1 Introduction

Nowadays there is a recognized need for designing and developing ICT(information and communications technology)-based strategies and tools to support decision makers in preparedness and response to disaster-related emergencies.The Council of the European Union(1999,2005)recommends,in its Community Action Programme Decisions in the field of Civil Protection,to “take account of scientific research and technological development,”“improve techniques and methods of response,”and “increase public information,education and awareness,”so as to help citizens who live in at risk areas to protect themselves more effectively.

The Hyogo Framework for Action 2005–2015(UNISDR 2005,p.9)promoted initiatives expected to improve early warning systems based on the direct involvement of the population and “the use,application and affordability of recent information,communication and space-based technologies and related services,as well as earth observations,to support disaster risk reduction.”The Sendai Frameworkfor Disaster Risk Redaction 2015–2030(UNISDR 2015,p.15)promotes a “real time access to reliable data,the use of space and in situ information,including geographic information systems(GIS),and use information and communications technology innovations to enhance measurement tools and the collection,analysis and dissemination of data.”

Within the above mentioned international frameworks,we designed and implemented an interoperable ICT-based spatial data infrastructure(SDI)and related Web services called SIRENE—Sistema Informativo per la Preparazione e la Risposta alle Emergenze(Information System for Emergency Preparedness and Response)to support local disaster managers to anticipate,cope with,resist against,and recover from the impacts of natural hazard-induced disasters(debris flows,landslides, floods,and wild fire,among others).The initial definition of the SDI requirements revealed a limited knowledge on the part of the locally appointed disaster managers about the mode and timing of intervention.Improving their decision-making tasks was identified as the primary aim of the SDI.This goal was accomplished by incorporating five principles:(1)plan in advance preventive and mitigation measures to reduce the effects of unexpected and adverse events;(2)anticipate,as far as possible,the demand for disaster relief operations;(3)enhance the knowledge of local managers on procedures and methods of intervention in order to have a positive control in the aftermath of the disaster(preparedness);(4)organize and manage resources and responsibilities to deal with the emergency;and(5)increase the level of data sharing and communication during the disaster(response).

糖蜜酸化液：80 g糖蜜加120 mL蒸馏水搅拌均匀，用硫酸调节pH 4.0～4.3，90～95 ℃水浴并不断搅拌15 min，4000 r/min离心10 min，取上清。

The SIRENE SDI comprises the following modules/services:

•A local repository in which to store and manage heterogeneous,multi source,and geographically localized information: meta dated, authoritative, and research-based susceptibility/hazard and risk maps;volunteered geographic information provided by observers directly in the field(Goodchild 2007);and data useful to cope with a disaster(strategic structures and infrastructures,resources,and so on);

•A GIS installation to visualize and interact with both local and remote geospatial data;

•A VGI module to create,assemble,and disseminate VGI reports concerning the critical environmental conditions that could require monitoring or rapid intervention;

•An engine to flexibly search and retrieve data from the repository;

•A cross-validation service to analyze the extracted institutional and research-based susceptibility/hazard and risk maps against VGI reports;

•A decision support system to suggest,for different types of natural hazards,the proper emergency management procedures(in agreement with the regulatory framework in force at the national and regional levels),the instructions of execution,the people in charge of performing each action,and the legal documents to be issued at each emergency phase;and

染色体的编码方式采用12位二进制编码(最高位权值为23,最低位权值为2-8),采用固定概率交叉和变异操作,交叉概率为0.9,变异概率为0.1。选择操作采用轮盘赌的方式。由于遗传算法是为了优化超参数,模型预测输出与训练样本所给输出越接近的染色体,其适应度应该越高。因此,本文考虑将均方误差用作适应度评价函数,如下所示:

•A communication system (e-mail,Short Message Service(SMS),Skype)to enable data sharing and dissemination.

From the citizens’side,SIRENE may improve risk awareness by its efforts to(1)increase citizen’s understanding of the risks and their components(hazard sources,vulnerable elements,potential consequences of impacts,and so on);(2)monitor and track identified risks;and(3)evaluate risk process effectiveness.People who may be threatened by a disaster may learn in advance what to expect and how to react,and increase their personal culture of safety as a result.This induced proactive participatory mechanism can complement the disaster managers’effort to save lives,reduce property damage,and sustain a community’s essential functions.

The geo-database is locally managed by an open-source database management system(DBMS)(PostgreSQL/Post-GIS5http://postgis.net/.)connected to an open-source desktop GIS(QGIS6https://www.qgis.org/en/site/.—GIS installation in Fig.1).It is populated off-line,and maintained and updated by each municipality with local information.Through the SDI synchronization protocol,each local geo-database is periodically accessed by a Web crawler of the central SDI component in order to copy its content to the central geo-database(managed by the Civil Protection Service).In this way,an updated backup copy is always available and can be shared among many potential end users(neighboring municipalities,local and regional administrative agencies,and so on).

•All the modules/services in a single infrastructure to cope with different types of risk;and

首先，对免耕播种技术概念认知不清。很多农民群众在具体农业生产过程中单一的将某一项看作是技术的全部，实际上，技术包含多种多样。由于对免耕播种技术认知上存在误区，导致技术在推广应用过程中过于单一，存在多种不规范之处，长此进行下去，势必会影响到先进技术的推广应用，甚至会进一步降低农民群众的应用积极性，使农技推广工作受到巨大影响。

An overview of the SIRENE SDI architecture is provided in the following subsections:each module or service is described from an end user’s point of view.

