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

60 results

Time (local)	Label
2022-01-23 07:56:59	ga_ls7e_ard_3-2-1_089078_2022-01-22_final
2022-01-23 07:57:23	ga_ls7e_ard_3-2-1_089079_2022-01-22_final
2022-01-23 07:57:47	ga_ls7e_ard_3-2-1_089080_2022-01-22_final
2022-01-23 07:58:11	ga_ls7e_ard_3-2-1_089081_2022-01-22_final
2022-01-23 07:58:35	ga_ls7e_ard_3-2-1_089082_2022-01-22_final
2022-01-23 07:58:59	ga_ls7e_ard_3-2-1_089083_2022-01-22_final
2022-01-23 07:59:23	ga_ls7e_ard_3-2-1_089084_2022-01-22_final
2022-01-23 09:32:16	ga_ls7e_ard_3-2-1_105069_2022-01-23_final
2022-01-23 09:32:40	ga_ls7e_ard_3-2-1_105070_2022-01-23_final
2022-01-23 09:33:04	ga_ls7e_ard_3-2-1_105071_2022-01-23_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-23 09:33:52	ga_ls7e_ard_3-2-1_105073_2022-01-23_final
2022-01-23 09:34:40	ga_ls7e_ard_3-2-1_105075_2022-01-23_final
2022-01-23 09:35:04	ga_ls7e_ard_3-2-1_105076_2022-01-23_final
2022-01-23 09:35:28	ga_ls7e_ard_3-2-1_105077_2022-01-23_final
2022-01-23 09:35:52	ga_ls7e_ard_3-2-1_105078_2022-01-23_final
2022-01-23 09:36:39	ga_ls7e_ard_3-2-1_105080_2022-01-23_final
2022-01-24 08:37:21	ga_ls7e_ard_3-2-1_096071_2022-01-23_final
2022-01-24 08:37:45	ga_ls7e_ard_3-2-1_096072_2022-01-23_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-24 08:38:57	ga_ls7e_ard_3-2-1_096075_2022-01-23_final
2022-01-24 08:40:09	ga_ls7e_ard_3-2-1_096078_2022-01-23_final
2022-01-24 08:40:33	ga_ls7e_ard_3-2-1_096079_2022-01-23_final
2022-01-24 08:40:56	ga_ls7e_ard_3-2-1_096080_2022-01-23_final
2022-01-24 08:41:20	ga_ls7e_ard_3-2-1_096081_2022-01-23_final
2022-01-24 08:41:44	ga_ls7e_ard_3-2-1_096082_2022-01-23_final
2022-01-24 08:42:08	ga_ls7e_ard_3-2-1_096083_2022-01-23_final
2022-01-24 08:42:32	ga_ls7e_ard_3-2-1_096084_2022-01-23_final
2022-01-24 08:42:56	ga_ls7e_ard_3-2-1_096085_2022-01-23_final
2022-01-24 08:43:20	ga_ls7e_ard_3-2-1_096086_2022-01-23_final
2022-01-24 10:17:26	ga_ls7e_ard_3-2-1_112074_2022-01-24_final
2022-01-24 10:17:49	ga_ls7e_ard_3-2-1_112075_2022-01-24_final
2022-01-24 10:18:13	ga_ls7e_ard_3-2-1_112076_2022-01-24_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-24 10:19:01	ga_ls7e_ard_3-2-1_112078_2022-01-24_final
2022-01-24 10:19:25	ga_ls7e_ard_3-2-1_112079_2022-01-24_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-24 10:21:01	ga_ls7e_ard_3-2-1_112083_2022-01-24_final
2022-01-25 09:19:43	ga_ls7e_ard_3-2-1_103069_2022-01-24_final
2022-01-25 09:20:07	ga_ls7e_ard_3-2-1_103070_2022-01-24_final
2022-01-25 09:21:43	ga_ls7e_ard_3-2-1_103074_2022-01-24_final
2022-01-25 09:22:06	ga_ls7e_ard_3-2-1_103075_2022-01-24_final
2022-01-25 09:22:30	ga_ls7e_ard_3-2-1_103076_2022-01-24_final
2022-01-25 09:23:18	ga_ls7e_ard_3-2-1_103078_2022-01-24_final
2022-01-25 09:23:42	ga_ls7e_ard_3-2-1_103079_2022-01-24_final
2022-01-25 09:24:30	ga_ls7e_ard_3-2-1_103081_2022-01-24_final
2022-01-26 08:25:36	ga_ls7e_ard_3-2-1_094073_2022-01-25_final
2022-01-26 08:27:11	ga_ls7e_ard_3-2-1_094077_2022-01-25_final
2022-01-26 08:27:35	ga_ls7e_ard_3-2-1_094078_2022-01-25_final
2022-01-26 08:28:47	ga_ls7e_ard_3-2-1_094081_2022-01-25_final
2022-01-26 08:29:11	ga_ls7e_ard_3-2-1_094082_2022-01-25_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-26 08:30:23	ga_ls7e_ard_3-2-1_094085_2022-01-25_final
2022-01-26 10:04:28	ga_ls7e_ard_3-2-1_110073_2022-01-26_final
2022-01-26 10:06:04	ga_ls7e_ard_3-2-1_110077_2022-01-26_final
2022-01-26 10:06:28	ga_ls7e_ard_3-2-1_110078_2022-01-26_final
2022-01-26 10:06:52	ga_ls7e_ard_3-2-1_110079_2022-01-26_final
2022-01-26 10:07:16	ga_ls7e_ard_3-2-1_110080_2022-01-26_final
2022-01-26 10:07:40	ga_ls7e_ard_3-2-1_110081_2022-01-26_final
2022-01-26 10:08:04	ga_ls7e_ard_3-2-1_110082_2022-01-26_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