REAL-TIME GPS DATA CAPTURE WITH BARCODE INTERFACE, GIS MAPPING AND DATABASE LINKAGE FOR A COMMUNITY RESOURCE MANAGEMENT PROGRAM

Paul Hsu

ASLA, Associate Professor

Landscape Architecture Program

Oklahoma State University, 360 Ag. Hall

Stillwater, OK 74078-6027

(405) 744-5421 office 744-9693 fax

e-mail: phsu@okway.okstate.edu

ABSTRACT

Global Positioning System (GPS) is a revolutional technology that is able to provide digital coordinates and elevation information for any location on the earth through the constellation of 24 satellites. Desktop Geographic Information System (GIS) which utilizes Computer Aided Design (CAD) maps and GPS data is gaining momentum in the market lately. Along with real-time differential correction, a data-logger, a laser barcode scanner, and a field computer with background maps and database, this system is an efficient tool for data collection and data input in the field. These locational data and attributes can be merged with CAD and GIS data in the field to provide an instant geographic information basis for inventory, analysis, and database management.

The author would like to present a pilot study of real-time GPS applications in community resource management. This project includes an university arboretum accession program, and a city street tree inventory and maintenance program. Both the arboretum and city have an existing database inventory program in place and the arboretum uses a barcode labelling system for display. Neither of them has a mapping system to interface with their current databases. This study is to fill the gap of mapping and database inventory analysis based on a GPS receiver, a real-time SpaceNet communication satellite data correction link, a barcode system interface, a datalogger or a field computer, background maps, and a data dictionary for locational data and attributes logging. The presentation will include a detailed operational procedure of the hardware setup, software interface, background map preparation, barcode system interface, data dictionary setup, real-time data correction, GIS software integration, database join and link, logistics of the project, and other field and office operations. Finally, this paper will conclude with findings of cost, technical difficulties, and the potentials and constraints of this new technology to a wide variety of audience.

INTRODUCTION

The collation of data about the spatial distribution of facilities, utilities, vegetation, and landscape amenities has become critical in order to address and solve problems regarding facility planning, facility management, and landscape design, maintenance and management. Unlike many other kinds of data handled routinely by modern information systems, geographic data are complicated by the fact that they must include information about position, possible topological connections, and attributes of the objects recorded. The topological and spatial aspects of geographic data processing provides capabilities for transforming the original spatial data in order to be able to answer particular queries.

Like many other professions, landscape architecture and horticulture require a great amount of attribute collection, data inventory, analysis, and design. In the past few years, major emphasis has been placed on the integration of computer aided design (CAD) and geographic information system (GIS) into our undergraduate teaching curriculum. Our students are able to use these technological advances to build site inventories and implement their design solutions. However, the lab projects are not reinforced by the real time experience of gathering information on site and collaborating site data with hands-on experience in computer software. Global positioning system(GPS) satellites, however, are able to provide digital coordinates and elevation information for any location on the earth. Along with a data-logger, this system is an efficient tool for data collection and data input in the field.

This project includes an university arboretum accession program, and a city street tree inventory and maintenance program. Both the arboretum and city have an existing database inventory program in place and the arboretum uses a barcode labeling system for display. Neither of them has a mapping system to interface with their current databases. This study is to fill the gap of mapping and database inventory analysis based on a GPS receiver, a real-time SpaceNet communication satellite data correction link, a barcode system interface, a datalogger or a field computer, background maps, and a data dictionary for locational data and attributes logging.

GPS technology has only been fully operational since 1993, and, to our best knowledge, very few landscape architecture and horticulture programs are utilizing GPS technology in conjunction with GIS and CAD in undergraduate teaching. This project intends to integrate this most current technology to train our undergraduate students ready for their future practice. This proposal also improves our current practice of teaching by introducing an innovative mobile lab concept with on-site data collection, database integration, and real-time interaction. Our ultimate goals are to enhance undergraduate course curricula, increase innovative lab research, stimulate greater undergraduate faculty interaction, and add marketable skills for professional degree undergraduate students.