•High_increasing pn=wind during TP=yesterday

2 Literature Review

The scientific literature relevant to our SDI ranges from volunteered geographic information(VGI)collection and exploitation to multisource spatial data infrastructures(SDIs)and decision support systems(DSS)for disasterrelated emergency management.

Craglia et al.(2012,p.389)provide useful insights into the value of social network data for policy and science reports.The authors extend “the paradigm of spatial data infrastructures by advocating an interactive and dynamic framework based on near-to-real time information from sensors and citizens”and analyze the extent to which it is possible to extract information(messages and photos)that are posted daily through social networks such as Twitter and Flickr.The results show that the proposed system can efficiently retrieve useful and timely information from the large volumes of VGI being exchanged daily.SIRENE exploits only structured information provided by different types of observers by means of the VGI portal.Ongoing activities are related to the inclusion,among the monitored sources,of the information that could be extracted from social networks.In fact,the big data created in the context of social networks are valuable,not only for detecting critical events but mainly and more importantly,for analyzing and studying the crowd habits and mode of reactions during the occurrence of critical events.

在过去的艺体类大学英语教学中，教师往往基本只强调词汇与语法结构而忽视篇章教学，采用“填鸭式”教学法，即先大量分析和串讲，然后进行机械性的重复操练，最后让学生背单词。我们常听学生抱怨说大学英语课堂教学枯燥乏味，一篇课文学完后脑里几乎只剩下零散的词汇，即使费劲记住了，也大多不会用，因而逐渐失去了学习的愿望和积极性。针对这一状况，我们对艺体类大学英语课堂教学进行了改革，创设问题情景（即具有一定难度，需要学生努力克服，而又是力所能及的学习情境），实施启发式教学，因为只有富有挑战性而又可以企及的并能激发学生思维的课堂学习才具有强大的吸引力，对学生的学习动机也才具有强烈的激发作用。具体做法如下：

A systematic literature review of collaborative approaches based on VGI exploitation in hazard analysis is presented by Klonner et al.(2016).The authors conclude that the use of VGI in preparedness and mitigation brings with it many opportunities,but also contend that there are still several challenges that remain.These difficulties include the need for integrated research,given that most of the analyses are revealed to be discipline-centric with a lack of interdisciplinary approaches.SIRENE starts from this suggestion and considers VGI as a complementary source of information in the SDI framework.

The research proposed by Schade et al.(2010)suggests that up to 6 billion human sensors are potentially available to monitor the state of the environment,validate global models with local knowledge,and provide information that only humans can capture.The authors argue that Sensor Web Enablement1http://www.opengeospatial.org/ogc/markets-technologies/swe.(SWE)standards can be applied to develop metadata from VGI reports,thus converting VGI into a timely,cost-effective,and valuable source of information for a SDI.Schade et al.describe a work flow for VGI integration into SDI and how VGI sensing and event detection techniques can support a crisis information system.This is close to our approach of deploying VGI maps that use the standard Open Geospatial Consortium(OGC)services in order to analyze the contemporary maps with information from other sources.In our approach we deploy VGI by Web Map Service2http://www.opengeospatial.org/standards/wms.(WMS)and Web Feature Service3http://www.opengeospatial.org/standards/wfs.(WFS)standard services.The rational for not using SWE standard is that in our case observers are asked to report observations described qualitatively by categories,free text,and pictures and not by quantitative measurements,as in the case of VGI created by means of sensors.

Hertfort et al.(2016)analyze the different kinds of geographic information generated by crowdsourcing as a new data source to complement official information.specifically,they distinguish three types of crowdsourcing with increasing complexity and demand in terms of experience or skills:classification,digitization,and conflation.They develop a geographical information crowdsourcing and use it to further point out the potential of the different types of crowdsourcing for disaster management and humanitarian aid.In our approach,VGI is mainly used to point out critical conditions affecting real world objects(classification)or to identify areas that could require monitoring or rapid intervention(digitization).Conflation is carried out later,during the VGI analysis phase,to identify areas with a sufficient density of VGI reports to become a priority for intervention.

Horita et al.(2015)stress the utility of VGI to complement sensor data.These authors use and evaluate the impact of VGI reports to improve the coverage of monitored areas in flood risk management.In order to be able to cross-analyze VGI with sensor data,created and managed within distinct VGI platforms and information systems,Horita and colleagues outline the need to adopt interoperable services.This meshed service is achieved by adopting the Sensor Observation Service(SOS)from the OGC standards,which defines the interfaces for both data receiving and sharing.The SOS also stores the received data in a sensor database.This SOS supports the integration of distinct data formats as well as the interoperability of diverse data sources.Data collected in an SOS are then converted to the geospatial service standard WFS,which enables the researcher to ask questions about geographical features on the Internet.Horita et al.(2015)provide two means to query VGI and sensor data:the former for specifying spatial conditions,the latter for specifying temporal conditions.In SIRENE,we rely on the WFS service for VGI querying with spatial and content conditions.We also apply a spatial/temporal density-based clustering algorithm(Arcaini et al.2016)to identify and validate VGI reporting of critical situations.

