Murray Woods

Government of Ontario, North Bay, Ontario Canada

Trees can differ enormously in their crown architectural traits, such as the scaling relationships that link their height and crown size to their stem diameter. Yet despite the importance of crown architecture in shaping the structure and function of woody ecosystems, we lack a complete picture of what drives this incredible diversity in crown shap...

Forest productivity is a key driver of forest growth and yield and a critical information need for forest management and planning. Traditionally, this information has come from field plots, but these are expensive to measure and have limited coverage. Remote sensing, on the other hand, can provide forest inventory attributes on landscape scales and...

Forest canopy vertical layering influences stand development and yield and is critical information for forest management planning and wood supply analysis. It is also relevant for other applications including habitat modelling, forest fuels management and assessing forest resilience. Forest inventories that use coincident airborne Light Detection a...

Establishing field inventories can be labor intensive, logistically challenging and expensive. Optimizing a sample to derive accurate forest attribute predictions is a key management-level inventory objective. Traditional sampling designs involving pre-defined, interpreted strata could result in poor selection of within-strata sampling intensities,...

Species identification is a critical factor for obtaining accurate forest inventories. This paper compares the same method of tree species identification (at the individual crown level) across three different types of airborne laser scanning systems (ALS): two linear lidar systems (monospectral and multispectral) and one single-photon lidar (SPL) s...

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research - from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring prog...

Le secteur forestier canadien a besoin d’information détaillée au sujet de la quantité et des caractéristiques des ressources forestières. Pour répondre à de tels besoins, des systèmes d’inventaire exacts, complets et opportuns qui quantifient spatialement le bois d’œuvre et les autres services écosystémiques liés aux forêts sont nécessaires. Le pr...

The Canadian forest sector requires detailed information regarding the amount and characteristics of the forest resource. To address these needs, inventory systems that spatially quantify timber and other forest related ecosystem services are required, that are accurate, comprehensive and timely. The Assessment of Wood properties using Remote Sensi...

Purpose of Review The increasing availability of three-dimensional point clouds, including both airborne laser scanning and digital aerial photogrammetry, allow for the derivation of forest inventory information with a high level of attribute accuracy and spatial detail. When available at two points in time, point cloud datasets offer a rich source...

A Publisher Correction to this paper has been published: https://doi.org/10.1007/s40725-021-00139-6

Accurate digital elevation models are key data products used to inform forest management. Light detection and ranging (lidar) technologies have emerged as a useful tool for acquiring detailed terrain information, although the accuracy of this data is known to vary with topographic complexity and the density and characteristics of overlying vegetati...

Airborne laser scanning (ALS; LiDAR) data are an increasingly common data source for forest inventories, and approaches integrating ALS data with field plot measurements have become operational in several jurisdictions. As technology continues to evolve, different LiDAR sensors can provide new opportunities to incorporate LiDAR data into forest inv...

The ability to expand the use of predictive Airborne Laser Scanning (ALS)-derived Forest Resource Inventory (FRI) models to broader regional scales is crucial for supporting large scale sustainable forest management. This research examined the transferability of ALS-based FRI attributes between two forest estates located in the eastern and western...

The value of combining Landsat time series and airborne laser scanning (ALS) data to produce regional maps of forest structure has been well documented. However, studies are often performed over single study areas or forest types, preventing a robust assessment of the approaches that produce the most accurate estimates. Here, we use Landsat time se...

The pace of technological change in forest inventory and monitoring over the past 50 years has been remarkable, largely asa result of the increased availability of various forms of remotely sensed data. Benchmarking sites, with the requisite refer-ence and baseline data for evaluating the capacities of new technologies, algorithms, and approaches,...

Forest understory vegetation is an important characteristic of the forest. Predicting and mapping understory is a critical need for forest management and conservation planning, but it has proved difficult with available methods to date. LiDAR has the potential to generate remotely sensed forest understory structure data, but this potential has yet...

Spatial models that provide estimates of wood quality enable value chain optimization approaches that consider the market potential of trees prior to harvest. Ecological land classification units (e.g., ecosite) and structural metrics derived from Airborne Laser Scanning (ALS) data have been shown to be useful predictors of wood quality attributes...

Forest understory vegetation is an important feature of wildlife habitat among other things. Predicting and mapping understory is a critical need for forest management and conservation planning, but it has proved difficult. LiDAR has the potential to generate remotely sensed forest understory structure data, yet this potential has to be fully valid...

Over the last decade, spatially-explicit modeling of landscape-scale forest attributes for forest inventories has greatly benefitted from airborne laser scanning (ALS) and the area-based approach (ABA) to derive wall-to-wall maps of these forest attributes. Which ALS-derived metrics to include when modeling forest inventory attributes, and how pred...

