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
2021-09-05 09:24:14	ga_ls7e_ard_3-2-0_101078_2021-09-04_final
2021-09-06 08:30:32	ga_ls7e_ard_3-2-0_092083_2021-09-05_final
2021-09-07 09:10:54	ga_ls7e_ard_3-2-0_099076_2021-09-06_final
2021-09-09 08:57:10	ga_ls7e_ard_3-2-0_097073_2021-09-08_final
2021-09-09 08:57:34	ga_ls7e_ard_3-2-0_097074_2021-09-08_final
2021-09-26 09:38:07	ga_ls7e_ard_3-2-0_104071_2021-09-26_final
2021-09-27 08:48:47	ga_ls7e_ard_3-2-0_095087_2021-09-26_final
2021-10-03 08:08:23	ga_ls7e_ard_3-2-0_089080_2021-10-02_final
2021-10-04 08:48:22	ga_ls7e_ard_3-2-0_096072_2021-10-03_final
2021-10-04 08:51:10	ga_ls7e_ard_3-2-0_096079_2021-10-03_final
2021-10-05 09:32:20	ga_ls7e_ard_3-2-0_103074_2021-10-05_final
2021-10-07 09:22:36	ga_ls7e_ard_3-2-0_101081_2021-10-06_final
2021-10-08 08:25:42	ga_ls7e_ard_3-2-0_092078_2021-10-07_final
2021-10-09 09:08:04	ga_ls7e_ard_3-2-0_099076_2021-10-08_final
2021-10-12 09:38:42	ga_ls7e_ard_3-2-0_104076_2021-10-12_final
2021-10-12 09:39:30	ga_ls7e_ard_3-2-0_104078_2021-10-12_final
2021-10-13 10:21:52	ga_ls7e_ard_3-2-0_111076_2021-10-13_final
2021-10-13 10:24:16	ga_ls7e_ard_3-2-0_111082_2021-10-13_final
2021-10-15 08:32:03	ga_ls7e_ard_3-2-0_093080_2021-10-14_final
2021-10-17 09:58:47	ga_ls7e_ard_3-2-0_107081_2021-10-17_final
2021-10-19 08:08:10	ga_ls7e_ard_3-2-0_089083_2021-10-18_final
2021-10-20 08:49:44	ga_ls7e_ard_3-2-0_096079_2021-10-19_final
2021-10-20 08:52:08	ga_ls7e_ard_3-2-0_096085_2021-10-19_final
2021-10-21 09:34:06	ga_ls7e_ard_3-2-0_103082_2021-10-21_final
2021-10-22 08:36:00	ga_ls7e_ard_3-2-0_094076_2021-10-21_final
2021-10-24 08:25:03	ga_ls7e_ard_3-2-0_092080_2021-10-23_final
2021-10-28 09:37:39	ga_ls7e_ard_3-2-0_104077_2021-10-28_final
2021-10-29 10:21:13	ga_ls7e_ard_3-2-0_111078_2021-10-29_final
2021-10-31 08:29:00	ga_ls7e_ard_3-2-0_093076_2021-10-30_final
2021-11-02 09:53:44	ga_ls7e_ard_3-2-0_107072_2021-11-02_final
2021-11-03 08:59:13	ga_ls7e_ard_3-2-0_098075_2021-11-02_final
2021-11-07 08:34:31	ga_ls7e_ard_3-2-0_094076_2021-11-06_final
2021-11-09 08:23:33	ga_ls7e_ard_3-2-0_092080_2021-11-08_final
2021-11-10 09:03:55	ga_ls7e_ard_3-2-0_099073_2021-11-09_final
2021-11-14 10:20:29	ga_ls7e_ard_3-2-1_111080_2021-11-14_final
2021-11-14 10:21:41	ga_ls7e_ard_3-2-1_111083_2021-11-14_final
2021-11-16 10:07:08	ga_ls7e_ard_3-2-1_109078_2021-11-16_final
2021-11-19 08:57:40	ga_ls7e_ard_3-2-1_098075_2021-11-18_final
2021-11-22 09:26:40	ga_ls7e_ard_3-2-1_103071_2021-11-21_final
2021-11-22 09:28:40	ga_ls7e_ard_3-2-1_103076_2021-11-21_final
2021-11-25 09:56:29	ga_ls7e_ard_3-2-1_108069_2021-11-25_final
2021-11-28 08:53:49	ga_ls7e_ard_3-2-1_097083_2021-11-27_final
2021-11-30 08:40:28	ga_ls7e_ard_3-2-1_095081_2021-11-29_final
2021-11-30 10:19:21	ga_ls7e_ard_3-2-1_111081_2021-11-30_final
2021-12-03 09:10:18	ga_ls7e_ard_3-2-1_100079_2021-12-02_final
2021-12-12 09:01:40	ga_ls7e_ard_3-2-1_099075_2021-12-11_final
2021-12-14 08:48:43	ga_ls7e_ard_3-2-1_097074_2021-12-13_final