Camponovo and Freundschuh(2014)have analyzed VGI reports created by volunteers via the Ushahidi4https://www.ushahidi.com/.Web platform(2015)in response to the earthquake that occurred in Haiti on 12 January 2010.Volunteers translated messages(text,e-mail,and voice)submitted by the victims of the earthquake and categorized each message into a primary and secondary category,expressing distinct emergency needs.Camponovo and Freundschuh’s analysis illustrated that the VGI categories and subcategories mostly failed to convey the main idea of the victims’message.Notwithstanding these results,the authors recognized the utility of VGI for emergency rescue was considerable and they outlined the need for novel methods to cope with the imprecision and uncertainty embedded in VGI.Haklay(2013)offers a different point of view:he points out that imprecision and uncertainties are integral parts of any VGI collection and he states that novel methods to represent and to deal with those problems are needed.A VGI creation and management facility is incorporated into SIRENE SDI.This element provides a flexible discovery service that can identify VGI reports able to answer vague queries and to rank the VGI reports.This feature helps to cope with VGI imprecision and uncertainty.

As for a multisource SDI for disaster risk management,Miyazaki et al.(2015)offer a comprehensive survey of many worldwide initiatives for disaster risk management.They highlight the important role played by exploitation of satellite data products,ground-based observation measurements,and crowdsourcing data created by volunteers with tools such as Ushahidi(2015)and Sahana(Sahana Software Foundation 2015).

A comprehensive overview that achieves state-of-the-art status in geoprocessing Web architecture and technologies,combined with examination of the most current developments in recent years,is undertaken by Zhao et al.(2012).These authors state that light-weight protocols,crowdsourcing capability,and the potential to process real-time geospatial data sources provided by sensors enables distributed,interoperable,and collaborative processing of geospatial data for information and knowledge discovery.

黑龙江省社科院孙文政研究员做了《海陵王瓜州失败始末及其原因》的报告。他认为，海陵王为了实现统一全国，做中国正统的皇帝，不顾金朝的实力，孤注一掷南伐灭宋，在瓜州惨遭失败。失败的原因是多方面的，既有主观原因，也有客观原因，既有历史的偶然性，也有历史的必然性。海陵王贸然发动统一全国的战争，不仅遭到宋朝军民的坚决抵抗，而且遭到金朝军民的强烈反对，以及宋、金双方战略战术上的差异，致使海陵王瓜州失败。

Manfre´et al.(2012)discuss the role of spatial data sharing in the context of the establishment of SDIs to deal with natural hazard-induced disasters.They maintain this can best be done by reinforcing participation from organizations and governments that improves preventive and emergency plans and that increases the potential involvement of citizens in the risk and disaster management process by providing VGI reports.These ideas are also at the basis of SIRENE,since the SDI provides access to multisource geospatial data and VGI.

The AGORA Project(2016) “aimed at advancing knowledge on the use of crowdsourcing and social media for supporting decision-making in disaster risk management.”This project fosters the use of VGI as a source of useful information to “improve the resilience of cities against disasters and extreme events.”SIRENE complements AGORA features by providing a flexible discovery service that uses susceptibility/hazard and risk maps consistent with current query conditions,a cross-validation service to compare VGI reports against the susceptibility/hazard and risk maps,and a DSS able to guide the disaster managers in emergency preparedness and response.SIRENE is an improvement of the original SDI presented by Bordogna et al.(2016)that integrates multisource heterogeneous geospatial data sets and time series information(for example,multitemporal satellite data and VGI)in a fully interoperable framework.The main differences rely on the following:(1)the susceptibility/hazard and risk maps management within an SDI,potentially distributed in several nodes on the Internet(to support scalability);the maps are derived by processing multisource geo-information by distinct models whose use depends on the type of risk,the authoritative and researchbased data available,and the geo-referenced observations collected in situ by observers(VGI);(2)the DSS work flow automation to support disaster managers in disaster preparedness and response;and(3)the query and retrieval engine,which can ease the analysis of the geospatial data sets by providing complex intelligent spatiotemporal querying and answering facilities.

由图4可知，当荷叶发酵上清稀释至200～4 000倍后，其对 Caco-2细胞的存活率无显著性差异(P>0.05)。后续实验选用200倍，即荷叶发酵上清浓度200 μg·mL-1测定细胞抗氧化活性。

而此时，城中早已看不到鳞次栉比的楼宇殿阁、整齐有序的房屋建筑和宽阔笔直的街道，只剩下狼藉一片。一堵堵居民房屋的残墙孤独而立，那些散布遍地的砖石瓦当、铁器铜镞、泥佛遗物无不诉说着当年的繁荣与兴旺。走在黑城里，有一种强烈的时光逆流的感觉，夕阳照在残垣断壁上，看着千年以前的古建筑变成金黄色，在湛蓝的天幕下，有一种无言的悲壮和苍凉。

秦明月摸出一包烟来，抽出一支点上，又把余下的丢在赵大刚的面前，长吐一口烟雾说：“我也感觉这案子不简单。志武的意见也很有道理，如果凶手是器官偷盗者，完全可以有无数种方式处理尸体，而不必这么费事。另外，从凶手缝合死者的伤口来看，他是一个心思缜密的人，他绝无可能不小心把这玩艺留在死者伤口中。所以有两种可能，一是大刚说的凶手故布迷阵，引我们走弯路，另一种就是如志武所说，这是凶手的标志。”

Analysis of hydrogeological surver results in serious kaschin-beck disease area of tibet

