Geospatial Information Infrastructure for Transportation Organizations (2004)

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1 5 CHAPTER 3 Trends in Decision-Making Tools Geospatial Technologies There is consensus among most professionalsthat the geospatial technology exists to supportmost of today’s decision-making activities. Developing the ability and commitment to adapt to this technology quickly, in terms of both upgrading equipment and techniques and educating and training staff, is a challenge facing transportation agencies. To complicate matters, geospatial technology continues to expand and improve rapidly to meet new demands, placing an even greater burden on relatively slow- moving public agencies to take advantage of the new capabilities. To provide decision makers with insight into the potential available to them, the following sections pre- sent relevant trends in geographic information systems (GIS) and geographic information science (GISci) that will affect decision-making abilities and tools. “GIS” refers to the technologies for capturing, storing, process- ing, and communicating geospatial information. “GISci” refers to the theories, models, and methods that underlie GIS (Goodchild 1992). The development of location-based services (LBS), an important trend in the provision of geoinformation to casual users, is also dis- cussed. These trends will change the scientific and tech- nological context for multimodal geospatial information infrastructure in transportation. INDUSTRY TRENDS In the past few years the geospatial information indus- try has undergone significant changes. It has evolved rapidly from proprietary and highly specific GIS-based applications to broader inclusion in an organization’s information technology enterprise environment (see Box 3-1). Although the market for highly specialized GIS will continue, a faster rate of growth for geospa- tially enabled applications and services (call centers, command and control, business intelligence, emergency response) is emerging. This transition is most pro- nounced in transportation, public safety, telecommuni- cations, and utilities. Public-sector agencies are beginning to realize the value of integrating location capability into their systems and, in doing so, reaping significant benefits in having access to and using the bil- lions of dollars worth of geospatial data created over the last two decades. GIS TRENDS GIS are evolving to reflect changes in several areas. The expanded ability to collect and manage information, multimedia capabilities, the development of location- aware technologies (LATs), and mobile computing are a few examples of these changes. The following para- graphs provide some ideas of what these may mean to transportation professionals. Data Poor to Data Rich New methods for collecting georeferenced data include automated, real-time data capture and environmental

monitoring devices such as automated weather stations and intelligent transportation systems (ITS). Such meth- ods, in combination with reductions in data storage costs, have led to massive enterprise databases and data warehouses. Geospatial data infrastructures, such as the U.S. National Spatial Data Infrastructure, are facil- itating the sharing and interoperation of geospatial data. This is resulting in rapid growth in digital geospa- tial data as well as new methods for exploiting the rich information buried in these data sets. Techniques such as data mining and exploratory visualization have great potential to reveal hidden space–time patterns and rela- tionships missed by traditional transportation models and analysis methods. Conversely, as data become more available, concerns and expectations about their use and quality rise. Resources for data maintenance, which are already limited, are stretched further. As the avail- ability and use of real-time systems grow, these strains will grow. Remote sensing (RS) is also experiencing a major renaissance. Improvements in RS technologies are cre- ating substantial increases in various types of resolu- tion: spatial (1 meter and below), temporal (high revisit rates, geosynchronous, aerial platforms), and spectral (hyperspectral sensors that can collect 200 or more bands of spectral data). This is leading to new opportu- nities for socioeconomic and transport applications, including RS of vehicles and detailed urban morphol- ogy. The U.S. Department of Transportation has cre- ated the National Consortium on Remote Sensing in Transportation to explore emerging transportation applications (www.ncrst.org). Multimedia GIS GIS are moving beyond traditional data models. The distinction between raster and vector will no longer be meaningful from the user’s perspective: GIS will include automated intelligent conversion between these formats as necessary. The collection and storage of georeferenced multimedia, including text, sound, and imagery, are also possible. Georeferenced multimedia can help elected officials, key stakeholders, and the general public under- stand complex transportation issues, such as proposed changes in transportation infrastructure and services. This can foster a supportive environment for collabora- tive decision making (Shiffer 2001; Shiffer et al. 2003). For example, by using a virtual geographic environment, a neighborhood group could “tour” a planned transit station and suggest changes while the station is still in the design phase. Similarly, transportation officials and stakeholders could “fly through” a proposed highway corridor to assess aesthetic and other impacts. Location-Aware Technologies LATs are devices