The effect of leaf-on and leaf-off forest canopy conditions on LiDAR derived estimations of forest structural diversity

Forest structural diversity metrics describing diversity in tree size and crown shape within forest stands can be used as indicators of biodiversity. These diversity metrics can be generated using airborne laser scanning (LiDAR) data to provide a rapid and cost effective alternative to ground-based inspection. Measures of tree height derived from LiDAR can be significantly affected by the canopy conditions at the time of data collection, in particular whether the canopy is under leaf-on or leaf-off conditions, but there have been no studies of the effects on structural diversity metrics. The aim of this research is to assess whether leaf-on/leaf-off changes in canopy conditions during LiDAR data collection affect the accuracy of calculated forest structural diversity metrics. We undertook a quantitative analysis of LiDAR ground detection and return height, and return height diversity from two airborne laser scanning surveys collected under leaf-on and leaf-off conditions to assess initial dataset differences. LiDAR data were then regressed against field-derived tree size diversity measurements using diversity metrics from each LiDAR dataset in isolation and, where appropriate, a mixture of the two. Models utilising leaf-off LiDAR diversity variables described DBH diversity, crown length diversity and crown width diversity more successfully than leaf-on (leaf-on models resulted in R² values of 0.66, 0.38 and 0.16, respectively, and leaf-off models 0.67, 0.37 and 0.23, respectively). When LiDAR datasets were combined into one model to describe tree height diversity and DBH diversity the models described 75% and 69% of the variance (R² of 0.75 for tree height diversity and 0.69 for DBH diversity). The results suggest that tree height diversity models derived from airborne LiDAR, collected (and where appropriate combined) under any seasonal conditions, can be used to differentiate between simple single and diverse multiple storey forest structure with confidence.     

融合多源时空数据的城市火灾危险性评估

城市层面的火灾风险评估主要包括火灾危险性、危害性及救援能力等方面。本文选取火灾危险性评估进行针对性研究,在大数据思维的指导下,以相关关系代替因果关系,采用多源数据对评估指标权重、分值进行率定,得出福州市城区火灾危险性时空分布图。首先利用高德地图API对消防历史出警记录进行地址解析,将近万条火灾出警地址空间落点,获得福州市历史火灾空间分布;然后综合城市用地性质现状、用地开发性质、人口分布热力图等多源异构数据,探索其与历史火灾空间分布的相关性;最后以福州城区为例,初步实现具有充分数理支撑的火灾危险性评估方法,形成火灾危险性动态评估成果,为城市消防规划等提供支撑和依据。     

加权混合估计中权值的确定方法

综合了大地测量中各种异方差多源观测模型和联合平差方法,说明了混合估计方法可以用于测量数据融合,平衡附加信息和样本信息对参数估计的影响。通过求取权值使参数估计的协方差阵的迹最小的方法,给出了一个权的最优选择方法。本文扩展了已有的加权混合估计方法,使得新方法中的权不受验前单位权方差的限制,能有效应用于大地测量数据处理。     

规则池塘群的复杂直线模式识别

针对现有面要素直线模式识别方法难以解决规则池塘中破碎区域的问题,提出了一种规则池塘群的复杂直线模式识别方法。首先,分析了规则池塘群的空间特征和认知特点,提出了“主次关系→并列关系→直线模式→复杂直线模式”的多层次认知顺序;其次,设计了主次关系池塘组、并列关系池塘组、直线模式池塘群的识别方法;最后,构建了复杂直线模式池塘群的识别模型。试验表明:本文方法能够消除破碎区域对规则池塘群直线模式提取的不利影响,有效提升复杂直线模式识别的质量。     

利用DINEOF方法重构缺测的卫星遥感海温数据

针对海温数据补缺问题提出一种基于经验正交函数(EOF)分解的缺测数据重构方法--经验正交函数插值法(DINEOF).此方法是一种自适应的EOF分解方法,不需要任何先验信息,并且能估算出重构数据的误差大小.奇异值(SVD)分解时采用了Lanczos算子以提高计算速度,并利用了交叉验证的算法以确定出重构时所需最优的EOF阶数.实测数据处理结果表明,DINEOF方法能很好地重构大面积的缺测数据,具有较高精度及实际可操作性.     