The Decision Support Systems Characteristics and Best Practices report drafted within the DECIDE project(DECIDE 2015)reviews the literature on the state-of-theart of DSSs for disaster management(DM).Advances and theory are investigated based on a project’s theoretical foundation,commonly used models,and usage of geographical information systems(GIS).Finally,a review of eight DSS for DM research and operational projects is performed,which also includes a comparative analysis of their functionalities.The review indicates that DM,especially in the phases of preparedness and response,includes complex decision processes.In such a context,situational awareness,forecasted conditions,efficient communications,and comprehensive visualization in a DSS for DM are valuable to decision makers.In designing the SIRENE SDI,such ideas are kept in mind by introducing modules that enhance specific aspects such as situational awareness and forecasted conditions(VGI reports and a flexible discovery service of susceptibility/hazard and risk maps),efficient communication by local stand-alone platforms to manage disaster-related emergencies at the local level,comprehensive visualization by means of the adoption of OGC Web services for maps,and VGI sharing and visualization on the Web.

Shan et al.(2012)propose an emergency response decision support system(ERDSS)as an important tool for authorities to enhance their emergency response capabilities.ERDSS is mainly used to make emergency early warning contingency plans,coordinate and command emergency response activities,manage resources,and provide related knowledge.An effective ERDSS is one of the key factors that determine whether emergency management will be successful.Shan and his fellow authors provide an in-depth literature review of existing research about emergency response,e-government,information technology(IT)service management,and decision support systems is provided.Such proposal,although focused on the emergency response control and planning,fails to offer a discovery service of susceptibility/hazard and risk maps whose efficacy can be great during the emergency preparedness and response phase.

Horita et al.(2015)propose a conceptual data model based on OGC interoperable standards and a framework that integrates voluntary(VGI)and conventional data from wireless sensor networks(WSN)with a spatial decision support system(SDSS)to assist the decision makers in flood risk management.This research is relevant to SIRENE because it also integrates VGI into the SDI and includes a DSS to support disaster managers in the execution of emergency procedures and protocols,in compliance with the regulations in force at the regional and national levels.

SIRENE takes great advantage of the studies analyzed in this section.Our emergency preparedness and response information system moves a step forward by integrating different modules and services in support of disaster management decision-process operations.

3 Overview of the SIRENE SDI Architecture

From a software Engineering point of view,the main characteristics of SIRENE implementation are the cost minimization of both hardware and software components gained by:(1)its freely distributable licence(with no royalties required);(2)its self-explanatory user interface and user interaction:(3)its comprehensive functionalities that exploit both authoritative/research-based and freely provided geographic information;(4)its stand-alone set up without external dependencies except for the common libraries provided by the operating system);(5)its rapid prototyping(functional requirements and logic details may change within the prototyping loop)and easiness to update;and(6)its network failure resilience,since its use is possible even in the event of Internet failure).

A flexible direct query can specify soft conditions for the values of some parameters.For example,the end user can specify a query by the following soft conditions:

稻谷（华梗5号）：宿州；叶黄素标准品（97%）：美国Sigma公司；2,6-二叔丁基-4-甲基苯酚（BHT）：上海阿拉丁生化科技股份有限公司；四氢呋喃（THF）：天津市致远化学试剂有限公司；甲醇、正己烷、乙酸乙酯（色谱纯）：天津市科密欧化学试剂有限公司；氢氧化钾：西陇科学股份有限公司。

Nevertheless,each municipality hosts a local minimal self-contained kernel installation of the Web services that includes a data repository(Preparedness and Response Geo-Database),a GIS application,a VGI portal(Ushahidi),and the DSS with its execution engine.This enables decision makers to manage local data and carry out preparedness and response procedures even if the Internet connection is not working.In effect,each component of the SDI has to be intended as a basic “brick,”designed and developed so that it can be installed and run as a standalone component,one independently from another.This makes possible a customized deployment of the digital environment in each municipality based on local policies and needs.

•The opportunity to adopt and deploy homogeneous and standardized emergency preparedness and response procedures all over the municipalities that are affected by the disaster.

3.1 Preparedness and Response Geo-Database

The rationale of the Preparedness and Response Geo-Database is to make available institutional and noninstitutional(mainly research based) information to a multidisciplinary group of potential end users(scientists,experts,and technicians).

Institutional information focuses on four data sources:(1)susceptibility/hazard and risk maps certified by authorities as reference information to be used in disaster management for different types of natural events(Fig.2a for landslides);(2)a list of strategic structures,infrastructures,and resources;(3)the people appointed to cope with an emergency;and(4)other thematic maps that may support the decision-making process.

Noninstitutional information primarily refers to susceptibility/hazard and risk maps generated off-line by applying different modeling techniques for different types of natural events(Fig.2b,c for debris flows).Although these models are compliant with uncertain information management,such as Bayesian,soft computing,and evolutionary computation modeling,the resulting maps are not ratified as “institutional”by the authorities and only can be used as supplemental information that is complementary to the institutional maps.application,a VGI portal(Ushahidi 2015),and the DSS with its execution engine.The Web services provide:query and retrieval facilities for both metadated susceptibility/hazard and risk maps and indexed VGI reports together with cross-validation functions to check VGI against susceptibility/hazard and risk maps

Although some of the SIRENE SDI services have already been proposed in the literature,the novelty consists in the services integration as a whole.As recognized by the Civil Protection Services,where testing installations are in use,this is one of the main pros in using SIRENE.specifically,disaster managers have at their disposal,in a timely and efficient manner:

Institutional and noninstitutional maps are indexed by an off-line procedure through their metadata,managed by a metadata catalogue service.Metadata allow decision makers to query flexibly and retrieve susceptibility/hazard and risk maps(via the query engine)on the basis ofrelevant user-defined criteria(mainly referring to static geo-environmental variables and/or the dynamic meteorological-climatic parameters).

