Ali A. Mahmood1 and Catherine N. Mulligan²

ABSTRACT

The following paper provides a general description of geographic information systems and outlines several research attempts towards wider application and adoption of this technology in civil engineering. The literature survey covers such areas as water pollution, waste collection, soil liquefaction, slope stability and rainfall runoff applications and the adoption of suitable computing technologies for incorporation into geographic information systems. It concludes with some recommendations for areas of future research.

¹Graduate student, Concordia University, Dept. Of Building Civil and Environmental Engrg., P.O.Box 473, Cote St. Luc, Montreal, Quebec, H4V 2Z1, Canada,
tel.: (514) 996-8365, email: ali_002000@yahoo.ca

²Assistant Professor, Concordia University, Dept. Of Building Civil and Environmental Engrg., 1455 de Maisonneuve Blvd. W., ER 303-15, Montreal (QC) Canada, H3G 1M8 Fax: (514) 848-2809, e-mail: mulligan@civil.concordia.ca

INTRODUCTION

When geographic information systems was introduced in the 1950s, its early use was limited to a small group of researchers. Botanists, meteorologists, and transportation planners began automating the process of thematic mapping. These researchers’ efforts represent the early attempts at computerized cartography, (Holdstock, 1998).
Today GIS is one of the fastest growing technologies. GIS has emerged as a powerful and sophisticated means to manage vast amount of geographic data. This growth of GIS over the last 30 years can clearly be linked to technological advancements in the computer, digitizers, and plotters, coupled with an increasing demand by interested parties for geographic information, (Holdstock, 1998).

This technology in enabling organizations to consider more effective ways of doing business and in doing so, reducing costs and increasing productivity. It is thought that GIS will soon become widely used as spreadsheet software, (Holdstock, 1998).

GIS relies on the integration of three areas of computer technology. A relational database management system to store graphic and nongraphic data; cartographic capabilities to depict, graph and plot geographic information; and spatial analytical capabilities to facilitate manipulation and spatial analysis. Three distinct areas:

• Graphic capabilities
• Relational database
• Spatial analysis

There are four integrated parts of a GIS: (1) data and databases; (2) hardware; (3) software including database management systems; and (4) users, (Holdstock, 1998).

1. Data and databases: The data in GIS are by definition geographic. Spatial data being specifically location information pertaining to objects of interest
    
2. Hardware: A fully functional GIS must contain hardware to support data input, output, storage, retrieval, display, and analysis.
    
3. Software: Many GIS software packages are on the market, each offering different levels of functionality. Turnkey systems ( ready for use directly out of the box) and customized installations are all possible.
    
4. Users: The GIS professional needs to be well versed in many disciplines like: map reading, database management, spatial analysis, computer cartography, computer science, programming, and basic geography.

The benefits derived from such a system become readily apparent, (Bowman, 1998):

1. The statewide comprehensive database becomes self maintaining.
2. An integrated Civil/GIS system of the future eliminates the primary impediment to data transference and sharing throughout the enterprise by eliminating proprietary formatted file storage.
3. Civil engineering data can be recaptured in a form that is precise and, therefore, useful by civil engineers in the future.
4. The database seamlessly integrates each department within an organization into an integrated data flow model that matches the natural workflow of the organization.

LITERATURE REVIEW

Case studies
Miles and Ho, (1999) discussed a variety of case studies relating to GIS, these are the case studies presented by them, (Miles and Ho, 1999):

Case study 1: Storm Water Pollution

Wong et al. (1997) embedded an empirical data model into a vector GIS, specifically, ARC/INFO running on a UNIX platform, for analyzing the Santa Monica Bay, Calif., watershed. The model used data on local rainfall, land use, drainage, and local and national water quality to estimate pollutant loadings.

GIS implementation of the model required three coverages (spatial data layers): Land use; (2) subbasins; and catchment. These coverages were scanned from USGS maps.

With all relevant attributes, the three coverages were unioned (overlain) and the empirical model was applied using the calculation functions of ARC/INFO. The analysis was used to determine basins and land uses producing the most polluted runoff. Model output was used to design a monitoring program that has become the framework for the Los Angeles County Department of Public Works monitoring program for the areas draining into the Santa Monica Bay. Wong et al. (1997) pointed out that by “using the GIS/model it was easy to position monitoring stations at locations that will sample a minimum fraction of the runoff.... The overall framework (GIS and model) takes advantage of the built-in relational database management technology of the GIS to construct an accurate and detailed database.”

