Eric C. Turnblom

Tree Species Detection Accuracies Using Discrete Point Lidar and Airborne Waveform Lidar

Species information is a key component of any forest inventory. However, when performing forest inventory from aerial scanning Lidar data, species classification can be very difficult. We investigated changes in classification accuracy while identifying five individual tree species (Douglas-fir, western redcedar, bigleaf maple, red alder, and black cottonwood) in the Pacific Northwest United States using two data sets: discrete point Lidar data alone and discrete point data in combination with waveform Lidar data. Waveform information included variables which summarize the frequency domain representation of all waveforms crossing individual trees. Discrete point data alone provided 79.2 percent overall accuracy (kappa = 0.74) for all 5 species and up to 97.8 percent (kappa = 0.96) when comparing individual pairs of these 5 species. Incorporating waveform information improved the overall accuracy to 85.4 percent (kappa = 0.817) for five species, and in several two-species comparisons. Improvements were most notable in comparing the two conifer species and in comparing two of the three hardwood species.

An objective approach for classifying precipitation patterns to study climatic effects on tree growth.

Abstract This study applied the simple, quantitative method of statistical cluster analysis to the task of objectively classifying precipitation patterns over northern California into paternally homogeneous regions. The statistical clustering results were then combined with geographical information to generate regional precipitation indices and study the relationship between precipitation levels and tree growth over specific areas. Generating regional indices replaces the often-used practice of associating growth rates with precipitation data from a single, ‘remote’ weather station, a station located outside the tree growth plot. Use of regional precipitation information generated in this manner can significantly improve the accuracy of growth predictions.

Fourier transformation of waveform Lidar for species recognition

In precision forestry, tree species identification is one of the critical variables of forest inventory. Lidar, specifically full-waveform Lidar, holds high promise in the ability to identify dominant hardwood tree species in forests. Raw waveform Lidar data contain more information than can be represented by a limited series of fitted peaks. Here we attempt to use this information with a simple transformation of the raw waveform data into the frequency domain using a fast Fourier transform. Some relationships are found among the influences of component frequencies across a given species. These relationships are exploited using a classification tree approach to separate three hardwood tree species native to the Pacific Northwest of the United States. We are able to correctly classify 75% of the trees ( 0.615) in our training data set. Each trees species was predicted using a classification tree built from all the other training trees. Two of the species grow in proximity and grow to a similar form, making differentiation difficult. Across all the classification trees built during the analysis, a small group of frequencies is predominantly used as predictors to separate the species.

Response of Three Young Douglas-Fir Plantations to Forest Fertilization with Low Rates of Municipal Biosolids

Abstract The growth of three young (5-6 years since planting) Douglas-fir plantations fertilized with a single low-rate application of municipal biosolids, ranging from 17-19 dry Mg ha-1, was studied. Stand measurements showed increases in DBH, height, average and total basal area, average and total volume and average and total dry-weight differences in the biosolids-fertilized vs. control. For instance, average per tree DBH was 14.7% greater than the controls, height by 2.7%, per stem basal area by 27%, per stem average volume by 33%, per stem average dry weight by 38%, basal area per hectare by 28%, volume per hectare by 32% and dry weight per hectare by 36% compared to untreated controls. Comparing differences in volume increases from initial growth periods with the latest growth period indicates that volume increases due to the biosolids treatment are continuing and apparently increasing over time. However, none of these observed differences were statistically significant (0.05 level) due to high variation within and between stands.

Effect of precommercial thinning followed by a fertilization regime on branch diameter in coastal United States Douglas-fir plantations

The effect of precommercial thinning in 6- to 13-year-old Douglas-fir (Pseudostuga menziesii (Mirb.) Franco var. menziesii) plantations with and without fertilization with 224 kgha -1 nitrogen (N) as urea on the mean diameter of the largest limb at breast height (DLLBH) was modeled. DLLBH is a simple, nondestructive field measurement related to log knot indices used to measure log quality in product recovery studies. Model (1) succeeded in predicting mean DLLBH (RMSE = 2.80 and radj 2 = 0.84) using only site, initial stocking, and treatment variables. Model (2), which used only mean tree variables, improved on model (1) and was simpler. However, model (3), which used a combination of both groups of variables, produced the best model. Model (4) successfully predicted mean DLLBH using variables that can be measured with light detection and ranging (LIDAR), a high-resolution remote sensing technology. Since the age when the live crown receded above breast height is an important variable in some of the models, model (5) was developed to predict when crown recession above breast height occurs. This study found that mean DLLBH of Douglas-fir plantations can be esti- mated using variables obtained from stand-level growth models or remote sensing, providing a quality indicator that can be easily measured and verified in the field.

