时间尺度重构EEMD-GRNN改进模型预测PM2.5的研究

合理构建PM_2.5浓度预测模型是科学、准确地预测PM_2.5浓度变化的关键。传统PM_2.5预测EEMD-GRNN模型具有较好的预测精度,但是存在过于关注研究数据本身而忽略其物理意义的不足。本研究基于南京市2014-2017年PM_2.5浓度时间序列数据,分析PM_2.5浓度多尺度变化特征及其对气象因子和大气污染因子的尺度响应,基于时间尺度重构进行EEMD-GRNN模型的改进与实证研究。南京市样本数据PM_2.5浓度变化表现为明显的天际尺度和月际尺度,从重构尺度（天际、月际）构建GRNN模型更具有现实意义;同时,PM_2.5对PM₁₀、NO₂、O₃、RH、MinT等因子存在多尺度响应效应,以其作为GRNN模型中的输入变量更具有时间序列上的解释意义。改进后的EEMD-GRNN模型具有更高的PM_2.5浓度预测精度,MAE、MAPE、RMSE和R²分别为6.17、18.41%、8.32和0.95,而传统EEMD-GRNN模型的模型有效性检验结果分别为8.37、27.56%、11.56、0.91。对于高浓度天（PM_2.5浓度大于100 μg/m³）的预测,改进模型更是全面优于传统EEMD-GRNN模型,MAPE为12.02%,相较于传统模型提高了9.03%。     

福州市地表温度热点及时空变化分析

中国作为世界第一大发展中国家,近年来城镇化发展迅速,大量自然地表转化为人工地表,从而引起了一系列环境问题,其中以城市热岛问题最为显著。因此如何缓解因城市化进程的加快引起的城市热岛效应已成为热门研究方向。为精确分析城市空间格局对热集聚的影响,本研究利用2000年5月4日的Landsat ETM+和2016年7月27日获取的Landsat OLI两期遥感影像,获取福州市的土地覆盖信息并进行精度验证。在地表温度（Land Surface Temperature, LST）反演基础上通过热点分析（Getis-Ord Gi*）,并结合不透水面（Impervious Surface Area, ISA）信息来研究城市化进程中福州市16 年来 LST的变化特性,空间集聚特性及其产生的尺度效应。热点分析结果显示：① 通过分析福州市内各地和热点中心的距离与LST的关系可较好地反映空间热聚集。2000 年在距热点中心0.97、1.03、0.95 km范围内热聚集明显;2016 年则增长到分别在距热点中心半径1.89、2.01、2.10、2.05、2.13 km范围内热集聚显著且热点区数量也从3 个增加至5 个。热集聚区（热点区和较热区）总面积在此期间从15.7%增至47.3%;② 由于热点图中的热点区和冷点区的形成不单取决于LST的高低,因此热点分析与空间自相关分析方法相比,能更直观地分析土地覆盖变化对LST的影响,了解城市内部热强度变化的细节。本研究采用的热点分析方法可用于城市环境保护与规划,将来还可作为城市土地规划与热环境影响的分析依据。同时可利用热点分析图模拟城市微气候,估算城市绿地降温程度等。此外,未来还可基于此进一步探讨更多时相以及不同城市的对比分析,特别是对不同城市类型如带状城市,多中心城市及中心城市等的研究。     

