Geomatics Solutions for Disaster Management

Frontmatter

An Online Colour 2D and 3D Image System for Disaster Management

Abstract

This paper presents a new automatic system for fast generation of multiscale colour 2D and 3D satellite images and for online dynamic visualization of the 2D and 3D information of the areas of interest. Mediumresolution satellite images such as Landsat 7 and high-resolution satellite images such as Ikonos or QuickBird are the main data sources for the multi-scale 2D and 3D images. Since Landsat imagery has a global coverage and the Ikonos and QuickBird images can be acquired quickly for the areas of interest, the generation and online visualization of global colour 2D and 3D satellite images at different scales is possible. Ground objects from mountain ranges, such as Rocky Mountains, to individual family houses and trees can be dynamically visualized and analyzed in 2D and 3D through the Internet. The system presents a great potential for fast and effective visualizing, monitoring, and analyzing disaster situations in 2D and 3D within a short time period, which can provide decision makers with important information for emergency response and disaster management. The concept of the 3D satellite image generation and online dynamic visualization are presented in this paper. Some examples on the potential of using online 3D for disaster management are given.

Yun Zhang, Pingping Xie, Hui Li

On the Application of Nighttime Sensors for Rapid Detection of Areas Impacted by Disasters

Abstract

Today a few sensors operating at night are available in the visible/near infrared part of the spectrum, e.g., the U.S. Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS). However, in the case of DMSP/OLS, the availability of a series of satellites arranged in a constellation and the width of the sensor’s swath allows Earth coverage twice nightly. This can result useful in the aftermath of a natural disaster such as earthquake, when first responders providing relief action need to know the location and the extent of the areas of damages, the potential amount of population involved and the place where survivors are concentrated. Naturally, after this prompt detection of the areas affected by the event, the corresponding very high spatial resolution satellite images can be acquired to obtain an accurate overview of the actual damages. In fact, the availability of a preliminary fast estimate of the areas mainly impacted can support a suitable selection of the very high spatial resolution (VHSR) satellite images acquisition time because these sensors are characterized by a very small frame size that makes unpractical a blind acquisition of the whole region possibly impacted. This way to proceed is also compatible with the longer time usually needed to obtain a VHSR image of a given area of interest, due to the orbital and observation geometry constraints.

Even if it is high, the OLS sensor’s sensitivity could be insufficient to detect settlements with reduced artificial lights, as is often the case in the selected regions of interest. Moreover, in many cases, as for informal settlements following the occurrence of natural or man-made disasters, only the presence of bone-fires could reveal the presence of a human community. As a consequence, it would be necessary to observe the affected areas using wavelengths in the Middle-Wave Infrared region of the spectrum (∼ 4 µm), which is presently not feasible due to the limited sensitivity of available sensors. Nevertheless a couple of examples of the results obtainable using night-time images in these scenarios are provided.

To overcome the difficulties described above, this study focuses on a design analysis of a new night-time sensor. The study is based on accurate simulations of the expected radiance scenario reaching the sensor. This, in fact, is required to assess the characteristics of a new sensor capable of detecting the desired target sources (lights/bone-fires).

A. de la Cruz, G. Laneve, D. Cerra, M. Mielewczyk, M. J. Garcia, G. Santilli, E. Cadau, G. Joyanes

A Fuzzy Relational Method For Image-Based Road Extraction For Traffic Emergency Services

Abstract

The new generation of high spatial resolution satellite imagery such as IKONOS and QuickBird provide a viable alternative to high resolution aerial imagery. These data have been readily adopted on various applications such as city planning, metropolitan mapping, emergency response and disaster management. In the applications of high resolution remote sensing images, road extraction is one of the most basic and important tasks. Though many image-based road extraction algorithms have been proposed in the past years, most of them extract roads either from grayscale imagery or low resolution satellite imagery. Approaches designed to process lowresolution satellite imagery generally describe roads as curvilinear structures and model roads as relatively homogeneous areas satisfying certain shape and size constraints.

