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
2021-10-08 10:04:58	ga_ls7e_ard_3-2-0_108079_2021-10-08_final
2021-10-10 08:13:57	ga_ls7e_ard_3-2-0_090080_2021-10-09_final
2021-10-11 08:57:31	ga_ls7e_ard_3-2-0_097081_2021-10-10_final
2021-10-13 08:43:00	ga_ls7e_ard_3-2-0_095076_2021-10-12_final
2021-10-13 08:44:35	ga_ls7e_ard_3-2-0_095080_2021-10-12_final
2021-10-13 10:23:04	ga_ls7e_ard_3-2-0_111079_2021-10-13_final
2021-10-13 10:23:52	ga_ls7e_ard_3-2-0_111081_2021-10-13_final
2021-10-15 08:31:39	ga_ls7e_ard_3-2-0_093079_2021-10-14_final
2021-10-15 10:09:44	ga_ls7e_ard_3-2-0_109077_2021-10-15_final
2021-10-15 10:10:32	ga_ls7e_ard_3-2-0_109079_2021-10-15_final
2021-10-17 08:21:54	ga_ls7e_ard_3-2-0_091086_2021-10-16_final
2021-10-27 08:54:05	ga_ls7e_ard_3-2-0_097076_2021-10-26_final
2021-10-28 09:36:27	ga_ls7e_ard_3-2-0_104074_2021-10-28_final
2021-10-30 09:24:42	ga_ls7e_ard_3-2-0_102076_2021-10-29_final
2021-10-31 08:29:48	ga_ls7e_ard_3-2-0_093078_2021-10-30_final
2021-10-31 10:09:04	ga_ls7e_ard_3-2-0_109079_2021-10-31_final
2021-11-04 09:43:58	ga_ls7e_ard_3-2-0_105079_2021-11-04_final
2021-11-09 08:23:57	ga_ls7e_ard_3-2-0_092081_2021-11-08_final
2021-11-10 09:04:19	ga_ls7e_ard_3-2-0_099074_2021-11-09_final
2021-11-12 10:31:51	ga_ls7e_ard_3-2-1_113077_2021-11-12_final
2021-11-14 08:41:37	ga_ls7e_ard_3-2-1_095080_2021-11-13_final
2021-11-14 10:19:41	ga_ls7e_ard_3-2-1_111078_2021-11-14_final
2021-11-15 09:24:46	ga_ls7e_ard_3-2-1_102080_2021-11-14_final
2021-11-16 08:29:27	ga_ls7e_ard_3-2-1_093081_2021-11-15_final
2021-11-17 09:12:37	ga_ls7e_ard_3-2-1_100081_2021-11-16_final
2021-11-22 09:28:40	ga_ls7e_ard_3-2-1_103076_2021-11-21_final
2021-11-23 08:32:33	ga_ls7e_ard_3-2-1_094075_2021-11-22_final
2021-11-29 09:35:23	ga_ls7e_ard_3-2-1_104079_2021-11-29_final
2021-11-29 09:36:11	ga_ls7e_ard_3-2-1_104081_2021-11-29_final
2021-11-30 10:17:21	ga_ls7e_ard_3-2-1_111076_2021-11-30_final
2021-12-05 08:58:57	ga_ls7e_ard_3-2-1_098082_2021-12-04_final
2021-12-07 08:44:24	ga_ls7e_ard_3-2-1_096077_2021-12-06_final
2021-12-07 10:24:05	ga_ls7e_ard_3-2-1_112079_2021-12-07_final
2021-12-09 08:31:51	ga_ls7e_ard_3-2-1_094077_2021-12-08_final
2021-12-09 08:32:39	ga_ls7e_ard_3-2-1_094079_2021-12-08_final
2021-12-12 09:01:16	ga_ls7e_ard_3-2-1_099074_2021-12-11_final
2021-12-13 09:46:02	ga_ls7e_ard_3-2-1_106078_2021-12-13_final
2021-12-16 10:17:26	ga_ls7e_ard_3-2-1_111080_2021-12-16_final
2021-12-17 09:21:19	ga_ls7e_ard_3-2-1_102079_2021-12-16_final
2021-12-18 08:26:24	ga_ls7e_ard_3-2-1_093081_2021-12-17_final
2021-12-20 08:13:03	ga_ls7e_ard_3-2-1_091079_2021-12-19_final
2021-12-20 09:52:20	ga_ls7e_ard_3-2-1_107080_2021-12-20_final
2021-12-21 08:57:25	ga_ls7e_ard_3-2-1_098082_2021-12-20_final
2021-12-23 10:22:56	ga_ls7e_ard_3-2-1_112080_2021-12-23_final
2021-12-24 09:26:49	ga_ls7e_ard_3-2-1_103079_2021-12-23_final