Addressing Unknown Variability in Seemingly Fixed National Forest Estimates: Aboveground Forest Biomass for Renewable Energy

When determining the capacity of National Forests to develop sustainable bio-energy systems, accurate estimates of forest biomass are needed. What appears to be a straight forward assessment of biomass availability is complicated by the existence of highly variable data sets. Country level data is mostly produced by scaling data from a few sites to the country level. Using Indonesia as a case study, reported data varied by more than 20%. Using the reliable data, three levels of biomass potential, namely the lower and upper “bounds” (5,083 million Mg and 10,726 million Mg, respectively) and moderate estimates (5,410 million Mg) at the country level are constructed.

Nontraditional Use of Biomass at Certified Forest Management Units: Forest Biomass for Energy Production and Carbon Emissions Reduction in Indonesia

Biomass conversion technologies that produce energy and reduce carbon emissions have become more feasible to develop. This paper analyzes the potential of converting biomass into biomethanol at forest management units experiencing three forest management practices (community-based forest management (CBFM), plantation forest (PF), and natural production forest (NPF)). Dry aboveground biomass collected varied considerably: 0.26–2.16 Mg/ha/year (CBFM), 8.08–8.35 Mg/ha/year (NPF), and 36.48–63.55 Mg/ha/year (PF). If 5% of the biomass was shifted to produce biomethanol for electricity production, the NPF and PF could provide continuous power to 138 and 2,762 households, respectively. Dedicating 5% of the biomass was not a viable option from one CBFM unit. However, if all biomasses were converted, the CBFM could provide electricity to 19–27 households. If 100% biomass from two selected PF was dedicated to biomethanol production: (1) 52,200–72,600 households could be provided electricity for one year; (2) 142–285% of the electricity demand in Jambi province could be satisfied; (3) all gasoline consumed in Jambi, in 2009, would be replaced. The net carbon emissions avoided could vary from 323 to 8,503 Mg when biomethanol was substituted for the natural gas methanol in fuel cells and from 294 to 7,730 Mg when it was used as a gasoline substitute.

Predicting the Diameter of the Largest Breast-Height Region Branch of Douglas-Fir Trees in Thinned and Fertilized Plantations

Diameter of the largest limb in the breast height region (DLLBH) of trees is a good predictor of largest limb average diameter, a log knot index used in product recovery studies to predict product grade mix and value. DLLBH was measured on 2,252 Douglas-fir (Pseudostuga menziesii (Mirb.) Franco) trees from nine sites each with three plot pairs established at age 6 to 13 years. One of each pair was thinned, and the other was thinned and fertilized with 224 kg ha -1 N as urea at establishment and every four years thereafter. DLLBH was measured at age 21 to 31 years when BH branches were dead. Fractional polynomials were used to develop models to predict DLLBH. One model (r 2 adj = 0.69, root mean square error [RMSE] = 4.86) used only tree variables: diameter at breast height (DBH), total height, height to crown base, taper, and tree social position in the stand. A model that included treatment (if fertilized or not), stand density, and site index was a significant improvement (r 2 adj = 0.72, RMSE = 4.62). The tree-variables-only model and the combined tree and stand variables model can be used with individual tree growth models to estimate the distribution of tree DLLBH in a stand for use with process capability analysis to assess conformance with external tree quality specifications. A model using variables measurable with light detection and ranging and knowledge of site index and treatment history was also developed (r 2 adj = 0.56, RMSE = 5.78). This model suggests that there is an opportunity to use remote sensing to obtain and map (using a geographic information system) preharvest distributions of tree DLLBH in stands across a landscape for harvest scheduling and silvicultural planning.

Models of Knot Characteristics in Young Coastal US Douglas-Fir: Are the Effects of Tree and Site Data Visibly Rendered in the Annual Ring Width Pattern at Breast Height?

Abstract The large variation in knot characteristics within and between trees and stands makes proper interpretation of wood properties in the different steps along the forest–to–forest product con...