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
2021-09-20 08:41:39	ga_ls7e_ard_3-2-0_094083_2021-09-19_final
2021-09-20 10:16:32	ga_ls7e_ard_3-2-0_110073_2021-09-20_final
2021-09-20 10:19:43	ga_ls7e_ard_3-2-0_110081_2021-09-20_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-26 09:47:24	ga_ls7e_ard_3-2-0_106070_2021-10-26_final
2021-11-02 08:19:14	ga_ls7e_ard_3-2-0_091083_2021-11-01_final
2021-11-02 09:57:43	ga_ls7e_ard_3-2-0_107082_2021-11-02_final
2021-11-03 08:59:37	ga_ls7e_ard_3-2-0_098076_2021-11-02_final
2021-11-03 09:01:12	ga_ls7e_ard_3-2-0_098080_2021-11-02_final
2021-11-07 08:33:43	ga_ls7e_ard_3-2-0_094074_2021-11-06_final
2021-11-07 08:35:19	ga_ls7e_ard_3-2-0_094078_2021-11-06_final
2021-11-11 09:46:17	ga_ls7e_ard_3-2-0_106071_2021-11-11_final
2021-11-12 10:32:15	ga_ls7e_ard_3-2-1_113078_2021-11-12_final
2021-11-19 08:57:40	ga_ls7e_ard_3-2-1_098075_2021-11-18_final
2021-11-23 08:33:21	ga_ls7e_ard_3-2-1_094077_2021-11-22_final
2021-11-23 10:10:38	ga_ls7e_ard_3-2-1_110073_2021-11-23_final
2021-11-25 09:57:17	ga_ls7e_ard_3-2-1_108071_2021-11-25_final
2021-11-25 10:00:52	ga_ls7e_ard_3-2-1_108080_2021-11-25_final
2021-11-29 09:31:24	ga_ls7e_ard_3-2-1_104069_2021-11-29_final
2021-12-03 09:07:06	ga_ls7e_ard_3-2-1_100071_2021-12-02_final
2021-12-05 08:55:21	ga_ls7e_ard_3-2-1_098073_2021-12-04_final
2021-12-08 09:24:46	ga_ls7e_ard_3-2-1_103070_2021-12-07_final
2021-12-11 08:21:42	ga_ls7e_ard_3-2-1_092083_2021-12-10_final
2021-12-11 09:56:59	ga_ls7e_ard_3-2-1_108074_2021-12-11_final
2021-12-13 09:47:13	ga_ls7e_ard_3-2-1_106081_2021-12-13_final
2021-12-14 08:51:07	ga_ls7e_ard_3-2-1_097080_2021-12-13_final
2021-12-17 09:18:32	ga_ls7e_ard_3-2-1_102072_2021-12-16_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-22 09:38:58	ga_ls7e_ard_3-2-1_105078_2021-12-22_final
2021-12-23 10:21:20	ga_ls7e_ard_3-2-1_112076_2021-12-23_final
2021-12-25 10:11:34	ga_ls7e_ard_3-2-1_110083_2021-12-25_final
2021-12-26 09:12:40	ga_ls7e_ard_3-2-1_101075_2021-12-25_final
2021-12-27 09:58:37	ga_ls7e_ard_3-2-1_108082_2021-12-27_final
2021-12-28 09:00:30	ga_ls7e_ard_3-2-1_099076_2021-12-27_final
2021-12-28 10:39:46	ga_ls7e_ard_3-2-1_115077_2021-12-28_final
2021-12-29 09:41:40	ga_ls7e_ard_3-2-1_106071_2021-12-29_final
2021-12-29 09:44:27	ga_ls7e_ard_3-2-1_106078_2021-12-29_final
2021-12-30 08:46:44	ga_ls7e_ard_3-2-1_097073_2021-12-29_final
2021-12-30 08:47:32	ga_ls7e_ard_3-2-1_097075_2021-12-29_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-01 08:38:10	ga_ls7e_ard_3-2-1_095083_2021-12-31_final
2022-01-03 09:59:17	ga_ls7e_ard_3-2-1_109070_2022-01-03_final
2022-01-05 09:47:55	ga_ls7e_ard_3-2-1_107073_2022-01-05_final
2022-01-05 09:51:07	ga_ls7e_ard_3-2-1_107081_2022-01-05_final
2022-01-10 08:29:55	ga_ls7e_ard_3-2-1_094080_2022-01-09_final
2022-01-12 08:17:46	ga_ls7e_ard_3-2-1_092081_2022-01-11_final
2022-01-12 08:18:10	ga_ls7e_ard_3-2-1_092082_2022-01-11_final
2022-01-13 10:37:49	ga_ls7e_ard_3-2-1_115076_2022-01-13_final