2021-12-27 08:21:20	ga_ls7e_ard_3-2-1_092086_2021-12-26_final
2021-12-27 09:57:01	ga_ls7e_ard_3-2-1_108078_2021-12-27_final
2021-12-30 08:50:44	ga_ls7e_ard_3-2-1_097083_2021-12-29_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-08 10:20:32	ga_ls7e_ard_3-2-1_112078_2022-01-08_final
2022-01-08 10:20:56	ga_ls7e_ard_3-2-1_112079_2022-01-08_final
2022-01-09 09:23:38	ga_ls7e_ard_3-2-1_103075_2022-01-08_final
2022-01-09 09:24:50	ga_ls7e_ard_3-2-1_103078_2022-01-08_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-19 10:00:58	ga_ls7e_ard_3-2-1_109078_2022-01-19_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-23 09:35:52	ga_ls7e_ard_3-2-1_105078_2022-01-23_final
2022-01-27 09:11:33	ga_ls7e_ard_3-2-1_101080_2022-01-26_final
2022-01-28 08:17:02	ga_ls7e_ard_3-2-1_092083_2022-01-27_final
2022-02-02 10:11:09	ga_ls7e_ard_3-2-1_111076_2022-02-02_final
2022-02-09 10:16:37	ga_ls7e_ard_3-2-1_112076_2022-02-09_final
2022-02-09 10:17:25	ga_ls7e_ard_3-2-1_112078_2022-02-09_final
2022-02-11 08:26:22	ga_ls7e_ard_3-2-1_094079_2022-02-10_final
2022-02-11 10:04:03	ga_ls7e_ard_3-2-1_110076_2022-02-11_final
2022-02-12 09:09:55	ga_ls7e_ard_3-2-1_101080_2022-02-11_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-18 08:30:38	ga_ls7e_ard_3-2-1_095076_2022-02-17_final
2022-02-18 10:09:55	ga_ls7e_ard_3-2-1_111077_2022-02-18_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-19 09:13:00	ga_ls7e_ard_3-2-1_102074_2022-02-18_final
2022-03-01 08:13:27	ga_ls7e_ard_3-2-1_092082_2022-02-28_final
2022-03-02 08:57:01	ga_ls7e_ard_3-2-1_099083_2022-03-01_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-06 08:31:54	ga_ls7e_ard_3-2-1_095083_2022-03-05_final
2022-03-06 10:08:47	ga_ls7e_ard_3-2-1_111078_2022-03-06_final
2022-03-09 09:01:42	ga_ls7e_ard_3-2-1_100081_2022-03-08_final
2022-03-10 09:44:28	ga_ls7e_ard_3-2-1_107080_2022-03-10_final
2022-03-13 08:35:47	ga_ls7e_ard_3-2-1_096079_2022-03-12_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-18 08:51:48	ga_ls7e_ard_3-2-1_099074_2022-03-17_final
2022-03-19 09:36:58	ga_ls7e_ard_3-2-1_106079_2022-03-19_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-23 09:10:41	ga_ls7e_ard_3-2-1_102076_2022-03-22_final
2022-03-25 09:00:08	ga_ls7e_ard_3-2-1_100081_2022-03-24_final
2022-03-26 09:42:30	ga_ls7e_ard_3-2-1_107079_2022-03-26_final
2022-03-26 09:43:42	ga_ls7e_ard_3-2-1_107082_2022-03-26_final
2022-03-27 08:47:35	ga_ls7e_ard_3-2-1_098081_2022-03-26_final
2022-03-29 08:34:14	ga_ls7e_ard_3-2-1_096079_2022-03-28_final
2022-03-29 08:35:02	ga_ls7e_ard_3-2-1_096081_2022-03-28_final
2022-03-30 09:15:24	ga_ls7e_ard_3-2-1_103074_2022-03-29_final
2022-04-01 09:04:51	ga_ls7e_ard_3-2-1_101079_2022-03-31_final
2022-04-02 08:08:44	ga_ls7e_ard_3-2-1_092078_2022-04-01_final
2022-04-02 09:46:49	ga_ls7e_ard_3-2-1_108076_2022-04-02_final
2022-04-02 09:47:12	ga_ls7e_ard_3-2-1_108077_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