With the increasingly availability of multi-spectral remote sensing images, colour provides another important feature for extracting road networks. The purpose of this study is to develop an efficient algorithm which combines the colour and shape features to extract road networks automatically from high resolution satellite imagery. The proposed method adopts the fuzzy relation based segmentation algorithm and colour similarity measure in the RGB colour space, and follows three steps, (1) calculating colour similarity measurement in the RGB colour space, (2) segmenting colour satellite imagery using fuzzy relation based segmentation algorithm, (3) extracting central lines of roads by a post-processing procedure. The advantage of this method is to automatically determinate the number of classes in segmentation. In most of situations, it is difficult to specify any desired number of clusters. For example, the situations often happen in the segmentations of remote sensing images, because the ground truth is always not available for the scenes covered by those images. The proposed method is examined by extracting road networks from QuickBird and IKONOS imagery. The results show that the proposed method for road extraction is very effective. In order to illustrate the accuracy, the extracted road centerlines are overlaid on the original images.

Yu Li, Jonathan Li, Michael A. Chapman

Development Of Processing Chains For Rapid Mapping With Satellite Data

Abstract

In case of a disaster on a large scale the International Charter of Space and Major Disasters (Charter) provides satellite data from different sensors. Since 2000 more than 140 Charter Calls have proven the great value of this fast disaster response instrument but have also shown different handling problems causing time delay and downgrading the value of rapid mapping products. This paper proposes a framework for a rapid mapping processing chain based on the experiences gathered during the 2005 flood crisis in Switzerland. It focuses on the pre-processing of satellite data, the value-adding step and the visualization of the results. Critical elements are hereby the availability of essential datasets, the processing time, the information extraction and the usability of the products for the end-users. International programs containing rapid mapping elements as PREVIEW or GMES RESPOND and RISK-EOS need further research on the abovementioned topics to improve the usability and significance of their products and to improve the benefit of satellite data for disaster management support.

Yves A. Buehler, Tobias W. Kellenberger

Automatic Generation of Remote Sensing Image Mosaics for Mapping Large Natural Hazards Areas

Abstract

Remotely sensed data, ranging from satellite imagery, airborne laser scanner data, and aerial photograph, play more and more important roles in environmental monitoring, emergency response, and disaster assessment. Among the products of the broad range of applications, raster base maps, which are generated from various sources of remote sensing data, are becoming very critical for effective and efficient disaster management. The raster base maps can provide detailed topographic, land-use and land-cover information on the earth’s surface in a short period or near real time. With the growing requirements of such raster base maps, the techniques which can be used for automatically correcting raw data and generating digital maps are urgently required.

This paper presents a system that consists of a set of processing steps to georeference and merge many satellite or aerial images together in order to quickly map a large geographic region. The periodic processing results can be compared and analyzed for monitoring a large emergency area. The technique makes full use of georeference and sensor model information, such as ephemeris data, geometric model, and/or GPS/INS navigation and positioning information, to automatically register and orthorectify the raw image data. Through mosaicking process, a seamless mosaicking image or image tiles is produced, which will be in a selected map projection system with consistent spatial resolution. Additionally, semi-automatic and manual editing can be performed to produce a standard map to satisfy the requirements of mapping agencies.

Yubin Xin, Jonathan Li, Qiuming Cheng

Mapping Hazardous Slope Processes Using Digital Data

Abstract

The use of satellite sensor data can be used to detect discrete slope processes and landforms with a high degree of accuracy. Whereas previous attempts to classify slope features using per pixel spectral response patterns have provided classification accuracies that are less than 60%, it is demonstrated that a combination of high resolution optical imagery, image segmentation and ancillary data derived from a digital elevation model can discriminate some types of mass wasting processes with accuracies of 80% or higher. The spatial resolution of the imagery is critical to the successful classification of such features both in terms of information derived from textural analysis and in the ability to successfully segment landslide features. Furthermore, the data generated in this manner can be used for geomorphic research in terms of characterizing the occurrence of mass wasting within the bounds of the image scene.

John Barlow, Steven E. Franklin

Monitoring Xi’an Land Subsidence Evolution by Differential SAR Interferometry

Abstract

Differential SAR Interferometry (D-InSAR) technique has been used to monitor the land subsidence evolution in Xi’an, China during the period of 1992 to 2005. Three schemes have been made to detect the three subsidence stages, namely, stage I 1992–1993, stage II 1996–1997 and stage III 2004–2005. And annual subsidence rates have been calculated in three schemes which uncovered the land subsidence evolution in Xi’an from 1990s to now days. The D-InSAR results show that the maximum subsidence rate was up to 20m/a in the 1996, and decreased greatly from 20cm/a in 1996 to 5cm/a in 2005, which mainly owing to the controlling of underground water withdrawal policy in 1996s. For the lack of traditional monitoring results, only the first stage of D-InSAR result has been compared with leveling result, which demonstrated high consistence each other.

