长江中游防浪林力学模拟试验研究

对长江中游防浪林的主要树种进行力学测定，为防涵林营造最佳树种的选择提供了科学理论依据。     

长江、汉江防浪林建设调查

本文概述了湖北省发展防浪林的历史,并对荆州地区长江、汉江防浪林营造、管理、效益等方面进行了调查研究。根据存在的问题提出了建议。     

基于多目标模型的防浪林优化布局设计

在滩地种植防浪林,可以减少风浪在堤防的爬高,是有效的生态护岸措施。为合理设计防浪林优化布局、提高防浪林的消波效果,提出了基于模糊熵权法的防浪林布局优选模型。在考虑防浪林的排列方式、行株距、树干半径、树冠半径和林带宽度多种消波影响因素作用的前提下,以在提高消波效果的同时减少经济成本和减少占地面积为目标进行多目标评价决策。以嫩江干流同盟水文站附近堤段为例,采用模糊熵权法优选出防浪林优化布局,推荐行株距2.5 m、林带宽度40 m的等边三角形排列作为嫩江干流防浪林的优化布局。     

堤防工程中防浪林的营造与管理

通过对目前堤防工程中防浪林存在的树种单一、成活率低、树种选择不当、模式不合理等问题的分析,阐述了防浪林营造的技术要求和模式,提出了后期管理的具体措施。     

黑龙江垦区江河堤坝防浪林营造技术

通过多年试验，总结出了一套江河堤坝防浪林设计模式、营造技术、树种选择及防浪林防浪护堤综合效益的评估方法，并建成了近２０００ｋｍ防浪林     

浅析长江防浪林特点与树种密度效应

通过对长江安徽段长江河道内防浪林在大洪水中防浪保土能力的调查,分析长江防浪林的特点、防浪原理及其树种密度对于防浪效益的重要价值,为沿江管理单位在营造长江防浪林和管理抚育实践中提供参考。     

洪泽湖大堤防浪林防浪机理及更新方案合理性的分析

１洪泽湖大堤防浪林工程概况洪泽湖大堤原柳树防浪林是防止风浪侵蚀湖堤的防护工程。它始建于１９６８年,全长２３．６７ｋｍ,宽５０ｍ,树种为柳树,至１９８５年的１８ａ间,尽管洪泽湖水位一直没有超过防浪林台（林台高程１４．５ｍ）,防浪林还是起到了减轻风浪水流...     

洪泽湖大堤防浪柳林造林成活率低的原因分析

洪泽湖大堤插干植柳的方法更新迎水面原有柳树防浪林,成活率极低。通过对柳树的生长进行观察,对洪泽湖大堤的土壤、气候条件进行测定,分析了各因子与柳树生长的关系,从而明确影响柳树成活的原因:土壤含水量高、土壤黏重板结、插干病虫害严重、插干埋土过深、缺乏管理等因素相互作用、综合影响。     

中山市防火林带9种典型林分的小气候特征研究

为探寻不同林分类型的防火林带的小气候效应,以广东省中山市防火林带的9个典型的林分类型为研究对象,在其林内进行了小气候要素的日变化观测,研究了不同防火树种组成的防火林带小气候特征及其日变化规律。从9个标准地的小气候的方差分析发现:林内不同标准地的风速、大气压以及海拔差异均极显著(P0.001),不同标准地间的温度差异显著(P0.05),而相对湿度差异不显著;针叶树为主的标准地风速相对较大,阔叶林的标准地风速则相对较小;生长不良的阔叶林以及针叶林,林内温度较高;阔叶林或以阔叶树为主的针阔混交林的林内相对湿度较高;不同的标准地其小气候特征日变化趋势有所差异,呈现出一定的变化规律,研究成果可为中山市防火林带树木的有序生长及防火林带的高效营建提供理论参考。     

