Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.     

On the scavenging of gaseous nitrogen compounds by large and small rain drops I. A wind tunnel and theoretical study of the uptake and desorption of NH3 in the presence of CO2

An experimental study has been carried out in the Mainz vertical wind tunnel to determine the rate at which NH₃ in the presence of CO₂ is absorbed by freely suspended water drops. The experimental uptake rates were found to be in good agreement with the rates predicted by the Kronig-Brink convective diffusion model and, for gas concentrations in the ppbv range also by the model in which it is assumed that the absorbed gas is well mixed inside the drop (henceforth called well mixed model). The same conclusion was shown to apply also to the desorption of NH₃ from a drop previously exposed to NH₃. The latter result is in contrast to the desorption of SO₂ which must be described by a model which accounts for the diffusion of the species inside the drop. Comparison of our experimental results with theory show further that the uptake of NH₃ in presence of CO₂ is significantly overestimated if the slow reaction CO_2(aq)+H₂OHCO ₃ ^– +H⁺ is neglected in the theoretical computation.     

Mean equatorial gravity derived from various geopotential models

Summary Mean equatorial gravity has been computed from geopotential models GEM-10C, GEM-7, GEM-T1, GEM-T2, GEM-T3, JGM-1, JGM-2, JGM-3 and OSU91A and compared to the normal equatorial gravity, _e=978 032·699 × 10^–5 m s^–2, computed from four given parameters defining the Earth's level ellipsoid. In all models g_e>_e.     

Seismic hazard maps for the U.K.

Past studies of seismic hazard in the U.K. that have used modern probabilistic methods of hazard assessment have been site-specific studies, mostly in connection with nuclear installations. There has been a need for general-purpose maps of seismic hazard to show relative variation of exposure within the U.K. and to give some guidance on absolute values. Such maps have now been produced, incorporating, for the first time, the wealth of new information on historical earthquakes in Britain that has been gathered over the last 15 years. The hazard calculations were undertaken using a new computer code based on the USGS program SEISRISK III, but incorporating a logic tree approach to model variation in the input parameters (e.g. focal depth) or uncertainty in the formulation of the model (e.g. attenuation parameters). An innovative approach was taken to the formulation of seismic source zones, in which two overlapping models were employed. The first of these uses relatively broad source zones based loosely on an interpretation of seismicity and tectonics, while the second uses numerous small zones that reflect the locations of past significant earthquakes. This double approach (using the logic tree methodology) has the merit of both considering the general trend of earthquake activity as well as focusing in on known danger spots. The results show that the areas of highest hazard are western Scotland, north-western England and Wales, where the intensity with 90% probability of non-exceedance in 50 years is 6 EMS.     

切片采样算法在光释光年龄模型参数估计中的应用

光释光(OSL)年代学模型是基于数理统计学的一类概率密度模型,它根据特定的假设条件对样品等效剂量(De)分布进行数学解释,由此估计具有不同沉积历史或者能够代表样品实际埋藏年龄的De组分。年龄模型参数估计常通过极大似然估计(MLE)算法实现,本文尝试了切片采样算法在年龄模型参数优化中的应用。切片采样属于一种马尔科夫链蒙特卡罗采样(MCMC)算法,能根据测量数据与模型的联合似然函数进行随机采样,由此获得参数的采样分布。本文编写了实现年龄模型切片采样算法的应用程序,并使用模拟及实测De数据验证了该算法估计的可靠性。相对于MLE算法,MCMC算法具有对参数初值依赖性低、误差估计更准确的特点,切片采样算法提供了实现释光年龄模型参数估计的一种新方法。     

森林景观模型研究新进展及其应用

森林景观模型(forest landscape models)是基于森林动态机制和干扰作用在景观尺度上模拟和预测森林时空变化特征的计算机模型。该类模型越来越多地用于森林规划、经营管理、生态资源保护与恢复及全球气候变化研究。本文通过对大量文献资料的整理,对森林景观模型的概念、尺度、类型、方法、应用和最新研究进展进行了综述。随着计算机、地理信息系统、遥感等技术的迅猛发展,森林景观模型将会越来越多地与地理信息系统、规划经营管理决策等紧密结合,未来将向服务性决策模型方向发展。     

Integrating agriculture and energy to assess GHG emissions reduction: a methodological approach

