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:

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First 100 results (query limit)

Time (local)	Label
2021-09-20 10:14:08	ga_ls7e_ard_3-2-0_110067_2021-09-20_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-09-24 09:54:15	ga_ls7e_ard_3-2-0_106080_2021-09-24_final
2021-09-29 10:09:32	ga_ls7e_ard_3-2-0_109073_2021-09-29_final
2021-09-29 10:13:08	ga_ls7e_ard_3-2-0_109082_2021-09-29_final
2021-10-09 09:10:52	ga_ls7e_ard_3-2-0_099083_2021-10-08_final
2021-10-10 08:14:45	ga_ls7e_ard_3-2-0_090082_2021-10-09_final
2021-10-14 09:24:34	ga_ls7e_ard_3-2-0_102072_2021-10-13_final
2021-10-17 08:19:31	ga_ls7e_ard_3-2-0_091080_2021-10-16_final
2021-10-17 09:57:11	ga_ls7e_ard_3-2-0_107077_2021-10-17_final
2021-10-17 09:59:59	ga_ls7e_ard_3-2-0_107084_2021-10-17_final
2021-10-22 08:39:12	ga_ls7e_ard_3-2-0_094084_2021-10-21_final
2021-10-24 09:59:33	ga_ls7e_ard_3-2-0_108069_2021-10-24_final
2021-10-24 10:05:32	ga_ls7e_ard_3-2-0_108084_2021-10-24_final
2021-10-27 08:54:53	ga_ls7e_ard_3-2-0_097078_2021-10-26_final
2021-10-31 10:05:29	ga_ls7e_ard_3-2-0_109070_2021-10-31_final
2021-11-02 08:19:14	ga_ls7e_ard_3-2-0_091083_2021-11-01_final
2021-11-02 09:55:19	ga_ls7e_ard_3-2-0_107076_2021-11-02_final
2021-11-05 08:48:16	ga_ls7e_ard_3-2-0_096079_2021-11-04_final
2021-11-07 08:35:19	ga_ls7e_ard_3-2-0_094078_2021-11-06_final
2021-11-07 10:14:11	ga_ls7e_ard_3-2-0_110078_2021-11-07_final
2021-11-09 08:24:45	ga_ls7e_ard_3-2-0_092083_2021-11-08_final
2021-11-12 10:32:39	ga_ls7e_ard_3-2-1_113079_2021-11-12_final
2021-11-14 08:42:00	ga_ls7e_ard_3-2-1_095081_2021-11-13_final
2021-11-16 10:07:56	ga_ls7e_ard_3-2-1_109080_2021-11-16_final
2021-11-17 09:10:37	ga_ls7e_ard_3-2-1_100076_2021-11-16_final
2021-11-19 10:37:44	ga_ls7e_ard_3-2-1_114078_2021-11-19_final
2021-11-19 10:38:08	ga_ls7e_ard_3-2-1_114079_2021-11-19_final
2021-11-26 10:42:51	ga_ls7e_ard_3-2-1_115077_2021-11-26_final
2021-11-28 08:51:25	ga_ls7e_ard_3-2-1_097077_2021-11-27_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-29 09:31:24	ga_ls7e_ard_3-2-1_104069_2021-11-29_final
2021-12-02 10:02:25	ga_ls7e_ard_3-2-1_109070_2021-12-02_final
2021-12-02 10:03:13	ga_ls7e_ard_3-2-1_109072_2021-12-02_final
2021-12-05 10:36:37	ga_ls7e_ard_3-2-1_114079_2021-12-05_final
2021-12-06 09:37:43	ga_ls7e_ard_3-2-1_105071_2021-12-06_final
2021-12-09 08:33:27	ga_ls7e_ard_3-2-1_094081_2021-12-08_final
2021-12-10 09:13:25	ga_ls7e_ard_3-2-1_101073_2021-12-09_final
2021-12-11 08:20:54	ga_ls7e_ard_3-2-1_092081_2021-12-10_final
2021-12-11 09:58:59	ga_ls7e_ard_3-2-1_108079_2021-12-11_final
2021-12-14 08:52:18	ga_ls7e_ard_3-2-1_097083_2021-12-13_final
2021-12-14 10:30:23	ga_ls7e_ard_3-2-1_113081_2021-12-14_final
2021-12-18 08:26:24	ga_ls7e_ard_3-2-1_093081_2021-12-17_final
2021-12-20 08:13:51	ga_ls7e_ard_3-2-1_091081_2021-12-19_final
