Root plates of uprooted trees – automatic detection and biotransport estimation using LiDAR data and field measurements

Abstract

The uprooting of trees is one of the most important biogeomorphological processes in temperate forests around the world. The direct cause of this process is the influence of hurricane-speed winds. However other factors (such as the features of soil, bedrock, topography, and stand) also play a significant role. Tree uprooting leads to the formation of root plates. Detecting the location of root plates may widen our knowledge about the contemporary impact of winds on forest ecosystem evolution. Tree uprooting involves the displacement of soil and weathered bedrock, and therefore may be considered in terms of biotransport (ie. transport of material caused by the impact of living organisms). Estimating the volume of the root plates can allow a better understanding of the scale and factors influencing the process of biotransport.Uprooted trees may be investigated with the use of LiDAR (Light Detection and Ranging) point clouds. Such data can provide a basis for creating Digital Surface Models (DSMs), which may be used to extract the location and estimate the volume of root plates. Previous research has focused on applying point clouds to detect 1) stems of fallen trees and 2) pit-mound topography. To date, as far as we know the LiDAR data were not applied to investigate root plates.The aim of the current project was to develop an automatic method for the detection of root plates and for biotransport estimation, based on point cloud data. Analysis was performed for two 100x100 m research plots located in the Babia Góra National Park (BgNP; Western Carpathians). The study plots were situated within the monitoring area established in 2005 following a catastrophic windstorm event that damaged the forest in November 2004. For the analysis two types of point clouds were applied: 1) open access point cloud from the Polish Institute of Geodesy and Cartography (minimal density: 4 points / m2, acquisition year: 2014) and 2) point cloud from BgNP (density: 40 - 55 points / m2, acquisition years: 2019-2020). Locations (GNSS receiver) and dimensions of 150 root plates measured in the field were used as validation data. DSMs in 0.25 m spatial resolution were created on the basis of three point classes: ground, low vegetation (< 0.2 m), and medium vegetation (< 2 m). Contour lines were generated every 0.1 m. Closed contours occurred frequently on the convex forms of root plates and therefore were used to extract the boundaries of potential root plates. Polygons created from closed contours were filtered using various criteria and compared to validation data to increase the accuracy of the method. The volume of root plates was estimated on the basis of DSMs and validated against the volume calculated from root plate dimensions measured in the field. The results underline the significance of LiDAR point clouds in the research on the tree uprooting process and the importance of GNSS technology to develop precise validation data with centimeter-level measurement accuracy.The study has been supported by the Polish National Science Centre (project no 2019/35/O/ST10/00032).