Tree species diversity is a key parameter to describe forest ecosystems. It is, for example, important for issues such as wildlife habitat modeling and close-to-nature forest management. We examined the suitability of 8-band WorldView-2 satellite data for the identification of 10 tree species in a temperate forest in Austria. We performed a Random Forest (RF) classification (object-based and pixel-based) using spectra of manually delineated sunlit regions of tree crowns. The overall accuracy for classifying 10 tree species was around 82% (8 bands, object-based). The class-specific producer’s accuracies ranged between 33% (European hornbeam) and 94% (European beech) and the user’s accuracies between 57% (European hornbeam) and 92% (Lawson’s cypress). The object-based approach outperformed the pixel-based approach. We could show that the 4 new WorldView-2 bands (Coastal, Yellow, Red Edge, and Near Infrared 2) have only limited impact on classification accuracy if only the 4 main tree species (Norway spruce, Scots pine, European beech, and English oak) are to be separated. However, classification accuracy increased significantly using the full spectral resolution if further tree species were included. Beside the impact on overall classification accuracy, the importance of the spectral bands was evaluated with two measures provided by RF. An in-depth analysis of the RF output was carried out to evaluate the impact of reference data quality and the resulting reliability of final class assignments. Finally, an extensive literature review on tree species classification comprising about 20 studies is presented.

Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data

https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/33377.pdf

Lidar sampling for large-area forest characterization: A review

Experiences from Nordic countries and Canada have shown that the retrieval of the stem volume and mean tree height of a tree or at stand level from laser scanner data performs as well as, or better than, photogrammetric methods, and better than other remote sensing methods. This paper reviews the methods of small-footprint airborne laser scanning for extracting forest inventory data, mainly in the boreal forest zone. The methods are divided into the following categories: extraction of terrain and canopy height model; feature extraction approaches (canopy height distribution and individual-tree-based techniques, techniques based on the synergetic use of aerial images and lidar, and other new approaches); tree species classification and forest growth using laser scanner; and the use of intensity and waveform data in forest information extraction. Despite this, the focus is on methods, some review of quality obtained, especially in the boreal forest area, is included. Several recommendations for future research are given to foster the methodology development.

Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests

Airborne lidar (Light Detection And Ranging) is a proven technology that can be used to accurately assess aboveground forest biomass and bio-energy feedstocks. The overall goal of this study was to develop a method for assessing aboveground biomass and component biomass for individual trees using airborne lidar data in forest settings typical for loblolly pine stands (Pinus taeda L.) in the southeastern United States. More specific objectives included: (1) assessing the accuracy of estimating diameter at breast height (dbh) for individual pine trees using lidar-derived individual tree measurements, such as tree height and crown diameter, and (2) investigating the use of lidar-derived individual tree measurements with linear and nonlinear regression to estimate per tree aboveground biomass. In addition, the study presents a method for estimating the biomass of individual tree components, such as foliage, coarse roots, stem bark, and stem wood, as derived quantities from the aboveground biomass prediction. A lidar software application, TreeVaW, was used to extract forest inventory parameters at individual tree level from a lidar-derived canopy height model. Lidar-measured parameters at individual tree level, such as height and crown diameter, were used with regression models to estimate dbh, aboveground tree biomass, and tree-component biomass. Field measurements were collected for 45 loblolly pine trees over 0.1- and 0.01-acre plots. Linear regression models were able to explain 93% of the variability associated with individual tree biomass, 90% for dbh, and 79–80% for components biomass.

Estimating biomass of individual pine trees using airborne lidar

Forest inventory and management requirements are changing rapidly in the context of an increasingly complex set of economic, environmental, and social policy objectives. Advanced remote sensing technologies provide data to assist in addressing these escalating information needs and to support the subsequent development and parameterization of models for an even broader range of information needs. This special issue contains papers that use a variety of remote sensing technologies to derive forest inventory or inventory-related information. Herein, we review the potential of 4 advanced remote sensing technologies, which we posit as having the greatest potential to influence forest inventories designed to characterize forest resource information for strategic, tactical, and operational planning: airborne laser scanning (ALS), terrestrial laser scanning (TLS), digital aerial photogrammetry (DAP), and high spatial resolution (HSR)/very high spatial resolution (VHSR) satellite optical imagery. ALS, in ...