Institutional and noninstitutional maps are then compared with the spatial distribution of vulnerable elements.The institutional approach classifies the study area into four qualitative risk classes(from very low to high,Fig.2d)by means of a bidimensional matrix(hazard against exposure/impact);the noninstitutional approach classifies the study area into four semiquantitative risk classes(Fig.2e)and also provides exposure data,expressed in monetary terms and the expected degree of loss(risk)by applying three different vulnerability values(Blahut et al.2014).

The geo-database also provides disaster managers with authoritative and geocoded information about strategic structures,infrastructures,resources,and personal contacts(related to authorities,technicians,and volunteers)with the intention to prepare for and cope with a disaster-related emergency.

A graphic user interface is designed and implemented to make data entry easier for people who are not expert in Structured Query Language(SQL).Control mechanisms are also implemented to constrain and regulate data entry by checking errors,data completeness,and consistency.

3.2 Susceptibility/Hazard and Risk Maps Query and Retrieval Engine

Given that modeling susceptibility/hazard and risk maps is a computationally time-consuming activity,a large number of institutional and noninstitutional maps are prepared and stored in advance for each study area,each of which is synthesized by thematic,modeling,geographic,and temporal metadata.This module(Susceptibility/Hazard and Risk Maps Query and Retrieval Engine in Fig.1)makes use of the SDI catalogue service to manage,query,and retrieve the metadata.It is based on the Open Geospatial Consortium(OGC)Catalogue Service for the Web(CSW)standard that describes common interfaces with which to access metadata information.This Web service provides the decision maker with a high level, flexible query language to search,retrieve,and display the most plausible institutional and noninstitutional maps(by exploring their metadata content).Plausible maps in this context are considered to be those maps that have been generated or modeled with parameter values that best fit an area’s current geo-environmental and meteorological-climatic conditions,ranked according to the degree of fulfillment of the above-mentioned conditions.

3.2.1 Storing the Metadata in a Catalogue Service

Metadata are encoded in Extensible Markup Language(XML),a format compliant with current regulations in force at the European level for geo-data interoperability(INSPIRE 2007).These metadata are an extension of the standard INSPIRE metadata schema,which guaranties full compliance with OGC CSW as far as the discovery facility is based on spatial,temporal,and thematic representation.The metadata fields,which describe the spatial content of the hazard/susceptibility and risk maps,are embedded within the content field of the standard metadata format,since they enable a content-based discovery of the maps as described below.

3.2.2 Searching Susceptibility/Hazard and Risk Maps

In order to retrieve susceptibility/hazard and risk maps that are most plausible with respect to current environmental and meteorological-climatic conditions,the metadata first are indexed.Each query must be flexible enough in order to allow the end user to specify vague selection conditions,which can containing linguistic terms that have vague meaning,such as “high temperature in the last week”(in case of wild fire)or “high precipitation in the last three days”(in case of floods).This is done by modeling flexible queries in the framework of fuzzy databases(Bordogna and Psaila 2004;Galindo 2008).When precise information concerning triggering or predisposing parameters is available,classic queries with crisp conditions can be formulated as a special type of flexible queries.

(1) Direct query by constraining the parameters values

土老帽：“哈哈哈！看大家说得如此热闹，我也忍不住看了一下，觉得有些感慨，在手机照相流行的今天，除了全家福、大合照、结婚照一类的有特殊意义的照片会冲印出来，大家现在很少会把照片洗出来，放在相册里留待翻看。想想以前爸妈帮我们拍照，再去照相馆精心选出来，那种期待的心情，之后回想起当时的场景，感受到亲人的陪伴，生活的有趣，与现在拍照一秒钟，精修美颜一小时的心情，截然不同了。拍照其实是次要的，我们更需要去关注的是身边的人，更需要去感受和发现的是身边的趣和美。这才是生活啊。”

From a conceptual point of view(Fig.1),SIRENE consists of several distributed modules and services,customized to the protocols,policies,and needs of local disaster managers,and connected via the Internet to a central server,which is located at the Civil Protection Service.The Web-based services provides:query and retrieval facilities of both susceptibility/hazard and risk maps and VGI reports;and cross-validation functions to check VGI against susceptibility/hazard and risk maps.The Internet connection allows information(maps and DSS rules)to be transferred from/to the central server and shared with other potential end users(neighboring municipalities,local and regional administrative agencies,and so on).

• Select SM= “wild fire susceptibility map”

For decision support of environmental domains,a review is proposed by Sokolova et al.(2011)in areas of complex system analysis and decision making by means of intelligent tools,including agent-based systems.The article also compares existing agent-oriented methodologies and frameworksfordecision support.Although multiple efforts,created for theoretic research and practical implementation of information systems,resulted in many successful applications,many successful efforts still lack a systemic view and cannot offer a coordinated and controlled approach that links methods together into a coherent methodology.Such partially successful DSSs focus excessively on a specific aspect of environmental management in contrast with the comprehensive nature of the SIRENE DSS,which is a work flow support tool for all the emergency management phases needed for all kinds of risk.