Case Study 2: sediment Transport

A geomorphic-based hydrologic and sediment transport model was embedded into a rastor GIS by Mashriqui and Cruise (1997). The modeling approach was based on the grouped response unit concept.
The model employed was the chemical, runoff, and erosion from agricultural management systems model, which is composed, of a set of simple equations. Spatial parameters of the model include drainage area and slope.

Drainage boundaries were delineated manually on a 7.5-min USGS topography map and digitized using ARC/INFO running on UNIX. Polygons representing distinct soil groups were also digitized at the same scale from a soil survey map. Rainfall point data were imported and interpolated into regions by creating Theissen polygons in ARC/INFO to account for spatial distribution. Land-use data were remotely sensed and classified using ERDAS Imagine, also running on UNIX. The database created using ARC/INFO and ERDAS Imagine was transferred to map II, a MacIntosh-based GIS, for subsequent modeling. Finally, spatial parameters were calculated and data coverages were overlain using Map II functions before applying model equations with Map II. Mashriqui and Cruise (1997) concluded that “GIS was used as a link between cartographic data and model parameters.... Techniques used in this study provided an efficient way of estimating the effects of spatial variation of slope, soil type, and land use of a watershed on the runoff and sediment yield.”

Case Study 3: Solid Waste Collection

Chang et al. (1997) studied the ability of GIS used with a multiobjective programming model for vehicle routing and scheduling to analyze the optimal path between a given origin and destination in a waste collection network. In this context, optimization was used to minimize total collection distance, costs and time.

The system created determines the network pattern in each subdistrict of the Lin-Ya district, Taiwan. Attributes of current population distribution and collection points were manually assigned to each network segment. The average output of solid waste over all of the links in the district was estimated. Data were transferred for use in LINDO optimization software so that optimal routing and scheduling could be determined . In this was the demand for the waste disposal of the entire district could be predicted for several social, economic and environmental parameters. This approach was determined to be crucial to create a more efficient solid waste management practice. (Chang et al., 1997).

Case Study 4: Seismic Slope Stability

Miles and Ho (1999) utilized a vector-based GIS framework for applying rigorous Newmark’s displacement method (Newmark 1965) for assessing relative hazard due to earthquake-induced land slides (Ho and Miles 1997; Miles 1997; Miles and Ho 1999). Hazard analysis was performed for the East Bay Hills in Berkeley, Calif. Newmark’s method is both data and computationally intensive, requiring critical acceleration (based on static factor of safety), acceleration time histories, and the double integration of those parts of the time histories that exceed the critical acceleration.

The simulation was coded in Mathsoft MathCAD for Windows. ASCII files describing 20 simulated earthquakes having a magnitude of 7.0 were generated. An interactive arc macro language (AML) was written for coverage, time history and analysis management.

Hazard maps expressing displacement in centimeters were plotted from analysis results. The values of such intensive method was justified in Miles (1997): “by using the rigorous analysis for regional hazard assessment, efforts can be focused to obtaining quality data rather than identifying and quantifying possible errors with analysis simplifications.”

Case Study 5: Liquefaction

Luna and Frost (1998) tied together ARC/INFO, Geo-statistical Environmental Assessment Software (Geo-EAS), Groundwater Modeling System (GMS, 3D subsurface visualization software), and in-house developed C programs to create an interactive spatial environment for evaluating soil liquefaction potential (LPI) at a site-specific scale. A primary objective of the environment is the provision of user interaction in which to permit both numerical and visual analysis.

Spatially distributed results of the liquefaction analysis are interpolated and processed to yield isolines describing LPI. Luna and Frost (1998) concluded that “the system allowed successful interaction with the user to the point of performing a parametric study of liquefaction by varying the earthquake magnitudes and peak ground accelerations of the input motion.”

Case Study 6: Distributed Rainfall Runoff

A software environment, real-time interactive basin simulation (RIBS), was developed by Garrote and Ignazio (1997) for real-time flood forecasting using distributed models.

RIBS is an independent software package (i.e. not based on commercial GIS) OF C++ base classes that can be employed and extended by modelers to implement a wide range of distributed rainfall-runoff models. The objective of RIBS is to provide a unifying framework to manage the variety of processes required for real-time flood forecasting system.

