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 10:29:28	ga_ls7e_ard_3-2-0_112074_2021-09-18_final
2021-09-20 08:38:51	ga_ls7e_ard_3-2-0_094076_2021-09-19_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-10-26 09:50:59	ga_ls7e_ard_3-2-0_106079_2021-10-26_final
2021-12-10 09:16:13	ga_ls7e_ard_3-2-1_101080_2021-12-09_final
2021-12-12 09:04:04	ga_ls7e_ard_3-2-1_099081_2021-12-11_final
2021-12-13 09:42:26	ga_ls7e_ard_3-2-1_106069_2021-12-13_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-17 09:19:20	ga_ls7e_ard_3-2-1_102074_2021-12-16_final
2021-12-17 09:20:07	ga_ls7e_ard_3-2-1_102076_2021-12-16_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-20 08:15:03	ga_ls7e_ard_3-2-1_091084_2021-12-19_final
2021-12-21 08:56:13	ga_ls7e_ard_3-2-1_098079_2021-12-20_final
2021-12-22 09:39:22	ga_ls7e_ard_3-2-1_105079_2021-12-22_final
2021-12-27 08:20:56	ga_ls7e_ard_3-2-1_092085_2021-12-26_final
2021-12-27 09:56:37	ga_ls7e_ard_3-2-1_108077_2021-12-27_final
2021-12-28 10:38:59	ga_ls7e_ard_3-2-1_115075_2021-12-28_final
2021-12-30 08:47:56	ga_ls7e_ard_3-2-1_097076_2021-12-29_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-31 09:30:42	ga_ls7e_ard_3-2-1_104075_2021-12-31_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-06 08:52:13	ga_ls7e_ard_3-2-1_098073_2022-01-05_final
2022-01-08 10:19:21	ga_ls7e_ard_3-2-1_112075_2022-01-08_final
2022-01-09 09:23:14	ga_ls7e_ard_3-2-1_103074_2022-01-08_final
2022-01-09 09:24:02	ga_ls7e_ard_3-2-1_103076_2022-01-08_final
2022-01-10 08:31:07	ga_ls7e_ard_3-2-1_094083_2022-01-09_final
2022-01-10 10:09:36	ga_ls7e_ard_3-2-1_110082_2022-01-10_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-14 09:41:18	ga_ls7e_ard_3-2-1_106074_2022-01-14_final
2022-01-14 09:43:18	ga_ls7e_ard_3-2-1_106079_2022-01-14_final
2022-01-17 08:34:14	ga_ls7e_ard_3-2-1_095077_2022-01-16_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-19 08:20:30	ga_ls7e_ard_3-2-1_093074_2022-01-18_final
2022-01-26 08:30:23	ga_ls7e_ard_3-2-1_094085_2022-01-25_final
2022-01-28 09:55:54	ga_ls7e_ard_3-2-1_108083_2022-01-28_final
2022-01-29 08:58:11	ga_ls7e_ard_3-2-1_099078_2022-01-28_final
2022-01-30 09:41:45	ga_ls7e_ard_3-2-1_106079_2022-01-30_final
2022-01-31 08:44:50	ga_ls7e_ard_3-2-1_097076_2022-01-30_final
2022-01-31 08:46:02	ga_ls7e_ard_3-2-1_097079_2022-01-30_final
2022-01-31 10:23:43	ga_ls7e_ard_3-2-1_113076_2022-01-31_final
2022-01-31 10:26:30	ga_ls7e_ard_3-2-1_113083_2022-01-31_final
2022-02-06 08:08:21	ga_ls7e_ard_3-2-1_091079_2022-02-05_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-12 09:06:20	ga_ls7e_ard_3-2-1_101071_2022-02-11_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-12 09:11:07	ga_ls7e_ard_3-2-1_101083_2022-02-11_final
2022-02-13 09:49:05	ga_ls7e_ard_3-2-1_108070_2022-02-13_final
2022-02-13 09:49:53	ga_ls7e_ard_3-2-1_108072_2022-02-13_final
2022-02-14 08:52:34	ga_ls7e_ard_3-2-1_099068_2022-02-13_final
