A network theory approach for a better understanding of overland flow connectivity

Hydrological connectivity describes the physical coupling (linkages) of different elements within a landscape regarding (sub‐) surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for example, habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has also been recognized within the scientific community, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterize and quantify overland flow connectivity dynamics on hillslopes in a humid sub‐Mediterranean environment by using a combination of high‐resolution digital‐terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow connectivity on agricultural areas and semi‐natural shrubs areas. Significant positive correlations between connectivity and precipitation characteristics were found. Significant negative correlations between connectivity and soil moisture were found, most likely because of soil water repellency and/or soil surface crusting. The combination of structural networks and dynamic networks for determining potential connectivity and actual connectivity proved a powerful tool for analysing overland flow connectivity. Copyright © 2016 John Wiley & Sons, Ltd.     

顾及邻域居民地群组相似性的道路网匹配方法

现有多源同比例尺道路网匹配方法中,大多只利用道路自身特征进行匹配,而较少顾及道路周边要素对匹配过程的影响和约束,从而影响了道路网匹配效果的进一步提高,特别是对系统误差改正后仍存在一定位置或旋转偏差的道路数据进行匹配时,这种影响尤为明显。本文借鉴人类对陌生环境的空间认知特点,提出了一种顾及邻域居民地群组相似性的道路网匹配方法。该方法通过构建城市骨架线网确定与道路相邻的居民地群组,进而计算居民地群组空间关系和几何特征相似度来获得对应道路的匹配结果。其特点在于:对存在位置或旋转偏差的道路数据匹配,以其邻域空间内居民地群组的整体相似性指标来带动道路自身匹配,实际上是增加了周边居民地群组对道路匹配过程的约束,更具鲁棒性。试验及对比分析表明,本方法能够较好地解决系统误差改正后仍存在较大位置和旋转偏差的道路数据间的匹配问题,提高匹配的正确率。     

Relations between professional groups in the Atlantic and Mediterranean fishing enclaves of Andalusia (Spain): A personal networks approach with clustered graphs

This paper proposes a new network-based approach to analyse intergroup relations in fishing ports. The technique of clustered graphs is applied to the case of the Andalusian fishing ports to assess the balance between intra and inter-professional relationships. The patterns of sociability in Mediterranean and Atlantic fishing enclaves in the southern region of Spain were compared, examining their implications for participatory governance of marine resources. The personal networks of 53 fishermen, ship owners or skippers and key individuals of 18 Andalusian fisheries were analysed. The personal networks were compared in terms of fishing ground (Atlantic versus Mediterranean) and port type (by size and form of participation). The data of 45 individuals with whom each respondent usually interacts in the harbour was summarised in clustered graphs of intra-group and inter-group relationships between 8 professional roles in the harbour. Results show primarily that personal networks of Mediterranean ports are overall denser, in comparison with those of the Atlantic, which are more centralised and have a higher average betweenness. Secondly, in the Atlantic a clear difference of roles between ship owners and skippers is observed. A strong link between ship owners and the crew was found, and also between the ship owner and commercial roles in the Mediterranean. Small ports seem to be more apt for the artisanalisation of fisheries, as well as for the European Union’s Common Fisheries Policy.     

中国装备制造业产学研合作创新网络初探

产学研合作是区域创新的主要途径和重要来源.以中国装备制造产业为例,基于中国知识产权局1985-2012年间的合作发明专利数据,借助SPSS,UCINET,ArcGIS等定量分析工具,对中国装备制造产业合作网络的创新主体结构,空间结构及其演变,创新合作的空间尺度的影响因素进行了分析.研究发现,民营企业,高校在中国装备制造产业创新网络中的地位不断上升,数量不断增加,且已经成为重要的创新源泉;市域空间合作成为发达地区城市产学研创新合作最重要的空间单元,国家空间是欠发达地区城市产学研创新合作的主要空间载体;理工科高校等科技资源的空间集聚态势是导致创新网络层级特征的主要因子,科技资源富集的行政中心如直辖市,省会城市等发达城市成为最重要的资源集聚地,创新源泉和创新合作对象.     