Knowledge based GIS for spatial knowledge

Jia (2000) presented a method to develop a GIS-enhanced KBES with a spatial reference engine for the representation and reasoning of spatial knowledge. It begins by summarizing primary components of a KBES in the context of knowledge representation and reasoning. It also examines various requirements of spatial knowledge in a KBES. This paper then discusses IntelliGIS, an operational system that implements the method. The discussion is centered on how the conceptual framework of IntelliGIS supports the inclusion of GIS functions in a spatial reference engine. Descriptions of the technical detail of IntelliGIS implementation can be found in other papers (Jia 1996; Jia and Sarasua 1996). As a case study, the paper also describes the use of IntelliGIS for the development of a pavement system (PMS).

The conceptual framework designed for the representation and reasoning of spatial knowledge is shown in Fig. 1. The framework, called IntelliGIS, adds two additional components into the conventional KBES. The two new components, GIS server and KBES-GIS interface, provide various functions and utilities for dealing with spatial facts and for representing and reasoning about spatial knowledge.

IntelliGIS allows spatial knowledge to be encoded and stored in the knowledge base along with other knowledge. It enhances the context component to contain various spatial facts that describe spatial conditions of problems to be solved. Furthermore, it strengthens the interface engine by adding new modules to handle spatial reasoning.
The KBES-GIS interface in InteliGIS interacts with the knowledge base, the context, the inference engine, and the GIS server. It converts requests of spatial from the inference engine and hands them over to the GIS server for execution. The interface also manages the execution results back from the GIS server and converts them to spatial facts for further spatial reasoning.

The GIS server provides KBES applications with GIS functions. The functions include the manipulation of spatial and attribute databases, as well as spatial analysis operations required by KBES applications in their reasoning process.

Siting procedure

Kao et al. (1996) proposed a computerized tool capable of facilitating siting procedure. Their previous work developed a network-based system to assist the siting analysis using a geographical information system, GRASS (1993), and a multimedia network interface (Kao et al. 1994). This early version of the system, however, required extensive manual judgment to review siting rules for evaluation of candidate sites. Therefore in this work a rule-based expert system is developed as a significant system improvement, capable of performing automated enforcement checking of siting criteria and rules. Also, the expert system is integrated into the system with the GIS and the multimedia network interface. The entire system is intended for use by officers of local environmental agencies, engineers of local consulting companies who implement any related landfill-siting projects, students in related course and other interested people on the Internet.

Several other enhancements for improving the prototype are in progress at National Chiao Tung University (NCTU) for adding a fuzzy weighting system to the expert system and GIS, a mix-integer linear compactness optimization based subsystem, and a directional risk analysis tool using a ground-water and an air pollution model. All programs developed in this study are available for noncommercial public accesses. The WWW home page address is http://ev004.ev.nctu.edu.tw/ENGLISH/wsite/index.html.

Subsurface Characterization

Gangopadhyay et al. (1999) developed a method for characterizing the subsurface using an artificial neural network (ANN) and geographic information system (GIS). Data on the distribution of aquifer materials from monitoring well lithologic logs are used to train a multilayer perceptron using the back-propagation algorithm. The trained ANN predicts an appropriate prediction scale, the subsurface formation materials at each point on a descretized grid of the model area. GIS is then used to develop subsurface profiles from the data generated using the ANN. The subsurface profiles are then compared with available geological sections to check the accuracy of the ANN-GIS generated profiles. This methodology is applied to determine the aquifer extent and calculate aquifer parameters for input to ground-water models for the multiaquifer system underlying the city of Bangkok, Thailand. The integrated approach of ANN and GIS is shown to be a powerful tool for characterizing complex aquifer geometry, and for calculating aquifer parameters for ground water flow modeling. Fig.2 outlines the ANN-GIS methodology used.

CONCLUSIONS AND FUTURE RESEARCH

The paper discussed above covered many aspects of civil engineering that include storm water pollution, waste collection and soil stability applications. Many investigators attempted to associate geographic information systems with computing technologies for easier adaptation into mainstream desktop engineering. However there still is a lot to be done in order for this technology to gain a wider acceptance and truly proliferate into the masses of practitioners and researchers in civil engineering.
Some areas of application that still need to be covered include the following:

• Software agent technology: there has not been even one research attempt to link GIS with emerging software agent technologies. This important area of computing has not received the attention that it deserves from civil engineering researchers. Incorporation of software agents into GIS applications will make the latter easier to function and will incorporate more artificial intelligence into it. One of the benefit gained from that will be easier and faster implementation of GIS into Internet and Intranet applications.
    
