Rewilding in Three Dimensions: What LiDAR Reveals About Forests
By Kamil Kral.
When I walk through a forest, I am always struck by the sense that there is more happening than I can perceive. My eyes trace the trunks of trees, the canopy stretching above me, and the shafts of light breaking through in places. But I also know that much of the forest remains hidden from my view. Forests are not some layers of vegetation; they are complex, three-dimensional worlds. They grow upward, outward, and in intricate layers, creating habitats within habitats. To truly understand how these structures form and evolve, we need tools that go beyond what our senses and traditional methods can capture. That is where LiDAR comes in, and why it has become such a powerful part of our work in the WILDCARD project.
LiDAR – Light Detection and Ranging – allows us to map forests in three dimensions at centimetre-to-metre resolution. By sending out laser pulses and measuring how they reflect, LiDAR creates an extraordinarily detailed picture of vegetation structure. From airplanes, it can cover entire landscapes, but in WILDCARD we focus mainly on ground-based and drone-mounted systems. These cover smaller areas, yet their precision is remarkable, revealing the layers of the understory, the openings in the canopy where light filters through, the presence of exceptionally large trees, and the way these elements combine into complex arrangements across a site. What excites me most is how LiDAR connects many different domains: a single dataset links the technical world of remote sensing with ecological research and the very practical sphere of management and policy. It shows us what remains invisible to aerial photographs and ground surveys – the fine-grained complexity of the understory, the architecture of the canopy, and the shifting patterns of light and space that drive ecological processes. And what truly matters is not just capturing these patterns but translating them into indicators that reflect biodiversity, turning three-dimensional point clouds (the reflections of laser beams emitted by the scanners) into ecological meaning.
For rewilding, this information is crucial. Rewilding is not just about leaving land unmanaged and hoping for the best. It is also about letting natural processes unfold and observing how they gradually create new ecological opportunities. LiDAR allows us to measure these changes. By comparing sites of different ages and management histories – what we call a space-for-time substitution or chronosequence – we can track how complexity develops once human interventions stop. Over decades, forests shift in structure, forming vertical layers, creating gaps, and offering niches for species that depend on a dynamic habitat. These transformations are difficult to capture with traditional field plots, which often rely on sampling a small number of trees or features. LiDAR, on the other hand, gives us a comprehensive picture and a repeatable way to observe these changes across dozens or even hundreds of sites.
With LiDAR, we can start to ask why forests behave the way they do. Why do carbon accumulation and biodiversity often rise together in some places, while in others the two seem to diverge? How does structure influence species composition? And how might we use this knowledge to guide rewilding in ways that support both climate goals and biodiversity? These are questions that matter deeply, not only to scientists but to policymakers, land managers, and communities who want to see landscapes recover.
From our pilot sites we already have encouraging results. We have built a robust processing pipeline and developed a first set of structural indicators. The early patterns are striking: rewilded stands seem to show higher levels of both vertical and horizontal complexity than managed stands. These structural differences are precisely the kinds of features that many species depend on, and we anticipate strong correlations with independent measures of biodiversity. At the same time, we are grappling with real challenges. Data collected from different sensors and platforms do not always align neatly, and we need to harmonise them to ensure comparability. We are also learning about the limits of scale – how small a plot can be before its complexity becomes too difficult to measure reliably. These are technical hurdles, but they are also stepping stones that will allow us to expand our analysis across the entire WILDCARD network.
For me, the most exciting aspect of this work is its potential to shift how we think about rewilding. Forests are often described as carbon sinks or as habitats for species, but the WILDCARD project reveals them as both at once: living, evolving, complex three-dimensional systems. With the LiDAR technology we can not only see but also measure the richness of their structure and begin to understand how it shapes biodiversity and carbon dynamics together. That knowledge can inform rewilding strategies, guide conservation investments, and support policies that build resilient ecosystems. Forests are more than collections of trees. They are dynamic, intricate habitats that we are only beginning to understand in full. LiDAR gives us a way to step into that complexity, to capture it with unprecedented precision, and to tell the story of rewilding in three dimensions. For WILDCARD, it means we are one step closer to making the so far hidden patterns measurable, and to building the knowledge that will help rewilding succeed at scales that truly matter.
