Modelling housing typologies for urban redevelopment scenario planning

Increasing levels of urbanization, combined with growing populations and a need to manage urban redevelopment more sustainably has prompted the need for new tools for urban regeneration in established urban areas. While significant activity is occurring in the areas of volumetric analysis and 3D visualization, utilising these technologies in the development of urban planning tools requires a data schema for defining precinct objects for performance assessment while simultaneously addressing the complexity and interconnected nature of issues relevant to the urban built environment. This paper presents the outcomes of the research and development of a web-based 3D precinct visualization and assessment system, Envision Scenario Planner (ESP), which uses a library of housing typologies to generate easy-to-use, bottom-up, precinct-scale reports on residential infill. The paper illustrates how, through the specification of a residential precinct object data schema and the provision of a set of housing typologies, end users can quickly, and without domain knowledge, generate visualizations and assessments for a variety of housing scenarios, which allows them to determine fit-for-purpose solutions that address a range of issues relevant to contemporary planners and policy makers.     

A scenario planning approach for propositioning rescue centers for urban waterlog disasters

An urban waterlog disaster can produce severe results, such as residents’ property loss, environmental damages and pollution, and even casualties. This paper presents a system specification for urban waterlog disasters according to the analysis of urban waterlog disaster risks. Then, a two-stage stochastic mixed-integer programming model is formulated. The model minimizes the total logistics cost, and risk-induced penalties. Moreover, a deterministic counterpart of the stochastic model is proposed to study the expected value of perfect information. The multi-attribute utility theory is used to build assessment functions that assess the utility of the rescue system and the degree contributed to disaster relief for each rescue center. Finally, a real example of rescue logistics is examined for the urban waterlog disasters in Pudong District of Shanghai, China. Using the proposed model, two main results can be obtained. First, the expected value of perfect information experiment reveals that an additional ¥45,005 logistics cost and an additional ¥2417 risk-induced penalties can be incurred due to the presence of uncertainty. Second, as the weight of risk-induced penalty increases from 0.1 to 0.9, the logistics cost is increased by 41.21%, which thus contributes to a decrease of risk-induced penalty by 97.44%. Some managerial implications are discussed based on the numerical studies.     

面向城市基础设施智慧管养的大数据智能融合方法

针对运维大数据维度高、形式多样化和变化迅速等特性,为提高数据融合效率以及平台的数据统计和决策分析性能,降低抽取-转换-加载（ETL）执行时间开销和数据中心负担,面向智慧管养需求提出一种多层次任务调度（MTS）ETL框架（MTS-ETL）。首先,将数据仓库分为数据临时区、数据仓储区、数据分类区和数据分析区,并根据所分区域将完整的ETL过程划分为4个层次的ETL任务调度环节,同时设计了多频率ETL运行调度以及顺序和非顺序两种ETL工作模式;接着,基于MTS-ETL框架的非顺序工作模式进行数据融合的概念建模、逻辑建模和物理建模;最后,利用Pentaho Data Integration设计ETL转换模块和工作模块以实现数据融合方法。在交通流量数据融合实验中,该方法融合136754条数据的时间仅为28.4s;在千量级的数据融合实验中比传统ETL方法的总平均执行时间降低了6.51%;报表分析结果表明其在融合400万条数据时依然能保证ETL过程的可靠性。所提方法能够有效融合运维大数据,提高平台统计分析性能,并维持ETL执行时间开销在较低水平。     

面向数字城管的数据分析与挖掘系统的设计与开发

数字城管在现代城市管理中具有重要的意义。介绍了一个面向数字城管的数据分析与挖掘系统的具体设计和实现,该系统基于Java EE平台开发,综合利用了统计分析方法和范例推理技术,能够提供对城市管理的科学决策。     