基于位置大数据的国庆假期青藏高原人群分布时空变化模式挖掘

人类活动是引起青藏高原生态环境发生改变的重要因素。很多学者对青藏高原史前人类活动和近几十年的人口分布格局与人口流动开展了大量研究,但有关人群时空分布的精细尺度研究相对缺乏。海量的位置大数据为认识高原人群短期的动态变化提供了新途径。本文利用手机定位数据、人口迁徙数据等高时空分辨率的位置大数据,通过时间序列分解方法和基于统计检验的异常判别方法,分析了2017年国庆期间青海与西藏的人群分布时空变化特征,并探讨了假期旅游行为及人口迁徙与变化特征之间的关系。研究结果显示：① 在省级和城市整体尺度上,定位请求量的假期变化在时间上呈现先降后升的“潮汐”变化模式;② 在精细网格尺度上,西宁和拉萨城市及周边地区的人群分布变化在空间上呈现中心跌、周边涨的“离心化”变化模式。国庆假期人们向城市周边热门景点移动聚集的旅游行为和城市之间的人口迁徙都是导致西宁和拉萨周边地区定位请求量上涨的重要潜在原因,而两座高原城市中心定位请求的下跌不仅与人口迁徙有关,还与假期人类日常行为及定位请求频次的变化等因素有关。通过位置大数据挖掘节庆假期人群分布的时空变化,不仅加深了对高原人口分布格局与流动变化的认识,也为高原城镇化与生态保护的精细化管理与决策提供支撑。     

Re-examining urban region and inferring regional function based on spatial–temporal interaction

Urban system is shaped by the interactions between different regions and regions planned by the government, then reshaped by human activities and residents’ needs. Understanding the changes of regional structure and dynamics of city function based on the residents’ movement demand are important to evaluate and adjust the planning and management of urban services and internal structures. This paper constructed a probabilistic factor model on the basis of probabilistic latent semantic analysis and tensor decomposition, for purpose of understanding the higher order interactive population mobility and its impact on urban structure changes. First, a four-dimensional tensor of time (T)?×?week (W)?×?origin (O)?×?destination (D) was constructed to identify the day-to-day activities in three time modes and weekly regularity of weekday/weekend pattern. Then we reclassified the urban regions based on the space clustering formed by the space factor matrix and core tensor. Finally, we further analysed the space–time interaction on different time scales to deduce the actual function and connection strength of each region. Our research shows that the application of individual-based spatial–temporal data in human mobility and space–time interaction study can help to analyse urban spatial structure and understand the actual regional function from a new perspective.     

Impacts of soil fauna on litter decomposition at different succession stages of wetland in Sanjiang Plain, China

Litter decomposition is the key process in nutrient recycling and energy flow. The present study examined the impacts of soil fauna on decomposition rates and nutrient fluxes at three succession stages of wetland in the Sanjiang Plain, China using different mesh litterbags. The results show that in each succession stage of wetland, soil fauna can obviously increase litter decomposition rates. The average contribution of whole soil fauna to litter mass loss was 35.35%. The more complex the soil fauna group, the more significant the role of soil fauna. The average loss of three types of litter in the 4mm mesh litterbags was 0.3–4.1 times that in 0.058mm ones. The decomposition function of soil fauna to litter mass changed with the wetland succession. The average contribution of soil fauna to litter loss firstly decreased from 34.96% (Carex lasiocapa) to 32.94% (Carex meyeriana), then increased to 38.16% (Calamagrostics angustifolia). The contributions of soil fauna to litter decomposition rates vary according to the litter substrata, soil fauna communities and seasons. Significant effects were respectively found in August and July on C. angustifolia and C. lasiocapa, while in June and August on C. meyeriana. Total carbon (TC), total nitrogen (TN) and total phosphorus (TP) contents and the C/N and C/P ratios of decaying litter can be influenced by soil fauna. At different wetland succession stages, the effects of soil fauna on nutrient elements also differ greatly, which shows the significant difference of influencing element types and degrees. Soil fauna communities strongly influenced the TC and TP concentrations of C. meyeriana litter, and TP content of C. lasiocapa. Our results indicate that soil fauna have important effects on litter decomposition and this influence will vary with the wetland succession and seasonal variation. Foundation item: Under the auspices of State Key Development Program for Basic Research of China (No. 2009CB421103), Key Program of National Natural Science Foundation of China (No. 40830535/D0101), Knowledge Innovation Programs of Chinese Academy of Sciences (No. KZCX2-YW-BR-16, KSCX2-YW-N-46-06)     

Decomposition analysis on direct material input and dematerialization of mining cities in Northeast China

