LiDAR and maps blend for rural decision support

Abstract

This study integrates aerial LiDAR data and 2D cartographic information to rapidly develop an advanced non‐photorealistic rendering (NPR) model for rural environment analysis. The focus is enhancing decision support in crises and assessing potential hazards in these territories. The methodology involves capturing LiDAR data from high altitudes and classifying it as Ground, Vegetation, and Buildings. The integration of this data with 2D cartographic information, augmented with attribute data from a GIS database, is achieved through a semi‐automatic process. This process facilitates the creation of detailed 3D models, providing a more nuanced, visually and semantically rich representation of the rural landscape. The study underscores the benefits of combining LiDAR, photogrammetric, and cartographic data for creating accurate and detailed models of the rural environment, which are crucial for effective decision‐making and threat assessment.