不同林龄杉木人工林中角规常数选择与误差分析

在不同林龄的杉木人工林中选择不同角规常数进行蓄积调查,以标准地实测调查结果进行对比验证,分析不同角规常数所产生的蓄积调查相对误差,从而确定杉木人工林蓄积测定的最佳角规常数,并以线性回归方程对其误差进行修正以提高调查精度。     

Estimating forest data for analyses of forest production and utilization possibilities at local level by means of multi-source National Forest Inventory

The sample plot data of National Forest Inventories (NFI) are widely used in the analysis of forest production and utilization possibilities to support national and regional forest policy. However, there is an increasing interest for similar impact and scenario analyses for strategic planning at the local level. As the fairly sparse network of field plots only provides calculations for large areas, satellite image data have been applied to produce forest information for smaller areas. The aim of this study was to test the feasibility of generating forest data for a Finnish forest analysis tool, the MELA system, by means of the Landsat satellite imagery and the NFI sample plot data. The study was part of the preparation of a local forestry programme, where a strategic scenario analysis for the forest area of two villages (ca 8000 ha) was carried out. Management units that approximate forest stands were delineated by image segmentation. Stand volume and other parameters for each forest segment were estimated from weighted means of the NFI sample plots, where the individual sample plot weights were estimated by the k nearest neighbour (kNN) method. Two different spectral features were tested: single pixel values and average pixel values within a segment. The estimated forest data were compared with the forest data based on independent stand-level field assessments in two subareas, a national park and an area of forest managed for timber production.In the national park, the estimated mean volume of the growing stock from both spectral feature sets (about 160 m³ ha⁻¹) was clearly lower than that obtained from stand-level field assessment (186 m³ ha⁻¹). Using average pixel values within a segment resulted in a higher proportion of pine and a lower proportion of spruce volume than using single pixel values. It also resulted in an estimated felling potential nearly 10% higher over the first 10-year period in the scenario analysis of the area dedicated to timber production. However, the maximum long-term sustainable removal was at the same level (about 30,000 m³ year⁻¹) for both feature sets over the simulated 30-year period. The resulting annual felling area in the first 10-year period was 12% lower when the segment averages were applied, but the difference subsequently levelled off. The kNN approach in estimating initial forest data for scenario analyses at the local level was found promising.     

Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data

Being able to accurately estimate and map forest biomass at large scales is important for a better understanding of the terrestrial carbon cycle and for improving the effectiveness of forest management. In this study, forest plot sample data, forest resources inventory(FRI) data, and SPOT Vegetation(SPOT-VGT) normalized difference vegetation index(NDVI) data were used to estimate total forest biomass and spatial distribution of forest biomass in northeast China(with 1 km resolution). Total forest biomass at both county and provincial scales was estimated using FRI data of 11 different forest types obtained by sampling 1156 forest plots, and newly-created volume to biomass conversion models. The biomass density at the county scale and SPOT-VGT NDVI data were used to estimate the spatial distribution of forest biomass. The results suggest that the total forest biomass was 2.4 Pg(1 Pg = 10~(15) g), with an average of 77.2 Mg ha~(-1), during the study period. Forests having greater biomass density were located in the middle mountain ranges in the study area. Human activities affected forest biomass at different elevations, slopes and aspects. The results suggest that the volume to biomass conversion models that could be developed using more plot samples and more detailed forest type classifications would be better suited for the study area and would provide more accurate biomass estimates. Use of both FRI and remote sensing data allowed the down-scaling of regional forest biomass statistics to forest cover pixels to produce a relatively fineresolution biomass map.     