2021-12-16 08:40:33	ga_ls7e_ard_3-2-1_095085_2021-12-15_final
2021-12-17 09:20:07	ga_ls7e_ard_3-2-1_102076_2021-12-16_final
2021-12-18 08:26:00	ga_ls7e_ard_3-2-1_093080_2021-12-17_final
2021-12-18 10:04:05	ga_ls7e_ard_3-2-1_109078_2021-12-18_final
2021-12-19 09:06:46	ga_ls7e_ard_3-2-1_100074_2021-12-18_final
2021-12-23 10:21:44	ga_ls7e_ard_3-2-1_112077_2021-12-23_final
2021-12-25 08:32:18	ga_ls7e_ard_3-2-1_094082_2021-12-24_final
2022-01-05 09:51:31	ga_ls7e_ard_3-2-1_107082_2022-01-05_final
2022-01-07 09:38:34	ga_ls7e_ard_3-2-1_105081_2022-01-07_final
2022-01-08 10:20:56	ga_ls7e_ard_3-2-1_112079_2022-01-08_final
2022-01-12 08:16:58	ga_ls7e_ard_3-2-1_092079_2022-01-11_final
2022-01-13 08:58:56	ga_ls7e_ard_3-2-1_099076_2022-01-12_final
2022-01-19 10:00:34	ga_ls7e_ard_3-2-1_109077_2022-01-19_final
2022-01-19 10:02:10	ga_ls7e_ard_3-2-1_109081_2022-01-19_final
2022-01-21 08:14:20	ga_ls7e_ard_3-2-1_091090_2022-01-20_final
2022-01-31 10:24:31	ga_ls7e_ard_3-2-1_113078_2022-01-31_final
2022-02-04 09:58:59	ga_ls7e_ard_3-2-1_109077_2022-02-04_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-20 09:57:22	ga_ls7e_ard_3-2-1_109077_2022-02-20_final
2022-02-25 08:36:57	ga_ls7e_ard_3-2-1_096078_2022-02-24_final
2022-02-25 08:38:57	ga_ls7e_ard_3-2-1_096083_2022-02-24_final
2022-02-27 08:25:12	ga_ls7e_ard_3-2-1_094080_2022-02-26_final
2022-03-01 08:11:27	ga_ls7e_ard_3-2-1_092077_2022-02-28_final
2022-03-04 08:43:39	ga_ls7e_ard_3-2-1_097081_2022-03-03_final
2022-03-05 09:25:13	ga_ls7e_ard_3-2-1_104077_2022-03-04_final
2022-03-07 09:11:52	ga_ls7e_ard_3-2-1_102075_2022-03-06_final
2022-03-07 09:12:16	ga_ls7e_ard_3-2-1_102076_2022-03-06_final
2022-03-10 09:44:28	ga_ls7e_ard_3-2-1_107080_2022-03-10_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-13 08:32:59	ga_ls7e_ard_3-2-1_096072_2022-03-12_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 10:15:27	ga_ls7e_ard_3-2-1_112081_2022-03-13_final
2022-03-14 09:18:32	ga_ls7e_ard_3-2-1_103078_2022-03-13_final
2022-03-17 08:11:03	ga_ls7e_ard_3-2-1_092080_2022-03-16_final
2022-03-17 08:11:27	ga_ls7e_ard_3-2-1_092081_2022-03-16_final
2022-03-17 09:50:43	ga_ls7e_ard_3-2-1_108082_2022-03-17_final
2022-03-18 10:31:53	ga_ls7e_ard_3-2-1_115077_2022-03-18_final
2022-03-20 08:42:51	ga_ls7e_ard_3-2-1_097083_2022-03-19_final
2022-03-22 10:03:12	ga_ls7e_ard_3-2-1_111068_2022-03-22_final
2022-03-23 09:09:53	ga_ls7e_ard_3-2-1_102074_2022-03-22_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-24 08:14:58	ga_ls7e_ard_3-2-1_093076_2022-03-23_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-27 08:47:11	ga_ls7e_ard_3-2-1_098080_2022-03-26_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-04-02 08:09:56	ga_ls7e_ard_3-2-1_092081_2022-04-01_final
2022-04-03 08:49:54	ga_ls7e_ard_3-2-1_099073_2022-04-02_final
2022-04-04 07:58:58	ga_ls7e_ard_3-2-1_090085_2022-04-03_final
2022-04-04 09:34:39	ga_ls7e_ard_3-2-1_106077_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