UAV-based canopy textures assess changes in forest structure from long-term degradation

• Published in: Ecological indicators Vol. 115; p. 106386
• Main Authors: Bourgoin, Clément, Betbeder, Julie, Couteron, Pierre, Blanc, Lilian, Dessard, Hélène, Oszwald, Johan, Le Roux, Renan, Cornu, Guillaume, Reymondin, Louis, Mazzei, Lucas, Sist, Plinio, Läderach, Peter, Gond, Valéry
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2020; Elsevier
• Subjects: Biodiversity; Biodiversity and Ecology; Botanics; Canopy structure; Ecology, environment; Ecosystems; Environmental Sciences; Forest degradation; Life Sciences; Remote sensing; Systematics, Phylogenetics and taxonomy; Texture; Tropical forest; Unmanned aerial vehicle; Vegetal Biology; Forest degradation; Tropical forest; Canopy structure; Unmanned aerial vehicle; Texture; Remote sensing; Canopy structure For; est degradation
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2020.106386

•We assessed canopy texture – structure relations along forest degradation gradients.•Canopy textures capture 58% of degradation-induced variability of canopy structure.•Degradation generates specific canopy textures linked with logging and fire history.•Texture metrics can be used to evaluate the state of degraded forests. Degraded tropical forests dominate agricultural frontiers and their management is becoming an urgent priority. This calls for a better understanding of the different forest cover states and cost-efficient techniques to quantify the impact of degradation on forest structure. Canopy texture analyses based on Very High Spatial Resolution (VHSR) optical imagery provide proxies to assess forest structures but the mechanisms linking them with degradation have rarely been investigated. To address this gap, we used a lightweight Unmanned Aerial Vehicle (UAV) to map 739 ha of degraded forests and acquire both canopy VHSR images and height model. Thirty-three years of degradation history from Landsat archives allowed us to sample 40 plots in undisturbed, logged, over-logged and burned and regrowth forests in tropical forested landscapes (Paragominas, Pará, Brazil). Fourier (FOTO) and lacunarity textures were used to assess forest canopy structure and to build a typology linking degradation history and current states. Texture metrics capture canopy grain, heterogeneity and openness gradients and correlate with forest structure variability (R2 = 0.58). Similar structures share common degradation history and can be discriminated on the basis of canopy texture alone (accuracy = 55%). Over-logging causes a lowering in forest height, which brings homogeneous textures and of finer grain. We identified the major changes in structures due to fire following logging which changes heterogeneous and intermediate grain into coarse textures. Our findings highlight the potential of canopy texture metrics to characterize degraded forests and thus be used as indicators for forest management and degradation mitigation. Inexpensive and agile UAV open promising perspectives at the interface between field inventory and satellite characterization of forest structure using texture metrics.