Discrimination of vegetation strata in a multi-layered Mediterranean forest ecosystem using height and intensity information derived from airborne laser scanning

• Published in: Remote sensing of environment Vol. 114; no. 7; pp. 1403 - 1415
• Main Authors: Morsdorf, Felix, Mårell, Anders, Koetz, Benjamin, Cassagne, Nathalie, Pimont, Francois, Rigolot, Eric, Allgöwer, Britta
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 15.07.2010; Elsevier
• Subjects: Accuracy; Airborne laser scanning; Airborne lasers; Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Canopy profile; Classification; Cluster analysis; Earth sciences; Earth, ocean, space; Ecosystems; Environmental Sciences; Exact sciences and technology; Forests; Fundamental and applied biological sciences. Psychology; Gaussian mixture models; General aspects. Techniques; Ground cover; Internal geophysics; LiDAR; Multi-layered ecosystems; Scanning; Shrubland; Strata; Supervised classification; Teledetection and vegetation maps; Vegetation; Vertical stratification; Wildland fires; MED; Cluster analysis; Multi-layered ecosystems; LiDAR; Gaussian mixture models; Shrubland; Wildland fires; Vertical stratification; Canopy profile; Airborne laser scanning; Supervised classification; Vertical; laser methods; terrains; stratification; Information; Profile; Field; separation; discrimination; Height; Forest zone; Mediterranean vegetation; Plot; topography; Multiple layer; utilization; forests; Mixed model; ecosystems; Laser; Mediterranean climate; methodology; Canopy(vegetation); dimensions; SHRUBLAND; BIODIVERSITY; WILDLIFE MANAGEMENT; LIDAR; CLUSTER ANALYSIS; WILDLAND FIRES; CANOPY PROFILE; MULTI-LAYERED ECOSYSTEMS; CONSERVATION BIOLOGY; VERTICAL STRATIFICATION; SUPERVISED CLASSIFICATION; GAUSSIAN MIXTURE MODELS; AIRBORNE LASER SCANNING
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2010.01.023

Height and intensity information derived from Airborne Laser Scanning (ALS) was used to obtain a quantitative vertical stratification of vegetation in a multi-layered Mediterranean ecosystem. A new methodology for the separation of different vegetation strata was implemented using supervised classification of a two-dimensional feature space spanned by ALS return height (terrain corrected) and intensity. The classification was carried out using Gaussian mixture models tuned on a control plot. The approach was validated using extensive field measurements from treated plots, ranging from single vegetation strata to a more complex multi-layered ecosystem. Plot-level canopy profiles derived from ALS and from a geometric reconstruction based on field measurements were in very good agreement, with correlation coefficients ranging from 0.73 (for complex, 3-layered) to 0.96 (simple, single-layered). In addition, it was possible to derive plot-level information on layer height, vertical extent and coverage with absolute accuracies of some decimetres (simple plots) to a meter (complex plots) for both height and vertical extent and about 10 to 15% for layer coverage. The approach was then used to derive maps of the layer height, vertical extent and percentage of ground cover for a larger area, and classification accuracy was evaluated on a per-pixel basis. The method performed best for single-layered plots or dominant layers on multi-layered plots, obtaining an overall accuracy of 80 to 90%. For subdominant layers in the more complex plots, accuracies obtained were as low as 48%. Our results demonstrate the possibility of deriving qualitative (presence and absence of specific vegetation layers) and quantitative, physical data (height, vertical extent and ground cover) describing the vertical structure of complex multi-layered forest ecosystems using ALS-based height and intensity information.