that can report their position in geo- graphic space. These technologies may also have wire- less communication capabilities, either to the Internet or to a voice communication system such as a cellular telephone network. Methods for reporting location include Global Positioning System receivers and radi- olocation methods that piggyback on wireless commu- nications. Vehicle-based inertial navigation systems that compute distance and direction from a known location are also possible. LATs will transform GIS and transportation. Some trends associated with these technologies include ITS that require vehicle tracking and LBS coupled with wire- less Internet to provide information about entities based on their location in space and time. These technologies and services will provide unprecedented capabilities for collecting real-time data on transportation systems that will allow designers, managers, and planners to assess system performance and policies for improving perfor- mance. They will also provide real-time transportation system information to users. 1 6 GEOSPATIAL INFORMATION INFRASTRUCTURE FOR TRANSPORTATION ORGANIZATIONS BOX 3-1 Enterprise Business System Environment The evolution toward location-enabled enterprise business systems is being driven, in part, by the native geospatial capability in mainstream database technology. The leading database vendors, Oracle and IBM, now provide native spatial data types, spatial indices, and spatial operators. With these advances, organizations are realizing that manag- ing geospatial data is just like managing any other data type. Advantages include the following: • Geospatial data can be managed in an open database management system format and accessed by using Standard Query Language (SQL). • Any third-party GIS tool can query and per- form spatial operations on geospatial data—just as it would attribute data. • Geospatial data can be queried and displayed from business applications such as customer call centers, command and control centers, and track- ing applications by industry standard reporting tools using SQL. • Centralizing geospatial data management reduces the overhead of running multiple data servers, reduces training requirements to run different applications, and minimizes application integration costs.

Network and Mobile Computing Network computing will lead to the development of “information appliances” or special-purpose comput- ers. With such systems, most computing and data pro- cessing will occur remotely at a server or servers. Internet GIS technology will allow the deployment of web-accessible geographic data servers and geographic data warehouses. It will also allow computation to be distributed and geospatial analytic tools to be shared. Mobile (wireless) technology will allow “ubiquitous computing” through handheld and wearable devices or possibly through devices embedded in infrastructure. This could permit GIS anywhere, anytime (within lim- its, of course: anyone with access to a wired or wireless telephone will have access to GIS). One possibility is the development of field-based GIS, with which a researcher could adaptively collect, edit, and analyze data in the field. Mobile GIS can allow “augmented reality.” For example, the analyst will be able to wear lightweight goggles and see a GIS data view imposed on a real view of some scene. With such devices, GIS could migrate from specialized technicians to every profes- sional within a transportation organization, including those in the field. GIS as a Tool Kit Traditional GIS, as a unique software package, is likely to disappear within the decade. Most enterprises store their data in large database management systems. GIS can more easily migrate to data than can data to GIS. Also, because geospatial database management is differ- ent from geospatial analysis and cartography, it is more effective to have separate software systems to support these different functionalities. Uncoupling geospatial data management from GIS allows the support of a much wider range of geospatial applications, including LBS. Instead of emerging as stand-alone software, GIS will emerge as a multilayer, modular architecture that sepa- rates geospatial database management from geospatial analysis and cartography. The development of object- orientation, componentware, and open-source software means that software in general, and GIS specifically, will no longer have a wide range of vendor-supplied tools that try to do everything with limited success. Rather, GIS will be a flexible tool kit of basic geospatial opera- tions that the user can combine to perform specific tasks. This means that GIS will probably cease to be inde- pendent software and will instead be transformed into a tool kit linked to enterprise database systems. For transportation organizations, this means that the sepa- ration between GIS data and other data will cease to exist, and thus the artificial separation between geospa- tial analysis and other types of analyses will also disap- pear. In addition, transportation organizations will be able to build or adapt models and methods for localized needs rather than use methods that are designed for everywhere and hence nowhere. The power and scope of geospatial analysis and cartographic visualization in transportation planning, design, and management may increase. Managers and decision makers will have access to GIS data and products in making high-level, strategic decisions. GISCI TRENDS At the same time that the tools are progressing, the sci- ence behind geospatial analysis is rapidly developing. Adding time and possibly other