Forest inventory attributes need to be updated regularly to accurately reflect continually changing forest conditions due to fire, harvesting, natural succession, insect infestation and climate change. A data fusion of multispectral satellite images, existing high-resolution Digital Surface Models (DSM) and Shuttle Radar Topographic Mission (SRTM)...

In this study, we demonstrate the potential of using high spatial resolution airborne imagery to characterize the structural development stages of forest canopies. Four forest succession stages were adopted: stand initiation, young multistory, understory reinitiation, and old growth. Remote sensing metrics describing the spatial patterns of forest...

SkyForest (TM) combines shuttle radar topography mission (SRTM) elevations, multispectral Landsat images and existing digital surface models (DSMs) at high-resolution, to produce a digital terrain model (DTM) under forest canopy. It can be calibrated with ground plots to produce forest inventory data with RMSEs comparable but generally larger than...

Our objective was to model the average wood density in black spruce trees in representative stands across a boreal forest landscape based on relationships with predictor variables extracted from airborne light detection and ranging (LiDAR) point cloud data. Increment core samples were collected from dominant or co-dominant black spruce trees in a n...

Globally, there is a growing desire to predict and map the spatial distribution of soil depth on the landscape due to its numerous roles in areas such as agriculture, forestry, hydrology and ecological land classification. The aim of this study was to develop a technique to model and map soil depth classes based on GIS-fuzzy logic modeling approach...

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools w...

Airborne Laser Scanning (ALS) metrics have been used to develop area-based forest inventories; these metrics generally include estimates of stand-level, per hectare values and mean tree attributes. Tree-based ALS inventories contain desirable information on individual tree dimensions and how much they vary within a stand. Adding size class distribu...

This study aims to provide detailed spatial information of valuable tree species to support improved management of winter habitat of white-tailed deer. To achieve this, we proposed a novel approach using information from two spatial scales and a suite of methods for analysis and classification of remotely sensed data. High-spatial resolution, multi...

There is a growing global need to generate high resolution digital soil maps for numerous ecological applications. We aim to address this issue by modeling and mapping soil texture using Geographic Information Systems (GIS) and fuzzy logic techniques over parts of the Clay Belt and Hornepayne region in Ontario, Canada as a case study. This was perf...

The decline of the woodland caribou population is a result of their habitat loss. To conserve the habitat of the woodland caribou and protect it from extinction, it is critical to accurately characterize and monitor its habitat. Conventionally, products derived from low to medium spatial resolution remote sensing data, such as land cover classifica...

Point clouds derived from the photogrammetric pixel matching of 35-cm Leica ADS40 imagery (similar to 2.4 points/m(2)) were compared to those derived from airborne laser scanning (ALS; 1.1 returns/m(2)) in terms of their capacity to predict core forest inventory attributes at 400-m(2) resolution on a boreal landscape in northeastern Ontario, Canada...

The ecosite unit in Ontario‘s boreal forest ecological land classification system is a polygon of common vegetation type and soil conditions intended to provide a standardized provincial framework to inform meso-scale forestry and planning applications. To determine whether the physical factors used for ecosite classification relate to patterns in...

Practitioner's Corner

Parametric and nonparametric predictions of forest inventory attributes from airborne LiDAR data are compared for a forest management unit in boreal Ontario. For the parametric approach, seemingly unrelated regression models were calibrated by forest type (SUR) and for all forest types combined (SUR_All). For the nonparametric approach, randomFores...

A best practice guide brings together state-of-the-art approaches, methods, and data to provide non-experts more detailed information about complex topics. With this guide, our goal is to inform and enable readers interested in using airborne laser scanning (ALS; also referred to as Light Detection and Ranging [LiDAR]) data to characterize, in an o...

Ce guide de pratiques exemplaires comprend des approches, des méthodes et des données de pointe afin de fournir aux profanes des renseignements précis sur des enjeux complexes. Grâce à ce guide, nous espérons informer les lecteurs qui souhaitent utiliser des données par balayage laser aéroporté (BLA), aussi appelé détection et télémétrie par ondes...

Airborne Laser Scanning (ALS), also known as Light Detection and Ranging (LiDAR) enables an accurate three-dimensional characterization of vertical forest structure. ALS has proven to be an information-rich asset for forest managers, enabling the generation of highly detailed bare earth digital elevation models (DEMs) as well as estimation of a ran...

Over the past two decades there has been an abundance of research demonstrating the utility of airborne light detection and ranging (LiDAR) for predicting forest biophysical/inventory variables at the plot and stand levels. However, to date there has been little effort to develop a set of protocols for data acquisition and processing that would mov...

22In 2009, five unique methods were used to inspect vegetation-related conditions along Bonneville Power Administration (BPA) rights-of-way (ROW). Some methods were trials that BPA committed to execute as part of a settlement with its regional regulatory organization, the Western Electric Coordination Council (WECC), for violations of reliability s...