面向城市水务管理的联合管理平台设计与实现

近年来,各地政府水务部门都在积极探索通过信息化技术应用来提升城市排水系统管理以及防洪排涝应急调度能力。为了支撑排水系统的长效运营管控,加强防洪排涝智慧化调度水平,针对城市水务部门的管控需求,结合多个项目实践经验与技术应用,总结形成了一套面向城市水务管理的厂网一体化管理平台解决方案。通过对城市排水系统涉及各要素进行系统性资源整合,形成结构化的拓扑关联水网,并对排水管网、易涝点、调蓄池、智能截流井等设施设备等进行全时段监控,基于水安全多源数据汇集与接入构建排水模型与调度模型,提供以目标为导向的分析预警、应急指挥与优化调度服务。在当下各地陆续开展水环境综合治理的背景下,在工程措施基础上,通过联合管理平台实现城市水务综合设施的一体化联合管理调度,能有效提升城市防汛应急决策的水平。     

Fuzzy-stochastic-based violation analysis method for planning water resources management systems with uncertain information

In this study, a fuzzy-stochastic-based violation analysis (FSVA) approach is developed for the planning of water resources management systems with uncertain information, based on a multistage fuzzy-stochastic integer programming (FSIP) model. In FSVA, a number of violation variables for the objective and constraints are allowed, such that in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk can be facilitated. Besides, the developed method can deal with uncertainties expressed as probability distributions and fuzzy sets; it can also reflect the dynamics in terms of decisions for water-allocation and surplus-flow diversion, through transactions at discrete points of a complete scenario set over a multistage context. The developed FSVA method is applied to a case study of water resources management within a multi-stream, multi-reservoir and multi-period context. The results indicate that the satisfaction degrees and system benefits would be different under varied violation levels; moreover, different violation levels can also lead to changed water-allocation and surplus-flow diversion plans. Violation analyses are also conducted to demonstrate that violating different constraints have different effects on system benefit and satisfaction degree.     

Advancing scenario planning through integrating urban growth prediction with future flood risk models

High uncertainty about future urbanization and flood risk conditions limits the ability to increase resiliency in traditional scenario-based urban planning. While scenario planning integrating urban growth prediction modeling is becoming more common, these models have not been effectively linked with future flood plain changes due to sea level rise. This study advances scenario planning by integrating urban growth prediction models with flood risk scenarios. The Land Transformation Model, a land change prediction model using a GIS based artificial neural network, is used to predict future urban growth scenarios for Tampa, Florida, USA, and future flood risks are then delineated based on the current 100-year floodplain using NOAA level rise scenarios. A multi-level evaluation using three urban prediction scenarios (business as usual, growth as planned, and resilient growth) and three sea level rise scenarios (low, high, and extreme) is conducted to determine how prepared Tampa's current land use plan is in handling increasing resilient development in lieu of sea level rise. Results show that the current land use plan (growth as planned) decreases flood risk at the city scale but not always at the neighborhood scale, when compared to no growth regulations (business as usual). However, flood risk when growing according to the current plan is significantly higher when compared to all future growth residing outside of the 100-year floodplain (resilient growth). Understanding the potential effects of sea level rise depends on understanding the probabilities of future development options and extreme climate conditions.     

Development of a tool for urban microgrid optimal energy planning and management

Small-sized variable renewable energy sources (RES) live a large-scale development in urban electrical systems. They increase local high dynamic unbalancing and then can create instabilities on the inertia response. Thus, setting an adequate operating reserve (OR) power to compensate the unpredicted imbalance between RES generation and consumption is essential for power system security. Indeed, effective calculation and dispatching of OR considering inaccurate forecast of both RES and load demand can provide substantial cost reductions. Thus, to facilitate the energy management and system optimization in an urban microgrid (MG), a user-friendly tool for Energy Management System and Operational Planning has been developed. The tool provides a complete set of user-friendly graphical interfaces to study the details of photovoltaic (PV) and batteries, load demand, as well as micro gas turbines (MGTs). Furthermore, this energy management system allows system operators to properly model RES uncertainty. In addition, it could assist operators for the day-ahead energy management with an efficient information system and an intelligent management.     

A geospatially-enabled web tool for urban water demand forecasting and assessment of alternative urban water management strategies

This study develops and demonstrates the Integrated Urban Water Model (IUWM) for forecasting urban water demand with options to assess effects of water conservation and reuse. While water and energy balance drive hydrologic, storage and recycling simulations on a daily timestep, social and infrastructural processes are resolved by spatially distributed parameters. IUWM is deployed as an online tool with geographical information system (GIS) interfaces, enhancing its ease of use and applicability at building to municipal scales. The performance of the model at varying spatial scales was evaluated with extensive water metering data for the City of Fort Collins, Colorado. The calibrated model provided very good estimates of demands at individual block group as well as the municipal service area. The capacity of IUWM for the assessment of the spatiotemporal variability of water consumption and effects of water demand management strategies under climate and urban growth scenarios is discussed.     