GPS/GIS BACKGROUND

Combinations of GPS, GIS, and CAD systems are being used throughout the world in a variety of education and research projects [Sorvig, 95; Wikle, 92]. Environmental protection agencies are using GPS and GIS for accurate positional information and real time attribute coding for well heads, wild life reserves, and underground utilities [Puterski, 92]. In Australia, GIS is being used for assessing land suitability for agriculture and livestock [Parent, 91]. Using satellite images with the aid of GIS and ground truthing, a Maine scientist is tracking the wetland loss of the coastal area [Podolsky, 91]. In Taiwan, geographers are using GPS and GIS to investigate the highway facilities and build a database [Tsai, 94]. In the Mohave Desert, a biologist is using the fast technology of GPS to track the endangered desert tortoise [Freilich, 91]. More and more, utility companies such as electric and water are using hand-held data entry devices to do inventory or update attribute information on light poles, street signs, sewers, or any other utility features [Parent, 92]. Local-governments are relying heavily on the blend of GPS technology and GIS capabilities in their mapping of parcel-based, large scale, and multiple data layers [Singh, 91]. During Operation Desert Shield and Desert Storm in 1990-1991, GPS was termed "the single most important piece of new gear in the desert". GPS was used to locate borders in the ocean of sand, establish refueling and supply points, retrieve damaged vehicles, and prevent supply trucks from getting lost [ARINC, 91]. With today's computing power, it is easier to integrate visual and environmental analyses in site planning and design.

GIS technology has evolved rapidly in recent years to become a valuable tool in the analysis of environmental problems. Taken in its broadest sense, GIS is any manual or computer based set of procedures used to store and manipulate geographically referenced data. GPS technology has revolutionized and simplified the way people collect site information and spatial data. The Navigation Satellite Time and Ranging (NAVSTAR) GPS has been under development by the Department of Defense since 1973 and was in full operation by 1993. GPS provides highly accurate position, velocity, and time information. With distance measurements to four satellites, a receiver on the ground can compute its exact latitude, longitude, and altitude.

Advanced computer technology provides a new avenue for integrating CAD graphics and spatial information analytical techniques into the teaching of design processes, design theories and site analyses. GIS combined with digital terrain modeling provides a rule based combination method and logic approach to the analysis of spatial phenomena. GPS offers an instant way of registering site location and collecting attributes that is usually very time consuming and costly using conventional surveying methods. Desktop GIS which utilizes CAD maps and GPS data is gaining momentum in the market lately. A map or GIS database is only as good as the information it contains. Unfortunately, gathering the data that goes into the maps or GIS databases has always been a tedious and expensive task. Surveys are accurate but slow and require teams of trained personnel. Digitizing aerial photography is faster than surveying, but is less accurate. With the features of our world changing so quickly, it's not cost-effective to fly a photo mission every time updates are required.

HARDWARE SETUP

Real-time mapping

Real-time mapping demands the occurrence of an event and the reporting and recording of it almost simultaneously. We like to see the map or spatial data produced while we are on the move. We also like to shorten the actual time used by a computer on solving a problem and give feed back to the designer as instantly as possible.

To ensure the successful execution of this concept, a mobile lab composed of a GPS receiver, Omnistar real-time link receiver, GPS antenna, Omnistar antenna, portable computers, and software is essential. A mobilized lab, where students could have real time action on the project site, would enable them to enhance their perceptions and amplify their reactions. It also would permit people to experience an artificial reality. Computer technology can aid in the development of conceptual understandings at the same time that it helps to generate practical design skills. By bringing the mobilized lab to a project site, students will be able to carry out the project assignment with accurate and timely data collection, site inventory, site analysis, plant selections, and design thought processes instantaneously.

Fig. 1. A conceptual sketch of a compact real time GPS mobile lab in an ext-cab truck

A cargo van or an extended cab pickup can be converted into a mobilized computer lab with only a few changes (See fig. 1 and 2). By putting the system on wheels, we advance ourselves into a more advantageous platform. The mobile lab introduces a cost effective approach to a job and expands the horizon for presentation and project design consultation at the job site. A designer will no longer have to travel back and forth between the job site and the office. Many design concepts can be executed on site while communicating efficiently and effectively with the clients. Time can be saved and the project budget trimmed to allow a designer stay competitive.

Fig. 2.a. A pick-up for real time GPS navigation is in action Fig. 2.b. A laptop display of background street map with naviagting route

Oministar

The Omnistar receiver is a part of "Omnistar(TM) The National DGPS System." This system is a nationwide real-time differential GPS (DGPS) data broadcast system delivering corrections from an array of GPS base stations positioned from coast to coast in the continental United States. Ten or more base stations provide industry standard formatted corrections to a Network Control Center near Houston, Texas where the corrections are decoded, checked, and re-packaged into a highly efficient format for broadcast. The data modulates a spread-spectrum sequence that is then upconverted for transmission to a c-band communications satellite. The signals are received and demodulated at the user's location by an antenna, processor, and receiver and then the corrections are passed to a differential-capable GPS receiver.

