西南山地区域森林火险综合预报模型研究——以重庆市为例

森林火灾严重破坏森林生态系统的结构和功能,针对其风险预报开展研究具有重要的理论意义和应用价值。通过融合气象、地表覆盖和人类活动等要素的方式构建森林火险综合预报模型,是西南山地区域森林火险综合预报业务化应用的重要发展方向。基于《森林火险气象等级》国家标准(GB/T 36743-2018),本文研究首先构建了重庆市森林火险气象风险预报模型。然后通过融合可燃物因素和人为因素的方式,进一步构建重庆市森林火险综合预报模型。最后利用历史火点数据针对上述两类模型的精度进行对比和分析。研究结果表明:重庆市森林火灾发生次数较多,且呈现出季节性规律;重庆市森林火灾的发生不仅受到气象条件的影响,而且受到地表覆盖和人类活动等多种要素条件的共同影响;与森林火险气象风险预报结果相比,森林火险综合预报结果在空间分布上具有更高的精细程度;森林火险综合预报模型能有效提高森林火险等级预报精度。     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.     

A Simulation Study to Assess the Sensitivity of a Forest Health Monitoring Network to Outbreaks of Defoliating Insects

The sensitivity of the United States Forest Health Monitoring network to outbreaks of defoliating insects was examined by means of a simulation study. A model constructed specifically for the study was used to generate a wide variety of defoliation patterns in forested landscapes. Forest configuration was that of Minnesota, USA, as expressed by the GAP land cover classification. Combinations of model parameters were based on a Latin Hypercube sample. The relationship between the average number of plots defoliated and outbreak characteristics was then examined via multiple regression. Both theoretical and model results pointed to a strong, linear relationship between the average number of plots defoliated and outbreak size. Model results provided additional insight, suggesting a significant relationship between the average number of plots defoliated and other outbreak characteristics after outbreak size was taken into account.     

Evaluation of Carbon Uptake and Emissions by Forests in Korea During the Last Thirty Years (1973–2002)

The contribution of Korean forests to carbon sequestration for anthropogenic carbon emissions was evaluated. In addition, monitoring of carbon species released from forest fires was conducted. Despite a high carbon uptake by Korean forests, a tremendous increase in fossil fuel burning resulted in a small contribution by forests to carbon removal. The removal efficiency had a 5–31% range with an average of 12% during the period 1973–2002. In 2000, the amount of carbon released from burned trees corresponded to 1.6% of carbon uptake by forests. The distribution of surface CO concentration (ppb) derived from MOPITT (Measurement of Pollution in the Troposphere) showed high CO levels over the East/Japan Sea on April 10, 2000 when the largest forest fires occurred along the east coast of Korea. Trajectory analysis and ground CO measurements also indicated that CO levels over the East/Japan Sea were influenced by forest fires. This study suggests that continuous monitoring of carbon emissions from forest fires is needed for a more reliable estimate of carbon flux in the environment.     

居住区地下车库噪声在建筑群间的传播和影响模拟计算

针对城市居住区2种典型的建筑布局,结合随机点声源模型,对居住区内地下车库噪声影响进行了分析计算.通过实测值和预测值的比较,该预测模型精度较好.运用该模型预测规划与新建的居住区地下车库的噪声的影响,可为城市小区建设规划中有效控制噪声污染提供科学依据.     

基于无人机多传感吊舱系统的火点实时定位方法

林火定位是林火智能监测设备的核心技术。提出了一种基于激光雷达、红外热像仪及组合惯导多数据融合的火点定位方法。首先设计了一个通用的无人机吊舱系统,并基于ROS框架实现数据采集、数据处理和数据传输等功能;其次提出了一个基于无人机吊舱系统的火点全局定位方案,根据红外热像仪成像特性识别火点,同时将密集点云与红外图像进行数据融合,估计出火点的三维空间位置;然后根据无人机位姿提出了一种基于墨卡托投影的火点全局定位方案,得到了火点的GPS位置。最后通过试验得到了该方案的全局定位精度：在实验中经度最大误差为2.36×10^-5°,纬度最大误差为1.84×10^-5°,高程最大误差为0.926 1 m,为其他林火定位方案提供了技术支持。     

南海重点海洋倾倒区表层沉积物富集特征及其潜在生态风险评价

根据2005南海三个重点海洋倾倒区,即九澳岛重点海洋倾倒区、黄茅岛重点海洋倾倒区、汕头重点海洋倾倒区的监测,分析其表层沉积物重金属的监测资料,采用富集系数法和Hakanson潜在生态危害系数法对其富集度和潜在生态危害程度进行了分析和评价.结果表明:在三个倾倒区表层沉积物所监测的重金属中,Cu和Pb元素的富集度相对最高,Hg和Cd元素的富集度较低,从空间上看,潜在生态危害系数评价结果显示,南海三个重点海洋倾倒区表层沉积物中的重金属对海洋生态系统的潜在生态危害非常轻微,均属于轻微潜在生态危害范畴,其中轻微潜在生态危害程度相对较重的是Cd和Hg元素,Cu和Pb元素的轻微生态危害程度较轻.     

森林消防人员防烟面罩技术探讨及应用

阐述了森林消防防烟面罩的研制及其改进过程,介绍了森林消防防烟面罩的主要技术经济指标及野外应用试验。     

试论资源可持续利用的评价指标

本文给出了判断资源是否可持续发展的四个条件，据此，并分析了1993年我国森林资源可持续利用的状况。