Material dematerialization is a basic approach to reduce the pressure on the resources and environment and to realize the sustainable development. The material flow analysis and decomposition method are used to calculate the direct material input (DMI) of 14 typical mining cities in Northeast China in 1995-2004 and to analyze the demateri-alization and its driving factors in the different types of mining cities oriented by coal, petroleum, metallurgy and multi-resources. The results are as follows: 1) from 1995 to 2006, the increase rates of the DMI and the material input intensity of mining cities declined following the order of multi-resources, metallurgy, coal, and petroleum cities, and the material utilizing efficiency did following the order of petroleum, coal, metallurgy, and multi-resources cities; 2) during the research period, all the kinds of mining cities were in the situation of weak sustainable development in most years; 3) the pressure on resources and environment in the multi-resources cities was the most serious; 4) the petro-leum cities showed the strong trend of sustainable development; and 5) in recent years, the driving function of eco-nomic development for material consuming has continuously strengthened and the controlling function of material utilizing efficiency for it has weakened. The key approaches to promote the development of circular economy of min-ing cities in Northeast China are put forward in the following aspects: 1) to strengthen the research and development of the technique of resources' cycling utilization, 2) to improve the utilizing efficiency of resources, and 3) to carry out the auditing system of resources utilization.     

半参数估计与LS估计的有效性比较

建立半参数回归模型,将系统误差加入,推导出了模型正则化矩阵时参数平差的计算方法,并用直接法得到了参数、非参数的估计量,在MSE准则下与最小二乘估值(简称LS估值)进行比较,证明了半参数估值的有效性。     

Triangulated spherical splines for geopotential reconstruction

We present an alternate mathematical technique than contemporary spherical harmonics to approximate the geopotential based on triangulated spherical spline functions, which are smooth piecewise spherical harmonic polynomials over spherical triangulations. The new method is capable of multi-spatial resolution modeling and could thus enhance spatial resolutions for regional gravity field inversion using data from space gravimetry missions such as CHAMP, GRACE or GOCE. First, we propose to use the minimal energy spherical spline interpolation to find a good approximation of the geopotential at the orbital altitude of the satellite. Then we explain how to solve Laplace’s equation on the Earth’s exterior to compute a spherical spline to approximate the geopotential at the Earth’s surface. We propose a domain decomposition technique, which can compute an approximation of the minimal energy spherical spline interpolation on the orbital altitude and a multiple star technique to compute the spherical spline approximation by the collocation method. We prove that the spherical spline constructed by means of the domain decomposition technique converges to the minimal energy spline interpolation. We also prove that the modeled spline geopotential is continuous from the satellite altitude down to the Earth’s surface. We have implemented the two computational algorithms and applied them in a numerical experiment using simulated CHAMP geopotential observations computed at satellite altitude (450 km) assuming EGM96 (n _max = 90) is the truth model. We then validate our approach by comparing the computed geopotential values using the resulting spherical spline model down to the Earth’s surface, with the truth EGM96 values over several study regions. Our numerical evidence demonstrates that the algorithms produce a viable alternative of regional gravity field solution potentially exploiting the full accuracy of data from space gravimetry missions. The major advantage of our method is that it allows us to compute the geopotential over the regions of interest as well as enhancing the spatial resolution commensurable with the characteristics of satellite coverage, which could not be done using a global spherical harmonic representation. The results in this paper are based on the research supported by the National Science Foundation under the grant no. 0327577.     

Singular value decomposition and cluster analysis as regression diagnostics tools for geodetic applications

It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature, mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g., multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry technique which serves as an application example of the regression diagnostics tool.     

带乘性噪声广义系统状态最优估计算法

针对带乘性噪声广义系统,提出1种在线性最小方差意义下的状态最优估计算法.首先,采用标准分解将系统变换为2个子系统;其次,通过估计子系统的状态,获得原系统的状态最优滤波.同时,算法还给出了动态噪声与量测噪声的估计.仿真结果表明了该算法的有效性.