Where

•high pn=temperature during TP=last month

AND

•very high pn=temperature during TP=last week

AND

•very high pn=wind during TP=yesterday

AND

•None pn=rainfall during TP=last month

in which SM stands for “spatial map theme,”pn stands for “parameter name,”and TP for “time parameter.”

1.2.1 缓冲溶液的制备 精密称取Na2B4O7、KH2PO4、NaH2PO4、Na2HPO4、Na3PO4、柠檬酸、柠檬酸钠适量，分别用超纯水溶解制成0.05、0.2、0.2、0.2、0.2、0.2、0.2 mol/L贮备液。根据种类和浓度需要配制运行缓冲溶液，若需调节缓冲溶液pH时，则通过滴加1 mol/L NaOH及磷酸(H3PO4)溶液调节，用pH计精密测量。缓冲溶液使用前用0.22 μm微孔滤膜过滤。

The end user formulates this query when interested in retrieving the most plausible wild fire susceptibility maps given the current conditions described by the linguistic values of the parameters.Such soft conditions constrain the values of the correspondent parameter to some ongoing recent meteorological-climatic conditions,which are expressed by the linguistic values “high”for “temperature”during the “last month,”or “very high”for “temperature”during the “last week,”and so on.

This query is evaluated by accessing the metadata indexes to compute the ranking score of each indexed map.The SM maps associated with the ranking scores greater than zero can be listed in decreasing order to the user.

(2) Direct query by constraining the parameters trends

The end user specifies a soft condition concerning the trend of some parameters based either on recent or forecasted values:

An example of such query can be:

• Select SM= “wild fire susceptibility map”

Where

•High_increasing pn=temperature during TP=last month

AND

The main aim of this article is to describe SIRENE’s design and implementation.A review of related research publications and projects is initially presented.An overview of the SDI architecture and the different modules and services then are described.A hypothetical use case of the SIRENE SDI follows.Discussion and ongoing activities conclude the article.

AND

•High_decreasingpn=rainfall during TP=last month

The evaluation is performed as in the previous case.The SM maps associated with the positive ranking scores are listed to the end user in decreasing order.

(3) Inverse query

软件系统设计也是整个监控系统设计中较为重要的一项系统设计，在其系统的设计中，主要针对系统设计监控成像系统的处理，通过软件设计，将对应的控制程序输入到监控系统设计的内部控制系统中，通过这种系统监督控制处理，能够发挥出整个系统监控工作开展的保障性工作。比如对于监控系统应用界面的设计，以及对应的监控系统启动程序设计等都属于软件系统设计中的构成因素，整个软件系统设计编写中，以国际编程计算机软件信息处理标准为依据。

Inverse queries are useful when a decision maker needs to know the lower/upper bounds of some environmental and/or meteorological-climatic parameters(pn)that may trigger a given susceptibility/hazard or risk level.In this case the result of a query is a summary of the parameter maps that generated the top ranked map that best satisfies the query condition.

An example of query could be the following:

• Select pn1= “temperature”,pn2= “wind”

Where

• SM= “wild fire susceptibility map”is high

in which “high”is a soft condition on the susceptibility values of wild fire maps.This query is evaluated by accessing the SM maps content index,by identifying the SM map that best matches the soft constraint“high”and in retrieving the parameters “temperature”and “wind”that are encoded into the metadata of the SM map.

(4) Results

The result of a flexible query must be an informative answer.Besides retrieving the most plausible susceptibility/hazard or risk maps,two virtual maps,which represent the most likely optimistic and pessimistic scenarios that may occur,are generated,together with the variability of susceptibility/hazard or risk levels in each pixel.To provide this additional information,a map fusion operation is performed.specifically,given m maps retrieved by a query,they are merged in order to obtain the most pessimistic/optimistic scenario.For the optimistic scenario,the value of a pixel can be computed as the minimum susceptibility/hazard or risk level in all maps.In fact,in the optimistic map the best case is expected to happen,that is,the lowest level within each pixel is selected.Conversely,for the pessimistic scenario,the value of a pixel is computed as the maximum value,the highest susceptibility/hazard or risk level in each pixel.

3.3 Volunteered Geographic Information(VGI)and Query and Retrieval Engine

This module(VGI Portal(Ushahidi)in Fig.1)exploits the geographic information freely reported by different types of observers (citizens,volunteers,technicians,and authorities),before or in the early stages of an emergency.In order to define the authorship of the VGI reports,four different types of observers are considered:(1)citizens are the general public;(2)volunteers are the civil protection volunteers who have received an adequate training in civil protection matters and so they can contribute to the disaster risk preparedness and response of an area;(3)technicians are local employees whose technical background can be effectively exploited during a disaster emergency;and(4)authorities are local representatives or delegates who have the power or right to give orders and make decisions.

VGI providers use a customized version of the free tool Ushahidi to create locally and submit their observations(VGI reports),which consist of text,date,and time categories,and possibly also images and videos(more details in Arcaini et al.2013).These observers connect to the local VGI portal,managed by the local control room operator,who authenticates their identity on the administration registry.This procedure discourages spam reports.Observers are categorized according to their status as authorities,technicians,volunteers,and citizens who may be unregistered or registered observers.

