《中南林业调查规划》性质及学科分类

根据期刊性质和学科分类方法,以文献数量对《中南林业调查规划》进行分类,以明确其性质和学科归属。研究表明,《中南林业调查规划》2010年刊登的论文以学术性为主,林业类文献占当年文献总量的的56.52%,其余学科文献量较少,不能划入相应学科,因此应将该刊归类为林业类专业学术期刊。     

Determination of Mean Tree Height of Forest Stands by Digital Photogrammetry

The mean tree height of 73 forest stands in a 1000 ha forest area was determined from canopy heights generated by automatic image matching using a digital photogrammetric workstation and digitized panchromatic aerial photographs with a scale of 1:15 000. First, the mean height of each stand was computed as the arithmetic mean of the quantile corresponding to the 75th percentile of the distribution of the canopy heights from the image matching within square grid cells with cell sizes of 236-400 m². The mean heights from the image matching underestimated the true heights by 5.42 m. Secondly, field-measured mean tree heights of 165 georeferenced sample plots distributed systematically throughout the 1000 ha forest area were regressed against the mean heights derived from the image matching. The regression equations were used to predict the mean heights of the 73 stands. In very young forest stands, the predicted mean heights overestimated the true heights by 0.4 m and the precision was 0.9-1.0 m. In young and mature stands, the average difference between predicted height and ground-truth ranged between -1.6 and 0.5 m, and the precision ranged from 1.1 to 2.1 m.     

基于RFID技术的图书盘点方式初探——以国家图书馆中文图书外借室为例

图书盘点工作是图书馆室藏文献管理的一项基本而又重要的工作。介绍了RFID技术条件下进行图书盘点的两种方法 (期末盘点法和循环盘点法)的基本原理及应用情况,并对二者进行了对比分析,指出在实际盘点操作过程中需要注意的一些问题。     

贮木场原木结存系数探讨

"结存系数"是贮木场设计的主要技术指标.本文拟就兴隆林业局的具体实践对现代贮木场的适宜结存系数做以探讨.     

Analysis of regional variation of height growth and slenderness in populations of six urban tree species using a quantile regression approach

Inventory data of six urban tree species from seven cities across Germany were used to model regional variation of height growth, allometric scaling, and slenderness over a wide range of size and age using a quantile regression approach. Variation within and between species and cities was large. Height did not reach an asymptote but declined at higher ages, presumably because of reduction cuts. Allometric scaling and slenderness varied with wind climate, modulus of elasticity, and coefficient of drag. Our data do not support the use of a threshold value of slenderness in tree risk assessment.     

基于生命周期评价的木结构环境影响评价方法

为了完善木结构建筑的环境影响评价方法,基于生命周期评价体系和国内外学者建立的关于建筑物的生命周期评价模型,对我国木结构建筑的环境影响评价方法进行了研究,阐述了木结构建筑生命周期评价的4个步骤：确定目标与范围、清单分析、影响评价和结果解释,着重介绍了木结构建筑的环境影响评价,指出了木结构建筑生命周期评价的发展方向.     

Comparison of Forest Inventory and Analysis surveys, basal area models, and fitting methods for the aspen forest type in Minnesota

The Forest Inventory and Analysis (FIA) unit of the U.S. Forest Service has collected, compiled, and made available plot data from three measurement periods (identified as 1977, 1990, and 2003, respectively) within Minnesota. Yet little if any research has compared the relative utility of these datasets for developing empirical yield models. This paper compares these and other subdatasets in the context of fitting a basal area (B) yield model to plot data from the aspen (Populus tremuloides Michx.) forest type. In addition, several models and fitting methods are compared for their applicability and stability over time. Results suggest that the three parent datasets, along with their subdatasets, provide very similar three parameter B yield model prediction capability, but as model complexity increases, variability in coefficient estimates increases between datasets. The absence of data for older aspen stands and the inherent noise within B data prevented the exact determination of an overall best model. However, the model B = b₁S^b₂(1 − exp( − b₃A)) with site index (S) and stand age (A) as predictors was found consistently among the highest in precision and stability. Additionally, nonlinear least squares and nonlinear mixed-effects fitting procedures produced similar model fits, but the latter is preferred for its potential to improve model projections. The results indicate little practical difference between datasets from different time periods and different sizes when used for fitting the models. Additionally, these results will likely extend to other states or regions with similar remeasurement data on aspen and other forest types, thus facilitating the development of other ecological models focused on forest management.     