The role of multidirectional temporal analysis in scenario planning exercises and Planning Support Systems

Planning Support Systems (PSSs) have advanced the process of scenario planning by anticipating potential future outcomes to specific scenario stimulus or investment choices. The models used in these PSSs have typically been restricted to forward-looking exercises, limiting the depth and breadth of understanding of particular problem sets. In this paper we argue that PSS-based scenario planning processes and outcomes might be improved by including multi-directional temporal analysis. This includes alternative timeline navigation methods such as backcasting, recasting, and pastcasting, along with traditional (forward looking) forecasting. These methods can greatly improve the general understanding of modeled results by providing an ability to more deeply inspect the potential consequences of proposed scenarios. We demonstrate these benefits using an application of University of Illinois' Land-use Evolution and impact Assessment Model (LEAM) in McHenry County, IL. In this study, multi-directional techniques were used to analyze the results of LEAM simulation scenarios in terms of actual county spatial and population distributions. Possible issues of variable co-linearity and error attribution were addressed along with a method for improving explanatory power through parameter shrinkage. Based on analysis, we discuss how the ability to navigate through timelines can augment scenario planning processes and help guide strategic sustainable development.     

An integrated materials information system for infrastructure planning

The vitality of a nation or region is based on the effective use of material resources for public and private infrastructure. There are an abundance of technological options and policy choices that can be defined. A value chain approach based on the Reference Material System, using state-of-the-art information systems, can be used to provide an integrated framework for information on material resources and finished materials markets to support planning and analysis of the physical infrastructure that is essential to social and economic development. This framework also provides a model for tracking annual flows and stock levels for the capital account of a region or nation.     

An intelligent management system for the development of a regional transport logistics infrastructure

This paper presents an intelligent management system realized on the basis of ontologies and formalized expert knowledge, mathematical models and numerical methods. We introduce a complex approach to the analysis of transport logistics systems using an original concept of multilevel modeling. The constructed mathematical models and software modules integrated in the system are described in brief. Modern intellectualization tools are applied for providing interaction among different modules and processing of incomplete statistical data. And finally, we consider some test and applied problems and their solution by the system.     

Location of infrastructure in urban railway networks

The location of the infrastructure of the Rapid Transit Network considers at upper level a list of potential transit corridors and stations on the basis of its own constraints, so the network design is modelled on a discrete space of alternatives. At lower level the alternatives are evaluated based on the route and mode user decisions. The optimization objectives are to maximize the transit demand and minimize the private travel time, considering the user's behavior, the physical network, budget constraints and the network design constraints. The design criteria are considered as location constraints, they have been traditionally defined by node and link compatibilities defining lines, but we define a new location constraints based in to minimize the number of routing intersections. The demand mode splitting constraints may be defined by all or nothing mode assignment or like it is proposed by us in this paper by Logit distribution. The models defined with the above alternatives are large integer multicommodity flow network design problems with side constraints. These sets of alternatives are computationally studied to obtain conclusions. The experiments are presented using two networks, a small network and a medium size network, simulating the city of Seville.     

An osmotic computing infrastructure for urban pollution monitoring

Urban pollution control systems suffer from the presence of fixed stations in a greater number than mobile monitoring devices. Data gathered from such stations provide detailed and reliable information, thanks to equipment quality and effective measuring protocols, but these sampled data are gathered from very limited areas and through discontinuous monitoring campaigns. Fortunately, the spread of technologies for mobility has fostered the development of new approaches like mobile crowdsensing (MCS), increasing the chances of using mobile devices, even personal ones, as suitable sensors for the urban monitoring scenario. Nevertheless, one of the open challenges is the management of integrated heterogeneous data flows, differing in terms of typology, technical specifications (eg, transmission protocols), and semantics. The osmotic computing paradigm aims at creating an abstract level between mobile devices/Internet-of-Things devices and a cloud platform, which enables opportunistic filtering and the addition of metadata for improving the data processing flow. This work focuses on the design and development of a middleware that integrates data coming from mobile and Internet-of-Things devices specifically deployed in urban contexts using the osmotic computing paradigm. Moreover, a component of the osmotic membrane has been developed for security management.     