Fig. 3. Local Area DGPS System with radio links.

Fig. 4. A Large Area DGPS Network with communication satellite link (Omnistar version)

Pro-XL Pathfinder with datalogger or a laptop computer

The GPS Pathfinder Pro XL System is a high-performance geographic data-acquisition tool. It is designed for the accurate creation and updating of a geographic information system database. One can quickly inventory resources by recording precise position and attribute information in digital form for later import into the geographic database of one's choice.

The Pro XL System has four main components:

* Trimble's Maxwell-based Pro XL Pathfinder receiver (8 or 12 channel). This receiver has two additional ports: one is External Sensor Port (ESP) which lets the user tie field measurements from digital devices (such as barcode scanner) to precise positions; the other is Radio Technical Commission for Maritime (RTCM) port which allows real-time differential correction in the field.

* A field data collector collects positional and attribute data. (This can be replaced with a laptop computer running Aspen software.)

* The software that runs on the data collector or laptop and allows you to collect GPS and GIS data quickly and efficiently.

* The PC based PFinder software that allows comprehensive GPS-postprocessing and data-export functions

Hardware interface with barcode scanner

A barcode scanner which uses a laser beam to scan barcode labels can be interfaced with either data logger of Pro XL through ESP or a laptop computer through keyboard interface. The GPS datalogging operation is essentially the same except the PC can display a background map with a cursor of current location on the screen. The software in the datalogger or laptop will prompt the user to log in (or type in) the ID attribute when we activate the point data capture. Upon activation of the Barcode Scanner, it sends a data string of the ASCII code directly to the data logger or laptop computer. This will ideally speed up the data collection process and eliminate operator entry error. Once the data is logged on , a user can hit a return key to move onto the next data field.

Fig. 5. Barcode scanner interface with a GPS receiver and a laptop or a datalogger

Fig. 6. Real-time GPS with barcode scanner interface and a datalogger

PROJECT DESCRIPTION

Project Background

In August 1991, the City of Stillwater received an "America the Beautiful" cost-share grant from the Oklahoma Department of Agriculture to be used for a street tree inventory. The city contracted with Robert Birchell and Associates to conduct the inventory. The inventory of street trees and planting spaces was conducted in the Fall of 1991 and the streets within the inventory area cover about 5 square miles. This area contains most of the older residential developments in the city, and most of the older, established street tree populations. A database was created for the management of Stillwater's street tree resource. The database created by the inventory will provide the basis for future projects such as tree plantings, removal of dead or hazardous trees, estimating budgets, and information and education efforts. This database may potentially be used by several city departments including Community Development, Parks and Recreation, Street Department, and Utility Department.

The OSU campus is very rich in its vegetation. Mature plants and wooded areas provide visual accents as well as micro-climatical regulations. Lawns, flower beds, and hedge rows are well maintained and manicured. However, the criticism in the past of the campus landscape has been pointed to the selection of plant materials and design coordination in the planning process. The campus vegetation has been an arboretum for many students, faculty and the general public. Currently, we are in need of a better mapping system which will tie the existing plant identification and labeling system together, providing an unique education opportunity. A well-tailored GIS mapping system would not only provide an inventory of campus-wide plant materials, but it would also offer an opportunity for planning and design analysis. Further, this information can be used for producing maps for multiple purposes and for generating labels for memorial plants as well as representative plants along campus trails.

Site descriptions

A quarter section of a residential neighborhood in the center of Stillwater consisting of approximately 160 acres, 40 blocks, and 700 street trees was chosen as the first study site. This is an older residential area with a lot of larger, mature trees. It is a good test site due to its density of housing, maturity of trees, and numbers of powerlines. GPS requires good visibility to satellites to acquire better accuracy. Our prediction was that if we successfully worked a neighborhood with dense foliage and complexity, then we would have an easier time of it in the open areas.

The second area is located at the SW corner of Oklahoma State University and is in a generally open area with very little obstruction of the line-of-sight. This site is approximately 10 acres with 100 existing trees. These trees were planted in 1990 in celebration of the OSU 100 year birthday, and hence it is also called the Centennial Grove. The Department of Horticulture and Landscape Architecture has a good barcode labeling system with an accession database in place.

Database from the University

The Department of Horticulture and Landscape Architecture developed a Plant Information Manager for the Oklahoma Botanical Garden and Arboretum (OBGA) at OSU. This manager organizes plant and OBGA information in nine databases in dBase IV format. These nine databases include Accession, Taxonomy, Affiliation, Donors, and so on. Each database is a stand alone information and can link to other databases relationally through the field of OBGAACCESN.

