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
2021-09-18 08:53:47	ga_ls7e_ard_3-2-0_096082_2021-09-17_final
2021-09-18 10:31:52	ga_ls7e_ard_3-2-0_112080_2021-09-18_final
2021-09-20 08:40:27	ga_ls7e_ard_3-2-0_094080_2021-09-19_final
2021-09-20 10:15:44	ga_ls7e_ard_3-2-0_110071_2021-09-20_final
2021-09-20 10:18:56	ga_ls7e_ard_3-2-0_110079_2021-09-20_final
2021-09-20 10:20:31	ga_ls7e_ard_3-2-0_110083_2021-09-20_final
2021-12-02 08:25:32	ga_ls7e_ard_3-2-1_093075_2021-12-01_final
2021-12-09 08:33:03	ga_ls7e_ard_3-2-1_094080_2021-12-08_final
2021-12-11 08:19:18	ga_ls7e_ard_3-2-1_092077_2021-12-10_final
2021-12-11 09:59:22	ga_ls7e_ard_3-2-1_108080_2021-12-11_final
2021-12-13 08:09:09	ga_ls7e_ard_3-2-1_090083_2021-12-12_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-20 09:51:32	ga_ls7e_ard_3-2-1_107078_2021-12-20_final
2021-12-20 09:52:44	ga_ls7e_ard_3-2-1_107081_2021-12-20_final
2021-12-22 09:38:34	ga_ls7e_ard_3-2-1_105077_2021-12-22_final
2021-12-23 08:46:03	ga_ls7e_ard_3-2-1_096085_2021-12-22_final
2021-12-27 08:19:20	ga_ls7e_ard_3-2-1_092081_2021-12-26_final
2021-12-27 09:55:01	ga_ls7e_ard_3-2-1_108073_2021-12-27_final
2021-12-27 09:57:49	ga_ls7e_ard_3-2-1_108080_2021-12-27_final
2021-12-29 08:06:22	ga_ls7e_ard_3-2-1_090080_2021-12-28_final
2021-12-30 08:50:20	ga_ls7e_ard_3-2-1_097082_2021-12-29_final
2021-12-30 10:27:37	ga_ls7e_ard_3-2-1_113078_2021-12-30_final
2021-12-31 09:28:18	ga_ls7e_ard_3-2-1_104069_2021-12-30_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-01 10:15:03	ga_ls7e_ard_3-2-1_111078_2022-01-01_final
2022-01-03 08:24:48	ga_ls7e_ard_3-2-1_093081_2022-01-02_final
2022-01-03 08:25:36	ga_ls7e_ard_3-2-1_093083_2022-01-02_final
2022-01-04 09:08:21	ga_ls7e_ard_3-2-1_100082_2022-01-03_final
2022-01-06 08:55:24	ga_ls7e_ard_3-2-1_098081_2022-01-05_final
2022-01-08 08:41:40	ga_ls7e_ard_3-2-1_096078_2022-01-07_final
2022-01-11 09:13:05	ga_ls7e_ard_3-2-1_101080_2022-01-10_final
2022-01-13 10:38:37	ga_ls7e_ard_3-2-1_115078_2022-01-13_final
2022-01-14 08:04:25	ga_ls7e_ard_3-2-1_090079_2022-01-13_final
2022-01-14 08:05:37	ga_ls7e_ard_3-2-1_090082_2022-01-13_final
2022-01-15 10:24:28	ga_ls7e_ard_3-2-1_113074_2022-01-15_final
2022-01-21 09:48:49	ga_ls7e_ard_3-2-1_107079_2022-01-21_final
2022-01-25 09:24:06	ga_ls7e_ard_3-2-1_103080_2022-01-24_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-01-28 09:54:18	ga_ls7e_ard_3-2-1_108079_2022-01-28_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-02-03 09:16:38	ga_ls7e_ard_3-2-1_102079_2022-02-02_final
2022-02-05 09:04:28	ga_ls7e_ard_3-2-1_100080_2022-02-04_final
2022-02-06 09:46:25	ga_ls7e_ard_3-2-1_107077_2022-02-06_final
2022-02-08 09:30:16	ga_ls7e_ard_3-2-1_105068_2022-02-08_final
2022-02-11 08:25:10	ga_ls7e_ard_3-2-1_094076_2022-02-10_final
2022-02-13 09:50:41	ga_ls7e_ard_3-2-1_108074_2022-02-13_final
2022-02-16 08:44:47	ga_ls7e_ard_3-2-1_097080_2022-02-15_final
2022-02-18 10:07:55	ga_ls7e_ard_3-2-1_111072_2022-02-18_final
2022-02-18 10:11:07	ga_ls7e_ard_3-2-1_111080_2022-02-18_final