GPS网络RTK内插算法分析与比较

在GPS网络RTK中,利用不同的内插算法,生成的流动站误差改正数不同,它们对定位结果的影响也不同。通过算例分析表明,选择合理的内插算法,不仅可以生成与流动站真实误差较为接近的误差改正数,还可以提高整周模糊度的解算成功率和导航定位的精度。     

基于空间自相关的阿根廷滑柔鱼CPUE标准化研究

CPUE的观测往往不是独立的,而是存在空间相关性的。但是,大多数的CPUE标准化方法通常都假设名义CPUE在空间上是相互独立的。为此,本研究以西南大西洋阿根廷滑柔鱼为例,采用2000-2014年1-5月中国大陆鱿钓生产统计数据以及对应的海表温度和叶绿素浓度数据,选择广义线性模型（general linear model,GLM）为基础模型,将空间自相关加入到GLM中,比较标准GLM和4种加入空间自相关的空间GLM的CPUE标准化。根据最小信息准则（Akaike Information Criterion,AIC）及贝叶斯信息准则（Bayesian Information Criterion,BIC）,空间自相关的GLM的CPUE标准化结果优于标准GLM,其中指数模型的CPUE标准化结果最佳。同时,标准GLM与空间自相关的GLM相比,存在精确度过高估计的问题。因此,在CPUE标准化中,应充分考虑空间自相关这一因素。     

捷联式航空重力扰动矢量解算及误差补偿

介绍捷联式航空重力矢量测量的基本原理,利用波数相关滤波（WCF）、比力线性校正的方法对重力扰动的水平和垂向分量进行误差补偿,评定内符合精度。对国产捷联式航空重力矢量仪的某次试验数据进行处理,以验证和评估航空重力矢量仪的性能。结果表明,在半波长分辨率为7.5 km时,6条重复测线的重力扰动水平分量经波数相关滤波处理后,东、北向分量的平均内符合精度分别从9.77 mGal、9.18 mGal提高到5.95 mGal、3.83 mGal;对比力的垂向分量线性校正后,将解算的重力扰动垂向分量再用WCF方法处理,其平均内符合精度从1.27 mGal提高到0.59 mGal。     

Dominant climate factors influencing the Arctic runoff and association between the Arctic runoff and sea ice

By using the Arctic runoff data from R-ArcticNET V4.0 and ArcticRIMS, trends of four major rivers flowing into the Arctic Ocean, whose climate factor plays an important role in determining the variability of the Arctic runoff, are investigated. The results show that for the past 30 years, the trend of the Arctic runoff is seasonally dependent. There is a significant trend in spring and winter and a significant decreasing trend in summer, leading to the reduced seasonal cycle. In spring, surface air temperature is the dominant factor influencing the four rivers. In summer, precipitation is the most important factor for Lena and Mackenzie, while snow cover is the most important factor for Yenisei and Ob. For Mackenzie, atmospheric circulation does play an important role for all the seasons, which is not the case for the Eurasian rivers. The authors further discuss the relationships between the Arctic runoff and sea ice. Significant negative correlation is found at the mouth of the rivers into the Arctic Ocean in spring, while significant positive correlation is observed just at the north of the mouths of the rivers into the Arctic in summer. In addition, each river has different relationship with sea ice in the eastern Greenland Sea.     

Skeletal linear extension rates of the foliose scleractinian coral Merulina ampliata (Ellis & Solander, 1786) in a turbid environment

Skeletal linear extension rates of a foliaceous, IndoPacific, skiophilous, heterotrophic, scleractinian Merulina ampliata (Ellis & Solander 1786) were obtained along a sediment/nutrient load gradient at the southern islands of Singapore. Measurements were made during November 1999– November 2000 using the alizarin red‐S staining technique. Suspended particulate matter concentration (r²_adj = 0.76), turbidity (r²_adj = 0.59), the organic content of suspended sediments (r² = 0.50), and nitrite‐nitrate concentration (r²_adj = 0.50) were significant predictors of the skeletal linear extension rate of M. ampliata. Maximum linear extension growth rates of M. ampliata (mean ± SD: 1.43 ± 0.67–3.26 ± 0.59 cm·year^?1) were comparable to 15‐year‐old accounts at the same research sites, indicating adaptation to low‐light, high‐sediment waters.