dimensions to the tra- ditional three dimensions of space, expanding the abil- ity to mine multiple data sets for previously unidentified patterns, and performing analyses from the perspective of an object in space as opposed to the space with objects moving through it will profoundly affect how transportation professionals do business over the next generation. These trends and their possible effects on transportation decision making are described below. Multidimensional GIS “Multidimensional GIS” refers to geospatial represen- tations and analytical tools that can accommodate two- or three-dimensional space and time in an integrated manner (see Box 3-2). The multidimensional linearly referenced system, recently developed under the spon- sorship of the National Cooperative Highway Research 1 7TRENDS IN DECISION-MAKING TOOLS: GEOSPATIAL TECHNOLOGIES BOX 3-2 Multidimensional GIS Multidimensional GIS goes beyond the traditional static map to include representation and analysis of 4D information (Raper 2000). Some of these ideas have also been developed for socioeconomic appli- cations (Frank et al. 2001). Recent breakthroughs in spatiotemporal data modeling include the event- based spatiotemporal data model, which maintains spatiotemporal data as a sequence of temporal events associated with an object in space (Peuquet and Duan 1995), and the three-domain model (Yuan 2001), which treats time as a temporal object instead of an attribute, giving the spatial, temporal, and semantic domains equal emphasis.

Program, uses the three-domain model to develop a transportation data model that can reference facilities and events in 3D space and time as they relate to a transportation network. The development of multidimensional GIS will remove a substantial mismatch between the static 2D world of GIS and the dynamic 3D world of transporta- tion. More data related to a transportation system will be easily accommodated and analyzed within a common framework. Geographic Data Mining Traditional geospatial analytical methods were devel- oped in an era when data collection was expensive and computational power was weak. The volume of georef- erenced data now available can overwhelm techniques designed to tease information from small, homogeneous databases (Miller and Han 2001). “Geographic data mining” refers to the search for patterns in massive geo- databases. Current tools include spatial clustering, clas- sification, exploratory spatial analysis, and geographic visualization. Geographic data mining will become more impor- tant in transportation as information, specifically spa- tiotemporal data on network flows and space–time trajectories, becomes available through ITS and LBS, respectively. Traditional transportation modeling and analytical techniques cannot handle the massive and noisy spatiotemporal data available through these tech- nologies. Also, transportation and land use systems can have complex spatial and temporal linkages that tradi- tional methods cannot capture, such as the effect of a traffic crash at one place and time on traffic congestion at other places and times in the network, or the effect of a new highway on land use in the first year and air qual- ity in 5 years. Geographic data mining techniques can help uncover these hidden relationships. Beyond Place-Based Theories and Methods Traditional place-based methods of analysis, such as travel demand modeling, urban theory, and general GIS, are increasingly limited in their ability to effec- tively analyze complex interrelated systems. Mobility and information technology have allowed activities to be increasingly disconnected from place. For example, work can occur in an office, a home, a coffee shop, or a park. A “people-based GIS” (see Box 3-3) extends place-based GIS to encompass dynamic and mobile objects that perform activities within a dynamic geom- etry that represents space (Miller 2004). Technologies that support a people-based GIS include position-aware technologies for data collection and geographic knowl- edge discovery for massive, noisy space–time databases. LOCATION-BASED SERVICES LBS consist of a broad range of services that incorporate location information with contextual data to provide a value-added experience to users of the web or wireless devices (see Box 3-4). In contrast to the passive fixed Internet, users in the mobile environment are demanding personalized, localized, and timely access to content and real-time services. Targeted data, combined with loca- tion determination technology, are essential to add per- sonalized value to an end user’s mobile experience. With such technology, wireless carriers and portals could sig- nificantly increase the value of services to subscribers while opening up new revenue opportunities. Through new applications, mobile offerings can be personalized to users’ lifestyles and preferences and can be synchronized with other portable devices. The vari- ety of applications and services is large, from pure con- tent and advertising to emergency 911, navigational services, fleet and asset management, logistics, and location-sensitive billing. The high level of interest in location services, coupled with corresponding technol- ogy developments, has spurred the development of a rapidly growing location services industry and has cre- ated a multifaceted assortment of participants, service concepts, and business models. Important similarities and differences between LBS technology and GIS exist. Much of the underlying map- ping, spatial indexing, spatial operating, geocoding, and routing technology that is used to deliver LBS orig- inates from the GIS industry. What makes LBS technol- ogy different is that it is deployed on a foundation of information and wireless technology. The value chain of a GIS is generally limited to the providers of a desktop or client server solution, whereas the value chain of LBS 1 8 GEOSPATIAL INFORMATION INFRASTRUCTURE FOR TRANSPORTATION ORGANIZATIONS BOX 3-3 People-Based GIS Numerous theories and technologies exist to sup- port a people-based GIS: • Time geography focuses on spatiotemporal constraints on behavior. • Activity theory examines how humans arrange activities in space and time and how trans- portation, telecommunication, and urban systems emerge from individual activities. • Multidimensional GIS (see Box 3-2) includes representation and analysis of 4D information.

