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
2021-09-13 10:11:23	ga_ls7e_ard_3-2-0_109074_2021-09-13_final
2021-09-13 10:12:10	ga_ls7e_ard_3-2-0_109076_2021-09-13_final
2021-09-18 08:54:59	ga_ls7e_ard_3-2-0_096085_2021-09-17_final
2021-09-25 10:38:37	ga_ls7e_ard_3-2-0_113083_2021-09-25_final
2021-09-28 09:25:10	ga_ls7e_ard_3-2-0_102070_2021-09-27_final
2021-09-28 09:26:46	ga_ls7e_ard_3-2-0_102074_2021-09-27_final
2021-09-29 08:31:27	ga_ls7e_ard_3-2-0_093075_2021-09-28_final
2021-09-30 09:17:49	ga_ls7e_ard_3-2-0_100083_2021-09-29_final
2021-10-01 09:58:12	ga_ls7e_ard_3-2-0_107076_2021-10-01_final
2021-10-11 10:36:00	ga_ls7e_ard_3-2-0_113080_2021-10-11_final
2021-10-11 10:36:48	ga_ls7e_ard_3-2-0_113082_2021-10-11_final
2021-10-14 09:24:10	ga_ls7e_ard_3-2-0_102071_2021-10-13_final
2021-10-17 09:56:00	ga_ls7e_ard_3-2-0_107074_2021-10-17_final
2021-10-18 09:03:53	ga_ls7e_ard_3-2-0_098083_2021-10-17_final
2021-10-20 08:52:32	ga_ls7e_ard_3-2-0_096086_2021-10-19_final
2021-10-22 10:14:53	ga_ls7e_ard_3-2-0_110076_2021-10-22_final
2021-10-25 09:06:14	ga_ls7e_ard_3-2-0_099075_2021-10-24_final
2021-10-30 09:22:43	ga_ls7e_ard_3-2-0_102071_2021-10-29_final
2021-11-02 09:56:07	ga_ls7e_ard_3-2-0_107078_2021-11-02_final
2021-11-03 10:40:05	ga_ls7e_ard_3-2-0_114080_2021-11-03_final
2021-11-07 08:33:43	ga_ls7e_ard_3-2-0_094074_2021-11-06_final
2021-11-07 10:11:24	ga_ls7e_ard_3-2-0_110071_2021-11-07_final
2021-11-07 10:12:12	ga_ls7e_ard_3-2-0_110073_2021-11-07_final
2021-11-09 08:25:09	ga_ls7e_ard_3-2-0_092084_2021-11-08_final
2021-11-10 10:44:00	ga_ls7e_ard_3-2-0_115076_2021-11-10_final
2021-11-10 10:44:24	ga_ls7e_ard_3-2-0_115077_2021-11-10_final
2021-11-13 09:36:32	ga_ls7e_ard_3-2-1_104078_2021-11-13_final
2021-11-15 09:23:34	ga_ls7e_ard_3-2-1_102077_2021-11-14_final
2021-11-16 10:06:20	ga_ls7e_ard_3-2-1_109076_2021-11-16_final
2021-11-19 08:55:40	ga_ls7e_ard_3-2-1_098070_2021-11-18_final
2021-11-23 10:11:01	ga_ls7e_ard_3-2-1_110074_2021-11-23_final
2021-11-28 08:53:01	ga_ls7e_ard_3-2-1_097081_2021-11-27_final
2021-11-28 08:53:25	ga_ls7e_ard_3-2-1_097082_2021-11-27_final
2021-12-02 08:30:19	ga_ls7e_ard_3-2-1_093087_2021-12-01_final
2021-12-03 09:10:42	ga_ls7e_ard_3-2-1_100080_2021-12-02_final
2021-12-04 08:14:35	ga_ls7e_ard_3-2-1_091079_2021-12-03_final
2021-12-04 08:18:10	ga_ls7e_ard_3-2-1_091088_2021-12-03_final
2021-12-04 09:52:16	ga_ls7e_ard_3-2-1_107076_2021-12-04_final
2021-12-07 10:22:53	ga_ls7e_ard_3-2-1_112076_2021-12-07_final
2021-12-08 09:28:46	ga_ls7e_ard_3-2-1_103080_2021-12-07_final
2021-12-11 09:55:47	ga_ls7e_ard_3-2-1_108071_2021-12-11_final
2021-12-12 09:04:51	ga_ls7e_ard_3-2-1_099083_2021-12-11_final
2021-12-14 10:29:59	ga_ls7e_ard_3-2-1_113080_2021-12-14_final
2021-12-18 08:28:00	ga_ls7e_ard_3-2-1_093085_2021-12-17_final
2021-12-18 10:05:41	ga_ls7e_ard_3-2-1_109082_2021-12-18_final
2021-12-21 10:34:41	ga_ls7e_ard_3-2-1_114078_2021-12-21_final
2021-12-25 08:29:30	ga_ls7e_ard_3-2-1_094075_2021-12-24_final
2021-12-28 09:03:17	ga_ls7e_ard_3-2-1_099083_2021-12-27_final
