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 08:54:35	ga_ls7e_ard_3-2-0_096084_2021-09-17_final
2021-10-25 09:09:01	ga_ls7e_ard_3-2-0_099082_2021-10-24_final
2021-10-26 09:47:48	ga_ls7e_ard_3-2-0_106071_2021-10-26_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2021-12-19 09:10:22	ga_ls7e_ard_3-2-1_100083_2021-12-18_final
2021-12-20 09:52:44	ga_ls7e_ard_3-2-1_107081_2021-12-20_final
2021-12-22 09:37:23	ga_ls7e_ard_3-2-1_105074_2021-12-22_final
2021-12-25 08:29:54	ga_ls7e_ard_3-2-1_094076_2021-12-24_final
2021-12-29 09:41:16	ga_ls7e_ard_3-2-1_106070_2021-12-29_final
2021-12-30 10:28:25	ga_ls7e_ard_3-2-1_113080_2021-12-30_final
2021-12-31 09:29:30	ga_ls7e_ard_3-2-1_104072_2021-12-30_final
2022-01-01 10:16:39	ga_ls7e_ard_3-2-1_111082_2022-01-01_final
2022-01-02 09:19:20	ga_ls7e_ard_3-2-1_102078_2022-01-01_final
2022-01-02 09:20:07	ga_ls7e_ard_3-2-1_102080_2022-01-01_final
2022-01-03 08:24:00	ga_ls7e_ard_3-2-1_093079_2022-01-02_final
2022-01-03 10:02:05	ga_ls7e_ard_3-2-1_109077_2022-01-03_final
2022-01-04 09:03:58	ga_ls7e_ard_3-2-1_100071_2022-01-03_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-08 08:42:52	ga_ls7e_ard_3-2-1_096081_2022-01-07_final
2022-01-10 08:31:07	ga_ls7e_ard_3-2-1_094083_2022-01-09_final
2022-01-10 10:07:12	ga_ls7e_ard_3-2-1_110076_2022-01-10_final
2022-01-12 08:16:58	ga_ls7e_ard_3-2-1_092079_2022-01-11_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-12 09:54:15	ga_ls7e_ard_3-2-1_108075_2022-01-12_final
2022-01-13 09:00:08	ga_ls7e_ard_3-2-1_099079_2022-01-12_final
2022-01-13 10:37:49	ga_ls7e_ard_3-2-1_115076_2022-01-13_final
2022-01-13 10:38:13	ga_ls7e_ard_3-2-1_115077_2022-01-13_final
2022-01-15 10:26:52	ga_ls7e_ard_3-2-1_113080_2022-01-15_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-24 08:38:57	ga_ls7e_ard_3-2-1_096075_2022-01-23_final
2022-01-24 10:19:25	ga_ls7e_ard_3-2-1_112079_2022-01-24_final
2022-01-25 09:24:30	ga_ls7e_ard_3-2-1_103081_2022-01-24_final
2022-01-26 08:29:59	ga_ls7e_ard_3-2-1_094084_2022-01-25_final
2022-01-26 08:30:47	ga_ls7e_ard_3-2-1_094086_2022-01-25_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-01-28 09:55:06	ga_ls7e_ard_3-2-1_108081_2022-01-28_final
2022-01-30 08:07:16	ga_ls7e_ard_3-2-1_090090_2022-01-29_final
2022-02-02 08:35:28	ga_ls7e_ard_3-2-1_095084_2022-02-01_final
2022-02-04 08:20:07	ga_ls7e_ard_3-2-1_093077_2022-02-03_final
2022-02-04 09:59:47	ga_ls7e_ard_3-2-1_109079_2022-02-04_final
2022-02-04 10:00:59	ga_ls7e_ard_3-2-1_109082_2022-02-04_final
2022-02-08 09:31:28	ga_ls7e_ard_3-2-1_105071_2022-02-08_final
2022-02-09 08:41:20	ga_ls7e_ard_3-2-1_096085_2022-02-08_final
2022-02-10 09:21:41	ga_ls7e_ard_3-2-1_103078_2022-02-09_final
2022-02-11 08:29:10	ga_ls7e_ard_3-2-1_094086_2022-02-10_final
2022-02-11 10:02:27	ga_ls7e_ard_3-2-1_110072_2022-02-11_final
2022-02-13 09:51:53	ga_ls7e_ard_3-2-1_108077_2022-02-13_final
2022-02-14 08:56:09	ga_ls7e_ard_3-2-1_099077_2022-02-13_final
2022-02-14 08:57:21	ga_ls7e_ard_3-2-1_099080_2022-02-13_final