includes many participants ranging from hardware and software vendors, content and online service providers, wireless network and infrastructure providers, wireless handset vendors, and branded portal sites. Significant performance and scalability requirements further differentiate GIS solutions from LBS solutions (Box 3-5). Delivery of wireless location services might be considered similar to the delivery of other utility ser- vices. Online content services generally require large data servers, large enterprise hardware offerings, and significant midtier cached application servers that allow the service to scale and perform. LBS also require the delivery of personalized content to tens of thousands of users on an hourly and daily basis, in contrast to GIS. Customers also want the provision of LBS to be automatic, with carriers and wireless portals integrating a variety of Internet and enterprise information services on the basis of customer preferences, enabling a user to focus on informed decision making. Using this func- tionality, a real-time traffic application may automati- cally access multiple information sources at other companies, across the Internet on dozens of websites, and on other servers within the organization to provide integrated traffic information. Similarly, a customer checking on the availability of a hotel in a given city might access geocoding services that identify the loca- tions of the hotels nearest the customer, who might then cull data from real-time travel services to obtain room availability, book a room, and obtain driving directions from the customer’s current location to the hotel. As the general public becomes accustomed to this type of environment, providers of transportation ser- vices and information will be expected to provide com- parable functionality, which will both require and 1 9TRENDS IN DECISION-MAKING TOOLS: GEOSPATIAL TECHNOLOGIES BOX 3-4 Types of LBS Safety services: End-user assistance services, such as Enhanced 911 (E911), are low-usage services designed to provide assistance to the end user in case of an emergency. These types of services can be expected to gain a high market acceptance because of the general concern of the public for personal secu- rity. With a push from the Federal Communications Commission’s E911 mandate and new location solu- tions, wireless carriers will be able to route an emer- gency call on the basis of the caller’s location and the Public Safety Answering Point jurisdictional bound- ary and determine the nearest emergency center, thus dramatically reducing response time. Information services: These types of services include traffic information, navigation assistance, Yellow Pages, travel/tourism, and so forth. Users will come to expect voice-enabled driving directions and walking directions, as well as information services, whereby requested information is delivered by Wireless Application Protocol, a Short Message Service mes- sage, interactive voice response, Multimedia Markup Language, or a call center operator. Enterprise services: These services include vehicle tracking, logistics systems, fleet management, work- force management, and “people finding.” Today, many of these services are offered by legacy mobile data systems. However, with the growing availability of broadband wireless capability, these services may be merged into digital wireless networks. Deployment of mobile location services is taking hold first in the enterprise applications. Consumer portal services: As consumer technology platforms and wireless carrier infrastructures are upgraded to support ubiquitous, accurate location information, consumers will begin to access naviga- tional services, such as driving directions. Location- aware devices will deliver “local” news, weather, and traffic information determined by the location of the device through an icon-based user interface. Telematics services: “Telematics” most often refers to vehicle navigation systems, such as OnStar, that allow drivers and passengers to use Global Positioning System technology to obtain directions, track their location, and obtain assistance when a vehicle is involved in a crash. In-car systems, however, are car- or machine- centric, as opposed to handheld mobile devices, which are user-centric. Unlike static CD-ROM–based in-car navigation systems, online mobile systems allow users access to up-to-date, time-sensitive information and databases, such as those concerning traffic congestion. Triggered location services: As carriers form partner- ships with location-based application providers and businesses, they will be able to initiate trigger services that provide information to consumers or corporate clients when they enter predetermined areas. Some examples of trigger services include location-sensitive advertising, billing, and logistics.