Qin Zhang, Chaoying Zhao, Xiaoli Ding, Jianbing Peng

Evaluation of NARAD Precipitation Data for Rainfall Monitoring in Eastern Ontario, Canada

Abstract

The development of NEXRAD weather radar products has greatly advanced the capacity to forecast and provide warnings of severe weather conditions over large areas in a time-efficient manner. However, most studies in the literature are conducted within the U.S. This study evaluates the reliability of NEXRAD precipitation data and rain gauge measurements in Eastern Ontario, Canada, for potential flood monitoring and water budget analysis. Five-month daily rainfall data from NEXRAD and rain gauge measurements were collected and generated for two Eastern Ontario conservation authority regions. The NEXRAD data was evaluated using rain gauge measurements as the reference. A good correlation (0.78) exists between the daily NEXRAD precipitation data and rain gauge measurements, especially for heavier rainfalls. The result also shows that 62% of radar precipitation data underestimates the daily precipitation. This underestimate is more common when the rainfall is small. The evaluation of spatial patterns of rainfall suggests that radar precipitation shows a more continuous pattern than the interpolated surfaces from rain gauges. Considering that small rainfall events contribute a relatively small portion of the total precipitation, NEXRAD products can play an important role in real-time flood monitoring and water budget analysis during heavy rainfall events in Canadian regions within the working range distance of the NEXRAD system.

Dongmei Chen, Andrew Farrar

Evaluating the Use of a Low-Cost Unmanned Aerial Vehicle Platform in Acquiring Digital Imagery for Emergency Response

Abstract

This research project evaluates the utilization of a low-cost Unmanned Aerial Vehicle (UAV) digital imaging platform developed in Manitoba, Canada for emergency response situations. Such a platform allows for the timely acquisition of high resolution imagery during emergency situations by personnel with relatively limited UAV flight training.

Although military use of UAVs has been around since the First World War, their relatively high expense and operational requirements have limited their civilian use. The UAV platform, as tested in this project, is a very valuable and useful tool for disaster response situations, allowing for the easy and timely acquisition of high resolution imagery, by meeting the following criteria:

• fly fully autonomously with little pilot experience
• assembled and ready for launching in less that one half hour
• acquire high resolution imagery (greater than 25 centimetre resolution)
• transported in a midsized car
• relatively low cost ($8,000 US)

A 5.0 mega pixel digital camera enables the UAV platform to acquire colour imagery with a 22 cm spatial resolution from a height of 2100 feet. With a stable and reliable UAV platform already developed, future research will focus on the development and integration of other imaging and sampling techniques such as thermal technologies and air sampling abilities for smoke plume analysis.

Lewis G.

Automatic Classification of Collapsed Buildings Using Object and Image Space Features

Abstract

We present a method based on two kinds of image-extracted features comparing stereo pairs of aerial images before and after an earthquake. The study area is a part of the city of Bam, Iran which was hit strongly by an earthquake on December 26, 2003. In order to classify damages caused by earthquakes, we have explored the use of two kinds of extracted features: volumes (defined in object space) and edges (defined in image space). For this purpose, digital surface models (DSM) were created automatically from pre- and post-earthquake aerial images. Then the volumes of the buildings were calculated. In addition, a criterion for edge existence - in accordance with pre-event building polygon lines — from post-event images is proposed. A simple clustering algorithm, based on the nearest neighbor rule was implemented using these two features simultaneously. Based on visual inspection of the stereo images, three levels of damage (total collapse, partial collapse, no damage) were considered. By comparing pre- and post-earthquake data the results have been evaluated. The overall success rate — total number of correctly classified divided by the total number of samples — was found to be 71.4%. With respect to the totally collapsed buildings we obtained a success rate of 86.5% and 90.4% in terms of producer’s and user’s accuracies respectively, which is quite encouraging. The results of the analysis show that using multiple features can be useful to classify damages automatically and with high success rate. This can give first very valuable hints to rescue teams.