• New networking technologies: The Jinni networking technology, developed by Sun Microsystems Incorporated, (Sun) is one that is newly developed to link multiple electronic devises through a single network. GIS can be modified and improved substantially through the use of Jinni and geographic information will have the potential to be accessed anywhere in the world using mobile and handheld devices.
   
• Extraterrestrial applications: with the current space program explorations of Mars and Jupiter's moon and other outer planets and moons. It will be required to integrate satellite data information with geographic information through a suitable computing technology such as Visual C++, Visual Basic or Java, having object orientation capabilities and inheritance characteristics. The developed, thus, package will be essential not only to space exploration but to earth engineers as well.

click to enlarge

Figure 1. Primary Components in IntelliGIS (reproduced after Jia, 2000).

Figure 2. ANN-GIS Methodology (reproduced after Gangopadhyay et al., 1999).

REFERENCES

Holdstock, David A., Geographic Information Systems/Global Positioning System Program (GPS) Director, Institute for Transportation Research and Education (ITRE), North Carolina State University, Centennial Campus, Box 8601, Raleigh, NC 27695-8601, 919-5158657.

Bowman, Dean, P.E., Director of Product Development GEOPAK Corporation, 305-944-5151, dean@geopak.com

Chang, N., Lo. H. Y., and Wei Y. L. (1997). "GIS technology for vehicle routing and scheduling in solid waste collection systems."J. Envir. Engrg., 123, (9), 901-910.

Garrote, L. And Ignazio, B. (1997). "Object-oriented software for distributed rainfall-runoff models." J. Comp. In Civ. Engrg., ASCE, 11, (3), 190-194.

Ho, C. L. And Miles, S.B. (1997). "Deterministic zonation of seismic slope instability: An application of GIS." Saptial analysis in soil dynamics and earthquake engineering, Geotch. Spec. Publ. No. 67, J.D. Frost, ed., ASCE, Reston, Va., 87-102.

Luna, R., and Frost, J.B. (1998). "Spatial liquifaction analysis system" J. Comp. In Civ. Engrg., ASCE, 12, (1), 48-56.

Mashriqui, H.S., AND Cruise, J.F. (1997). "Sediment yield modeling by grouped responce units." J. Water Resour. Plng. And Mgmt., ASCE, 123, (2), 95-103

Miles, S.B., and Ho. C.H. (1999) "Applications and issues of GIS as tool for civil engineering modeling." J. Comp. In Civ. Engrg., ASCE, 13, (3), 144-152.

Miles, S.B. (1997). "Rigorous landslide hazard zonation using Newmark's method and stochastic ground motion simulation." MS thesis, University of Massachusetts, Amherst, Mass.

Miles, S.B., and Ho. C.H. (1999) "Rigorous landslide hazard zonation using Newmark's method and stochastic ground motion simulation." Int. J. Soil Dyn. And Earthquake Engrg., 18, (4), 305-323.

Newmark, N.M. (1965). "Effects of earthquakes on dams and embankments." Geotechnique, 15, 139-160.

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Jia, X. (1996). "A client/server based intelligent GIS shell for transportation," Ph.D. dissertation, Georgia Institute of Technology, Atlanta.

Jia, X. And Sarasua, W. (1996). "A client/server based intelligent GIS for transportation." Proc. 1996 GIS-T Symp., AASHTO, Kansas City, Mo.

Kao, J.-J., Chen, W.-Y., Lin, H.-Y., And Guo, S.-J., " Network expert geographic information system for landfill siting" J. Comp. In Civ. Engrg., ASCE, 10, (4), 307-317.

GRASS 4.1 User's reference manual. (1993) U.S. Army Constr. Engrg. Res. Lab. (USACERL), Champaign,Ill.

Kao, J.-J., Chen, W.-Y., Lin, H.-Y., (1994). "Geographic information system for municipal solid waste landfill siting and evaluation (I)." Rep. Prepared for Miaoli Prefecture, Inst. Of Engrg., Nat. Chiao Tung Univ., Hsinchu, Taiwan, Republic of China.

Gangopadhyay, S., Tirtha, R.G. and Gupta, A.D., (1999) " Subsurface characterization using artificial neural network and GIS." J. Comp. In Civ. Engrg., ASCE, 13, (3), 153-161.

Sun Microsystems Incorporated, www.sun.com

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