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
2021-08-21 10:09:59	ga_ls7e_ard_3-2-0_108081_2021-08-21_final
2021-08-22 09:13:53	ga_ls7e_ard_3-2-0_099080_2021-08-21_final
2021-08-24 09:03:21	ga_ls7e_ard_3-2-0_097085_2021-08-23_final
2021-09-08 08:16:48	ga_ls7e_ard_3-2-0_090080_2021-09-07_final
2021-09-08 08:20:47	ga_ls7e_ard_3-2-0_090090_2021-09-07_final
2021-09-12 09:26:13	ga_ls7e_ard_3-2-0_102069_2021-09-11_final
2021-09-19 09:36:09	ga_ls7e_ard_3-2-0_103080_2021-09-19_final
2021-09-27 08:46:47	ga_ls7e_ard_3-2-0_095082_2021-09-26_final
2021-09-28 09:29:34	ga_ls7e_ard_3-2-0_102081_2021-09-27_final
2021-09-30 09:15:26	ga_ls7e_ard_3-2-0_100077_2021-09-29_final
2021-10-05 09:31:32	ga_ls7e_ard_3-2-0_103072_2021-10-05_final
2021-10-05 09:34:44	ga_ls7e_ard_3-2-0_103080_2021-10-05_final
2021-10-08 08:28:05	ga_ls7e_ard_3-2-0_092084_2021-10-07_final
2021-10-09 09:09:16	ga_ls7e_ard_3-2-0_099079_2021-10-08_final
2021-10-10 08:13:57	ga_ls7e_ard_3-2-0_090080_2021-10-09_final
2021-10-13 08:46:59	ga_ls7e_ard_3-2-0_095086_2021-10-12_final
2021-10-16 09:14:49	ga_ls7e_ard_3-2-0_100079_2021-10-15_final
2021-11-01 09:12:57	ga_ls7e_ard_3-2-0_100078_2021-10-31_final
2021-11-02 08:16:51	ga_ls7e_ard_3-2-0_091077_2021-11-01_final
2021-11-04 08:06:18	ga_ls7e_ard_3-2-0_089082_2021-11-03_final
2021-11-09 09:59:14	ga_ls7e_ard_3-2-0_108072_2021-11-09_final
2021-11-09 10:02:26	ga_ls7e_ard_3-2-0_108080_2021-11-09_final
2021-11-11 08:13:00	ga_ls7e_ard_3-2-0_090085_2021-11-10_final
2021-11-16 10:06:44	ga_ls7e_ard_3-2-1_109077_2021-11-16_final
2021-11-20 08:03:56	ga_ls7e_ard_3-2-1_089080_2021-11-19_final
2021-11-21 08:47:54	ga_ls7e_ard_3-2-1_096082_2021-11-20_final
2021-11-22 09:29:04	ga_ls7e_ard_3-2-1_103077_2021-11-21_final
2021-12-03 09:07:06	ga_ls7e_ard_3-2-1_100071_2021-12-02_final
2021-12-04 08:18:34	ga_ls7e_ard_3-2-1_091089_2021-12-03_final
2021-12-06 09:37:43	ga_ls7e_ard_3-2-1_105071_2021-12-06_final
2021-12-10 09:12:37	ga_ls7e_ard_3-2-1_101071_2021-12-09_final
2021-12-11 08:22:54	ga_ls7e_ard_3-2-1_092086_2021-12-10_final
2021-12-11 09:55:23	ga_ls7e_ard_3-2-1_108070_2021-12-11_final
2021-12-13 08:11:32	ga_ls7e_ard_3-2-1_090089_2021-12-12_final
2021-12-18 08:24:25	ga_ls7e_ard_3-2-1_093076_2021-12-17_final
2021-12-23 08:46:27	ga_ls7e_ard_3-2-1_096086_2021-12-22_final
2021-12-25 10:11:10	ga_ls7e_ard_3-2-1_110082_2021-12-25_final
2021-12-27 08:22:32	ga_ls7e_ard_3-2-1_092089_2021-12-26_final
2021-12-29 08:05:59	ga_ls7e_ard_3-2-1_090079_2021-12-28_final
2022-01-03 08:23:12	ga_ls7e_ard_3-2-1_093077_2022-01-02_final
2022-01-06 08:51:25	ga_ls7e_ard_3-2-1_098071_2022-01-05_final
2022-01-07 09:33:47	ga_ls7e_ard_3-2-1_105069_2022-01-07_final
2022-01-08 08:44:03	ga_ls7e_ard_3-2-1_096084_2022-01-07_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-14 08:08:49	ga_ls7e_ard_3-2-1_090090_2022-01-13_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-01-23 09:35:28	ga_ls7e_ard_3-2-1_105077_2022-01-23_final
2022-01-28 08:18:37	ga_ls7e_ard_3-2-1_092087_2022-01-27_final