Evaluation of coseismic landslide hazard on the proposed Haast-Hollyford Highway,South Island,New Zealand

Coseismic landsliding presents a major hazard to infrastructure in mountains during large earthquakes. This is particularly true for road networks, as historically coseismic landsliding has resulted in road losses larger than those due to ground shaking. Assessing the exposure of current and planned highway links to coseismic landsliding for future earthquake scenarios is therefore vital for disaster risk reduction. This study presents a method to evaluate the exposure of critical infrastructure to landsliding from scenario earthquakes from an underlying quantitative landslide hazard assessment. The method is applied to a proposed new highway link in South Island, New Zealand, for a scenario Alpine Fault earthquake and compared to the current network. Exposure (the likelihood of a network being affected by one or more landslides) is evaluated from a regional-scale coseismic landslide hazard model and assessed on a relative basis from 0 to 1. The results show that the proposed Haast-Hollyford Highway (HHH) would be highly exposed to coseismic landsliding with at least 30–40?km likely to be badly affected (the Simonin Pass route being the worse affected of the two routes). In the current South Island State Highway network, the HHH would be the link most exposed to landsliding and would increase the total network exposure by 50–70% despite increasing the total road length by just 3%. The present work is intended to provide an effective method to assess coseismic landslide hazard of infrastructure in mountains with seismic hazard, and potentially identify mitigation options and critical network segments.     

VGI and crowdsourced data credibility analysis using spam email detection techniques

Volunteered geographic information (VGI) can be considered a subset of crowdsourced data (CSD) and its popularity has recently increased in a number of application areas. Disaster management is one of its key application areas in which the benefits of VGI and CSD are potentially very high. However, quality issues such as credibility, reliability and relevance are limiting many of the advantages of utilising CSD. Credibility issues arise as CSD come from a variety of heterogeneous sources including both professionals and untrained citizens. VGI and CSD are also highly unstructured and the quality and metadata are often undocumented. In the 2011 Australian floods, the general public and disaster management administrators used the Ushahidi Crowd-mapping platform to extensively communicate flood-related information including hazards, evacuations, emergency services, road closures and property damage. This study assessed the credibility of the Australian Broadcasting Corporation’s Ushahidi CrowdMap dataset using a Naïve Bayesian network approach based on models commonly used in spam email detection systems. The results of the study reveal that the spam email detection approach is potentially useful for CSD credibility detection with an accuracy of over 90% using a forced classification methodology.     

具有随机扰动和混合时滞的两层异质网络的同步研究

在现实生活中,很多复杂的系统不是由单个网络来表示,而是由一组相互依赖的网络系统来表示的.本文研究了具有随机扰动和混合时滞的两层异质网络的对应节点的同步控制问题.基于随机微分时滞方程的LaSalle不变原理和Lyapunov稳定性理论,采用牵制控制方法,对部分节点实施控制,给出了实现同步的充分条件.为了降低反馈控制的增益,结合自适应控制的方法,进一步弱化了两层异质网络实现同步的条件.最后,通过数值仿真,验证了理论结果的有效性.     

Machine learning for pore-water pressure time-series prediction: Application of recurrent neural networks

Knowledge of pore-water pressure(PWP)variation is fundamental for slope stability.A precise prediction of PWP is difficult due to complex physical mechanisms and in situ natural variability.To explore the applicability and advantages of recurrent neural networks(RNNs)on PWP prediction,three variants of RNNs,i.e.,standard RNN,long short-term memory(LSTM)and gated recurrent unit(GRU)are adopted and compared with a traditional static artificial neural network(ANN),i.e.,multi-layer perceptron(MLP).Measurements of rainfall and PWP of representative piezometers from a fully instrumented natural slope in Hong Kong are used to establish the prediction models.The coefficient of determination(R^2)and root mean square error(RMSE)are used for model evaluations.The influence of input time series length on the model performance is investigated.The results reveal that MLP can provide acceptable performance but is not robust.The uncertainty bounds of RMSE of the MLP model range from 0.24 kPa to 1.12 k Pa for the selected two piezometers.The standard RNN can perform better but the robustness is slightly affected when there are significant time lags between PWP changes and rainfall.The GRU and LSTM models can provide more precise and robust predictions than the standard RNN.The effects of the hidden layer structure and the dropout technique are investigated.The single-layer GRU is accurate enough for PWP prediction,whereas a double-layer GRU brings extra time cost with little accuracy improvement.The dropout technique is essential to overfitting prevention and improvement of accuracy.     

区域性网络定位服务应用技术探讨

通过建立区域连续运行卫星基准站网络系统,建立一种新型定位测量与服务模式,取代现有传统标志式控制点位保存、管理与应用模式,实现虚拟化的、现代网络定位服务,并介绍了不同的测绘精度需求的作业与应用模式。