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
2022-02-18 10:06:44	ga_ls7e_ard_3-2-1_111069_2022-02-18_final
2022-02-18 10:07:55	ga_ls7e_ard_3-2-1_111072_2022-02-18_final
2022-02-18 10:08:19	ga_ls7e_ard_3-2-1_111073_2022-02-18_final
2022-02-18 10:09:07	ga_ls7e_ard_3-2-1_111075_2022-02-18_final
2022-02-18 10:09:55	ga_ls7e_ard_3-2-1_111077_2022-02-18_final
2022-02-20 09:54:11	ga_ls7e_ard_3-2-1_109069_2022-02-20_final
2022-02-20 09:54:35	ga_ls7e_ard_3-2-1_109070_2022-02-20_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-20 09:55:46	ga_ls7e_ard_3-2-1_109073_2022-02-20_final
2022-02-20 09:56:10	ga_ls7e_ard_3-2-1_109074_2022-02-20_final
2022-02-20 09:56:34	ga_ls7e_ard_3-2-1_109075_2022-02-20_final
2022-02-20 09:57:22	ga_ls7e_ard_3-2-1_109077_2022-02-20_final
2022-02-20 09:57:46	ga_ls7e_ard_3-2-1_109078_2022-02-20_final
2022-02-20 09:58:10	ga_ls7e_ard_3-2-1_109079_2022-02-20_final
2022-02-20 09:58:34	ga_ls7e_ard_3-2-1_109080_2022-02-20_final
2022-02-20 09:59:22	ga_ls7e_ard_3-2-1_109082_2022-02-20_final
2022-02-22 09:45:13	ga_ls7e_ard_3-2-1_107078_2022-02-22_final
2022-02-22 09:45:37	ga_ls7e_ard_3-2-1_107079_2022-02-22_final
2022-02-22 09:46:01	ga_ls7e_ard_3-2-1_107080_2022-02-22_final
2022-02-22 09:46:49	ga_ls7e_ard_3-2-1_107082_2022-02-22_final
2022-02-22 09:47:13	ga_ls7e_ard_3-2-1_107083_2022-02-22_final
2022-02-27 10:01:17	ga_ls7e_ard_3-2-1_110073_2022-02-27_final
2022-02-27 10:01:41	ga_ls7e_ard_3-2-1_110074_2022-02-27_final
2022-02-27 10:02:29	ga_ls7e_ard_3-2-1_110076_2022-02-27_final
2022-02-27 10:02:53	ga_ls7e_ard_3-2-1_110077_2022-02-27_final
2022-02-27 10:03:41	ga_ls7e_ard_3-2-1_110079_2022-02-27_final
2022-02-27 10:04:05	ga_ls7e_ard_3-2-1_110080_2022-02-27_final
2022-02-27 10:04:29	ga_ls7e_ard_3-2-1_110081_2022-02-27_final
2022-03-15 09:58:30	ga_ls7e_ard_3-2-1_110070_2022-03-15_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-15 09:59:42	ga_ls7e_ard_3-2-1_110073_2022-03-15_final
2022-03-15 10:00:06	ga_ls7e_ard_3-2-1_110074_2022-03-15_final
2022-03-15 10:00:30	ga_ls7e_ard_3-2-1_110075_2022-03-15_final
2022-03-15 10:01:18	ga_ls7e_ard_3-2-1_110077_2022-03-15_final
2022-03-15 10:01:42	ga_ls7e_ard_3-2-1_110078_2022-03-15_final
2022-03-15 10:02:05	ga_ls7e_ard_3-2-1_110079_2022-03-15_final
2022-03-15 10:02:29	ga_ls7e_ard_3-2-1_110080_2022-03-15_final
2022-03-15 10:02:53	ga_ls7e_ard_3-2-1_110081_2022-03-15_final
2022-03-17 09:47:32	ga_ls7e_ard_3-2-1_108074_2022-03-17_final
2022-03-17 09:47:56	ga_ls7e_ard_3-2-1_108075_2022-03-17_final
2022-03-17 09:48:20	ga_ls7e_ard_3-2-1_108076_2022-03-17_final
2022-03-17 09:48:44	ga_ls7e_ard_3-2-1_108077_2022-03-17_final
2022-03-17 09:49:07	ga_ls7e_ard_3-2-1_108078_2022-03-17_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-17 09:49:55	ga_ls7e_ard_3-2-1_108080_2022-03-17_final
2022-03-17 09:50:19	ga_ls7e_ard_3-2-1_108081_2022-03-17_final
2022-03-17 09:50:43	ga_ls7e_ard_3-2-1_108082_2022-03-17_final
2022-03-17 09:51:07	ga_ls7e_ard_3-2-1_108083_2022-03-17_final
2022-03-19 09:38:10	ga_ls7e_ard_3-2-1_106082_2022-03-19_final
2022-03-19 09:38:34	ga_ls7e_ard_3-2-1_106083_2022-03-19_final
