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
2021-07-04 10:12:10	ga_ls7e_ard_3-2-0_108076_2021-07-04_final
2021-07-06 09:58:03	ga_ls7e_ard_3-2-0_106072_2021-07-06_final
2021-07-13 10:05:14	ga_ls7e_ard_3-2-0_107076_2021-07-13_final
2021-07-15 08:17:49	ga_ls7e_ard_3-2-0_089086_2021-07-14_final
2021-07-15 09:53:06	ga_ls7e_ard_3-2-0_105077_2021-07-15_final
2021-07-16 10:35:04	ga_ls7e_ard_3-2-0_112074_2021-07-16_final
2021-07-20 10:09:37	ga_ls7e_ard_3-2-0_108073_2021-07-20_final
2021-07-23 10:42:15	ga_ls7e_ard_3-2-0_113078_2021-07-23_final
2021-07-24 09:44:09	ga_ls7e_ard_3-2-0_104072_2021-07-24_final
2021-07-24 09:46:56	ga_ls7e_ard_3-2-0_104079_2021-07-24_final
2021-07-25 10:28:07	ga_ls7e_ard_3-2-0_111074_2021-07-25_final
2021-07-27 08:42:18	ga_ls7e_ard_3-2-0_093088_2021-07-26_final
2021-08-06 09:15:18	ga_ls7e_ard_3-2-0_099080_2021-08-05_final
2021-08-06 10:51:47	ga_ls7e_ard_3-2-0_115074_2021-08-06_final
2021-08-06 10:53:47	ga_ls7e_ard_3-2-0_115079_2021-08-06_final
2021-08-17 10:33:03	ga_ls7e_ard_3-2-0_112076_2021-08-17_final
2021-08-19 10:20:07	ga_ls7e_ard_3-2-0_110075_2021-08-19_final
2021-08-24 08:58:58	ga_ls7e_ard_3-2-0_097074_2021-08-23_final
2021-08-31 10:44:37	ga_ls7e_ard_3-2-0_114077_2021-08-31_final
2021-09-03 09:35:10	ga_ls7e_ard_3-2-0_103074_2021-09-03_final
2021-09-07 10:48:59	ga_ls7e_ard_3-2-0_115074_2021-09-07_final
2021-09-11 10:26:18	ga_ls7e_ard_3-2-0_111080_2021-09-11_final
2021-09-15 10:00:02	ga_ls7e_ard_3-2-0_107077_2021-09-15_final
2021-09-18 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-21 09:20:01	ga_ls7e_ard_3-2-0_101071_2021-09-20_final
2021-09-21 09:22:25	ga_ls7e_ard_3-2-0_101077_2021-09-20_final
2021-09-25 08:55:45	ga_ls7e_ard_3-2-0_097073_2021-09-24_final
2021-09-26 09:37:43	ga_ls7e_ard_3-2-0_104070_2021-09-26_final
2021-09-27 10:21:41	ga_ls7e_ard_3-2-0_111072_2021-09-27_final
2021-09-27 10:24:52	ga_ls7e_ard_3-2-0_111080_2021-09-27_final
2021-10-01 09:56:36	ga_ls7e_ard_3-2-0_107072_2021-10-01_final
2021-10-02 09:05:17	ga_ls7e_ard_3-2-0_098083_2021-10-01_final
2021-10-04 08:51:34	ga_ls7e_ard_3-2-0_096080_2021-10-03_final
2021-10-04 10:28:51	ga_ls7e_ard_3-2-0_112076_2021-10-04_final
2021-10-05 09:33:32	ga_ls7e_ard_3-2-0_103077_2021-10-05_final
2021-10-06 10:15:31	ga_ls7e_ard_3-2-0_110074_2021-10-06_final
2021-10-20 10:27:25	ga_ls7e_ard_3-2-0_112076_2021-10-20_final
2021-10-21 09:30:31	ga_ls7e_ard_3-2-0_103073_2021-10-21_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-26 09:48:36	ga_ls7e_ard_3-2-0_106073_2021-10-26_final
2021-10-27 10:32:58	ga_ls7e_ard_3-2-0_113076_2021-10-27_final
2021-11-01 09:14:09	ga_ls7e_ard_3-2-0_100081_2021-10-31_final
2021-11-04 08:05:54	ga_ls7e_ard_3-2-0_089081_2021-11-03_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-10 09:04:43	ga_ls7e_ard_3-2-0_099075_2021-11-09_final
2021-11-10 10:43:36	ga_ls7e_ard_3-2-0_115075_2021-11-10_final
2021-11-11 09:45:53	ga_ls7e_ard_3-2-0_106070_2021-11-11_final
