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

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.