地动噪声RMS值计算方法的适用性及误差概率分析

对比两种计算RMS值的方法,结合误差概率统计给出结果的误差概率分布。在使用有限脉冲响应（FIR）带通滤波器进行滤波并计算RMS值的过程中,滤波器窗口函数和阶数是影响计算结果误差的主要因素,其中阶数的作用更大。通过计算功率谱密度（PSD）反算RMS值的误差主要受pwelch函数的窗口函数类型、窗口长度及重叠率等参数影响,其中窗口长度作用更大。从同等误差水平的概率分布看,在合理设置参数的前提下,使用PSD反算RMS值的方法更优。     

Foliar Particulate Matter Distribution in Urban Road System of Beijing,China

Particulate matter(PM), one of the most important pollutants of traffic emission, threatens the health of urban ecosystems and citizens. Roadside trees play an important role in trapping PM, and the foliar PM load is a useful indicator for air PM pollution in road systems. To detect the relationships of foliar PM load with road structures, urbanization, and meteorology in road systems, we studied a widely-planted tree Sophora japonica L. in 100 roads and 10 yards of Beijing, China, and found that the foliar PM loads increased with the distances from the urban centre(DUC) linearly, while decreased with the road density. All-subsets regression analysis indicated that DUC, average monthly relative humidity, average monthly wind speed, and mean annual wind speed were the most important factors in predicting foliar PM load, rather than general situation of buildings and road cleanliness. The monthly relative humidity and monthly wind speed had a negative correlation to foliar PM, while the annual relative humidity and annual wind speed had a positive correlation to foliar PM. Suburban areas and these effective factors should be highlighted in PM control in Beijing.     

中国城市碳排放强度的空间溢出效应及驱动因素探究（英文）

In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission intensity in 283 Chinese cities from 1992 to 2013. The following results were obtained.(1) Nuclear density estimation shows that the overall average carbon intensity of cities in China has decreased, with differences gradually narrowing.(2) The spatial autocorrelation Moran's I index indicates significant spatial agglomeration of carbon emission intensity is gradually increasing; however, differences between regions have remained stable.(3) Spatial Markov chain analysis shows a Matthew effect in China's urban carbon emission intensity. In addition, low-intensity and high-intensity cities characteristically maintain their initial state during the transition period. Furthermore, there is a clear "Spatial Spillover" effect in urban carbon emission intensity and there is heterogeneity in the spillover effect in different regional contexts; that is, if a city is near a city with low carbon emission intensity, the carbon emission intensity of the first city has a higher probability of upward transfer, and vice versa.(4) Panel quantile results indicate that in cities with low carbon emission intensity, economic growth, technological progress, and appropriate population density play an important role in reducing emissions. In addition, foreign investment intensity and traffic emissions are the main factors that increase carbon emission intensity. In cities with high carbon intensity, population density is an important emission reduction factor, and technological progress has no significant effect. In contrast, industrial emissions, extensive capital investment, and urban land expansion are the main factors driving the increase in carbon intensity.     

Spatial spillover effect and driving forces of carbon emission intensity at the city level in China

Journal of Geographical Sciences - In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial...     

Self-thinning Rules at Chinese Fir (Cunninghamia lanceolata) Plantations—Based on a Permanent Density Trial in Southern China

Data selection and methods for fitting coefficients were considered to test the self-thinning law. The Chinese fir (Cunninghamia lanceolata) in even-aged pure stands with 26 years of observation data were applied to fit Reineke’s (1933) empirically derived stand density rule (N $propto$ d¯ ^-1.605, N = numbers of stems, d¯ = mean diameter), Yoda’s (1963) self-thinning law based on Euclidian geometry (v¯ $propto$ N ^-3/2, v¯ = tree volume), and West, Brown and Enquist’s (1997, 1999) (WBE) fractal geometry (w¯ $propto$ d¯ ^-8/3). OLS, RMA and SFF algorithms provided observed self-thinning exponents with the seven mortality rate intervals (2%-80%, 5%-80%, 10%-80%, 15%-80%, 20%-80%, 25%-80% and 30%-80%), which were tested against the exponents, and expected by the rules considered. Hope for a consistent allometry law that ignores species-specific morphologic allometric and scale differences faded. Exponents α of N $propto$ d¯^α, were significantly different from -1.605 and -2, not expected by Euclidian fractal geometry; exponents β of w¯ $propto$ N^β varied around Yoda’s self-thinning slope -3/2, but was significantly different from -4/3; exponent γ of w¯ $propto$ d¯^γ tended to neither 8/3 nor 3.     