2022-03-22 10:03:12	ga_ls7e_ard_3-2-1_111068_2022-03-22_final
2022-03-22 10:03:36	ga_ls7e_ard_3-2-1_111069_2022-03-22_final
2022-03-22 10:04:00	ga_ls7e_ard_3-2-1_111070_2022-03-22_final
2022-03-22 10:04:24	ga_ls7e_ard_3-2-1_111071_2022-03-22_final
2022-03-22 10:04:48	ga_ls7e_ard_3-2-1_111072_2022-03-22_final
2022-03-22 10:05:12	ga_ls7e_ard_3-2-1_111073_2022-03-22_final
2022-03-22 10:05:36	ga_ls7e_ard_3-2-1_111074_2022-03-22_final
2022-03-22 10:06:00	ga_ls7e_ard_3-2-1_111075_2022-03-22_final
2022-03-22 10:06:24	ga_ls7e_ard_3-2-1_111076_2022-03-22_final
2022-03-22 10:06:48	ga_ls7e_ard_3-2-1_111077_2022-03-22_final
2022-03-24 09:51:03	ga_ls7e_ard_3-2-1_109069_2022-03-24_final
2022-03-24 09:51:27	ga_ls7e_ard_3-2-1_109070_2022-03-24_final
2022-03-24 09:51:51	ga_ls7e_ard_3-2-1_109071_2022-03-24_final
2022-03-24 09:52:15	ga_ls7e_ard_3-2-1_109072_2022-03-24_final
2022-03-24 09:52:39	ga_ls7e_ard_3-2-1_109073_2022-03-24_final
2022-03-24 09:53:03	ga_ls7e_ard_3-2-1_109074_2022-03-24_final
2022-03-24 09:53:27	ga_ls7e_ard_3-2-1_109075_2022-03-24_final
2022-03-24 09:53:51	ga_ls7e_ard_3-2-1_109076_2022-03-24_final
2022-03-24 09:54:15	ga_ls7e_ard_3-2-1_109077_2022-03-24_final
2022-03-24 09:54:39	ga_ls7e_ard_3-2-1_109078_2022-03-24_final
2022-03-24 09:56:15	ga_ls7e_ard_3-2-1_109082_2022-03-24_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-24 09:57:03	ga_ls7e_ard_3-2-1_109084_2022-03-24_final
2022-03-26 09:42:06	ga_ls7e_ard_3-2-1_107078_2022-03-26_final
2022-03-26 09:42:30	ga_ls7e_ard_3-2-1_107079_2022-03-26_final
2022-03-26 09:42:54	ga_ls7e_ard_3-2-1_107080_2022-03-26_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_final
2022-03-26 09:43:42	ga_ls7e_ard_3-2-1_107082_2022-03-26_final
2022-03-26 09:44:06	ga_ls7e_ard_3-2-1_107083_2022-03-26_final
2022-03-26 09:44:30	ga_ls7e_ard_3-2-1_107084_2022-03-26_final
2022-03-31 09:56:58	ga_ls7e_ard_3-2-1_110070_2022-03-31_final
2022-03-31 09:57:22	ga_ls7e_ard_3-2-1_110071_2022-03-31_final
2022-03-31 09:57:46	ga_ls7e_ard_3-2-1_110072_2022-03-31_final
2022-03-31 09:58:10	ga_ls7e_ard_3-2-1_110073_2022-03-31_final
2022-03-31 09:58:34	ga_ls7e_ard_3-2-1_110074_2022-03-31_final
2022-03-31 09:58:58	ga_ls7e_ard_3-2-1_110075_2022-03-31_final
2022-03-31 09:59:22	ga_ls7e_ard_3-2-1_110076_2022-03-31_final
2022-03-31 09:59:46	ga_ls7e_ard_3-2-1_110077_2022-03-31_final
2022-03-31 10:00:10	ga_ls7e_ard_3-2-1_110078_2022-03-31_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-03-31 10:00:58	ga_ls7e_ard_3-2-1_110080_2022-03-31_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_final
2022-04-02 09:46:01	ga_ls7e_ard_3-2-1_108074_2022-04-02_final
2022-04-02 09:46:25	ga_ls7e_ard_3-2-1_108075_2022-04-02_final
2022-04-02 09:46:49	ga_ls7e_ard_3-2-1_108076_2022-04-02_final
2022-04-02 09:47:12	ga_ls7e_ard_3-2-1_108077_2022-04-02_final
2022-04-02 09:48:48	ga_ls7e_ard_3-2-1_108081_2022-04-02_final
2022-04-02 09:49:12	ga_ls7e_ard_3-2-1_108082_2022-04-02_final
2022-04-02 09:49:36	ga_ls7e_ard_3-2-1_108083_2022-04-02_final
2022-04-02 09:50:00	ga_ls7e_ard_3-2-1_108084_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