Lennart Noordermeer

• PhD
• Researcher at Norwegian Institute of Bioeconomy Research

Errors in forest inventory data can lead to sub-optimal management decisions and dramatic economic losses. Forest inventory approaches are typically evaluated by their levels of precision and accuracy; however, this overlooks the specific usefulness of the data in decision-making. By evaluating the value of information (VoI), we can assess the usef...

Tree species composition is essential information for forest management and remotely sensed (RS) data have proven to be useful for its prediction. In forest management inventories, tree species are commonly interpreted manually from aerial images for each stand, which is time and resource consuming and entails substantial uncertainty. The objective...

In prediction of forest parameters with data from remote sensing (RS), regression models have traditionally been trained on a small sample of ground reference data. This paper proposes to impute this sample of true prediction targets with data from an existing RS-based prediction map that we consider as pseudo-targets. This substantially increases...

Bitemporal airborne laser scanning (ALS) data are increasingly being used in forest management inventories for the determination of site index (SI). SI determination using bitemporal ALS data requires undisturbed height growth of dominant trees. Therefore, areas with disturbed top height development are unsuitable for SI determination, and should b...

The main objective of this study was to demonstrate a method for monitoring tree occupancy and height in the alpine treeline ecotone using a time series of ALS data. We applied data collected in a longitudinal survey, comprising three spatially consistent campaigns from the years 2008, 2012 and 2018, on 25 sites along the Scandinavian Mountain Rang...

Stem frequency distributions provide useful information for pre-harvest planning. We compared four inventory approaches for imputing stem frequency distributions using harvester data as reference data and predictor variables computed from airborne laser scanner (ALS) data. We imputed distributions and stand mean values of stem diameter, tree height...

Newly developed positioning systems in cut-to-length harvesters enable georeferencing of individual trees with submeter accuracy. Together with detailed tree measurements recorded during processing of the tree, georeferenced harvester data are emerging as a valuable tool for forest inventory. Previous studies have shown that harvester data can be l...

Cut-to-length harvesters collect detailed information on the dimensions and characteristics of individual harvested trees. When equipped with global navigation satellite system (GNSS) receivers and motion sensors, the obtained measurements can be linked to locations of single harvested trees, benefitting a range of forest inventory applications. We...

Forest productivity is a crucial variable in forest planning, usually expressed as site index (SI). In Nordic commercial forest inventories, SI is commonly estimated by a combination of aerial image interpretation, field assessment and information obtained from previous inventories. Airborne laser scanning (ALS) and digital aerial photogrammetry (D...

Site index (SI) indicates the magnitude of timber production that can be realized at a given site and is a crucial variable in forest planning. In Norwegian forest management inventories, SI is commonly quantified with large uncertainty by means of aerial image interpretation, field assessment and information from previous inventories. Airborne las...

Forest productivity reflects the wood production capacity of a given site and provides crucial information for forest management planning. The most widely accepted measure of forest productivity is site index (SI), defined as the average height of dominant trees at a given index age. In forest management inventories, SI is commonly interpreted manu...

Changes in forest areas have great impact on a range of ecosystem functions, and monitoring forest change across different spatial and temporal resolutions is a central task in forestry. At the spatial scales of municipalities, forest properties and stands, local inventories are carried out periodically to inform forest management, in which airborn...

Airborne laser scanning (ALS) data provide a detailed representation of forest canopy structure and are highly suitable for forest inventory applications. Providing three-dimensional data at a lower cost, digital aerial photogrammetry (DAP) has emerged as an alternative to ALS. Previous studies have compared the utility of ALS and DAP data for pred...

Predicting attributes of young forest is crucial for making sylvicultural treatment decisions in forest management planning. However, producing accurate predictions of such attributes is challenging. In this study, airborne laser scanning (ALS) data were used to develop, compare, and validate various methods for inventory of young forest, and to de...