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
2021-03-25 10:03:40	ga_ls7e_ard_3-2-0_105080_2021-03-25_final
2021-03-25 10:04:51	ga_ls7e_ard_3-2-0_105083_2021-03-25_final
2021-09-09 08:59:10	ga_ls7e_ard_3-2-0_097078_2021-09-08_final
2021-09-11 10:21:31	ga_ls7e_ard_3-2-0_111068_2021-09-11_final
2021-09-24 09:50:39	ga_ls7e_ard_3-2-0_106071_2021-09-24_final
2021-09-29 08:31:27	ga_ls7e_ard_3-2-0_093075_2021-09-28_final
2021-09-29 10:13:32	ga_ls7e_ard_3-2-0_109083_2021-09-29_final
2021-09-30 09:17:49	ga_ls7e_ard_3-2-0_100083_2021-09-29_final
2021-10-06 10:14:19	ga_ls7e_ard_3-2-0_110071_2021-10-06_final
2021-10-07 09:21:00	ga_ls7e_ard_3-2-0_101077_2021-10-06_final
2021-10-09 09:10:28	ga_ls7e_ard_3-2-0_099082_2021-10-08_final
2021-10-10 09:50:02	ga_ls7e_ard_3-2-0_106073_2021-10-10_final
2021-10-11 08:53:32	ga_ls7e_ard_3-2-0_097071_2021-10-10_final
2021-10-15 08:30:27	ga_ls7e_ard_3-2-0_093076_2021-10-14_final
2021-10-15 08:30:51	ga_ls7e_ard_3-2-0_093077_2021-10-14_final
2021-10-16 09:14:49	ga_ls7e_ard_3-2-0_100079_2021-10-15_final
2021-10-17 08:20:43	ga_ls7e_ard_3-2-0_091083_2021-10-16_final
2021-10-19 08:06:58	ga_ls7e_ard_3-2-0_089080_2021-10-18_final
2021-10-21 09:33:18	ga_ls7e_ard_3-2-0_103080_2021-10-21_final
2021-10-24 10:04:20	ga_ls7e_ard_3-2-0_108081_2021-10-24_final
2021-10-25 09:09:25	ga_ls7e_ard_3-2-0_099083_2021-10-24_final
2021-10-27 10:35:45	ga_ls7e_ard_3-2-0_113083_2021-10-27_final
2021-10-31 10:08:16	ga_ls7e_ard_3-2-0_109077_2021-10-31_final
2021-11-02 08:20:02	ga_ls7e_ard_3-2-0_091085_2021-11-01_final
2021-11-02 08:21:38	ga_ls7e_ard_3-2-0_091089_2021-11-01_final
2021-11-06 09:29:26	ga_ls7e_ard_3-2-0_103074_2021-11-05_final
2021-11-09 08:25:09	ga_ls7e_ard_3-2-0_092084_2021-11-08_final
2021-11-10 10:44:00	ga_ls7e_ard_3-2-0_115076_2021-11-10_final
2021-11-14 08:38:49	ga_ls7e_ard_3-2-1_095073_2021-11-13_final
2021-11-14 10:18:29	ga_ls7e_ard_3-2-1_111075_2021-11-14_final
2021-11-20 08:03:56	ga_ls7e_ard_3-2-1_089080_2021-11-19_final
2021-11-21 08:49:06	ga_ls7e_ard_3-2-1_096085_2021-11-20_final
2021-11-23 08:35:20	ga_ls7e_ard_3-2-1_094082_2021-11-22_final
2021-11-27 08:09:27	ga_ls7e_ard_3-2-1_090080_2021-11-26_final
2021-11-28 08:53:01	ga_ls7e_ard_3-2-1_097081_2021-11-27_final
2021-11-28 10:31:30	ga_ls7e_ard_3-2-1_113080_2021-11-28_final
2021-12-05 10:34:38	ga_ls7e_ard_3-2-1_114074_2021-12-05_final
2021-12-07 10:22:53	ga_ls7e_ard_3-2-1_112076_2021-12-07_final
2021-12-11 08:21:42	ga_ls7e_ard_3-2-1_092083_2021-12-10_final
2021-12-16 08:36:10	ga_ls7e_ard_3-2-1_095074_2021-12-15_final
2021-12-16 08:38:57	ga_ls7e_ard_3-2-1_095081_2021-12-15_final
2021-12-16 08:39:21	ga_ls7e_ard_3-2-1_095082_2021-12-15_final
2021-12-18 08:25:12	ga_ls7e_ard_3-2-1_093078_2021-12-17_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-23 08:45:39	ga_ls7e_ard_3-2-1_096084_2021-12-22_final
2021-12-23 10:23:44	ga_ls7e_ard_3-2-1_112082_2021-12-23_final
2021-12-25 08:29:54	ga_ls7e_ard_3-2-1_094076_2021-12-24_final
2021-12-27 09:57:25	ga_ls7e_ard_3-2-1_108079_2021-12-27_final
2021-12-29 08:05:59	ga_ls7e_ard_3-2-1_090079_2021-12-28_final