2021-11-11 09:48:17	ga_ls7e_ard_3-2-0_106076_2021-11-11_final
2021-11-12 08:52:34	ga_ls7e_ard_3-2-0_097076_2021-11-11_final
2021-11-15 09:21:35	ga_ls7e_ard_3-2-1_102072_2021-11-14_final
2021-11-22 09:29:28	ga_ls7e_ard_3-2-1_103078_2021-11-21_final
2021-11-28 10:29:30	ga_ls7e_ard_3-2-1_113075_2021-11-28_final
2021-12-03 09:07:06	ga_ls7e_ard_3-2-1_100071_2021-12-02_final
2021-12-07 08:43:12	ga_ls7e_ard_3-2-1_096074_2021-12-06_final
2021-12-07 10:25:16	ga_ls7e_ard_3-2-1_112082_2021-12-07_final
2021-12-09 10:11:55	ga_ls7e_ard_3-2-1_110080_2021-12-09_final
2021-12-13 09:44:26	ga_ls7e_ard_3-2-1_106074_2021-12-13_final
2021-12-14 08:48:43	ga_ls7e_ard_3-2-1_097074_2021-12-13_final
2021-12-17 09:21:43	ga_ls7e_ard_3-2-1_102080_2021-12-16_final
2021-12-22 09:39:46	ga_ls7e_ard_3-2-1_105080_2021-12-22_final
2021-12-25 08:33:30	ga_ls7e_ard_3-2-1_094085_2021-12-24_final
2021-12-30 10:28:48	ga_ls7e_ard_3-2-1_113081_2021-12-30_final
2022-01-03 10:04:53	ga_ls7e_ard_3-2-1_109084_2022-01-03_final
2022-01-09 09:20:50	ga_ls7e_ard_3-2-1_103068_2022-01-08_final
2022-01-09 09:22:26	ga_ls7e_ard_3-2-1_103072_2022-01-08_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-12 09:57:03	ga_ls7e_ard_3-2-1_108082_2022-01-12_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-17 08:32:15	ga_ls7e_ard_3-2-1_095072_2022-01-16_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-28 09:50:43	ga_ls7e_ard_3-2-1_108070_2022-01-28_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-02-02 10:13:57	ga_ls7e_ard_3-2-1_111083_2022-02-02_final
2022-02-07 08:53:06	ga_ls7e_ard_3-2-1_098083_2022-02-06_final
2022-02-08 09:35:27	ga_ls7e_ard_3-2-1_105081_2022-02-08_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-12 09:08:43	ga_ls7e_ard_3-2-1_101077_2022-02-11_final
2022-02-15 09:37:43	ga_ls7e_ard_3-2-1_106073_2022-02-15_final
2022-02-17 09:27:09	ga_ls7e_ard_3-2-1_104078_2022-02-16_final
2022-02-23 08:48:42	ga_ls7e_ard_3-2-1_098076_2022-02-22_final
2022-02-25 10:17:50	ga_ls7e_ard_3-2-1_112083_2022-02-25_final
2022-02-26 09:21:43	ga_ls7e_ard_3-2-1_103082_2022-02-25_final
2022-03-03 09:36:35	ga_ls7e_ard_3-2-1_106074_2022-03-03_final
2022-03-05 09:23:37	ga_ls7e_ard_3-2-1_104073_2022-03-04_final
2022-03-09 09:00:30	ga_ls7e_ard_3-2-1_100078_2022-03-08_final
2022-03-13 08:33:47	ga_ls7e_ard_3-2-1_096074_2022-03-12_final
2022-03-15 10:00:06	ga_ls7e_ard_3-2-1_110074_2022-03-15_final
2022-03-20 08:39:16	ga_ls7e_ard_3-2-1_097074_2022-03-19_final
2022-03-22 08:27:07	ga_ls7e_ard_3-2-1_095075_2022-03-21_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-27 10:24:52	ga_ls7e_ard_3-2-1_114077_2022-03-27_final
2022-03-28 09:28:21	ga_ls7e_ard_3-2-1_105075_2022-03-27_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_2022-04-02_final
2022-04-04 09:33:51	ga_ls7e_ard_3-2-1_106075_2022-04-04_final
2022-04-05 10:19:24	ga_ls7e_ard_3-2-1_113081_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