Fig. 7. An example of OBGA plant accession database

Database from the City

The city's database comes in one file of dBase IV format. Information collected included species, trunk diameter, condition, problems, maintenance needs, overhead utilities, location (street name and address), direction of travel of data collector, block number, and available planting spaces. The file contains more than 8,000 fields.

Fig. 8. A brief view of City of Stillwater street tree inventory database

Background map preparation

One of the key successful components for real-time GPS mapping is a background map. We were fortunate to acquire the background map in AutoCAD.dwg format from the city. It was then converted to dxf format for Aspen or ArcView as a background layer or theme. The map was also set at Nad-83 Geodatic datum and Oklahoma North State Plane Nad-83 Coordinate System. An improper coordinate system would cause the software to malfunction or erroneously display the wrong location of the map. This map coordinate transformation tends to pose difficulty for common users since the process needs to be done in Arc/Info or other similar software.

Other project material

Although this project is high tech oriented, we also rely on several low tech practices and materials. First, we carry a paper print out of the database and an aerial photo of a street map of the site to insure the positive identification of our target trees and our working environment. Second, we keep a daily work journal and take notes whenever it is necessary. There are variations and conditions that arise which will require double checking or a rerun. A work journal and notes serve the most basic function.

DATA COLLECTION

Planning

Before you go out to do field work, you should have done good planning in order to obtain the desired accuracy. The software QUICK PLAN allows you to plan the best times to collect GPS data. Because of the satellite orbital data error due to DOD's intentional degradation of orbital information (commonly called Selective Availability or SA) or prediction error, satellite clock synchronization error, signal path delays from direct line-of-sight and other possible error sources, it is wise to check out the number of visible satellites, where the satellites will travel, and the PDOP (Position Dillusion of Precision). The more satellites that are visible, the better. PDOP provides an indication of the expected accuracy of your GPS positions based on the relative positions of the satellites. Lower PDOP values provide more accurate data.

Data Dictionary

A data dictionary is information about the data you want to collect. It defines the information you will capture in the field. For example, if you are doing an inventory of a tree species, one entry in your data dictionary may be "Tree_ID" and the other may be "Species". In the field, you are prompted to enter the tree's ID and species. Understanding how to put together data dictionaries is very important. Design your data dictionary with your GIS application in mind. In particular, be familiar with any format restrictions imposed by the GIS, otherwise you may not be able to import or join the data you capture. For example, if the tree inventory database in a GIS has a number field called "Tree_No", then the same format needs to be designed in your data dictionary. In our study, our data dictionaries are very simple due to the fact that both the City and University already have its GIS database in place. Our mission is to integrate our tree positions collected from GPS with the proper tree in the existing database. Tree_no, names, and comments are the basic three attributes in our data dictionaries.

Field Operation

Experiment one--City Street Tree Inventory:

A GPS receiver along with a datalogger will be brought to a designated project site to record locations and enter attributes. A proper data dictionary is made before the field operator goes out into the field. The system will prompt the field operator from the site to record the attributes which our project dictates, such as the tree inventory number, the condition of the tree, and other changes since last inventory. The City's tree database does not have a barcode labeling system, therefore an aerial photo with block numbers, street names, and original inventory routing along with a database print out became essential for the field operator to positively identify a tree that is corresponding to the tree number listed in the database.

Fig. 9. A typical situation of city street tree GPS mapping under heavy foliage

Once a tree is positively located, the GPS data logging starts and attributes are entered. A typical city block takes about 30 minutes minimum, but this could be varied depending on the size of the block and number of trees. A typical work load is three hours from 1 p.m. to 3 p.m. and will accomplish five blocks of mapping and inventory. The entire project site of 160 acres, 40 blocks, and 700 trees took approximately 10 sessions or 60 man/hours of field survey.

Experiment two--OSU Centennial Grove:

The GPS operational procedure for the second site is essentially the same as for the first one except the OSU Centennial Grove plant collections are accessioned and bear labels with bar codes for access to those plants' inventory database records. Position data is stored simultaneously when the barcode scanner receives a positive scan. This locational data and attributes can be fed into the portable computer and used for updating the inventory or cross-checking maintenance requirements later on.

The site is less than 10 acres with 100 newly planted trees. All trees are already labeled with barcode identifications which enabled us to move along quickly to log their positions. It took only one three hour session to complete the mapping process. We did encounter different kinds of technical difficulties which will be addressed later on.