2021-12-30 08:46:44	ga_ls7e_ard_3-2-1_097073_2021-12-29_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2022-01-03 09:59:17	ga_ls7e_ard_3-2-1_109070_2022-01-03_final
2022-01-03 10:04:05	ga_ls7e_ard_3-2-1_109082_2022-01-03_final
2022-01-12 08:17:46	ga_ls7e_ard_3-2-1_092081_2022-01-11_final
2022-01-12 08:19:22	ga_ls7e_ard_3-2-1_092085_2022-01-11_final
2022-01-14 08:06:25	ga_ls7e_ard_3-2-1_090084_2022-01-13_final
2022-01-15 08:45:12	ga_ls7e_ard_3-2-1_097073_2022-01-14_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-19 09:58:34	ga_ls7e_ard_3-2-1_109072_2022-01-19_final
2022-01-21 08:09:56	ga_ls7e_ard_3-2-1_091079_2022-01-20_final
2022-01-21 08:10:44	ga_ls7e_ard_3-2-1_091081_2022-01-20_final
2022-01-21 09:49:13	ga_ls7e_ard_3-2-1_107080_2022-01-21_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-24 10:18:13	ga_ls7e_ard_3-2-1_112076_2022-01-24_final
2022-01-25 09:24:06	ga_ls7e_ard_3-2-1_103080_2022-01-24_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-01-29 08:57:24	ga_ls7e_ard_3-2-1_099076_2022-01-28_final
2022-01-31 08:44:02	ga_ls7e_ard_3-2-1_097074_2022-01-30_final
2022-01-31 10:23:43	ga_ls7e_ard_3-2-1_113076_2022-01-31_final
2022-02-01 09:25:36	ga_ls7e_ard_3-2-1_104070_2022-01-31_final
2022-02-02 08:32:17	ga_ls7e_ard_3-2-1_095076_2022-02-01_final
2022-02-06 08:07:57	ga_ls7e_ard_3-2-1_091078_2022-02-05_final
2022-02-07 08:49:30	ga_ls7e_ard_3-2-1_098074_2022-02-06_final
2022-02-08 09:31:28	ga_ls7e_ard_3-2-1_105071_2022-02-08_final
2022-02-11 10:02:03	ga_ls7e_ard_3-2-1_110071_2022-02-11_final
2022-02-11 10:05:15	ga_ls7e_ard_3-2-1_110079_2022-02-11_final
2022-02-18 08:33:02	ga_ls7e_ard_3-2-1_095082_2022-02-17_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-22 08:09:32	ga_ls7e_ard_3-2-1_091086_2022-02-21_final
2022-02-22 09:43:37	ga_ls7e_ard_3-2-1_107074_2022-02-22_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-23 10:27:59	ga_ls7e_ard_3-2-1_114077_2022-02-23_final
2022-02-24 09:29:29	ga_ls7e_ard_3-2-1_105070_2022-02-23_final
2022-03-01 09:51:32	ga_ls7e_ard_3-2-1_108080_2022-03-01_final
2022-03-03 08:00:54	ga_ls7e_ard_3-2-1_090082_2022-03-02_final
2022-03-03 08:04:05	ga_ls7e_ard_3-2-1_090090_2022-03-02_final
2022-03-03 09:35:47	ga_ls7e_ard_3-2-1_106072_2022-03-03_final
2022-03-04 10:22:56	ga_ls7e_ard_3-2-1_113082_2022-03-04_final
2022-03-08 08:18:56	ga_ls7e_ard_3-2-1_093082_2022-03-07_final
2022-03-09 09:00:54	ga_ls7e_ard_3-2-1_100079_2022-03-08_final
2022-03-10 09:44:52	ga_ls7e_ard_3-2-1_107081_2022-03-10_final
2022-03-11 08:45:33	ga_ls7e_ard_3-2-1_098072_2022-03-10_final
2022-03-11 10:25:13	ga_ls7e_ard_3-2-1_114074_2022-03-11_final
2022-03-20 08:40:52	ga_ls7e_ard_3-2-1_097078_2022-03-19_final
2022-03-25 08:58:08	ga_ls7e_ard_3-2-1_100076_2022-03-24_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-27 08:46:47	ga_ls7e_ard_3-2-1_098079_2022-03-26_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-31 08:22:53	ga_ls7e_ard_3-2-1_094082_2022-03-30_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_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