2022-02-14 08:57:21	ga_ls7e_ard_3-2-1_099080_2022-02-13_final
2022-02-15 09:36:07	ga_ls7e_ard_3-2-1_106069_2022-02-15_final
2022-02-15 09:36:55	ga_ls7e_ard_3-2-1_106071_2022-02-15_final
2022-02-15 09:38:30	ga_ls7e_ard_3-2-1_106075_2022-02-15_final
2022-02-16 08:43:11	ga_ls7e_ard_3-2-1_097076_2022-02-15_final
2022-02-18 10:11:55	ga_ls7e_ard_3-2-1_111082_2022-02-18_final
2022-02-19 09:12:36	ga_ls7e_ard_3-2-1_102073_2022-02-18_final
2022-02-20 08:21:41	ga_ls7e_ard_3-2-1_093085_2022-02-19_final
2022-02-21 09:00:28	ga_ls7e_ard_3-2-1_100074_2022-02-20_final
2022-02-21 09:00:51	ga_ls7e_ard_3-2-1_100075_2022-02-20_final
2022-02-22 09:46:25	ga_ls7e_ard_3-2-1_107081_2022-02-22_final
2022-02-23 08:47:07	ga_ls7e_ard_3-2-1_098072_2022-02-22_final
2022-02-24 09:29:29	ga_ls7e_ard_3-2-1_105070_2022-02-23_final
2022-02-24 09:30:17	ga_ls7e_ard_3-2-1_105072_2022-02-24_final
2022-02-24 09:33:52	ga_ls7e_ard_3-2-1_105081_2022-02-24_final
2022-02-27 10:04:05	ga_ls7e_ard_3-2-1_110080_2022-02-27_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-03-03 09:36:59	ga_ls7e_ard_3-2-1_106075_2022-03-03_final
2022-03-04 08:41:40	ga_ls7e_ard_3-2-1_097076_2022-03-03_final
2022-03-04 08:44:03	ga_ls7e_ard_3-2-1_097082_2022-03-03_final
2022-03-05 09:25:13	ga_ls7e_ard_3-2-1_104077_2022-03-04_final
2022-03-08 08:17:21	ga_ls7e_ard_3-2-1_093078_2022-03-07_final
2022-03-08 08:19:44	ga_ls7e_ard_3-2-1_093084_2022-03-07_final
2022-03-09 09:02:06	ga_ls7e_ard_3-2-1_100082_2022-03-08_final
2022-03-10 08:05:59	ga_ls7e_ard_3-2-1_091081_2022-03-09_final
2022-03-11 08:43:57	ga_ls7e_ard_3-2-1_098068_2022-03-10_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-13 08:32:35	ga_ls7e_ard_3-2-1_096071_2022-03-12_final
2022-03-13 10:15:27	ga_ls7e_ard_3-2-1_112081_2022-03-13_final
2022-03-15 08:23:37	ga_ls7e_ard_3-2-1_094080_2022-03-14_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_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 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-20 08:40:04	ga_ls7e_ard_3-2-1_097076_2022-03-19_final
2022-03-20 08:40:28	ga_ls7e_ard_3-2-1_097077_2022-03-19_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-25 08:56:09	ga_ls7e_ard_3-2-1_100071_2022-03-24_final
2022-03-25 08:57:44	ga_ls7e_ard_3-2-1_100075_2022-03-24_final
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_final
2022-03-30 09:15:00	ga_ls7e_ard_3-2-1_103073_2022-03-29_final
2022-03-31 08:23:17	ga_ls7e_ard_3-2-1_094083_2022-03-30_final
2022-04-01 09:02:03	ga_ls7e_ard_3-2-1_101072_2022-03-31_final
2022-04-02 09:45:37	ga_ls7e_ard_3-2-1_108073_2022-04-02_final
2022-04-04 07:58:58	ga_ls7e_ard_3-2-1_090085_2022-04-03_final
2022-04-04 09:34:15	ga_ls7e_ard_3-2-1_106076_2022-04-04_final
2022-04-04 09:36:15	ga_ls7e_ard_3-2-1_106081_2022-04-04_final
2022-04-05 10:18:12	ga_ls7e_ard_3-2-1_113078_2022-04-05_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