Mehdi Rezaeian, Armin Gruen

Rapidly Realizing 3D Visualisation for Urban Street Based on Multi-Source Data Integration

Abstract

Streets are important component of cities since they provide the best direct impression of the city. Therefore street scenes are important aspect in 3D modeling. Fast 3D City Modeling from a street level can also be quite important for emergency response by providing realistic, updated, accurate information about accessibility to and from affected areas.

This paper presents a 3D reconstruction approach for rapid 3D visualization from street level, which is based on a combination of vehicle-based image sequence and 2D vector map. The approach consists of two general steps: the rapid reconstruction of facade along the street based on side-shooting vehicle-based image sequence and 2D map, and road texture recovery using. The algorithms presented are verified by experiments on real data set.

Zhizhong Kang, Zuxun Zhang, Jianqing Zhang, Sisi Zlatanova

3D Dynamic Simulation within GIS in Support of Disaster Management

Abstract

Modeling and simulation of dynamic phenomena helps specialists and decision makers to better understand, analyze, and predict natural disasters to reduce the related damages. Hence, several models and simulation approaches have been developed with their own strengths and limitations. One important factor which has to be taken into account when dealing with a disaster is its dynamic behavior and its geometrical and topological representation. Geographic information systems are very well adapted for spatial data organization, visualization, querying, and analysis, and may be helpful in the context of simulation and modeling of spatial phenomena (e.g. floods). However, regarding the three dimensional and dynamic nature of spatial data related to a disaster (which changes with respect to space and time), several complexities are added to the entire process of simulation using the existing GIS.

In order to use GIS as a suitable platform to implement the simulation of disaster phenomena, GIS must be improved; adding the ability to manage and model the 3D and dynamic properties of spatial data (i.e. a truly 3D GIS), as the data structures of the current GIS are static. This research work is an attempt to overcome the current GIS limitations to simulating such natural phenomenon by proposing a 3D dynamic data structure. This structure is based on 3D Delaunay tetrahedralization that deals with objects and field representation of space at the same time, and provides an on-the-fly interactive topological mesh for numerical simulation. This means that cell (or element) size and shape depend on the distribution of the data and it is possible to do local on-the-fly updating of topology after any movement or change in 3D space. In order to analyze the different capabilities of the proposed data structure, its application to flood simulation is discussed at the end of the paper.

L. Hashemi Beni, M. A. Mostafavi, J. Pouliot

Ontologies for Disaster Management Response

Abstract

Increasing numbers of natural disasters and man-made disasters, such as earthquakes, tsunamis, floods, air crashes, etc., have posed a challenge to the public and demonstrated the importance of disaster management. The success of disaster management, amongst all, largely depends on finding and successfully integrating related information to make decisions during the response phase. This information ranges from existing data to operational data. Most of this information is geographically related and therefore when discussing integration of information for disaster management response, we often refer to the integration of geo-information. Current efforts to integrate geo-information have been restricted to keyword-basedmatching Spatial Information Infrastructure (SII, may also known as Spatial Data Infrastructure). However, the semantic interoperability challenge is still underestimated. One possible way to deal with the problem is the use of ontology to reveal the implicit and hidden knowledge. This paper presents an approach for ontology development and ontology architecture, which can be used for emergency response.

Wei Xu, Sisi Zlatanova

Mapping between dynamic ontologies in support of geospatial data integration for disaster management

Abstract

The effective management of disasters requires providing relevant and right information to the concerned decision makers. By its nature, disaster management involves multiple actors and organizations, potentially implying a significant volume of geospatial data coming from heterogeneous and autonomous geospatial data sources. Integration of these data sources is difficult not only because of the semantic heterogeneity of data but also because of the dynamic nature of the reality that is studied. The dynamic aspect of the reality has a direct impact in the conceptualisation of such a reality by adding different event categories to the domain ontology, thus making more complicated to apply existing methods for the mapping and integration of ontologies. In this article, we highlight some problems of heterogeneity that complicate the integration of ontologies composed of objects and events concepts; we also propose a similarity model designed to support mapping of these ontologies.

