Introduction
LIght
Detection And Ranging (LiDAR) technology is capable of making spatially located
point elevation measurements to generate precise and high resolution Digital
Elevation Model (DEM) of a chosen canopy or particular structure. Vegetation
and trees mapping can be expertly done using LiDAR technology. LiDAR’s fast,
dense, and systematic dataset permits mapping of land-use classification,
vegetation canopy, ground elevations in dense vegetation covers, areas of
minute textural differences, areas of minute elevation differences, and point
and line features i.e. trees, water lines etc.
Why vegetation mapping is
important?
Natural
resources when managed for a positive reason of saving the ecosystem in an
optimistic way, can offer benefits for longer time period without getting
deteriorated. Natural resources management is not comprehensive unless
vegetation is properly identified with its characteristics, uses and impacts on
the environment. Such vegetation mapping is sure to be efficiently done using
LiDAR for determining species and groups of vegetation, measuring vegetation in
three dimensions, and mapping vegetation spectrally, spatially, and temporally.
If and when vegetation mapping is done in a resourceful and well-organized
manner, it can solve widespread concerns during forest inventories, ecological
studies, environmental modeling, hazards control, risk mapping, and wildlife
safety. LiDAR data can be used to identify distinct structures in any canopy
such as trees in parks, fruit orchards or forests. Distinct 3D models of trees
can be created using LiDAR data. LiDAR can also acquire data on leaves’
characteristics, diversity of microhabitat, and transpiration.
Factors that effect LiDAR data
The
accuracy of LiDAR data depends upon the factors like alignment of the
coordinate system, quality of point data, point density, vegetation height
thresholds, vegetation density in the canopy, wind that affects the leaves, leaf-on
and leaf-off seasons, forest cover effects, complex vegetation cover, size of
individual trees, undergrowth of herbs, shrubs’ areas, wood quality, birds in
the vicinity, slope and elevation of the terrain, terrains with high and low
reliefs, data recruitment times and dates, aircraft fluctuations, the distance
between LiDAR sensor and trees, pulse mode, site conditions, weather, interpolation
of points, stitching accuracy, and the LiDAR sensor itself. The task of creating
a well-defined 3D model of tree is accomplished when the modeling of leaves, twigs,
branches, tree height, tree crown, and crown diameter are incorporated into it.
The DEM
When
LiDAR data is achieved, generation of DEM can be done flawlessly after
filtering of errors and outliers removal from LiDAR points, interpolating and
reorganization of the points, and separation of ground points i.e. ground
filtering. DEM which is representation of the landscape along with its
vegetation quantitatively can be used to assess the terrain, vegetation, and
trees conditions and their effects on the surroundings. DEM provides a broad
vision and is used to get the spatial information about processes occurring
within the forest canopy. After evaluation of DEM, the decision can be made for
the management and control of vegetation areas for the betterment of
neighboring flora and fauna, wildlife, water bodies, human settlement, and the
vegetation itself.
Conclusion
LiDAR
technology acquires accurate and workable 3D data swiftly and competently. The
use of LiDAR technology in forest environments can speedily attain precise
spatial data of trees and vegetation temporally. When LiDAR data is presented
in form of DEM, it enables researchers to visualize the canopies’ physical, chemical,
and biological scenarios through an unprecedented visualization for the
quantitative analysis of the forest’s canopy.
References
Analysis of the factors affecting LiDAR DTM accuracy in a steep shrub area
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