2021-12-25 08:32:42	ga_ls7e_ard_3-2-1_094083_2021-12-24_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2022-01-03 10:03:41	ga_ls7e_ard_3-2-1_109081_2022-01-03_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-08 10:21:44	ga_ls7e_ard_3-2-1_112081_2022-01-08_final
2022-01-10 10:09:36	ga_ls7e_ard_3-2-1_110082_2022-01-10_final
2022-01-14 08:04:01	ga_ls7e_ard_3-2-1_090078_2022-01-13_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-15 10:27:40	ga_ls7e_ard_3-2-1_113082_2022-01-15_final
2022-01-20 09:06:03	ga_ls7e_ard_3-2-1_100080_2022-01-19_final
2022-01-21 08:13:56	ga_ls7e_ard_3-2-1_091089_2022-01-20_final
2022-01-24 10:17:49	ga_ls7e_ard_3-2-1_112075_2022-01-24_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-28 08:18:13	ga_ls7e_ard_3-2-1_092086_2022-01-27_final
2022-02-02 10:07:58	ga_ls7e_ard_3-2-1_111068_2022-02-02_final
2022-02-04 08:21:19	ga_ls7e_ard_3-2-1_093080_2022-02-03_final
2022-02-06 08:09:09	ga_ls7e_ard_3-2-1_091081_2022-02-05_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-10 09:18:54	ga_ls7e_ard_3-2-1_103071_2022-02-09_final
2022-02-10 09:20:06	ga_ls7e_ard_3-2-1_103074_2022-02-09_final
2022-02-11 10:05:39	ga_ls7e_ard_3-2-1_110080_2022-02-11_final
2022-02-12 09:07:32	ga_ls7e_ard_3-2-1_101074_2022-02-11_final
2022-02-12 09:07:56	ga_ls7e_ard_3-2-1_101075_2022-02-11_final
2022-02-13 09:54:40	ga_ls7e_ard_3-2-1_108084_2022-02-13_final
2022-02-16 08:42:23	ga_ls7e_ard_3-2-1_097074_2022-02-15_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-17 09:24:45	ga_ls7e_ard_3-2-1_104072_2022-02-16_final
2022-02-18 08:33:26	ga_ls7e_ard_3-2-1_095083_2022-02-17_final
2022-02-21 09:00:04	ga_ls7e_ard_3-2-1_100073_2022-02-20_final
2022-02-22 08:10:44	ga_ls7e_ard_3-2-1_091089_2022-02-21_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-23 10:27:11	ga_ls7e_ard_3-2-1_114075_2022-02-23_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_final
2022-02-27 10:04:29	ga_ls7e_ard_3-2-1_110081_2022-02-27_final
2022-02-28 09:05:10	ga_ls7e_ard_3-2-1_101072_2022-02-27_final
2022-02-28 09:07:10	ga_ls7e_ard_3-2-1_101077_2022-02-27_final
2022-03-01 08:12:15	ga_ls7e_ard_3-2-1_092079_2022-02-28_final
2022-03-02 10:33:30	ga_ls7e_ard_3-2-1_115077_2022-03-02_final
2022-03-03 08:01:18	ga_ls7e_ard_3-2-1_090083_2022-03-02_final
2022-03-06 08:32:42	ga_ls7e_ard_3-2-1_095085_2022-03-05_final
2022-03-07 09:12:40	ga_ls7e_ard_3-2-1_102077_2022-03-06_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-10 08:06:23	ga_ls7e_ard_3-2-1_091082_2022-03-09_final
2022-03-10 08:09:11	ga_ls7e_ard_3-2-1_091089_2022-03-09_final
2022-03-11 08:48:21	ga_ls7e_ard_3-2-1_098079_2022-03-10_final
2022-03-11 10:26:25	ga_ls7e_ard_3-2-1_114077_2022-03-11_final
2022-03-15 10:01:18	ga_ls7e_ard_3-2-1_110077_2022-03-15_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
2022-03-20 08:41:40	ga_ls7e_ard_3-2-1_097080_2022-03-19_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-24 09:55:51	ga_ls7e_ard_3-2-1_109081_2022-03-24_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_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