Mohamed Bakillah, Mir Abolfazl Mostafavi, Jean Brodeur, Yvan Bédard

An Open GeoSpatial Standards-Enabled Google Earth Application to Support Crisis Management

Abstract

Google Earth (GE) and related open geospatial technologies have changed both the accessibility of and audience for geospatial information dramatically. Through data rich applications with easy to use interfaces, these technologies bring personalized geospatial information directly to the non-specialist. When coupled with open geospatial data standards, such as Web Map Services (WMS), Web Features Services (WFS), and GeoRSS, the resulting web-based technologies have the potential to assimilate heterogeneous data from distributed sources rapidly enough to support time-critical activities such as crisis response. Although the ability to view and interact with data in these environments is important, this functionality alone is not sufficient for the demands of crisis response activity. For example, GE’s standard version currently lacks geoanalysis capabilities such as geographic buffering and topology functions. In this paper, we present development of the “Google Earth Dashboard” (GED), a web-based interface powered by open geospatial standards and designed for supplementing and enhancing the geospatial capabilities of GE. The GED allows users to create custom maps through WMS layer addition to GE and perform traditional GIS analysis functions. Utility of the GED is presented in a usecase scenario where GIS operations implemented to work with GE are applied to support crisis management activities. The GED represents an important first step towards combining the ubiquity of GE and geospatial standards into an easy-to-use, data rich, geo-analytically powerful environment that can support crisis management activity.

Scott Pezanowski, Brian Tomaszewski, Alan M. MacEachren

Web Service Orchestration of OGC Web Services for Disaster Management

Abstract

Flexibility and reusability are major goals when developing complex applications based on OGC Web Services (OWS). Within the project OKGIS (www.ok-gis.de) we evaluate the suitability of the Web Service Orchestration (WSO) technology as possible solution for disaster management scenarios. We present an example of a part of an evacuation scenario after a bomb has been found. This scenario includes in particular the need for emergency route planning. We evaluate how the actions to be performed by the system supporting the rescue workers can be mapped onto a service chain of basic OWS. The service chain is represented as a BPEL document and can be executed in a web service orchestration engine, such as Oracle BPEL-engine. BPEL is a standard for service orchestration and means Business Process Execution Language.

Albrecht Weiser, Alexander Zipf

Agent-Based Simulation of Spatial Cognition and Wayfinding in Building Fire Emergency Evacuation

Abstract

There is a need to understand how people and environment react in a fire building emergency. Sometimes in the wayfinding process decision errors may occur mainly based on topological errors of the signage. A situation is critical if a decision about which path to take cannot be made with certainty, especially in a crisis situation. An agent-based simulation of human’s behavior in escaping from the fire with due attention to the building’s signage and dynamic nature of fire propagation affecting the wayfinding task is outlined in this paper. The hypothesis of the paper is that successful navigation is possible if the agent is able to make the correct decision through well-defined cues in critical cases, so the design of the building signage is evaluated through the agent-based simulation. Construction of mental representations of spatial environment and exploring models in the agent-based simulation have been proposed and a computational model successfully tested in an indoor complex hospital environment in different situations and the evacuation time from the building is computed. The most appropriate signage design resulted in the shortest evacuation time in various situations.

L. Hajibabai, M. R. Delavar, M. R. Malek, A. U. Frank

Exploratory Spatial Data Analysis to Support Maritime Search and Rescue Planning

Abstract

Managers are often expected to analyze, report, plan, and make decisions using data that are aggregated to administrative areas historically delineated for other purposes. This enforced aggregation may misinterpret true patterns or complexities underlying the data, hindering recognition and communication of potentially important insights. The result may well provide misleading information on which to base decisions. Spatial data analysis tools are available that could allow managers to analyze and aggregate data more meaningfully and effectively for decision-making and planning, while still allowing them to report to the standard administrative units. These spatial analytical tools would be of importance to managers who are using data to prevent, plan for, or mitigate risk-related events.

The Canadian Coast Guard is offered as an example whereby managers are responsible for planning for the provision of maritime search and rescue emergency response using historical maritime incident data collected site-specific but aggregated to historical reporting units. We explore how spatial data analysis techniques, in combination with GIS, can provide a way to analyze incident data spatially regardless of existing reporting units, providing a better way to ‘package’ the data for use in emergency response planning and decision-making. We show how marine incident patterns over the region can be monitored to help planners anticipate emerging incident hot-spots or gauge the persistence of existing hot-spots. Finally, we show how a better understanding of incident patterns within existing administrative units can inform the development of new reporting boundaries that better reflect incident patterns.

