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
2021-05-23 09:35:24	ga_ls7e_ard_3-2-0_102068_2021-05-23_final
2021-05-25 09:24:04	ga_ls7e_ard_3-2-0_100071_2021-05-24_final
2021-05-27 09:14:19	ga_ls7e_ard_3-2-0_098078_2021-05-26_final
2021-06-02 10:18:00	ga_ls7e_ard_3-2-0_108084_2021-06-02_final
2021-06-03 09:18:18	ga_ls7e_ard_3-2-0_099074_2021-06-02_final
2021-06-06 09:48:34	ga_ls7e_ard_3-2-0_104073_2021-06-06_final
2021-06-06 09:52:09	ga_ls7e_ard_3-2-0_104082_2021-06-06_final
2021-06-13 09:54:59	ga_ls7e_ard_3-2-0_105075_2021-06-13_final
2021-06-16 10:29:13	ga_ls7e_ard_3-2-0_110084_2021-06-16_final
2021-06-23 10:29:38	ga_ls7e_ard_3-2-0_111071_2021-06-23_final
2021-06-28 10:48:58	ga_ls7e_ard_3-2-0_114074_2021-06-28_final
2021-06-30 08:59:33	ga_ls7e_ard_3-2-0_096079_2021-06-29_final
2021-06-30 10:39:37	ga_ls7e_ard_3-2-0_112082_2021-06-30_final
2021-07-05 10:54:33	ga_ls7e_ard_3-2-0_115074_2021-07-05_final
2021-07-13 08:29:57	ga_ls7e_ard_3-2-0_091085_2021-07-12_final
2021-07-19 09:28:02	ga_ls7e_ard_3-2-0_101077_2021-07-18_final
2021-07-23 08:59:47	ga_ls7e_ard_3-2-0_097069_2021-07-22_final
2021-07-29 08:28:58	ga_ls7e_ard_3-2-0_091086_2021-07-28_final
2021-08-04 09:29:02	ga_ls7e_ard_3-2-0_101083_2021-08-03_final
2021-08-06 09:14:54	ga_ls7e_ard_3-2-0_099079_2021-08-05_final
2021-08-11 09:30:36	ga_ls7e_ard_3-2-0_102073_2021-08-11_final
2021-08-12 10:18:09	ga_ls7e_ard_3-2-0_109084_2021-08-12_final
2021-08-16 08:15:00	ga_ls7e_ard_3-2-0_089086_2021-08-15_final
2021-08-16 09:49:29	ga_ls7e_ard_3-2-0_105075_2021-08-16_final
2021-08-22 09:12:41	ga_ls7e_ard_3-2-0_099077_2021-08-21_final
2021-08-28 08:39:05	ga_ls7e_ard_3-2-0_093087_2021-08-27_final
2021-08-28 10:12:46	ga_ls7e_ard_3-2-0_109074_2021-08-28_final
2021-08-31 09:08:08	ga_ls7e_ard_3-2-0_098083_2021-08-30_final
2021-09-03 09:32:47	ga_ls7e_ard_3-2-0_103068_2021-09-03_final
2021-09-04 08:43:52	ga_ls7e_ard_3-2-0_094085_2021-09-03_final
2021-09-06 08:32:31	ga_ls7e_ard_3-2-0_092088_2021-09-05_final
2021-09-08 08:20:47	ga_ls7e_ard_3-2-0_090090_2021-09-07_final
2021-09-15 09:59:38	ga_ls7e_ard_3-2-0_107076_2021-09-15_final
2021-09-20 10:17:20	ga_ls7e_ard_3-2-0_110075_2021-09-20_final
2021-09-23 09:07:29	ga_ls7e_ard_3-2-0_099071_2021-09-22_final
2021-09-24 08:16:58	ga_ls7e_ard_3-2-0_090084_2021-09-23_final
2021-09-24 09:49:27	ga_ls7e_ard_3-2-0_106068_2021-09-24_final
2021-09-26 09:38:55	ga_ls7e_ard_3-2-0_104073_2021-09-26_final
2021-10-01 10:01:00	ga_ls7e_ard_3-2-0_107083_2021-10-01_final
2021-10-09 09:04:29	ga_ls7e_ard_3-2-0_099067_2021-10-08_final
2021-10-16 09:11:38	ga_ls7e_ard_3-2-0_100071_2021-10-15_final
2021-10-18 09:03:53	ga_ls7e_ard_3-2-0_098083_2021-10-17_final
2021-10-18 09:04:17	ga_ls7e_ard_3-2-0_098084_2021-10-17_final
2021-11-01 09:10:34	ga_ls7e_ard_3-2-0_100072_2021-10-31_final
2021-11-07 10:13:47	ga_ls7e_ard_3-2-0_110077_2021-11-07_final
2021-11-11 09:45:53	ga_ls7e_ard_3-2-0_106070_2021-11-11_final
2021-11-12 10:30:39	ga_ls7e_ard_3-2-1_113074_2021-11-12_final
2021-11-14 08:44:00	ga_ls7e_ard_3-2-1_095086_2021-11-13_final
2021-11-15 09:21:59	ga_ls7e_ard_3-2-1_102073_2021-11-14_final
2021-11-16 10:04:20	ga_ls7e_ard_3-2-1_109071_2021-11-16_final