Technical difficulty

This technology does have its share of problems due to its complex nature. There are so many pieces of the puzzle that need to be put together to make the whole operation work. We encountered several technical difficulties which were not disastrous enough to hinder a project but would surely slow down the project or change the accuracy of the result.

Satellite Visibility

At certain times of day the satellite signals may be too weak or their position may be out of sight, thus causing an interruption in the daily operation. A daily observance of Quick Plan is advisable to ensure satellite availability during each field trip.

Dense Foliage

We intentionally chose the most difficult site to start with this project. The first few technical difficulties we encountered were the failure of the Omnistar receiver and high PDOP in the city residential area. The Omnistar is supposed to give us real-time differential correction so that we can view the tree location on the background map instantaneously while we are walking around. Because of this unreliability, we decided to go for a post-processing route and view our mapping data after each session. The GPS Pro XL receiver is fully functional, but the PDOP reading is generally around 4 and 5 which is high but under the acceptable range of 6.

The centennial Grove site is open with good satellite visibility. We were able to use Omnistar and Pro XL together with real-time differential correction and view our mapping of trees on the background map simultaneously. The PDOP was generally around 2 to 3. However, we had different types of equipment drawbacks which will be discussed later on.

Base station

If the data from the datalogger or laptop has not been corrected for selective availability due to a real-time differential correction failure or weak signals, then we will need to rely on the base station data to do post processing. We had to use a base station to correct our data from the city street tree project. Originally, we were counting on the base station at the Geography Department at OSU. However, their data turned out to be unusable due to an unknown reason. We decided to download base station data from the Center for Advanced Spatial Technology (CAST) at Fayetteville, Arkansas (http://www.cast.uark.edu/). The corrections were adequate, but the distance from this base station which is 164 miles raised some questions about the post processing accuracy. Accuracy degrades as the distance between the base and rover increases. A reasonable working estimate of this degradation is approximately +/-10 ft to 30 ft. In contrast to our Oministar real-time or our working Geography Department base station, we should have had an accuracy of within 1 ft to 3 ft in the best possible conditions.

Proximity to trees

Most of the trees in this city's residential neighborhoods are well established. The majority of them are Pin Oaks, American Elms, Pecans, and Sycamores. Those trees with heavily woody trunks prevent a good reading right by the tree trunk. In general, the field operator needs to offset a distance of 2 to 5 feet away from the tree trunk and under branches to log in good data. For this project, offsetting a tree location is not a critical problem since the offset value can be adjusted later on during post processing.

Conditional problems

During the survey, we had encountered several problems that were conditional. For example, passing vehicles tend to bounce back a multipath signal that distorts an accurate reading. Barking dogs, defensive residents, and curious neighbors may interrupt the concentration of the operator sometimes.

Equipment problems

The current design of the laptop computer is purely for indoor use. On a sunny day with an operator who wears light-color clothes, the LCD display panel is almost impossible to visualize. There is no easy way to remedy this problem except by working at dawn or at night. The barcode labeling system is neat and adequate for visitors' viewing, but it is certainly not designed for a GPS mapping operator or a maintenance crew with a barcode scanner. Its location under the tree dictates two operators, one standing still to log the GPS data and the other bending on the knee for scanning the barcode label. The other fatal flaw of the barcode scanning system is its design. Under the bright daylight, the laser red beam on the inversed barcode label is almost invisible. After five unsuccessful tries of scanning, a normal person could have manually entered the code.

Fig. 10: A vinyl etched barcode label with black background and white lines. This is a medium to high density barcode.

SOFTWARE INTERFACE

If good field techniques are observed, the data processing procedure is fast and easy. There are several software involved with this mapping interface. First, use PFinder to differentially correct the GPS data and transfer to GIS output format of Arc/Info or AutoCAD.dxf. Second, use ArcView to transfer Arc/Info files to ArcView.shp files.

Post processing: Correction for Selective Availability

Inaccuracies imposed by the U.S. Department of Defense (Selective Availability or S/A), and caused by atmospheric and timing errors limit the accuracy of a single GPS receiver to +/- 150 feet. However, there are methods which can be used to provide accuracies of +/- 1 to 10 feet. These methods use a known position, such as a surveyed control point, as a reference point to correct the GPS position error. These methods of correcting GPS positions are referred to as Differential GPS or DGPS. The DGPS can be applied to the GPS data in real-time using Omnistar in our case or can be done later on a PC using base station data. Most of our data for the City street tree project were not corrected via real-time, so we had to resort to a base station differential correction. Our local base station at the Geography Department was unavailable during the project duration, so we used CAST at the University of Arkansas, Fayetteville via the Internet. The accuracy is degraded as previously mentioned in the Base station in the last section--Technical Difficulty.