2022-01-28 09:53:31	ga_ls7e_ard_3-2-1_108077_2022-01-28_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-31 08:47:38	ga_ls7e_ard_3-2-1_097083_2022-01-30_final
2022-02-02 10:11:57	ga_ls7e_ard_3-2-1_111078_2022-02-02_final
2022-02-06 08:08:45	ga_ls7e_ard_3-2-1_091080_2022-02-05_final
2022-02-10 09:23:17	ga_ls7e_ard_3-2-1_103082_2022-02-09_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-14 08:56:57	ga_ls7e_ard_3-2-1_099079_2022-02-13_final
2022-02-20 09:57:46	ga_ls7e_ard_3-2-1_109078_2022-02-20_final
2022-02-21 09:00:04	ga_ls7e_ard_3-2-1_100073_2022-02-20_final
2022-02-22 08:09:08	ga_ls7e_ard_3-2-1_091085_2022-02-21_final
2022-02-22 08:09:56	ga_ls7e_ard_3-2-1_091087_2022-02-21_final
2022-02-22 09:44:01	ga_ls7e_ard_3-2-1_107075_2022-02-22_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-23 10:28:47	ga_ls7e_ard_3-2-1_114079_2022-02-23_final
2022-03-02 08:55:25	ga_ls7e_ard_3-2-1_099079_2022-03-01_final
2022-03-03 08:03:41	ga_ls7e_ard_3-2-1_090089_2022-03-02_final
2022-03-03 08:04:05	ga_ls7e_ard_3-2-1_090090_2022-03-02_final
2022-03-03 09:34:35	ga_ls7e_ard_3-2-1_106069_2022-03-03_final
2022-03-03 09:35:23	ga_ls7e_ard_3-2-1_106071_2022-03-03_final
2022-03-04 08:39:40	ga_ls7e_ard_3-2-1_097071_2022-03-03_final
2022-03-05 09:21:38	ga_ls7e_ard_3-2-1_104068_2022-03-04_final
2022-03-06 10:08:23	ga_ls7e_ard_3-2-1_111077_2022-03-06_final
2022-03-07 09:13:28	ga_ls7e_ard_3-2-1_102079_2022-03-06_final
2022-03-08 08:15:45	ga_ls7e_ard_3-2-1_093074_2022-03-07_final
2022-03-10 08:07:11	ga_ls7e_ard_3-2-1_091084_2022-03-09_final
2022-03-11 10:25:37	ga_ls7e_ard_3-2-1_114075_2022-03-11_final
2022-03-13 08:36:35	ga_ls7e_ard_3-2-1_096081_2022-03-12_final
2022-03-13 10:13:04	ga_ls7e_ard_3-2-1_112075_2022-03-13_final
2022-03-15 10:00:30	ga_ls7e_ard_3-2-1_110075_2022-03-15_final
2022-03-18 08:53:00	ga_ls7e_ard_3-2-1_099077_2022-03-17_final
2022-03-18 08:54:36	ga_ls7e_ard_3-2-1_099081_2022-03-17_final
2022-03-18 10:32:41	ga_ls7e_ard_3-2-1_115079_2022-03-18_final
2022-03-21 09:22:26	ga_ls7e_ard_3-2-1_104074_2022-03-20_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-24 08:16:10	ga_ls7e_ard_3-2-1_093079_2022-03-23_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-26 08:05:13	ga_ls7e_ard_3-2-1_091083_2022-03-25_final
2022-03-26 08:08:01	ga_ls7e_ard_3-2-1_091090_2022-03-25_final
2022-03-26 09:42:54	ga_ls7e_ard_3-2-1_107080_2022-03-26_final
2022-03-27 08:48:47	ga_ls7e_ard_3-2-1_098084_2022-03-26_final
2022-03-29 08:30:39	ga_ls7e_ard_3-2-1_096070_2022-03-28_final
2022-03-31 08:20:53	ga_ls7e_ard_3-2-1_094077_2022-03-30_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-04-01 09:06:27	ga_ls7e_ard_3-2-1_101083_2022-03-31_final
2022-04-02 08:08:20	ga_ls7e_ard_3-2-1_092077_2022-04-01_final
2022-04-02 08:10:44	ga_ls7e_ard_3-2-1_092083_2022-04-01_final
2022-04-03 10:29:34	ga_ls7e_ard_3-2-1_115075_2022-04-03_final
2022-04-04 07:56:10	ga_ls7e_ard_3-2-1_090078_2022-04-03_final
2022-04-04 09:31:51	ga_ls7e_ard_3-2-1_106070_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years