Each municipality hosts a local installation of Ushahidi.The local acquisition of VGI was chosen to allow the operator to con firm the reliability of VGI reports by:(1)cross-checking the authorship of the VGI authors with their personal information(status);and(2)comparing the VGI reports with the contents of the other incoming VGI reports.In effect,one of the primary problems in the use of VGI is estimating the quality of the information,which depends on several factors,such as the reputation of the source,and the truthfulness and accuracy of the content(Devillers and Jeansoulind 2006;Goodchild and Li 2012).A method for estimating report quality is based on a comparison between the textual content of the VGI reports close to each other both in space and time.A high density of records that point out the same observation in a given region at the same time reinforces the truthfulness of their content and thus increases the level of attention to and possible intervention in the reporting area.After applying these filters,the operator can demand a supplementary in situ monitoring activity or can make the VGI reports directly visible both locally and remotely to other municipalities.

Each local,independent Ushahidi database is periodically visited by the central VGI crawler of the SIRENE SDI and the new VGI reports are indexed and managed by the central VGI catalog service to enable their availability to other municipalities.Finally,a mapping and a crossvalidation component(Arcaini et al.2013)allows users to visualize VGI reports by matching a query from all municipalities.The operator can extract and visualize on a map where all reports concerning a particular hazard category(for example, “smoke”in Fig.3)are located in a given time interval.The operator can also visualize,by distinct colors and symbols,different levels of the same hazard(high flames,medium flames,low flames,smoke,fire off)and the category of observers who are submitting the reports.A cross-validation service also can be used to compare the preselected susceptibility/hazard and risk maps against the VGI maps in order to analyze their spatial correlations and,eventually,highlight their consistencies and/or conflicts.As a consequence,by exploiting VGI reports,each map can be updated and made into a dynamic support for disaster managers.

3.4 Decision Support System(DSS)

The DSS module(Fig.1)is the core of the SDI that supports decision makers in disaster-related emergency management.Four emergency phases are prescribed by the Italian National and Regional laws:null,normal,moderate,and high.For each of these,a list of expected/mandatory activities is provided.The DSS does not take any direct decision on the actions to execute.The role of the DSS is passive,since it suggests the expected or compulsory actions for different types of events(in agreement with the regulatory framework in force at the national and regional levels,for different types of natural hazards)together with the instructions of execution,the people in charge of performing each action,and the legal documents to be issued at each emergency phase.

The emergency management procedures(DSS rules in Fig.1)are formalized by using Petri Nets(Murata 1989)and executed by the DSS engine installed locally(Fig.4).A Petri Net is a formal mathematical modeling language used to describe stepwise processes that include choice,iteration,and concurrent execution.Finally,the DSS engine and related Graphic User Interface(GUI)take the user to the guided execution of an emergency procedure.

When accessing SIRENE,the disaster manager is allowed to(Fig.5):

1.Select the proper management procedure(work flow)among those that are listed(as explained in the Use Case)in relation to the hazard type,graphically visualize and interactively execute it;

2. follow the instructions of execution of each procedural step;

3.access the local geo-database and extract institutional and noninstitutional data;

4.access and issue the documents linked to each procedural step;

5. deliver the current state of emergency management to the Civil Protection Service,through the Internet connection;

6. access institutional regional/national weather forecast websites through Web services;

7. access institutional regional/national volunteers’management websites through Web services;and

8.guarantee communication and information sharing by communication tools(Skype,SMS,and e-mails).

At any time,the work flow can be forced to move forward,although the ongoing action may not yet be completely accomplished.This is important when an event becomes extreme and no time is available to start and conclude each step before getting to the proper emergency phase.A log file registers all the executed actions,the operator in charge and the time and date of each action.This log file plays a crucial role:in the training phase,to measure the response capacity to different hazard types and,if needed,to check and modify the formalized procedures;to carry out back analysis(identify lessons learned from past events or simulations);and to control,verify,and validate the consistency of each procedural step.

4 SIRENE SDI Use Case

In this section we describe the steps that a decision maker can perform when managing a hypothetical disaster-related emergency by means of SIRENE SDI.After receiving a meteorological bulletin that details severe weather forecast for the following hours in an area vulnerable to flood hazard,the decision maker launches SIRENE and starts a new session selecting the procedure formalized for Hydraulic Risk.When the Moderate Emergency Phase is adopted by the Regional Office of Civil Protection,SIRENE leads the decision maker throughout the flow of procedural steps defined in compliance with the Italian legislative framework and guides him/her in planning the earliest countermeasures to be put into practice to deal with the predicted phenomena.

The decision maker proceeds choosing the proper action and,jointly,the DSS shows the instructions of execution.For each operational step the decision maker visualizes information and contacts( fixed and mobile phone numbers or e-mails)of either authorities or responsible parties who must be alerted(that is,the Operative Municipal Responsible,the Volunteers Responsible,the Municipal Police Commander,and all other members of the Local Crisis Unit),and generates the documentation to be issued(for example,for the activation of volunteers).Through the geo-database,the decision maker verifies the location and availability of strategic structures and logistic resources.already carried out;F:the graphic window showing the ongoing action(in green)and the expected ones;G:execution button of the ongoing action.The module’s tool bar contains buttons and dropdown lists to access the log file,the weather forecast websites,the volunteers’management websites,among others

At the same time,the DSS allows the decision maker to stay up-to-date with evolving meteorological conditions through direct access to the Regional Civil Protection website.A worsening of meteorological conditions initiates a statement of the High Emergency Phase by the Regional Meteorological Office of Civil Protection.This warning triggers SIRENE to push the decision maker to elevate the local emergency phase to a regional scale response.The DSS suggests the decision maker prearranging the activation of local coordination centers for emergency management(the Local Crisis Unit)and,eventually,provides supporting material and documentation to be approved and submitted.The decision maker is exhorted to carry on and adjust monitoring actions that focus attention on the potential to exceed instrumental thresholds(that is,rainfall or river water depth thresholds)that activate risk scenarios in the most critical points.

