Saturday, 24 December 2016

Vegetation mapping using LiDAR

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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1 Response to "Vegetation mapping using LiDAR"

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