Francesca Giannetti

Comparing Three Different Ground Based Laser Scanning Methods for Tree Stem Detection

A forest inventory is often carried out using airborne laser data combined with ground measured reference data. Traditionally, the ground reference data have been collected manually with a caliper combined with land surveying equipment. During recent years, studies have shown that the caliper can be replaced by equipment and methods that capture the ground reference data more efficiently. In this study, we compare three different ground based laser measurement methods: terrestrial laser scanner, handheld laser scanner and a backpack laser scanner. All methods are compared with traditional measurements. The study area is located in southeastern Norway and divided into seven different locations with different terrain morphological characteristics and tree density. The main tree species are boreal, dominated by Norway spruce and Scots pine. To compare the different methods, we analyze the estimated tree stem diameter, tree position and data capture efficiency. The backpack laser scanning method captures the data in one operation. For this method, the estimated diameter at breast height has the smallest mean differences of 0.1 cm, the smallest root mean square error of 2.2 cm and the highest number of detected trees with 87.5%, compared to the handheld laser scanner method and the terrestrial laser scanning method. We conclude that the backpack laser scanner method has the most efficient data capture and can detect the largest number of trees.

European Forest Types: toward an automated classification

Key messageThe outcome of the present study leads to the application of a spatially explicit rule-based expert system (RBES) algorithm aimed at automatically classifying forest areas according to the European Forest Types (EFT) system of nomenclature at pan-European scale level. With the RBES, the EFT system of nomenclature can be now easily implemented for objective, replicable, and automatic classification of field plots for forest inventories or spatial units (pixels or polygons) for thematic mapping.ContextForest Types classification systems are aimed at stratifying forest habitats. Since 2006, a common scheme for classifying European forests into 14 categories and 78 types (European Forest Types, EFT) exists.AimsThis work presents an innovative method and automated classification system that, in an objective and replicable way, can accurately classify a given forest habitat according to the EFT system of nomenclature.MethodsA rule-based expert system (RBES) was adopted as a transparent approach after comparison with the well-known Random Forest (RF) classification system. The experiment was carried out based on the information acquired in the field in 2010 ICP level I plots in 17 European countries. The accuracy of the automated classification is evaluated by comparison with an independent classification of the ICP plots into EFT carried out during the BioSoil project field survey. Finally, the RBES automated classifier was tested also for a pixel-based classification of a pan-European distribution map of beech-dominated forests.ResultsThe RBES successfully classified 94% of the plots, against a 92% obtained with RF. When applied to the mapped domain, the accuracy obtained with the RBES for the beech forest map classification was equal to 95%.ConclusionThe RBES algorithm successfully automatically classified field plots and map pixels on the basis of the EFT system of nomenclature. The EFT system of nomenclature can be now easily and objectively implemented in operative transnational European forest monitoring programs.

Deadwood distribution in European forests

ABSTRACT National forest inventories are a primary source of data for the assessment of forest resources and lastly more often biodiversity at national scales. The diversity of adopted sampling designs and measurements reduces the prospect for a reliable comparison of generated estimates. The ICP Forest dataset represents a unique opportunity for a standardized approach of forest estimates through Europe. This work aims to provide a distribution map of the mean deadwood volume in European forest. A total of 3243 ICP Forests plots were analysed and presented. The study area extends over 3,664,576 km2 interesting 19 countries. We observed that the highest percentage of plots show a deadwood volume lower than 50 m3 ha−1, with a few of forests attaining around the maximum of 300 m3 ha−1. Forests with more than 100 m3 ha−1 are concentrated in mountainous regions, central Europe and other regions, linked to high-forest management types, while coppices-derived forest systems (part of the Great Britain, Mediterranean region) show lower deadwood content. The map of deadwood volume on European Forests is of interests for scientists, land planners, forest managers and decision-makers, as a reference for further evaluation of changes, stratified sampling, ground reference for model validation, restoration and conservation purposes.

Photogrammetric estimation of wheel rut dimensions and soil compaction after increasing numbers of forwarder passes

ABSTRACT Compaction and rutting on forest soils are consequences of harvesting operations. The traditional methods used to investigate these consequences are time consuming and unable to represent the entire longitudinal profile for a forest trail. New methods based on photogrammetry have been developed. The overall objective was to compare photogrammetry and traditional methods (e.g. cone penetrometer, manual rut depth measurements, bulk density and porosity) used for the evaluation of soil compaction and rutting (i.e. depth and rut volume) after multiple passes of a loaded forwarder using two different tyre pressure levels. The comparison of photogrammetric versus manually measured profiles resulted in R2 0.93. Both tyre inflation pressure and number of passes had effect on soil disturbance. The rut volumes on 100 m long trails after 60 passes were 8.48 and 5.74 m3 for tire pressures of 300 and 150 kPa, respectively. Increased rut volume correlated positively with increased soil compaction and decreased soil porosity. Structure-from-motion photogrammetry is an accurate method for informing the creation of high-resolution digital evolution models and for the morphological description of forest soil disturbance after forest logging. However, a problem with photogrammetry is object reflection (grass, logging residues and water) that in some cases influence the accuracy of the method.

Integrating terrestrial and airborne laser scanning for the assessment of single-tree attributes in Mediterranean forest stands

ABSTRACT The development of laser scanning technologies has gradually modified methods for forest mensuration and inventory. The main objective of this study is to assess the potential of integrating ALS and TLS data in a complex mixed Mediterranean forest for assessing a set of five single-tree attributes: tree position (TP), stem diameter at breast height (DBH), tree height (TH), crown base height (CBH) and crown projection area radii (CPAR). Four different point clouds were used: from ZEB1, a hand-held mobile laser scanner (HMLS), and from FARO® FOCUS 3D, a static terrestrial laser scanner (TLS), both alone or in combination with ALS. The precision of single-tree predictions, in terms of bias and root mean square error, was evaluated against data recorded manually in the field with traditional instruments. We found that: (i) TLS and HMLS have excellent comparable performances for the estimation of TP, DBH and CPAR; (ii) TH was correctly assessed by TLS, while the accuracy by HMLS was lower; (iii) CBH was the most difficult attribute to be reliably assessed and (iv) the integration with ALS increased the performance of the assessment of TH and CPAR with both HMLS and TLS.