2022-02-20 08:20:29	ga_ls7e_ard_3-2-1_093082_2022-02-19_final
2022-02-20 08:22:05	ga_ls7e_ard_3-2-1_093086_2022-02-19_final
2022-02-21 09:00:51	ga_ls7e_ard_3-2-1_100075_2022-02-20_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-23 08:51:06	ga_ls7e_ard_3-2-1_098082_2022-02-22_final
2022-02-24 09:31:28	ga_ls7e_ard_3-2-1_105075_2022-02-24_final
2022-02-25 10:15:02	ga_ls7e_ard_3-2-1_112076_2022-02-25_final
2022-02-25 10:15:26	ga_ls7e_ard_3-2-1_112077_2022-02-25_final
2022-02-25 10:16:14	ga_ls7e_ard_3-2-1_112079_2022-02-25_final
2022-02-26 09:19:43	ga_ls7e_ard_3-2-1_103077_2022-02-25_final
2022-02-27 08:23:36	ga_ls7e_ard_3-2-1_094076_2022-02-26_final
2022-02-27 08:24:48	ga_ls7e_ard_3-2-1_094079_2022-02-26_final
2022-02-28 09:08:46	ga_ls7e_ard_3-2-1_101081_2022-02-27_final
2022-03-02 08:56:13	ga_ls7e_ard_3-2-1_099081_2022-03-01_final
2022-03-03 08:03:41	ga_ls7e_ard_3-2-1_090089_2022-03-02_final
2022-03-06 10:05:11	ga_ls7e_ard_3-2-1_111069_2022-03-06_final
2022-03-07 09:11:04	ga_ls7e_ard_3-2-1_102073_2022-03-06_final
2022-03-08 08:16:57	ga_ls7e_ard_3-2-1_093077_2022-03-07_final
2022-03-08 08:20:08	ga_ls7e_ard_3-2-1_093085_2022-03-07_final
2022-03-10 09:40:52	ga_ls7e_ard_3-2-1_107071_2022-03-10_final
2022-03-11 08:49:56	ga_ls7e_ard_3-2-1_098083_2022-03-10_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-12 07:54:37	ga_ls7e_ard_3-2-1_089084_2022-03-11_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-13 08:34:35	ga_ls7e_ard_3-2-1_096076_2022-03-12_final
2022-03-13 08:38:10	ga_ls7e_ard_3-2-1_096085_2022-03-12_final
2022-03-13 10:13:04	ga_ls7e_ard_3-2-1_112075_2022-03-13_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-13 10:13:52	ga_ls7e_ard_3-2-1_112077_2022-03-13_final
2022-03-17 08:11:03	ga_ls7e_ard_3-2-1_092080_2022-03-16_final
2022-03-19 07:57:42	ga_ls7e_ard_3-2-1_090078_2022-03-18_final
2022-03-19 09:36:58	ga_ls7e_ard_3-2-1_106079_2022-03-19_final
2022-03-20 08:42:27	ga_ls7e_ard_3-2-1_097082_2022-03-19_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-21 09:21:38	ga_ls7e_ard_3-2-1_104072_2022-03-20_final
2022-03-21 09:24:02	ga_ls7e_ard_3-2-1_104078_2022-03-20_final
2022-03-21 09:25:13	ga_ls7e_ard_3-2-1_104081_2022-03-20_final
2022-03-23 09:11:29	ga_ls7e_ard_3-2-1_102078_2022-03-22_final
2022-03-24 08:16:34	ga_ls7e_ard_3-2-1_093080_2022-03-23_final
2022-03-24 09:52:39	ga_ls7e_ard_3-2-1_109073_2022-03-24_final
2022-03-28 09:25:34	ga_ls7e_ard_3-2-1_105068_2022-03-27_final
2022-03-28 09:26:46	ga_ls7e_ard_3-2-1_105071_2022-03-27_final
2022-03-29 08:32:38	ga_ls7e_ard_3-2-1_096075_2022-03-28_final
2022-03-29 08:34:14	ga_ls7e_ard_3-2-1_096079_2022-03-28_final
2022-03-30 09:15:24	ga_ls7e_ard_3-2-1_103074_2022-03-29_final
2022-03-31 08:20:29	ga_ls7e_ard_3-2-1_094076_2022-03-30_final
2022-03-31 08:24:05	ga_ls7e_ard_3-2-1_094085_2022-03-30_final
2022-04-01 09:04:51	ga_ls7e_ard_3-2-1_101079_2022-03-31_final
2022-04-04 09:35:27	ga_ls7e_ard_3-2-1_106079_2022-04-04_final
2022-04-05 08:40:08	ga_ls7e_ard_3-2-1_097080_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years