Integrating LiDAR Data into GIS Analysis for Terrain Modeling

LiDAR (Light Detection and Ranging) technology has revolutionized the way we collect and process high-precision geospatial data.

This article explores the workflow for integrating aerial LiDAR data into Geographic Information Systems (GIS), with a focus on generating Digital Elevation Models (DEM) and Digital Terrain Models (DTM).

Primary Data Processing

Raw LiDAR data, in the form of a point cloud, requires filtering and classification to separate points representing the ground from those representing vegetation or built structures. This step is critical for the accuracy of the final model.

The use of interpolation algorithms, such as TIN (Triangulated Irregular Network) or kriging, transforms classified points into continuous surfaces, usable for visibility analysis, hydrology, or urban planning.

Practical Applications and Case Studies

In Romania, LiDAR data is increasingly used for monitoring landslide risk areas or for forest resource inventory. Overlaying these models with traditional vector maps provides a multidimensional perspective on the territory.

The continuous development of sensors and processing software promises to democratize access to these technologies, bringing high-resolution geospatial analysis within reach of a greater number of specialists.