A Workflow to Extract the Geometry and Type of Vegetated Landscape Elements from Airborne LiDAR Point Clouds

Ine Rosier,Jos Van Orshoven,Jan Diels,Ben Somers

doi:10.3390/rs13204031

Abstract

Rural European landscapes are characterized by a variety of vegetated landscape elements. Although it is often not their main function, they have the potential to affect river discharge and the frequency, extent, depth and duration of floods downstream by creating both hydrological discontinuities and connections across the landscape. Information about the extent to which individual landscape elements and their spatial location affect peak river discharge and flood frequency and severity in agricultural catchments under specific meteorological conditions is limited. This knowledge gap can partly be explained by the lack of exhaustive inventories of the presence, geometry, and hydrological traits of vegetated landscape elements (vLEs), which in turn is due to the lack of appropriate techniques and source data to produce such inventories and keep them up to date. In this paper, a multi-step methodology is proposed to delineate and classify vLEs based on LiDAR point cloud data in three study areas in Flanders, Belgium. We classified the LiDAR point cloud data into the classes ‘vegetated landscape element point’ and ‘other’ using a Random Forest model with an accuracy classification score ranging between 0.92 and 0.97. The landscape element objects were further classified into the classes ‘tree object’ and ‘shrub object’ using a Logistic Regression model with an area-based accuracy ranging between 0.34 and 0.95.

Highlights

The European agricultural landscape is characterized by a range of landscape elements, both vegetated like hedges and lines of trees and non-vegetated like ditches and sunken roads. vegetated landscape elements (vLEs) include natural elements growing spontaneously across the landscape, but encompass predominantly vLEs from anthropogenic origin such as hawthorn hedges planted on plot boundaries. vLEs are often linearly shaped and are frequently situated on the border between agricultural fields where they provide a multitude of agroecosystem services [1]
The workflow that was developed and applied to extract the geometric characteristics of shrub and tree-based types of vLE from airborne high-resolution LiDAR point clouds consists of seven steps (Figure 3): (1) preprocessing of the LiDAR point data, (2) characterisation of each of the LiDAR points by a set of features extracted from the neighbouring
‘vLE point’ or ‘other non-ground point’ by using a Random Forest classifier were evaluated in the testing phase by calculating the recall, precision and overall accuracy from the confusion matrix (Table 5)

Summary

Introduction

The European agricultural landscape is characterized by a range of landscape elements, both vegetated (vLE) like hedges and lines of trees and non-vegetated like ditches and sunken roads. vLEs include natural elements growing spontaneously across the landscape, but encompass predominantly vLEs from anthropogenic origin such as hawthorn hedges planted on plot boundaries. vLEs are often linearly shaped and are frequently situated on the border between agricultural fields where they provide a multitude of agroecosystem services [1]. VLEs are often linearly shaped and are frequently situated on the border between agricultural fields where they provide a multitude of agroecosystem services [1] They act as a habitat and movement corridor for animals and plant species and have a key role in the maintenance of biodiversity in intensive agricultural landscapes [2,3,4]. Their typical geometrical arrangement following the edges of agricultural parcels and their association with non-vegetated elements like ditches and fences creates networks of landscape elements [5].

Methods

Results

Discussion

Conclusion