generate geospatial information that is not currently available. The technologies presented in this section will play an important role in the future of transportation as they evolve, both in the development of decision-mak- ing tools and in data collection. How transportation organizations harness this technology has yet to be established or even considered. However, they must begin positioning themselves to take advantage of the technology as it becomes a part of everyday activities. REFERENCES Frank, A. U., J. F. Raper, and J.-P. Cheylan (eds.). 2001. Life and Motion of Socio-Economic Units. Taylor and Francis, London. Goodchild, M. F. 1992. Geographical Information Science. International Journal of Geographical Information Systems, Vol. 6, No. 1, pp. 31–45. Miller, H. J. 2004. What About People in Geographic Information Science? In Re-Presenting Geographic Information Systems (P. Fisher and D. Unwin, eds.), John Wiley (in press). Miller, H. J., and J. Han. 2001. Geographic Data Mining and Knowledge Discovery: An Overview. In Geographic Data Mining and Knowledge Discovery (H. J. Miller and J. Han, eds.), Taylor and Francis, London, pp. 3–32. Peuquet, D. J., and N. Duan. 1995. An Event-Based Spatiotemporal Data Model (ESTDM) for Temporal Analysis of Geographical Data. International Journal of Geographical Information Systems, Vol. 9, No. 1, pp. 7–24. Raper, J. F. 2000. Multidimensional Geographic Information Science. Taylor and Francis, London. Shiffer, M. 2001. Spatial Multimedia for Planning Support. In Planning Support Systems: Integrating Geographic Information Systems, Models and Visualization Tools (R. K. Brail and R. E. Klosterman, eds.), ESRI Press, Redlands, Calif. Shiffer, M., A. Chakraborty, B. Donahue, G. Garfield, R. Srini- vasan, and S. McNeil. 2003. Spatial Multimedia Represen- tation of Chicago Transit Authority Rail Infrastructure. In Transportation Research Record: Journal of the Transportation Research Board, No. 1838, TRB, National Research Council, Washington, D.C., pp. 1–10. Yuan, M. 2001. Representing Complex Geographic Phenomena in GIS. Cartography and Geographic Information Science, Vol. 28, No. 2, pp. 83–96. 2 0 GEOSPATIAL INFORMATION INFRASTRUCTURE FOR TRANSPORTATION ORGANIZATIONS BOX 3-5 LBS Requirements High performance: Delivers answers to subsecond queries required for Internet and wireless. Scalable: Supports thousands of concurrent users and terabytes of data. Reliable: Delivers up to 99.9999 percent uptime. Current: Supports real-time and static information delivery. Mobile: Available from any device, wireless or wire line, and from any location. Open: Supports common standards and protocols— HTTP, Wireless Application Protocol, Wireless Markup Language, Extensible Markup Language, Multimedia Markup Language. Secure: Leverages underlying database locking and security services. Interoperable: Integrates with e-business applica- tions such as customer relationship management, billing, personalization, and wireless positioning gateways.