2022-01-02 09:15:44	ga_ls7e_ard_3-2-1_102069_2022-01-01_final
2022-01-03 08:22:48	ga_ls7e_ard_3-2-1_093076_2022-01-02_final
2022-01-03 10:00:29	ga_ls7e_ard_3-2-1_109073_2022-01-03_final
2022-01-07 09:35:23	ga_ls7e_ard_3-2-1_105073_2022-01-07_final
2022-01-09 09:26:26	ga_ls7e_ard_3-2-1_103082_2022-01-08_final
2022-01-12 08:19:22	ga_ls7e_ard_3-2-1_092085_2022-01-11_final
2022-01-14 08:05:13	ga_ls7e_ard_3-2-1_090081_2022-01-13_final
2022-01-15 08:45:12	ga_ls7e_ard_3-2-1_097073_2022-01-14_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-15 10:25:16	ga_ls7e_ard_3-2-1_113076_2022-01-15_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-18 09:14:13	ga_ls7e_ard_3-2-1_102069_2022-01-17_final
2022-01-19 08:24:53	ga_ls7e_ard_3-2-1_093085_2022-01-18_final
2022-01-28 08:15:50	ga_ls7e_ard_3-2-1_092080_2022-01-27_final
2022-01-29 08:59:47	ga_ls7e_ard_3-2-1_099082_2022-01-28_final
2022-02-06 08:08:21	ga_ls7e_ard_3-2-1_091079_2022-02-05_final
2022-02-06 08:11:08	ga_ls7e_ard_3-2-1_091086_2022-02-05_final
2022-02-06 09:45:14	ga_ls7e_ard_3-2-1_107074_2022-02-06_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-07 10:29:35	ga_ls7e_ard_3-2-1_114077_2022-02-07_final
2022-02-11 08:27:10	ga_ls7e_ard_3-2-1_094081_2022-02-10_final
2022-02-13 09:50:17	ga_ls7e_ard_3-2-1_108073_2022-02-13_final
2022-02-14 08:58:57	ga_ls7e_ard_3-2-1_099084_2022-02-13_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-16 08:45:59	ga_ls7e_ard_3-2-1_097083_2022-02-15_final
2022-02-22 08:11:08	ga_ls7e_ard_3-2-1_091090_2022-02-21_final
2022-02-24 09:29:29	ga_ls7e_ard_3-2-1_105070_2022-02-23_final
2022-02-27 10:01:17	ga_ls7e_ard_3-2-1_110073_2022-02-27_final
2022-02-27 10:02:29	ga_ls7e_ard_3-2-1_110076_2022-02-27_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-02 10:32:18	ga_ls7e_ard_3-2-1_115074_2022-03-02_final
2022-03-03 08:00:06	ga_ls7e_ard_3-2-1_090080_2022-03-02_final
2022-03-04 10:20:08	ga_ls7e_ard_3-2-1_113075_2022-03-04_final
2022-03-08 09:55:49	ga_ls7e_ard_3-2-1_109077_2022-03-08_final
2022-03-08 09:57:25	ga_ls7e_ard_3-2-1_109081_2022-03-08_final
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-09 09:02:30	ga_ls7e_ard_3-2-1_100083_2022-03-08_final
2022-03-10 09:41:16	ga_ls7e_ard_3-2-1_107072_2022-03-10_final
2022-03-11 08:47:33	ga_ls7e_ard_3-2-1_098077_2022-03-10_final
2022-03-12 07:53:49	ga_ls7e_ard_3-2-1_089082_2022-03-11_final
2022-03-13 08:33:23	ga_ls7e_ard_3-2-1_096073_2022-03-12_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-20 08:40:52	ga_ls7e_ard_3-2-1_097078_2022-03-19_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-20 08:43:39	ga_ls7e_ard_3-2-1_097085_2022-03-19_final
2022-03-22 08:26:43	ga_ls7e_ard_3-2-1_095074_2022-03-21_final
2022-03-25 08:58:08	ga_ls7e_ard_3-2-1_100076_2022-03-24_final
2022-03-25 09:00:56	ga_ls7e_ard_3-2-1_100083_2022-03-24_final
2022-03-26 08:07:37	ga_ls7e_ard_3-2-1_091089_2022-03-25_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_2022-04-02_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