Tree Species Classification using Semi-automatic Delineation of Trees on Aerial Images

The purpose of this study was to develop a method for classifying tree species from remote sensing images by combining a semi-automatic pattern recognition technique and spectral properties of trees. Five stands in southern Finland were studied. Individual trees in the digital colour infrared (CIR) aerial photographs were segmented by a method based on the recognition of tree crown patterns at subpixel accuracy. The images were filtered with the Gaussian N-by-N smoothing operator and local maxima above a threshold level were segmented. The segments were classified into three tree species classes. The kappa coefficients for stands varied from 0.43 to 0.86 when the training data and test data were from the same aerial photograph. When training data from other photographs were used as reference data, the kappa coefficients ranged from 0.40 to 0.75. The method described provides an interesting approach for detecting tree species semi-automatically in digital aerial data.     

Validating a Time Series of Annual Grass Percent Cover in the Sagebrush Ecosystem

We mapped yearly (2000–2016) estimates of annual grass percent cover for much of the sagebrush ecosystem of the western United States using remotely sensed, climate, and geophysical data in regression-tree models. Annual grasses senesce and cure by early summer and then become beds of fine fuel that easily ignite and spread fire through rangeland systems. Our annual maps estimate the extent of these fuels and can serve as a tool to assist land managers and scientists in understanding the ecosystem’s response to weather variations, disturbances, and management. Validating the time series of annual maps is important for determining the usefulness of the data. To validate these maps, we compare Bureau of Land Management Assessment Inventory and Monitoring (AIM) data to mapped estimates and use a leave-one-out spatial assessment technique that is effective for validating maps that cover broad geographical extents. We hypothesize that the time series of annual maps exhibits high spatiotemporal variability because precipitation is highly variable in arid and semiarid environments where sagebrush is native, and invasive annual grasses respond to precipitation. The remotely sensed data that help drive our regression-tree model effectively measures annual grasses’ response to precipitation. The mean absolute error (MAE) rate varied depending on the validation data and technique used for comparison. The AIM plot data and our maps had substantial spatial incongruence, but despite this, the MAE rate for the assessment equaled 12.62%. The leave-one-out accuracy assessment had an MAE of 8.43%. We quantified bias, and bias was more substantial at higher percent cover. These annual maps can help management identify actions that may alleviate the current cycle of invasive grasses because it enables the assessment of the variability of annual grass ? percent cover distribution through space and time, as part of dynamic systems rather than static systems.     

Can plot edge bias be reduced by means of airborne laser scanning?

This paper presents new methods for plot edge bias (PEB) correction of individual tree competition indices (CIs) using airborne laser scanning (ALS) as auxiliary information in multivariate ratio and multivariate regression models. I applied the methods to 557 plots from the Norwegian National Forest Inventory located in Hedmark County in South East Norway and compared them to the benchmarks methods linear expansion and simulated annealing by studying the individual tree growth predictions before and after PEB correction. Generally, the simulated annealing method seemed to improve growth prediction most and overall the existing methods performed better than those based on ALS. All PEB-correction methods tested gave minor changes in growth predictions and the absolute change in percent in adj. R² and Akaike's Information Criterion (AIC) was numerically small, with an average percentage change for the tested CIs between 1.8 for adj. R² and 0.6 for AIC of the observed values in the original data. The small differences in the results between the original data and the PEB-corrected data show that on average PEB remains a minor problem for individual tree growth prediction. Whether the results are valid for forests with significantly different spatial composition than that of this database remains to be confirmed.