Improving models for environmental applications of LiDAR: Novel approaches based on soft computing

Abstract

This work proposes novel methodologies to improve the use of Light Detection And Ranging (LiDAR) for environ mental purposes, especially for thematic mapping (LiDAR only or fused with other remote sensors) and the estimation of for est variables. The methodologies make use of well-known techniques from soft computing (machine learning and evolutionary computation) and their adaptation to develop LiDAR-derived products.