A comparison of three image-object methods for the multiscale analysis of landscape structure

Within the conceptual framework of Complex Systems, we discuss the importance and challenges in extracting and linking multiscale objects from high-resolution remote sensing imagery to improve the monitoring, modeling and management of complex landscapes. In particular, we emphasize that remote sensing data are a particular case of the modifiable areal unit problem (MAUP) and describe how image-objects provide a way to reduce this problem. We then hypothesize that multiscale analysis should be guided by the intrinsic scale of the dominant landscape objects composing a scene and describe three different multiscale image-processing techniques with the potential to achieve this. Each of these techniques, i.e., Fractal Net Evolution Approach (FNEA), Linear Scale-Space and Blob-Feature Detection (SS), and Multiscale Object-Specific Analysis (MOSA), facilitates the multiscale pattern analysis, exploration and hierarchical linking of image-objects based on methods that derive spatially explicit multiscale contextual information from a single resolution of remote sensing imagery. We then outline the weaknesses and strengths of each technique and provide strategies for their improvement.     

高耸塔架结构节点损伤基于神经网络的两步诊断法

本文针对高耸钢塔架结构的损伤特点，建立了具有节点损伤的有限元模型，提出了一种分层神经网络两步诊断法：第一步，由基于区域残余力理论的第一层神经网络进行结构损伤区域的初诊；第二步，由基于应变模态理论的第二层神经网络进行损伤区域内的具体损伤节点位置和程度的诊断。对一平面塔架结构的数值仿真分析表明：本文提出的损伤诊断方法的结果是令人满意的。     

隧道GPS网对横向贯通误差的影响

本文在阐述隧道工程独立坐标系和隧道ＧＰＳ网数据处理方法的基础上推导出ＧＰＳ网对横向贯通误差影响的通用计算公式，分析了隧道ＧＰＳ网基准数据位置对横向贯通误差的影响。     

推求无资料地区设计洪水的一种方法

在地貌单位线、菲利浦下渗公式和暴雨特征频率分布的基础上,引用产流开始时刻和净雨量的概念,推求不同净雨情况下不产流暴雨事件的概率,从而求得洪峰流量小于和等于给定Q_p值的理论频率分布及其相应的重现期。在贵州和山西应用结果表明,该方法更适用于半干旱地区。由模型验证实例分析了这种理论洪水频率分布模型的应用前景。     

关于当前我国战略性矿产勘查工作几个问题的思考

战略性矿产勘查是近几年根据中国地勘管理体制的新变化和国家对矿产勘查工作的新要求提出的概念。本文从战略性矿产的基本内涵、战略性矿产资源勘查工作的性质与任务、战略性矿产资源勘查工作与传统矿产勘查工作的差异、战略性矿产资源勘查工作的管理体制与运行机制等几个方面进行了初步探讨，旨在明确其性质定位和目标任务，逐步建立国家出资的公益性地质工作与后续商业性矿产勘查工作良性互动、有机结合的有效机制，促进中国矿产勘查业全面、健康地发展。     

Spatially weighted supervised classification for remote sensing

A simple approach for incorporating a spatial weighting into a supervised classifier for remote sensing applications is presented. The classifier modifies the feature-space distance-based metric with a spatial weighting. This is facilitated by the use of a non-parametric (k-nearest neighbour, k-NN) classifier in which the spatial location of each pixel in the training data set is known and available for analysis. A remotely sensed image was simulated using a combined Boolean and geostatistical unconditional simulation approach. This simulated image comprised four wavebands and represented three classes: Managed Grassland, Woodland and Rough Grassland. This image was then used to evaluate the spatially weighted classifier. The latter resulted in modest increase in the accuracy of classification over the original k-NN approach. Two spatial distance metrics were evaluated: the non-centred covariance and a simple inverse distance weighting. The inverse distance weighting resulted in the greatest increase in accuracy in this case.     

水质大涡模拟数学模型研究

建立了基于弱可压缩流基础上的水质大涡模拟数学模型及污染物质扩散系数与平均运动的关系。数值计算采用有限体积法和预测校正法,固壁边界条件采用"部分滑移条件"。并应用该模型对重庆嘉陵江、长江两江交汇段的流场,污染物质浓度分布进行了计算,计算结果与实测值比较吻合。研究表明,横向扩散与流动状态有关,当支流流量相对较小时,横向扩散较弱,形成岸边污染带,当支流流量相对较大时,横向扩散较强,污染带向江心移动。     

The neoliberalization of ecosystem services: wetland mitigation banking and problems in environmental governance

Wetland mitigation banking is an American neoliberal environmental policy that has created a functioning market in `ecosystem services', commodities defined using the holistic measures of ecological science. The development of this market is discussed as a project of environmental governance, defined as the nation-state's regulation of ecological relations within its territory towards stabilizing capitalist relations of power and accumulation. I argue that the wetland banking industry serves as a bellwether that presages problems that other strategies of neoliberal environmental governance will experience. Ethnographic, economic and ecological data from the Chicago-area wetland banking industry inform a discussion of two major obstacles to neoliberal strategy: the problem of relying on ecological science to define the unit of trade, and the problem of aligning the somewhat independent relations of law, politics, markets and ecosystems across an array of spatial scales. Theoretical guidance is sought from recent work on `social natures' and from the Regulationist approach to institutional political economics.     

Estimation of daily stream water temperatures with a Bayesian regression approach

Stream water temperature plays a significant role in aquatic ecosystems where it controls many important biological and physical processes. Reliable estimates of water temperature at the daily time step are critical in managing water resources. We developed a parsimonious piecewise Bayesian model for estimating daily stream water temperatures that account for temporal autocorrelation and both linear and nonlinear relationships with air temperature and discharge. The model was tested at 8 climatically different basins of the USA and at 34 sites within the mountainous Boise River Basin (Idaho, USA). The results show that the proposed model is robust with an average root mean square error of 1.25 °C and Nash–Sutcliffe coefficient of 0.92 over a 2‐year period. Our approach can be used to predict historic daily stream water temperatures in any location using observed daily stream temperature and regional air temperature data.