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Last Return
Last Return in LiDAR is the term that denotes the last significant return of a LiDAR pulse from the objects on the Earth's surface. The number of returns may be several, depending on whether a single laser pulse strikes vegetation, buildings, terrain, and any other objects. In many cases, the last return is related to the Earth surface and is usually used for analysis of the terrain and its elevation.
Last-return data is helpful for finding the ground points located under other elements such as vegetation and building constructions. This type of data is used for creating Digital Terrain Models (DTMs), Digital Elevation Models (DEMs), contour maps, and 3D representation of the area. It is also useful for analysis of the forest cover, topography, surveys, floods, infrastructure construction, and environmental researches.
The understanding of the concept of last returns is essential while working with LiDAR data because the return data helps to understand the structure and elevation of the territory better. With the help of last returns together with the first, intermediate and single returns one can get precise geospatial data for GIS and remote sensing purposes.

The Last Return in LiDAR is the last recorded return from a laser pulse after it is reflected from the surface of the Earth or any objects above the Earth's surface. LiDAR devices allow capturing several returns of each pulse in order to measure several layers, including tree canopies, vegetation, buildings, and terrain. The last return becomes useful for determining the bottom layers and ground elevation levels.
Last returns become useful in many applications including the creation of topographic maps, land surveys, forestry, constructions, and environmental analysis. Based on these returns, specialists in GIS and remote sensing can filter out ground objects and elevated objects and produce elevation datasets. Last returns are often used in the production of DTMs, elevation maps, contours, and 3D models of terrain.
The distinction between last returns and other LiDAR returns becomes useful for improving the classification of point clouds and creating a more precise representation of the landscape.
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