泰森多边形与传统四株树法的天然红树林空间结构比较研究

【目的】以漳江口红树林为研究对象,利用泰森多边形和四株树法划分天然红树林林木平面空间分布结构,确定对象木的最邻近竞争木,计算林分空间结构指数,对比分析两种方法的异同,探讨泰森多边形法应用红树林林分空间结构量化的适用性。【方法】设置20 m×20 m样地,每木调查时用钢尺测量横纵坐标,在坐标纸上标记调查木的位置和编号,同时在调查表上记录树种、树高、胸径等林分因子。利用ArcGIS软件,将外业调查的坐标纸上的样木位置图矢量化形成样木点图层,将林分因子调查表导入样木属性表,并由调查木的点位置生成泰森多边形。用VBA编程来计算林分空间结构指数:混交度、大小比数、角尺度。【结果】在福建漳江口红树林国家自然保护区选择样地进行试验,对比分析基于泰森多边形法与传统的四株树法的计算结果,结果表明:1)基于泰森多边形法确定的林分空间结构单元由1株对象木和3~12株竞争木构成,平均值为6株。2)两种方法计算的混交度的相关系数为0.828,大小比数的相关系数为0.881,角尺度的相关系数为0.225。这两种方法计算的混交度和大小比数具有较高的相关性和一致性,而角尺度,两者差异较大。3)基于泰森多边形法与四株树法的不同树种的混交度和大小比数平均值非常接近,混交度最大差0.05,大小比数最大差0.02;角尺度差异较大,最大差值达0.11;泰森多边形法计算的混交度比四株树法的略大一些,而大小比数和角尺度则略小一些。【结论】无论从单株还是从整个调查林分上看,基于泰森多边形法计算的混交度和大小比数与传统四株树法的计算结果差异小,两种方法有较高的相关性和一致性,但其中泰森多边形法与四株树法相比,混交度略大,大小比数略小;而对于角尺度,两种方法的计算结果有较大的差异,并且泰森多边形法的计算结果值小于四株树法。这种差异的根源在于泰森多边形法确定的竞争木数量波动。泰森多边形法通过最邻近原则将平面空间进行划分,不重不漏,对于量化表达林木在空间上的竞争关系具有合理性和有效性,同时外业调查时不需要判断对象木的最邻近竞争木以及距离量算和角度测量,大幅减轻外业调查工作量,适用于天然红树林林分空间结构研究。     

Comparison of organic matter dynamics in soil between Japanese cedar (Cryptomeria japonica) forest and adjacent Japanese red pine (Pinus densiflora) forest established on flatland

In order to clarify the effects of tree species on organic matter dynamics in soil, we investigated the amount of forest floor material, leaf litter decomposition rate, soil chemical characteristics, soil respiration rate and cellulose decomposition rate in a Japanese cedar forest (cedar plot) and an adjacent Japanese red pine forest (pine plot) established on a flatland. The amount of forest floor material in the cedar plot was 34.5 Mg ha⁻¹ which was greater than that in the pine plot. Because the leaf litter decomposition rate was higher in the pine plot than in the cedar plot, it is likely that the difference in the amount of forest floor material between the plots is caused by the difference in the leaf litter decomposition rate. The C concentrations of soil in the cedar plot were 1.2–2.1 times higher than those in the pine plot. Soil pH(H₂O)s in the cedar plot were significantly higher than those in the pine plot. The soil respiration rates and the rates of mineralized C in the cedar plot byin vitro incubation were higher than those in the pine plot. From this result, it is assumed that soil organic matter in the cedar plot was decomposed relatively faster compared with the pine plot. Furthermore, microbial activities, which were reflected as cellulose decomposition rates in the cedar plot, were higher than those in the pine plot. A part of this paper was presented at the 109th Annual Meeting of the Japanese Forestry Society (1998).     