2022-02-14 10:35:02	ga_ls7e_ard_3-2-1_115077_2022-02-14_final
2022-02-15 08:01:38	ga_ls7e_ard_3-2-1_090080_2022-02-14_final
2022-02-15 08:02:25	ga_ls7e_ard_3-2-1_090082_2022-02-14_final
2022-02-15 08:05:13	ga_ls7e_ard_3-2-1_090089_2022-02-14_final
2022-02-16 08:41:59	ga_ls7e_ard_3-2-1_097073_2022-02-15_final
2022-02-17 09:23:10	ga_ls7e_ard_3-2-1_104068_2022-02-16_final
2022-02-17 09:26:21	ga_ls7e_ard_3-2-1_104076_2022-02-16_final
2022-02-19 09:11:01	ga_ls7e_ard_3-2-1_102069_2022-02-18_final
2022-02-23 08:47:07	ga_ls7e_ard_3-2-1_098072_2022-02-22_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-23 08:52:18	ga_ls7e_ard_3-2-1_098085_2022-02-22_final
2022-02-26 09:17:43	ga_ls7e_ard_3-2-1_103072_2022-02-25_final
2022-02-26 09:19:19	ga_ls7e_ard_3-2-1_103076_2022-02-25_final
2022-02-27 08:22:25	ga_ls7e_ard_3-2-1_094073_2022-02-26_final
2022-02-27 08:25:12	ga_ls7e_ard_3-2-1_094080_2022-02-26_final
2022-02-28 09:06:22	ga_ls7e_ard_3-2-1_101075_2022-02-27_final
2022-03-01 09:50:20	ga_ls7e_ard_3-2-1_108077_2022-03-01_final
2022-03-02 10:32:42	ga_ls7e_ard_3-2-1_115075_2022-03-02_final
2022-03-04 08:44:27	ga_ls7e_ard_3-2-1_097083_2022-03-03_final
2022-03-04 10:20:56	ga_ls7e_ard_3-2-1_113077_2022-03-04_final
2022-03-05 09:22:02	ga_ls7e_ard_3-2-1_104069_2022-03-04_final
2022-03-06 10:06:47	ga_ls7e_ard_3-2-1_111073_2022-03-06_final
2022-03-07 09:10:16	ga_ls7e_ard_3-2-1_102071_2022-03-06_final
2022-03-08 08:16:09	ga_ls7e_ard_3-2-1_093075_2022-03-07_final
2022-03-08 08:16:33	ga_ls7e_ard_3-2-1_093076_2022-03-07_final
2022-03-08 08:17:45	ga_ls7e_ard_3-2-1_093079_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
2022-03-09 08:58:07	ga_ls7e_ard_3-2-1_100072_2022-03-08_final
2022-03-11 08:47:57	ga_ls7e_ard_3-2-1_098078_2022-03-10_final
2022-03-14 09:14:57	ga_ls7e_ard_3-2-1_103069_2022-03-13_final
2022-03-15 08:26:24	ga_ls7e_ard_3-2-1_094087_2022-03-14_final
2022-03-17 08:11:03	ga_ls7e_ard_3-2-1_092080_2022-03-16_final
2022-03-17 08:11:27	ga_ls7e_ard_3-2-1_092081_2022-03-16_final
2022-03-17 09:48:44	ga_ls7e_ard_3-2-1_108077_2022-03-17_final
2022-03-17 09:50:43	ga_ls7e_ard_3-2-1_108082_2022-03-17_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-21 09:21:14	ga_ls7e_ard_3-2-1_104071_2022-03-20_final
2022-03-21 09:24:50	ga_ls7e_ard_3-2-1_104080_2022-03-20_final
2022-03-22 08:29:31	ga_ls7e_ard_3-2-1_095081_2022-03-21_final
2022-03-22 08:29:55	ga_ls7e_ard_3-2-1_095082_2022-03-21_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-24 09:55:27	ga_ls7e_ard_3-2-1_109080_2022-03-24_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-29 10:11:07	ga_ls7e_ard_3-2-1_112074_2022-03-29_final
2022-03-31 08:20:29	ga_ls7e_ard_3-2-1_094076_2022-03-30_final
2022-04-02 08:09:08	ga_ls7e_ard_3-2-1_092079_2022-04-01_final
2022-04-03 08:54:17	ga_ls7e_ard_3-2-1_099084_2022-04-02_final
2022-04-04 08:00:34	ga_ls7e_ard_3-2-1_090089_2022-04-03_final
2022-04-05 08:41:43	ga_ls7e_ard_3-2-1_097084_2022-04-04_final
2022-04-05 10:17:48	ga_ls7e_ard_3-2-1_113077_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years