Cindy A. Marven, Rosaline R. Canessa, Peter Keller

A Model of Spatial Data Integration Interoperability on Oracle Spatial

Abstract

An Open GIS Consortium (OGC) white paper said that the future vision for sharing data might look like this: Each of the smaller counties or towns hosts its own online GIS. Each uses software and a data model selected to best meet its local needs, which is the objective of this paper studies to close with. This paper gives a model based on Oracle Spatial, within a local government or enterprise the spatial data is centralized storage, and with metadata interoperability, which enables organizations to use the right tool for the job while eliminating complicated data transfers and multiple copies of the same data throughout the enterprise or department. This paper has realized MapInfo and ArcGIS work together under the same oracle spatial database use trigger and storage process. And at another hand, with the situation of between the departments or enterprises this paper gives a three-tier structure solution: spatial data server, application server and application client. The application server is a mediation system, this model uses oracle application server as the mediation system, and through the application server the application client sends WMS or WFS request and get the map server for background application. The three-tier structure model exposes a GIS portal which is an online GIS for outside of the department. Any client can request the server if it accords with WMS or WFS specification.

Qiansheng Zhao, Quanyi Huang, Jiming Guo, Renqiang Wen, Shaobo Zhong

Collaboration enabled GIS Tools for Emergency Operation Centre

Abstract

Geographical information systems (GIS) have been widely used in emergency operation centre (EOC) for modeling, spatial decision-making and map distribution. However, the collapse of EOC itself, for example the destroyed EOC in the World Trade Centre on September 11, 2001 and the Hurricane Katrina in Louisiana had inevitably delayed the emergency response. Although virtual EOC (VEOC) provides partial solutions to this problem, most of the VEOC software products are limited in providing real-time collaboration and coordination using GIS tools. This paper presents the results of a research project, aiming at providing such collaborative GIS software tools over the Internet for the VEOC. The prototype software adopts a semi-replicated and distributed architecture and is deployed over Internet. Several collaborative tools such as telepointer, radar view, participant list and action status, chat and video are designed to support participant’s awareness and collaboration. Using these tools, emergency personals, experts and government agencies at all levels and dispersed all over the country can share not only data sources but also the views, GIS modelling or process, even work environments hosted in a EOC or several EOCs, so that everyone with access privilege can evaluate the critical situations at the same time without physically present in the operations centre.

Zheng Chang, Songnian Li

Comparison of Simplifying Line Algorithms for Recreational Boating Trajectory Dedensification

Abstract

In order to recognize patterns of recreational boating, three different types (canoes, kayaks and sailboats) of recreational boats’ trajectories were collected by GPS in Halifax, NS. Since the fact that not every GPS point represents useful features, classic line simplification algorithms are adapted to dedensify the original GPS trajectory and retain the most important feature: turns. In this work, since the Douglas-Peucker algorithm is inadequate in terms of retaining turns without losing the recreational boat’s general tendency, the MARIN Douglas-Peucker approach was tailored to guarantee keeping such characteristics. One algorithm includes two criteria, while the other two methods each depend on only one criterion. These three algorithms for dedensifying trajectories of recreational boating were applied to the three recreational boat types and the results of the dedensified trajectories were compared. The advantage and disadvantage of each algorithm are demonstrated. This investigation provided insight about customizing the simplification algorithm for dedensifying recreational boating trajectories in order to extract boating movement features. The output of this process also provided input to maritime spatial decision-making tools, which is important for properly targeting accident prevention programs and advancing the research on risk analysis associated with this activity.

Yan Wu, Ronald Pelot

Hierarchical Risk- Based Spatial Analysis of Maritime Fishing Traffic and Incidents in Canadian Atlantic Waters

Abstract

Maritime traffic analysis is growing in importance for many reasons: risk management, accident prevention and response planning. Since most decisions are location-sensitive, one important consideration in maritime traffic analysis involves maritime risk analysis, including spatial analysis to identify hot spots. Hot spots areas are concentrations of incidents within a limited geographical area that appear over time.

In recent years, information - particularly spatially referenced information - and the tools for information analysis have become increasingly recognized as an essential part of the policy-making and decision- making processes to make the descriptive, explanatory, predictive and risk prevention models.

The increasing power of computing hardware and software and the increasing sophistication of the analytical geomatics techniques mean that new opportunities are available for spatial analysis to improve the quality of risk prevention plans.

Recent studies have shown that geospatial information is of fundamental importance to maritime risk analysis providing efficient risk management and GISs represent a powerful new technology that can address many information needs of risk managers and decision makers working with geographically referenced data.