An existing Light Detection and Ranging (LiDAR) data set captured on the Romeo Malette Forest near Timmins, Ontario, was used to explore and demonstrate the feasibility of such data to enrich existing strategic forest-level resource inventory data. Despite suboptimal calibration data, stand inventory variables such as top height, average height, ba...

This study investigates the ability to predict forest diameter distributions from light detection and ranging (LiDAR) data using Weibull modelling for forest stands in central Ontario. Results suggest that the unimodal 2-parameter Weibull model is a promising technique for the prediction of diameter class distributions, with strong relationships ev...

Models were developed to predict forest stand variables for common species of the Great Lakes - St. Lawrence forest of central Ontario, Canada from light detection and ranging (LiDAR) data. Stands that had undergone various ranges of partial harvesting or initial spacing treatments from multiple geographic sites were considered. A broad forest stra...

In Ontario, yield tables for forest management planning have remained relatively unchanged since initial work in the 1950s that was based on a limited number of temporary sample plots. In 2000, the Forestry Research Partnership accelerated work on the Benchmark Yield Curve Project (initiated several years earlier by the Ontario Ministry of Natural...

The province of Ontario holds approximately 70.2 million hectares of forests: about 17% of Canada's and 2% of the world's forests. Approximately 21 million hectares are managed as commercial forests, with an annual harvest in the early part of the decade approaching 200 000 ha. Yield tables developed by Walter Plonski in the 1950s provide the basis...

Forest species classification is important for forest management and environment monitoring and protection. As the conventional methods are mainly based on the spectral signatures of forest canopies and the results are at stand level. With the high spatial resolution data, classification at individual tree level becomes achievable. The objective of...

The Ontario Ministry of Natural Resources is leading a government-industry partner-ship to develop an Ontario variant of the Forest Vegetation Simulator (FVS). Based on the Lake States variant and the Prognosis BC user-interface, the FVS Ontario project is motivated by a need to model the impacts of intensive forest management strategies and the mu...

The forest vegetation simulator (FVS) model was calibrated for use in Ontario, Canada, to predict the growth of forest stands. Using data from permanent sample plots originating from different regions of Ontario, new models were derived for dbh growth rate, survival rate, stem height and species group density index for large trees and height and db...

We used data from hardwood-dominated permanent sample plots in Ontario to estimate the probability of a tree falling during the 5 year period in which it dies ("tree fall"), and likewise the 5 year probability of snag fall. Tree fall probabilities ranged from 5% to 31% across species, with smaller dead trees more likely to be downed than larger one...

The Lake States variant of the FVS (Forest Vegetation Simulator) model (LS-FVS), also known as the LS-TWIGS variant of FVS, was validated for black spruce (Picea mariana (Mill.) BSP), white spruce (Picea glauca (Moench) Voss), jack pine (Pinus banksiana Lamb.) and trembling aspen (Populus tremuloides Michx.) forests in northern Ontario. Individual-...

The response of good and poor clones of trembling aspen (Populus tremuloides Michx) to thinning was assessed 16 years after treatment. Prior to the thinning treatment, the clones had been assessed as either poor or good using a rating matrix that considered height, diameter, quality and vigour of the clones. Results indicate that the 250 largest DB...

Density management diagrams (DMD's) have been developed for a wide range of North American tree species. They have proven to be an excellent exploratory tool in understanding the interaction of density, average tree volume and diameter within a forest stand. DMD's have been recently promoted as a suitable tool for determining timing and extent of s...

The individual-tree, distance-independent stand growth simulator NE-TWIGS has been tested for Ontario's tolerant hardwood stands using data from long-term permanent sample plots. NE-TWIGS provides reliable short-term (5-year) predictions of stand basal area (modelling efficiency from 77% to 99%), but in longer projections the efficiency of the mode...

SILVAH, a stand growth simulator commonly used in the northeastern United States, has been evaluated by comparing predicted and actual growth of tolerant hardwoods in southern Ontario. The data came from 139 stands, unmanaged or managed (thinned), even-aged or uneven-aged. The data were used to test the accuracy of diameter distribution, basal area...

Growth and yield projections aid foresters in assessing timber management opportunities and in making management decisions. With these uses, questions arise about the reliability and limits of growth and yield simulators. Using long-term studies of hardwood stands in Ontario the growth simulator FIBER 3.0 has been tested, Short-term (5 years) proje...

As part of an objective of maintaining wood supply on a shrinking land base, Tembec initiated a project in Ontario to improve the yield estimates for their land base. Using permanent sample plot data from provincial, federal, and industrial sources, stand level empirical yield curves were developed for the major forest types. The plots represent a...

Literature from the past two decades documents how airborne LIDAR can be used to predict forest inventory variables, such as basal area, volume, and biomass, at the plot and stand level. However, a key question that has yet to be fully addressed, and that the forest industry continues to ask as it considers operationalizing the use of LIDAR in fore...