2022-01-14 09:43:42	ga_ls7e_ard_3-2-1_106080_2022-01-14_final
2022-01-14 09:44:06	ga_ls7e_ard_3-2-1_106081_2022-01-14_final
2022-01-15 08:48:23	ga_ls7e_ard_3-2-1_097081_2022-01-14_final
2022-01-15 10:26:28	ga_ls7e_ard_3-2-1_113079_2022-01-15_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-21 08:10:44	ga_ls7e_ard_3-2-1_091081_2022-01-20_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-27 09:11:09	ga_ls7e_ard_3-2-1_101079_2022-01-26_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-02-02 08:31:53	ga_ls7e_ard_3-2-1_095075_2022-02-01_final
2022-02-02 10:13:09	ga_ls7e_ard_3-2-1_111081_2022-02-02_final
2022-02-04 10:01:23	ga_ls7e_ard_3-2-1_109083_2022-02-04_final
2022-02-05 09:02:28	ga_ls7e_ard_3-2-1_100075_2022-02-04_final
2022-02-05 09:05:16	ga_ls7e_ard_3-2-1_100082_2022-02-04_final
2022-02-07 10:29:59	ga_ls7e_ard_3-2-1_114078_2022-02-07_final
2022-02-08 09:35:27	ga_ls7e_ard_3-2-1_105081_2022-02-08_final
2022-02-11 08:24:46	ga_ls7e_ard_3-2-1_094075_2022-02-10_final
2022-02-11 08:28:22	ga_ls7e_ard_3-2-1_094084_2022-02-10_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-12 09:09:31	ga_ls7e_ard_3-2-1_101079_2022-02-11_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-17 09:25:57	ga_ls7e_ard_3-2-1_104075_2022-02-16_final
2022-02-20 08:22:29	ga_ls7e_ard_3-2-1_093087_2022-02-19_final
2022-02-23 08:48:19	ga_ls7e_ard_3-2-1_098075_2022-02-22_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-27 10:04:53	ga_ls7e_ard_3-2-1_110082_2022-02-27_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-02-28 09:07:58	ga_ls7e_ard_3-2-1_101079_2022-02-27_final
2022-03-04 10:20:56	ga_ls7e_ard_3-2-1_113077_2022-03-04_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-06 08:28:42	ga_ls7e_ard_3-2-1_095075_2022-03-05_final
2022-03-06 10:07:11	ga_ls7e_ard_3-2-1_111074_2022-03-06_final
2022-03-08 08:16:09	ga_ls7e_ard_3-2-1_093075_2022-03-07_final
2022-03-08 08:18:09	ga_ls7e_ard_3-2-1_093080_2022-03-07_final
2022-03-08 08:18:33	ga_ls7e_ard_3-2-1_093081_2022-03-07_final
2022-03-10 08:07:59	ga_ls7e_ard_3-2-1_091086_2022-03-09_final
2022-03-10 08:08:47	ga_ls7e_ard_3-2-1_091088_2022-03-09_final
2022-03-11 08:47:57	ga_ls7e_ard_3-2-1_098078_2022-03-10_final
2022-03-11 10:26:25	ga_ls7e_ard_3-2-1_114077_2022-03-11_final
2022-03-12 07:51:49	ga_ls7e_ard_3-2-1_089077_2022-03-11_final
2022-03-13 10:15:27	ga_ls7e_ard_3-2-1_112081_2022-03-13_final
2022-03-15 10:00:06	ga_ls7e_ard_3-2-1_110074_2022-03-15_final
2022-03-18 08:52:12	ga_ls7e_ard_3-2-1_099075_2022-03-17_final
2022-03-20 08:40:04	ga_ls7e_ard_3-2-1_097076_2022-03-19_final
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-24 08:14:34	ga_ls7e_ard_3-2-1_093075_2022-03-23_final
2022-03-27 08:47:35	ga_ls7e_ard_3-2-1_098081_2022-03-26_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-04-02 08:10:20	ga_ls7e_ard_3-2-1_092082_2022-04-01_final
2022-04-05 08:40:55	ga_ls7e_ard_3-2-1_097082_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years