基于长期密度试验的杉木人工林自然稀疏线研究（英文）

采用杉木人工同龄纯林26年连续观测数据,拟合Reineke(1933)经典的林分密度效应法则、Yoda(1963)基于欧几里德几何的自疏法则以及West, Brown和Enquist的分形几何(1997, 1999)。通过OLS、RMA和SFF算法得到7种枯损率区间(2%-80%, 5%-80%, 10%-80%, 15%-80%, 20%-80%, 25%-80%and 30%-80%)的自稀疏指数,对这些指数与考虑的几种法则相应指数进行验证。发现Reineke密度效应法则的指数显著区别于-1.605和-2,而不是预想的欧几里德分形几何结果。Yoda自疏法则指数在-3/2左右变动,但显著区别于-4/3。West、Brown和Enquist的分形几何式中指数参数既不趋向于8/3,亦不趋向于3。     

温度、盐度和光照对球形棕囊藻生长和卤代烃释放的影响

氯甲烷(CH_3Cl)、溴甲烷(CH_3Br)和碘甲烷(CH_3I)是挥发性卤代烃的3种主要成分,对温室效应和大气臭氧破坏有重要影响。由于海藻可以在一定条件下产生卤代烃,本文选择了球形棕囊藻进行室内培养,研究了不同温度、盐度和光照对其释放CH_3Cl、CH_3Br和CH_3I含量的影响。在不同温度(15、20、25℃),盐度(19、23、29)和光照(14、25、38μmol·m^-2·s^-1)条件下,藻细胞密度和卤甲烷的释放受温度的影响较明显。温度偏低(15～20℃)更适宜藻的生长和CH_3I的存在(CH_3I最大平均浓度为5.90～6.29pmol·L^-1),但25℃释放的CH_3Cl和CH_3Br最多(最大平均浓度分别为452.48和9.49pmol·L^-1),表明CH_3Cl的最大平均浓度比CH_3Br和CH_3I高约10倍。总体上CH_3Cl和CH_3Br的释放随着温度、盐度和光照强度的增加而增大,但盐度和光照的变化对藻的生长和卤甲烷释放的影响不明显。     

遥感影像与POI数据相结合的城市建成区提取适用性研究——以沈阳市为例

城市建成区的发展状况是地理国情监测的重要内容,本文基于遥感影像数据和POI数据对城市建成区进行提取,针对二者的适用性问题进行了研究。试验以沈阳市为研究区域,在研究区域内选择2016年遥感影像数据和POI数据作为数据源进行对比分析。首先,对遥感影像数据和POI数据进行预处理;其次,通过监督分类的方法对遥感影像进行建成区的提取;然后,采用核密度估计法分析POI数据并提取出建成区;最后,利用叠加分析法对比分析这两种数据的适用性。试验结果表明：使用遥感影像数据作为数据源可以较为全面客观地反映城市建成区的发展现状;利用POI数据提取出的城市建成区具有较强的经济属性,能够很好地反映出城市中的经济活跃区。     

广东沿海陆地地质灾害区划

研究中使用了主要地质灾害（地震、崩塌、滑坡、泥石流、地面沉降、地面塌陷、地基下沉、地裂缝、水土流失、港口淤积等）大量的野外调查和文献资料的实际数据,根据综合分析并运用“灾害密度”和“灾害强度”2种指标,将广东沿海陆地划分出9个地质灾害一级区及其所属的32个二级分区,其中包括10个重灾区、10个中灾区和12个弱灾区。首次编制了基于数据库和GIS的1：50万广东沿海陆地主要地质灾害类型与区划图,为地质灾害发育规律的理论研究和国民经济建设的实际应用提供了基础信息和实际数据。分区的结果揭示了地质灾害空间分布特征及其与地质环境和人类活动的关系。     

基于自发地理信息的“一带一路”区域陆路交通状况分析

路网密度的研究是实施“一带一路”愿景之互联互通倡议的基础工作。“一带一路”顺应了世界经济全球化、一体化、多极化、信息化的趋势,牵连着蓬勃发展的亚太和发达的欧洲经济圈,带动中间国家的经济发展。在新形势下,如何通过交通基础设施建设推进丝绸之路经济带沿线区域间的互联互通、促进区域合作和经济发展,具有重要的现实意义。本文利用自发地理信息数据——OpenStreetMap（OSM）道路网数据,运用地理信息系统（GIS）空间分析技术,探究了“一带一路”陆路经济带辐射区域亚欧大陆的路网络密度和通行能力的空间分布格局,并分析了六大经济走廊节点城市的公路可达性空间格局。结果表明：“一带一路”陆路经济带的交通基础设施的发展存在着不平衡现象;路网密度和通行能力均呈现沿海高内陆低的空间格局;中亚、西亚地区和中南半岛地区成为道路水平落后带,限制了丝绸之路经济带资源整合与贸易畅通,建议在建设新跨国公路铁路同时,对原有老旧道路进行加宽加固等升级改造;全区域道路等级级配不合理;节点城市可达性具有明显的分异状况,六大经济走廊中83%的区域可达性在10 h以内。研究产出亚欧大陆1 km分辨率路网密度和通行能力数据集,发现了“一带一路”陆路经济带道路水平的薄弱区域,为“一带一路”陆路经济带的交通基础设施建设以及进一步的道路网研究提供了基础数据。