Effects of field plot configurations on the uncertainties of ALS-assisted forest resource estimates

The effects of field plot configurations on the uncertainties of plot-level forest resource estimates were analyzed using airborne laser scanner data, aerial photographs and field measurements. The aim was to select a field sample plot configuration that can be used for both large area and management inventories. Error estimates were evaluated at the plot level using six different training plot configurations. Additionally, separate plots with two different sizes were used for evaluation. Stem volume and five other forest resource characteristics were considered. The field measurement costs of the different plot configurations were also studied. RMSEs and mean deviations for airborne laser scanning ALS-assisted estimates were practically the same for the fixed radius plot, the two concentric plots and the angle count plot with a basal area factor of q = 1 for all three evaluation plot sizes. Angle count plots with basal area factors of q = 1.5 and 2 increased the RMSEs. For the former plot configurations, the RMSEs for the ALS-assisted estimates could be attributed to inaccuracy in the predicted relationships between the field data and ALS data, not to the training plot configuration. Tree measurements and costs can, therefore, be reduced from those of the Finnish management inventories without increasing RMSEs.     

基于CASIO fx-5800P计算器的森林资源规划设计调查蓄积量计算

基于CASIOfx-5800P计算器的可编程功能,以及其所具有的便携性、持久续航性和广泛应用性等特点,实现新一轮森林资源规划设计调查相关蓄积的自动化计算,蓄积计算类型包括标准地蓄积、控制样地蓄积和小班蓄积计算。本文分别给出三种蓄积计算的全部程序代码和使用说明。     

公益林林木材积生长率的调查

在公益林区布设固定样地,定期、定点对公益林林木材积生长率进行调查,结果表明,2010年与2007年相比较,样地1、样地2、样地3、样地4、样地5的活立木材积净生长量分别为0.642 8 m3、0.641 9 m3、0.952 6 m3、1.179 4 m3、0.237 4 m3、3.627 1 m3,生长率分别为12.80%、4.73%、8.12%、3.87%、1.52%。对公益林进行有效管护,可以使林分蓄积稳步增长,森林生态功能和经济效益逐年增强。     

A model-based performance test for forest classifiers on remote-sensing imagery

Ambiguity between forest types on remote-sensing imagery is a major cause of errors found in accuracy assessments of forest inventory maps. This paper presents a methodology, based on forest plot inventory, ground measurements and simulated imagery, for systematically quantifying these ambiguities in the sense of the minimum distance (MD), maximum likelihood (ML), and frequency-based (FB) classifiers. The method is tested with multi-spectral IKONOS images acquired on areas containing six major communities (oak, pine, fir, primary and secondary high tropical forests, and avocado plantation) of the National Forest Inventory (NFI) map in Mexico. A structural record of the canopy and optical measurements (leaf area index and soil reflectance) were performed on one plot of each class. Intra-class signal variation was modelled using the Discrete Anisotropic Radiative Transfer (DART) simulator of remote-sensing images. Atmospheric conditions were inferred from ground measurements on reference surfaces and leaf optical properties of each forest type were derived from the IKONOS forest signal. Next, all forest types were simulated, using a common environmental configuration, in order to quantify similarity among all forest types, according to MD, ML and FB classifiers. Classes were considered ambiguous when their dissimilarity was smaller than intra-class signal variation.     

Spatial prediction of forest stand variables

This study aims at the development of a model to predict forest stand variables in management units (stands) from sample plot inventory data. For this purpose we apply a non-parametric most similar neighbour (MSN) approach. The study area is the municipal forest of Waldkirch, 13 km north-east of Freiburg, Germany, which comprises 328 forest stands and 834 sample plots. Low-resolution laser scanning data, classification variables as well rough estimations from the forest management planning serve as auxiliary variables. In order to avoid common problems of k-NN-approaches caused by asymmetry at the boundaries of the regression spaces and distorted distributions, forest stands are tessellated into subunits with an area approximately equivalent to an inventory sample plot. For each subunit only the one nearest neighbour is consulted. Predictions for target variables in stands are obtained by averaging the predictions for all subunits. After formulating a random parameter model with variance components, we calibrate the prior predictions by means of sample plot data within the forest stands via BLUPs (best linear unbiased predictors). Based on bootstrap simulations, prediction errors for most management units finally prove to be smaller than the design-based sampling error of the mean. The calibration approach shows superiority compared with pure non-parametric MSN predictions.