By accessing the geo-database through the Query and Retrieval Engine,the decision maker retrieves previously stored institutional and noninstitutional susceptibility/hazard and risk maps in order to evaluate the extent of the areas potentially affected by the expected flood event.By overlapping the expected scenarios with the VGI provided by different types of observers directly in the field(Cross-Validation Module),the decision maker is able to update the hazard scenario and to verify the number and location of the exposed elements in order to plan a possible evacuation.The communication capabilities implanted in SIRENE allow the decision maker to alert the strategic structures available to shelter people who could be displaced during an evacuation,as well as alert the responsible parties appointed to perform the evacuation procedure.The decision maker keeps a positive control on monitoring all such actions and resources deployment.

When a critical hazard condition arises and threatens to become extreme,the decision maker can raise the local emergency phase.The decision maker is called to activate the Local Crisis Unit and to intensify countermeasures to manage rescue activities,evacuation,and population assistance.The decision maker carefully examines each operational step suggested by the DSS,which makes available execution instruction for every responsible person involved in local coordination centers for emergency management.The action protocol can be stopped uniquely by the senior decision maker with the revocation of the emergency phase previously activated.The DSS guarantees the decision maker a positive control on the return to the Normal Emergency Phase as well as on the proper management of human and logistic resources.

5 Discussions and Ongoing Activities

Risk managers need up-to-date,authoritative,researchbased,and geo-localized information in order to improve their ability to prepare and deal with critical ongoing or expected events,under specific static and dynamic environmental conditions.This allows monitoring and mitigation options and emergency interventions to be planned effectively in advance and deployed on time.

The main challenge of SIRENE is to provide disaster managers with a modular,collaborative ICT-based SDI aimed at preparing for and coping with disaster-related emergencies.Although some modules and services of the infrastructure have already been proposed in the literature,others are relatively new as is their integration into a coherent emergency information,decision,and action framework.

SIRENE SDI provides different modules and services that can be used to manage both the preparedness and the response phases of an emergency.During the former,the Preparedness and Response Geo-Database can be continuously updated.The VGI portal can be used to collect freely provided data on most at risk areas that potentially need monitoring and/or mitigation actions.The Query and Retrieval Engine can be used to extract and collate data to know in advance what to expect and how to visualize potential hazardous events within a Web GIS.The DSS can be used under normal conditions to check the work flow consistency of the model and train disaster managers and responders.During an emergency response,the crossvalidation functions can be used to check VGI evidence against existing susceptibility/hazard and risk maps and,if needed,re fine them.The integration of authoritative and research-based data with freely provided volunteer information makes the maps’updating procedure more reliable and very effective.The DSS also makes emergency management more controlled and completely compliant with the relevant laws at the national and regional levels.The communication system(Skype,SMS,and e-mails)supports easy and quick data sharing and dissemination.

No similar SDI is currently available in Italy.Although advantages have been recognized by the Civil Protection Services,where a test version has been running for over a year,the main disadvantage is that multirisk procedure,intended to manage jointly different types of concurrent or subsequent correlated events(for example,a landslide that dams a river),have not yet been designed and implemented.Today,each event is managed separately and independently one from another.In the next release of SIRENE,we will address this weakness by providing new mechanisms to improve multirisk procedures and share related information.

SIRENE has not yet been used to manage an actual disaster of ficially;nevertheless the Civil Protection Services of the study areas in northern Italy and Umbria have tested the SDI and provided feedback to support its upgrading and redesign of the graphic user interface(GUI).Initially,the study areas contribution was mainly restricted to the definition of system requirements and then to error identification both in the system’s architecture and its work flow contents.Nowadays many volunteers,technicians,and authorities(no citizens at this stage of the development)are using SIRENE in order to provide feedback concerning SIRENE’s usability,efficiency,reliability,and,above all,the correctness and completeness of its work flows contents.

Other work flows will be designed and implemented by Petri Nets for chemical and industrial accidents,heat waves,and dam collapse.So far only the work flows for the management of disaster-related emergencies caused by floods,wild fires,landslides,and debris- flows have been designed and implemented by Petri Nets.Because these hazards are the main risks in the study areas,which disaster managers have faced in the past and are expected to cope with in the future,they represent the first priority in the design of comprehensive management work flows.

Acknowledgements This work has been carried out within the project:SIMULATOR—Sistema Integrato Mod ULAre per la ges Tione e prevenzi Onedei Rischi—Integrated Modular System forRisk Prevention and Management, financed by the Lombardy regional government,Italy.The authors would like to thank the anonymous reviewer for the valuable comments aimed to improve the manuscript.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://crea tivecommons.org/licenses/by/4.0/),which permits unrestricted use,distribution,and reproduction in any medium,provided you give appropriate credit to the original author(s)and the source,provide a link to the Creative Commons license,and indicate if changes were made.

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