GIS software integration

Transfer into GIS format

Fig. 11. A background map of the study site of City of Stillwater with spatial data of trees. On the right is the blow up of one typical block.

After all GPS data are corrected and combined, it can be converted to Arc/Info files with PFinder software and then transferred to ArcView.shp files through a translator called Trim2Shp.Apr. ArcView is a desktop geographic information software that gives you the power to visualize, explore, query, and analyze data spatially.

GIS application

The GPS tree inventory data is now transformed into two distinct views in ArcView software. One is the spatially mapped tree theme and the other is its attributes in tabular format. Additional themes such as streets, buildings, utility lines, and other background information can be loaded in as another theme for spatial visualization and query purposes. Other tabular data such as dBase files of City street tree inventory or OSU arboretum accessions from database servers can be loaded into the view and joined with the existing GPS tree attributes. After joining, all tabular data can be displayed geographically (Fig. 13). It is obvious that a map with spatial data will allow one to accomplish many tasks as such:

1. To find the attributes of any feature

2. To select features according to their attributes

3. To select features based on their proximity to other features

4. To find places where certain features coincide

5. To summarize and generate statistics on the attributes of features

6. To layout a map and print it

Fig. 12. A layout map of Centennial Grove with part of the joined database. It highlights a particular interested tree ID. #2 and its hot linked image.

OTHER APPLICATIONS

During the project period, we also experimented with a couple of different types of GPS applications which turned out very satisfactory. One used real-time GPS to log a series of point data and then used these x,y,z locational attributes to create a quadrangle digital terrain model (DTM). The DTM was then used for slope, view, and aspect analyses. The other was to trace the foot paths along a slopping terrain of dense foliage site with real-time GPS and to determine the optimum routing for a vehicular access route. This method combined with a background map in real-time helped tremendously in avoiding poor terrain and mature trees which would be difficult to visualize using paper map planning.

Fig. 13. On the left is a DTM slope analysis of a 130 acre site. On the right is a path tracing of a 80 acre woodland.

CONCLUSION

Cost

This technology does not come without cost. A GPS receiver with good accuracy will cost around $12,500. An Omnistar receiver with data correction service for two years will cost $8,500. A laptop computer with the necessary software will cost about $5,000. The total amounts up to $26,000. This does not include the personnel time, equipment training, permanent base station, and software or hardware upgrade cost. For a larger project site for a company with on-going projects perhaps this technology would be beneficial. For a small project site, this technology may be too costly to implement alone.

Potentials and Constraints

GPS is a powerful and efficient tool for position mapping with attribute recording which is difficult to do with conventional survey. Without this technology, one will need to cross-reference the nearest permanent site feature -- first to locate the relative location of the tree on a paper map and then hand write down all its attributes in a notebook to be retyped into a computer in the lab later on. Combined with GIS, GPS offers many opportunities in spatial data manipulation and query. Spatial data can be used in planning, design, and maintenance with additional software and database interface design capabilities. Real-time GPS mapping allows a designer to conceptualize ideas on site quickly, as evidenced by the path tracing and vehicular routing examples in fig. 14. GPS mapping experiment will certainly advance our students into a more marketable skills of efficiency, accuracy, and time saving.

GPS is a young technology and its signals are being scrutinized by the DOD. The degradation of signals, the prohibitive cost of equipment, and the blockage of dense foliage and buildings tends to lower the effectiveness of this technology. The real-time concept works except for the equipment design and constant availability of correction signals. Current portable computers are not well suited for outdoor use. They are heavy, cumbersome, and bulky. The barcode labeling system is designed for visitor viewing and not for maintenance or inventory purposes. A fundamental design change will entail the successful scanning under bright daylight conditions and single operator maneuverability. It takes too many software operations and format transformations in order to achieve real-time inventory, analysis, and planning. This is not for a novice operator to achieve without intensive training.

ACKNOWLEDGMENT

The author would like to thank two of my students, Frank Hutto and Shu-Yi Chang, who devoted their time under the hot sun in doing all the foot work. The author also would like to thank the National Science Foundation, Oklahoma State University, PSC INC. and the City of Stillwater for providing funding and technical assistance to make this project become true.

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