On the integration of LiDAR and field data for riparian biomass estimation. (15th November 2022)

• Record Type: Journal Article
• Authors: Latella, M.; Raimondo, T.; Belcore, E.; Salerno, L.; Camporeale, C.
• Is Part Of: Journal of environmental management. Volume 322(2022)
• Publication Date: 2022-11-15
• Subjects: Riparian vegetation -- Riparian biomass -- LiDAR -- Point clouds -- Field measurements -- Concave hull method; ALS Airborne Laser Scanners -- ATTZ Aquatic-Terrestrial Transitional Zone -- CHS Concave Hull Slicing -- EBE Extensive Biomass Estimation -- FM Field-Measured -- LiDAR Light Detection And Ranging -- MAE Mean Absolute Error -- MBE Mean Bias Error -- RMSE Root Mean Square Error -- RTK-GNSS Real-Time Kinematic Global Navigation Satellite System -- TLS Terrestrial Laser Scanners; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2022.116046
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: The role of vegetation in supporting life on Earth is widely known. Nevertheless, the relevance of riparian corridors has been overlooked for a long time, leading to a dramatic reduction of vegetated buffers alongside them. Vegetation monitoring systems, including those for biomass estimation, are required to manage riparian corridors properly. Field surveys may support monitoring, but their usefulness is reduced by numerous drawbacks, therefore needing coupling with other data sources. The present work shows how Light Detection And Ranging (LiDAR) datasets can integrate targeted field measurements to estimate above-ground biomass at temperate or boreal latitudes and generate accurate biomass maps over large areas. By referring to the case study of the Orco river (northwest Italy), we defined a technique to reconstruct the geometry of an individual shrub from LiDAR point clouds. We tested the technique by comparing field measurements with Terrestrial and Airborne Laser Scanner data (TLS and ALS, respectively), assessing the former's superiority but the broader range of applicability of the latter. After these preliminary tests, we coupled the presented technique with a literature algorithm for individual tree detection, providing a more generalized procedure for the overall mapping and budgeting of riparian biomass based on ALS data. We applied the procedure to a fluvial bar of the Orco river, achieving a quantitative assessment of the shrub and tree biomass budget for 2019 and 2021 and visualizing the changes that occurred in that period. These results allowed us to shed light on the prevailing natural and anthropogenic processes in the investigated area and provide insights into the strengths and weaknesses of the proposed procedure. Graphical abstract: Image 1 Highlights: EBE is a new method to monitor and map riparian corridors by airborne laser scanners. EBE integrates airborne LiDAR and field data to yield biomass maps at the reach scale. Individual tree detection is combined with concave hull shrub geometry reconstruction. Terrestrial and airborne laser scanners are compared to estimate plant volume. Airborne LiDAR data need a field-based volume correction for vegetation mapping.