Agriculture is responsible for approximately 25% of anthropogenic global GHG emissions. This significant share highlights the fundamental importance of the agricultural sector in the global GHG emissions reduction challenge. This article develops and tests a methodology for the integration of agricultural and energy systems modelling. The goal of the research is to extend an energy systems modelling approach to agriculture in order to provide richer insights into the dynamics and interactions between the two (e.g. in competition for land-use). We build Agri-TIMES, an agricultural systems module using the TIMES energy systems modelling framework, to model the effect of livestock emissions and explore emissions reduction options. The research focuses on Ireland, which is an interesting test case for two reasons: first, agriculture currently accounts for about 30% of Ireland's GHG emissions, significantly higher than other industrialized countries yet comparable with global levels (here including emissions associated with other land-use change and forestation); second, Ireland is both a complete and reasonably sized agricultural system to act as a test case for this new approach. This article describes the methodology used, the data requirements, and technical assumptions made to facilitate the modelling. It also presents results to illustrate the approach and provide associated initial insights.

Policy relevance

Most of the policy focus with regard to climate mitigation targets has been on reducing energy-related CO₂ emissions, which is understandable as they represent by far the largest source of emissions. Non-energy-related GHG emissions – largely from agriculture, industrial processes, and waste – have received significantly less attention in policy discourse. Going forward, however, if significant cuts are made in energy-related CO₂ emissions, the role of non-energy-related GHG emissions will grow in importance. It is therefore crucial that climate mitigation analyses and strategies are not limited to the energy system. This article shows the value of using integrated energy and agriculture techno-economic modelling techniques to draw evidence for new comprehensive climate policy strategies able to discern between the full range of technical solutions available. It enables the production of economy-wide least-cost climate mitigation pathways.     

Fitting boxes to Manhattan scenes using linear integer programming

We propose an approach for automatic generation of building models by assembling a set of boxes using a Manhattan-world assumption. The method first aligns the point cloud with a per-building local coordinate system, and then fits axis-aligned planes to the point cloud through an iterative regularization process. The refined planes partition the space of the data into a series of compact cubic cells (candidate boxes) spanning the entire 3D space of the input data. We then choose to approximate the target building by the assembly of a subset of these candidate boxes using a binary linear programming formulation. The objective function is designed to maximize the point cloud coverage and the compactness of the final model. Finally, all selected boxes are merged into a lightweight polygonal mesh model, which is suitable for interactive visualization of large scale urban scenes. Experimental results and a comparison with state-of-the-art methods demonstrate the effectiveness of the proposed framework.     

基于MapGIS K9三维数字校园虚拟系统的设计与实现

近年来,数字校园继数字地球、数字城市之后成为各高校研究的热点,三维数字校园虚拟系统构建平台多样、方法多元,却鲜有基于国内自主产权的MapGIS K9数字校园系统。因此,本文以某农业大学(南校区)为研究对象,对三维数字校园虚拟系统进行设计与实现。利用南方CASS、3DS Max、MapGIS K9及其他相关软件,通过资料收集整理、地理信息测量采集、建立1:500校园数字地形图、建立属性数据库、三维建模、多平台融合、交互式设计等一系列步骤,实现了某农业大学(南校区)三维数字校园虚拟系统的三维可视化和信息查询、测距、校园导航、自由路径游览、漫游视频录制的交互式功能,可以有效进行校园建筑属性信息查询与部分管理。     

Dealing with double vagueness in DEM morphometric analysis

A method is presented to explicitly incorporate spatial and scale vagueness – double vagueness – into geomorphometric analyses. Known limitations of usual practices include using a single fixed set of crisp thresholds for morphometric classification and the imposition of a single arbitrary number of scales of analysis to the entire digital elevation model (DEM). Among the advantages of the proposed method are: fuzzification of morphometric classification rules, scale-dependent adaptive fuzzy set parametrization and an objective definition of maximum scale of analysis on a cell-by-cell basis. The method was applied to several DEMs ranging from the ocean floor to surface landscapes of both Earth and Mars. The result was evaluated with respect to modal morphometric features and to characteristic scales, suggesting a more robust method for deriving both morphometric classifications and terrain attributes. We argue that the method would be preferable to any single-scale crisp approach, at least in the context of preliminary hands-off morphometric analyses of DEMs.