This study used the increased capabilities offered by Geomatics techniques and geographic information systems to identify hazardous locations for maritime traffic in Canadian Atlantic waters. This research uses spatial analysis to examine risks associated with maritime commercial fishing vessels activities and incidents.

Jamal Shahrabi, Ronald Pelot

A Fuzzy Relation Analysis Method Implemented in GIS for Modeling Infrastructure Interdependency

Abstract

Infrastructure Interdependency (II) involved in emergency and disaster management processes is a complex phenomena. Understanding and modeling II is an emerging interdisciplinary field of study which has attracted substantial interests from modelers and geomatics professionals. This paper introduces a new method for modeling and analyzing interdependencies of critical infrastructures. The modeling processes include the following four components: (1) an asymmetrical fuzzy relation matrix representing direct relationships between nodes in infrastructure networks; (2) an asymmetrical fuzzy relation matrix representing direct and cascade relationships between infrastructure networks; (3) a mathematical transformation converting asymmetric relations in to transitive relations with properties of direct relations stronger than indirect relations; and (4) a method for ranking infrastructures in terms of relative importance of infrastructures.

Qiuming Cheng

Modeling of Flood-Related Interdependencies among Critical Infrastructures

Abstract

This study presents an integrated approach for modeling the flood-related interdependencies among critical infrastructures and their vulnerabilities. The developed method is based on the development of a Petri-Net model and fragility curves analysis. Specifically, infrastructure interdependency is simulated using Petri Nets, and consequences to infrastructures following a flood are quantified through developing fragility curves. Both empirical and analytical fragility curves are developed using a regional flood hazard database, hydraulic modeling of dam failure, and Monte Carlo simulation. The developed method has been applied to a case study. Cascading disruptions in the interconnected water infrastructures due to a dam failure are simulated in this study. Reasonable results have been obtained, which indicate that the proposed modeling system can address the interdependency among critical infrastructures and serve as a decision tool for flood-related emergency response and management.

Sharmin Sultana, Zhi Chen

Challenges for the Application of GIS Interoperability in Emergency Management

Abstract

This paper highlights application challenges for GIS interoperability for emergency management with emphasis on critical infrastructure sectors. In the first part, this paper provides a comparative analysis of emergency management operations in the City of Vancouver; the City of Toronto, the Kitchener Waterloo Region, and the Dufferin County. A variety of qualitative research methods were employed for gathering information from key decision-makers involved with emergency management. The second part of this paper presents a scenario-based case study, which aims to provide a demonstration of the utility of GIS interoperability, for disaster management. This paper also discusses the strengths and weaknesses of leveraging GIS interoperability for disaster management.

Rifaat Abdalla, C. Vincent Tao, Jonathan Li

Increasing public and environmental safety through integrated monitoring and analysis of structural and ground deformations

Abstract

Any engineered or natural structure, when subjected to loading, undergoes deformation and/or rigid body movements. Once the deformation, its velocity and/or acceleration exceed critical values, the structure fails. The critical values are determined using failure criteria that are based upon either empirical formulae or principles of continuum mechanics. By providing continuous and properly designed deformation monitoring schemes, one may provide information about the new state of the deformation. This information can then be used to provide advance warning of imminent structural failure.

Adam Chrzanowski, Anna Szostak-Chrzanowski, Jason Bond, Rick Wilkins

Using GPS for Monitoring Landslides in Kala Reservoir of the Yalong River Area

Abstract

Landslide is a kind of serious geologic disaster. It’s very important to monitor the deformation of the landslide area that threatens the lives or constructions. There are some successful applications in deformation monitoring using GPS. In certain circumstance, the continuous observation and real-time 3D coordinates with high precision can be carried out automatically using GPS. However, most of the landslide areas lie in canyons where the signals from GPS satellites are sheltered seriously. So in this case, to get precise and reliable results in deformation monitoring using GPS is a problem which needs being discussed and solved. In this paper, the landslides monitoring project in the Kala Reservoir area using GPS in China is introduced firstly. The design of deformation monitoring GPS network and the data processing method are discussed subsequently. The results of the deformation monitoring indicate that the requirements of the project are accomplished.

Zhihong Xue, Guangyun Li, Zongchun Li, Xiaoping Wu, Jiandong Wei

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