2021-11-20 09:38:02	ga_ls7e_ard_3-2-1_105068_2021-11-20_final
2021-11-21 10:26:47	ga_ls7e_ard_3-2-1_112082_2021-11-21_final
2021-11-25 09:57:17	ga_ls7e_ard_3-2-1_108071_2021-11-25_final
2021-11-26 09:00:22	ga_ls7e_ard_3-2-1_099068_2021-11-25_final
2021-11-27 09:46:44	ga_ls7e_ard_3-2-1_106076_2021-11-27_final
2021-11-28 10:32:42	ga_ls7e_ard_3-2-1_113083_2021-11-28_final
2021-12-02 08:25:32	ga_ls7e_ard_3-2-1_093075_2021-12-01_final
2021-12-02 10:04:01	ga_ls7e_ard_3-2-1_109074_2021-12-02_final
2021-12-02 10:04:49	ga_ls7e_ard_3-2-1_109076_2021-12-02_final
2021-12-04 09:49:52	ga_ls7e_ard_3-2-1_107070_2021-12-04_final
2021-12-05 08:56:57	ga_ls7e_ard_3-2-1_098077_2021-12-04_final
2021-12-16 10:14:15	ga_ls7e_ard_3-2-1_111072_2021-12-16_final
2021-12-21 08:52:13	ga_ls7e_ard_3-2-1_098069_2021-12-20_final
2021-12-25 10:09:11	ga_ls7e_ard_3-2-1_110077_2021-12-25_final
2021-12-27 09:55:25	ga_ls7e_ard_3-2-1_108074_2021-12-27_final
2021-12-29 08:07:10	ga_ls7e_ard_3-2-1_090082_2021-12-28_final
2021-12-30 08:45:33	ga_ls7e_ard_3-2-1_097070_2021-12-29_final
2022-01-02 09:20:31	ga_ls7e_ard_3-2-1_102081_2022-01-01_final
2022-01-04 09:09:09	ga_ls7e_ard_3-2-1_100084_2022-01-03_final
2022-01-08 10:22:32	ga_ls7e_ard_3-2-1_112083_2022-01-08_final
2022-01-09 09:22:26	ga_ls7e_ard_3-2-1_103072_2022-01-08_final
2022-01-10 10:07:12	ga_ls7e_ard_3-2-1_110076_2022-01-10_final
2022-01-14 08:07:13	ga_ls7e_ard_3-2-1_090086_2022-01-13_final
2022-01-22 10:32:46	ga_ls7e_ard_3-2-1_114081_2022-01-22_final
2022-01-28 09:56:18	ga_ls7e_ard_3-2-1_108084_2022-01-28_final
2022-01-31 10:26:06	ga_ls7e_ard_3-2-1_113082_2022-01-31_final
2022-02-03 09:17:50	ga_ls7e_ard_3-2-1_102082_2022-02-02_final
2022-02-06 08:11:32	ga_ls7e_ard_3-2-1_091087_2022-02-05_final
2022-02-06 09:48:49	ga_ls7e_ard_3-2-1_107083_2022-02-06_final
2022-02-07 08:53:06	ga_ls7e_ard_3-2-1_098083_2022-02-06_final
2022-02-08 07:56:11	ga_ls7e_ard_3-2-1_089080_2022-02-07_final
2022-02-08 09:30:16	ga_ls7e_ard_3-2-1_105068_2022-02-08_final
2022-02-09 10:19:25	ga_ls7e_ard_3-2-1_112083_2022-02-09_final
2022-02-16 10:24:51	ga_ls7e_ard_3-2-1_113083_2022-02-16_final
2022-02-17 09:23:34	ga_ls7e_ard_3-2-1_104069_2022-02-16_final
2022-02-21 08:59:16	ga_ls7e_ard_3-2-1_100071_2022-02-20_final
2022-02-23 08:49:30	ga_ls7e_ard_3-2-1_098078_2022-02-22_final
2022-02-27 08:22:49	ga_ls7e_ard_3-2-1_094074_2022-02-26_final
2022-02-27 10:01:17	ga_ls7e_ard_3-2-1_110073_2022-02-27_final
2022-03-03 08:03:17	ga_ls7e_ard_3-2-1_090088_2022-03-02_final
2022-03-08 09:55:25	ga_ls7e_ard_3-2-1_109076_2022-03-08_final
2022-03-18 10:31:05	ga_ls7e_ard_3-2-1_115075_2022-03-18_final
2022-03-21 09:20:02	ga_ls7e_ard_3-2-1_104068_2022-03-20_final
2022-03-21 09:25:37	ga_ls7e_ard_3-2-1_104082_2022-03-20_final
2022-03-26 08:08:01	ga_ls7e_ard_3-2-1_091090_2022-03-25_final
2022-03-26 09:40:54	ga_ls7e_ard_3-2-1_107075_2022-03-26_final
2022-04-01 09:06:27	ga_ls7e_ard_3-2-1_101083_2022-03-31_final
2022-04-03 10:31:10	ga_ls7e_ard_3-2-1_115079_2022-04-03_final
2022-04-04 09:35:51	ga_ls7e_ard_3-2-1_106080_2022-04-04_final
2022-04-05 08:39:20	ga_ls7e_ard_3-2-1_097078_2022-04-04_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