Understanding and measuring the urban pervasive infrastructure

The increasing popularity of mobile computing devices has allowed for new research and application areas. Specifically, urban areas exhibit an elevated concentration of such devices enabling potential ad-hoc co-operation and sharing of resources among citizens. Here, we argue that people, architecture and technology together provide the infrastructure for these applications and an understanding of this infrastructure is important for effective design and development. We focus on describing the metrics for describing this infrastructure and elaborate on a set of observation, analysis and simulation methods for capturing, deriving and utilising those metrics.

Integrating spatial planning and flood risk management: A new conceptual framework for the spatially integrated policy infrastructure

Flooding is a widely occurring natural hazard that noticeably damages property, people, and the environment. In the context of climate change, the integration of spatial planning with flood-risk management has gained prominence as an approach to mitigating the risks of flooding. The absence of easy access to integrated and high-quality information, and the technologies and tools to use information are among the factors that impede this integration. Limited research has been conducted to develop a framework and to investigate the role of information and technologies in this integration. This study draws primarily on the European experiences and literature and identifies three dimensions of the integration of spatial planning with flood-risk management: territorial, policy, and institutional. To facilitate integration and in accord with these three dimensions, a Spatially Integrated Policy Infrastructure (SIPI) is conceptualised that encompasses data and information, decision support and analysis tools, and access tools and protocols. This study presents the connections between SIPI elements and integration dimensions, which is important for a better understanding of roles of geographic information and technologies in integration. The conceptual framework of SIPI will govern further development and evaluation of SIPI.     

A bilevel mixed-integer program for critical infrastructure protection planning

Vulnerability to sudden service disruptions due to deliberate sabotage and terrorist attacks is one of the major threats of today. In this paper, we present a bilevel formulation of the r-interdiction median problem with fortification (RIMF). RIMF identifies the most cost-effective way of allocating protective resources among the facilities of an existing but vulnerable system so that the impact of the most disruptive attack to r unprotected facilities is minimized. The model is based upon the classical p-median location model and assumes that the efficiency of the system is measured in terms of accessibility or service provision costs. In the bilevel formulation, the top level problem involves the decisions about which facilities to fortify in order to minimize the worst-case efficiency reduction due to the loss of unprotected facilities. Worst-case scenario losses are modeled in the lower-level interdiction problem. We solve the bilevel problem through an implicit enumeration (IE) algorithm, which relies on the efficient solution of the lower-level interdiction problem. Extensive computational results are reported, including comparisons with earlier results obtained by a single-level approach to the problem.     

面向水域保护的水域信息管理平台建设研究

为加强水域保护,实现水域管理的信息化和规范化,提高水域保护的效率与科学水平,设计并开发基于WebGIS的水域信息管理平台。以镇江市为研究区域,从水域管理和规划的双重需求出发,整合数据资源构建水域本底数据库、完善水域档案资料,在此基础上,采用框架结构设计和面向对象相结合的技术,设计并实现水域一张图管理、水域动态监测、洪涝分析、侵占补偿、查询统计、变化分析、档案管理和权限设置等功能模块。水域信息管理平台的应用一方面可以辅助政府工作,有效提升河湖水域管理与保护工作水平,另一方面可为水域保护与规划、城市排水系统建设及城市用地规划等相关工作提供数据服务、技术支撑和科学化测评手段,同时可为其他城市水域保护信息化平台建设提供参考。     

A hierarchical infrastructure for SoC test management

HD/sup 2/BIST - a complete hierarchical framework for BIST scheduling, data-patterns delivery, and diagnosis of complex systems - maximizes and simplifies the reuse of built-in test architectures. HD/sup 2/BIST optimizes the flexibility for chip designers in planning an overall SoC test strategy by defining a test access method that provides direct virtual access to each core of the system.