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
2021-11-18 09:51:47	ga_ls7e_ard_3-2-1_107071_2021-11-18_final
2021-12-02 08:30:19	ga_ls7e_ard_3-2-1_093087_2021-12-01_final
2021-12-20 09:52:44	ga_ls7e_ard_3-2-1_107081_2021-12-20_final
2021-12-22 09:36:11	ga_ls7e_ard_3-2-1_105071_2021-12-22_final
2021-12-24 09:27:13	ga_ls7e_ard_3-2-1_103080_2021-12-23_final
2021-12-30 08:48:44	ga_ls7e_ard_3-2-1_097078_2021-12-29_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2022-01-03 08:26:00	ga_ls7e_ard_3-2-1_093084_2022-01-02_final
2022-01-03 10:03:17	ga_ls7e_ard_3-2-1_109080_2022-01-03_final
2022-01-05 08:15:26	ga_ls7e_ard_3-2-1_091089_2022-01-04_final
2022-01-06 08:52:37	ga_ls7e_ard_3-2-1_098074_2022-01-05_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-08 10:22:08	ga_ls7e_ard_3-2-1_112082_2022-01-08_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-12 09:51:52	ga_ls7e_ard_3-2-1_108069_2022-01-12_final
2022-01-12 09:55:51	ga_ls7e_ard_3-2-1_108079_2022-01-12_final
2022-01-13 08:58:32	ga_ls7e_ard_3-2-1_099075_2022-01-12_final
2022-01-13 09:01:44	ga_ls7e_ard_3-2-1_099083_2022-01-12_final
2022-01-14 08:04:25	ga_ls7e_ard_3-2-1_090079_2022-01-13_final
2022-01-14 08:04:49	ga_ls7e_ard_3-2-1_090080_2022-01-13_final
2022-01-14 09:42:06	ga_ls7e_ard_3-2-1_106076_2022-01-14_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-15 10:25:16	ga_ls7e_ard_3-2-1_113076_2022-01-15_final
2022-01-17 08:37:26	ga_ls7e_ard_3-2-1_095085_2022-01-16_final
2022-01-17 08:37:50	ga_ls7e_ard_3-2-1_095086_2022-01-16_final
2022-01-19 08:20:54	ga_ls7e_ard_3-2-1_093075_2022-01-18_final
2022-01-21 09:46:01	ga_ls7e_ard_3-2-1_107072_2022-01-21_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-24 10:18:13	ga_ls7e_ard_3-2-1_112076_2022-01-24_final
2022-01-29 08:57:00	ga_ls7e_ard_3-2-1_099075_2022-01-28_final
2022-01-29 10:35:28	ga_ls7e_ard_3-2-1_115074_2022-01-29_final
2022-01-30 09:41:21	ga_ls7e_ard_3-2-1_106078_2022-01-30_final
2022-01-31 10:23:19	ga_ls7e_ard_3-2-1_113075_2022-01-31_final
2022-02-01 09:29:59	ga_ls7e_ard_3-2-1_104081_2022-01-31_final
2022-02-02 10:11:33	ga_ls7e_ard_3-2-1_111077_2022-02-02_final
2022-02-03 09:16:14	ga_ls7e_ard_3-2-1_102078_2022-02-02_final
2022-02-06 09:45:14	ga_ls7e_ard_3-2-1_107074_2022-02-06_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-10 09:18:54	ga_ls7e_ard_3-2-1_103071_2022-02-09_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-12 09:07:08	ga_ls7e_ard_3-2-1_101073_2022-02-11_final
2022-02-12 09:10:43	ga_ls7e_ard_3-2-1_101082_2022-02-11_final
2022-02-13 09:51:29	ga_ls7e_ard_3-2-1_108076_2022-02-13_final
2022-02-14 08:58:33	ga_ls7e_ard_3-2-1_099083_2022-02-13_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-15 09:38:54	ga_ls7e_ard_3-2-1_106076_2022-02-15_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-17 09:25:09	ga_ls7e_ard_3-2-1_104073_2022-02-16_final
