079_2022-03-02_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-07 09:11:28	ga_ls7e_ard_3-2-1_102074_2022-03-06_final
2022-03-08 08:20:32	ga_ls7e_ard_3-2-1_093086_2022-03-07_final
2022-03-08 09:55:49	ga_ls7e_ard_3-2-1_109077_2022-03-08_final
2022-03-10 08:05:59	ga_ls7e_ard_3-2-1_091081_2022-03-09_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-10 08:06:47	ga_ls7e_ard_3-2-1_091083_2022-03-09_final
2022-03-11 08:46:21	ga_ls7e_ard_3-2-1_098074_2022-03-10_final
2022-03-11 10:25:13	ga_ls7e_ard_3-2-1_114074_2022-03-11_final
2022-03-13 08:34:11	ga_ls7e_ard_3-2-1_096075_2022-03-12_final
2022-03-14 09:16:32	ga_ls7e_ard_3-2-1_103073_2022-03-13_final
2022-03-15 09:59:18	ga_ls7e_ard_3-2-1_110072_2022-03-15_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-19 07:58:06	ga_ls7e_ard_3-2-1_090079_2022-03-18_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-19 09:37:46	ga_ls7e_ard_3-2-1_106081_2022-03-19_final
2022-03-20 10:20:32	ga_ls7e_ard_3-2-1_113080_2022-03-20_final
2022-03-22 08:30:19	ga_ls7e_ard_3-2-1_095083_2022-03-21_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-23 09:12:17	ga_ls7e_ard_3-2-1_102080_2022-03-22_final
2022-03-25 08:58:08	ga_ls7e_ard_3-2-1_100076_2022-03-24_final
2022-03-26 08:04:01	ga_ls7e_ard_3-2-1_091080_2022-03-25_final
2022-03-26 08:06:01	ga_ls7e_ard_3-2-1_091085_2022-03-25_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-27 08:44:24	ga_ls7e_ard_3-2-1_098073_2022-03-26_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-03-29 08:35:26	ga_ls7e_ard_3-2-1_096082_2022-03-28_final
2022-03-30 09:13:25	ga_ls7e_ard_3-2-1_103069_2022-03-29_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_final
2022-04-01 09:02:51	ga_ls7e_ard_3-2-1_101074_2022-03-31_final
2022-04-02 08:10:20	ga_ls7e_ard_3-2-1_092082_2022-04-01_final
2022-04-02 09:46:49	ga_ls7e_ard_3-2-1_108076_2022-04-02_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_2022-04-02_final
2022-04-03 08:53:53	ga_ls7e_ard_3-2-1_099083_2022-04-02_final
2022-04-04 09:34:39	ga_ls7e_ard_3-2-1_106077_2022-04-04_final
2022-04-04 09:35:03	ga_ls7e_ard_3-2-1_106078_2022-04-04_final
2022-04-04 09:36:15	ga_ls7e_ard_3-2-1_106081_2022-04-04_final
2022-04-05 08:38:32	ga_ls7e_ard_3-2-1_097076_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years