LIDAR Composite First Return DSM 2022 - 1m

The LIDAR Composite First Return DSM (Digital Surface Model) is a raster elevation model at 1m spatial resolution produced by the Environment Agency in 2022. The first return DSM is produced from the first or only LIDAR signal returned to the sensor and includes heights of objects, such as vehicles, buildings and vegetation, as well as the terrain surface where the first or only return was the ground. The first return DSM composite product is derived from LIDAR data captured as part of our national timeseries programme between 11 November 2016 and 5th May 2022. This programme divided England into local blocks for survey over continuous winters from 2016 onwards. These individual surveys have then been merged together to create the first return LIDAR composite using a feathering technique along the overlaps to remove any small differences in elevation between surveys. The first return DSM will not match in coverage or extent the standard DSM composite which is produced from the last or only return as the last return DSM composite is produced from both the national LIDAR programme and Timeseries surveys. The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-10cm RMSE. Please refer to the survey index files which shows for any location what national LIDAR programme survey went into the production of the LIDAR composite for any specific location. ESRI Image REST services are available for elevation, hillshade, slope and aspect and a tinted shaded relief image is also available as a WMS feed. This metadata record is for Approval for Access product AfA458. Attribution statement: (c) Environment Agency copyright and/or database right 2022. All rights reserved. Attribution Statement: © Environment Agency copyright and/or database right 2015. All rights reserved.