2022-02-17 09:25:33	ga_ls7e_ard_3-2-1_104074_2022-02-16_final
2022-02-17 09:26:45	ga_ls7e_ard_3-2-1_104077_2022-02-16_final
2022-02-18 10:08:43	ga_ls7e_ard_3-2-1_111074_2022-02-18_final
2022-02-18 10:09:31	ga_ls7e_ard_3-2-1_111076_2022-02-18_final
2022-02-19 09:10:37	ga_ls7e_ard_3-2-1_102068_2022-02-18_final
2022-02-19 09:14:36	ga_ls7e_ard_3-2-1_102078_2022-02-18_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-23 08:47:55	ga_ls7e_ard_3-2-1_098074_2022-02-22_final
2022-02-23 08:48:19	ga_ls7e_ard_3-2-1_098075_2022-02-22_final
2022-02-23 08:50:42	ga_ls7e_ard_3-2-1_098081_2022-02-22_final
2022-02-23 08:52:18	ga_ls7e_ard_3-2-1_098085_2022-02-22_final
2022-02-24 09:30:40	ga_ls7e_ard_3-2-1_105073_2022-02-24_final
2022-02-24 09:33:52	ga_ls7e_ard_3-2-1_105081_2022-02-24_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-02-28 09:09:10	ga_ls7e_ard_3-2-1_101082_2022-02-27_final
2022-03-06 08:32:18	ga_ls7e_ard_3-2-1_095084_2022-03-05_final
2022-03-07 09:09:28	ga_ls7e_ard_3-2-1_102069_2022-03-06_final
2022-03-09 08:59:18	ga_ls7e_ard_3-2-1_100075_2022-03-08_final
2022-03-10 08:05:59	ga_ls7e_ard_3-2-1_091081_2022-03-09_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-11 08:45:57	ga_ls7e_ard_3-2-1_098073_2022-03-10_final
2022-03-11 08:49:08	ga_ls7e_ard_3-2-1_098081_2022-03-10_final
2022-03-11 10:25:13	ga_ls7e_ard_3-2-1_114074_2022-03-11_final
2022-03-12 07:54:37	ga_ls7e_ard_3-2-1_089084_2022-03-11_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-12 09:32:42	ga_ls7e_ard_3-2-1_105082_2022-03-12_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-17 08:09:27	ga_ls7e_ard_3-2-1_092076_2022-03-16_final
2022-03-17 08:11:51	ga_ls7e_ard_3-2-1_092082_2022-03-16_final
2022-03-17 09:46:20	ga_ls7e_ard_3-2-1_108071_2022-03-17_final
2022-03-18 08:55:24	ga_ls7e_ard_3-2-1_099083_2022-03-17_final
2022-03-19 07:59:17	ga_ls7e_ard_3-2-1_090082_2022-03-18_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-20 08:38:28	ga_ls7e_ard_3-2-1_097072_2022-03-19_final
2022-03-20 08:42:04	ga_ls7e_ard_3-2-1_097081_2022-03-19_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-24 08:18:10	ga_ls7e_ard_3-2-1_093084_2022-03-23_final
2022-03-26 08:05:13	ga_ls7e_ard_3-2-1_091083_2022-03-25_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-27 10:26:28	ga_ls7e_ard_3-2-1_114081_2022-03-27_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-31 08:19:17	ga_ls7e_ard_3-2-1_094073_2022-03-30_final
2022-03-31 09:58:10	ga_ls7e_ard_3-2-1_110073_2022-03-31_final
2022-04-01 09:02:27	ga_ls7e_ard_3-2-1_101073_2022-03-31_final
2022-04-02 09:49:36	ga_ls7e_ard_3-2-1_108083_2022-04-02_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_2022-04-03_final
2022-04-04 07:58:10	ga_ls7e_ard_3-2-1_090083_2022-04-03_final
2022-04-05 08:36:56	ga_ls7e_ard_3-2-1_097072_2022-04-04_final
2022-04-05 10:17:24	ga_ls7e_ard_3-2-1_113076_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years