https://tandfonline.com/doi/pdf/10.1080/07038992.2016.1207484

Remote Sensing Technologies for Enhancing Forest Inventories: A Review

This article reviews the research and application of airborne laser scanning for forest inventory in Finland, Norway and Sweden. The first experiments with scanning lasers for forest inventory were conducted in 1991 using the FLASH system, a full-waveform experimental laser developed by the Swedish Defence Research Institute. In Finland at the same time, the HUTSCAT profiling radar provided experiences that inspired the following laser scanning research. Since 1995, data from commercially operated time-of-flight scanning lasers (e.g. TopEye, Optech ALTM and TopoSys) have been used. Especially in Norway, the main objective has been to develop methods that are directly suited for practical forest inventory at the stand level. Mean tree height, stand volume and basal area have been the most important forest mensurational parameters of interest. Laser data have been related to field training plot measurements using regression techniques, and these relationships have been used to predict corresponding properti...

Laser scanning of forest resources: the nordic experience

Individual tree crowns can be delineated from dense airborne laser scanning (ALS) data and their species can be classified from the spatial distribution and other variables derived from the ALS data within each tree crown. This study reports a new clustering approach to delineate tree crowns in three dimensions (3-D) based on ellipsoidal tree crown models (i.e., ellipsoidal clustering). An im-portant feature of this approach is the aim to derive information also about the understory vegeta-tion. The tree crowns are delineated from echoes derived from full-waveform (fwf) ALS data as well as discrete return ALS data with first and last returns. The ellipsoidal clustering led to an im-provement in the identification of tree crowns. Fwf ALS data offer the possibility to derive also the echo width and the amplitude in addition to the 3-D coordinates of each echo. In this study, tree species are classified from variables describing the fwf (i.e., the mean and standard deviation of the echo amplitude, echo width, and total number of echoes per pulse) and the spatial distribution of the clusters for pine, spruce, birch, oak, alder, and other species. Supervised classification is done for 68 field plots with leave-one-out cross-validation for one field plot at a time. The total accuracy was 71% when using both fwf and spatial variables, 60% when using only spatial variables, and 53% when using discrete return data. The improvement was greatest for discriminating pine and spruce as well as pine and birch.

/pdf/delineation-of-tree-crowns-and-tree-species-classification-13johkyfj1.pdf

Delineation of Tree Crowns and Tree Species Classification From Full-Waveform Airborne Laser Scanning Data Using 3-D Ellipsoidal Clustering

Early results from automatic tree species discrimination, using the Z/I DMC digital aerial photographic camera are reported. The position of single trees is identified using template matching techniques and spectral data are extracted from the sunlit part of each detected tree crown. The imagery was acquired in mid-October 2003 for a test site in western Sweden. A discriminant analysis based on canopy colour yielded 88.7% overall accuracy when discriminating between Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and deciduous trees. The promising results are of great practical interest since the Swedish National Land Survey has recently acquired a Z/I DMC camera.

Tree species discrimination using Z/I DMC imagery and template matching of single trees

Miljoovervakningsprogrammet Nationell Inventering av Landskapet i Sverige (NILS) bygger pa en kombination av faltinventering och flygbildstolkning och ger ett dataunderlag for att skatta tillstand ...

Utveckling av metodik för flygbildstolkning inom NILS landskapsrutor (5x5 km)

Flygburen laserskanning har under de senaste 15 aren blivit en datakalla for skogsbruksplanering. Data fran flygburen laserskanning ar noggranna tredimensionella matningar av mark och vegetation med laserljus fran ett flygplan eller helikopter.Flygburna laserdata kan kombineras med referensdata fran faltobservationer for att automatiskt ta fram heltackande skogsskattningar.Skogsagare och skogsforvaltare kan anvanda resultaten for battre planering av avverkningar och naturvard.Om man mater tillrackligt tatt kan enskilda trad identifieras i laserdata. Detta ger nya mojligheter att effektivt beskriva bade diameterfordelningar och tradslag for stora omraden.

Johan Holmgren

Papers

Laser scanning of forest resources: the nordic experience

Delineation of Tree Crowns and Tree Species Classification From Full-Waveform Airborne Laser Scanning Data Using 3-D Ellipsoidal Clustering

Tree species discrimination using Z/I DMC imagery and template matching of single trees

Utveckling av metodik för flygbildstolkning inom NILS landskapsrutor (5x5 km)

Flygburen laserskanning för skogliga skattningar