Location-based intelligence - modeling behavior in humans

SECTION 1. Introduction

This paper considers the specific data elements that can be gathered by service providers about telecommunications customers subscribed to location-based service (LBS) applications. Increasingly private companies are investing in location-based technologies for asset, animal and people tracking. Depending on the type of technology in use, the level of accuracy in terms of identifying the outdoor position of the subscriber can vary from cell-based identification to nearest landmark, to the pinpoint longitude and latitude coordinates of an object or subject. The application context is also important-is information being gathered about employees by an employer or is the use of the technology a voluntary option for the subscriber or their caretaker. Till now, there have been only a few cases which have ended in litigation over the accuracy of a location fix, but as the number of LBS adopters sets to grow for niche application areas, it is predicted that a greater number of conflicts may arise between the end-user and stakeholders. Liability is a key issue here, as is privacy [1].

SECTION 2. Location-based surveillance

2.1 Tracking people

“Mobility is a basic and indispensable human activity that is essential for us to be able to lead independent lives on a daily basis” [2]. Someone who is moving can be tracked manually or digitally. The information being gathered as the end-user moves around can be considered a type of “electronic chronicle” [3]. To allow oneself to be tracked can be a voluntary act, but in most cases it is imposed by a third party who has some control over the end-user. Tracking is critical in the process “of people motion capture, people behavior control and indoor video surveillance” [4]. In this paper we do not consider location information gathered using indoor tracking techniques such as knowledge representation or models of temporal correlation, although these techniques could be complementary to outdoor GPS tracking. There are also other techniques for tracking humans based on Assisted-GPS (A-GPS) [5], Wi-Fi technology such as the ‘Human Tracking and Following’ system [6], or embedded technologies [7] which all may become used in the future as a replacement or contingency technique to GPS. The Wi-Fi tracking approach employs an obtrusive technique requiring the end-user to employ active beacons on their body, as opposed to vision systems which are generally unobtrusive. In like manner, a GPS receiver in the form of a watch or handheld device clipped to a belt can be considered obtrusive [8].

2.2 Storing tracking data

Tracking data gathered by a GPS, such as route or point information, can be spatially represented in a geographic information system (GIS). The GIS may contain multiple layers of information, from civic data to administrative political data, statistical information and even non-earth unit data. The GIS can store trajectory data that is based on assumptions related to the end-user's historical speed and direction data, and static road/path segment information. Related to this idea is the notion of “digital trail libraries”, in effect the study of overlapping GPS trails and their digital storage [9]. Morris et al. explain that GPS track logs, are sequences of precise locations created by dropping a breadcrumb. While Morris' paper focuses on GPS for recreational activity, there is the potential for “private” track logs to be compared in order to find originating and terminating points of interaction between people. The outcomes of such an analysis fall into the category of location-based intelligence. Consider the potential for “collision” alerts of persons of interest. Access to the tracking data of an end-user's records requires strict policing. Hengartner and Steenkiste (2005) reaffirm that “[1] ocation is a sensitive piece of information” and that “releasing it to random entities might pose security and privacy risks” [10]. They emphasize the need for individual and institutional policies and the importance of formal models of trust.

SECTION 3. Methodology

One way to deduce some of the unforeseen consequences of GPS-based human tracking is to experience the process first hand. In this pilot study, a civilian participant tracked themselves for a period of 2 weeks using a GPS 24/7. Participant observation is where the observer “seeks to become some kind of member of the observed group” [11]. For the purposes of this study the participant represents individuals who would have their movements tracked and monitored by a third party. Measures need to be taken to ensure the participant's normal activities are not impacted in any way by carrying the GPS.

Two sets of data are to be gathered throughout this observational study: geographical co-ordinates and diary logs (table 1). The geographical coordinates will be collected through the means of a GPS device as quantitative data. However, in order to interpret this data, GIS software will be used to transform co-ordinates into comprehensible geolocations. The daily diary logs will be collected as complementary qualitative data. Each day during the study the participant will record any thoughts and opinions they may have with respect to being tracked.

3.1 Set-up

The following guidelines were used in the pilot study:

  • Daily activities–at the start of each day the GPS device is turned on as soon as the participant leaves their place of residence. At the end of each day the device is switched off.

  • Carrying the GPS device–the device is carried in the participant's bag or pocket while walking. When driving, the device is placed securely in a dock.

  • Tracking node limitation–the device is only capable of collecting 2000 tracking nodes at a time. While this is more than enough for a single day of tracking it is not enough for more than one day. Care must be taken to ensure that track data is erased at the end of each day so there will be enough memory the following day.

  • Getting a signal–it takes about one minute to get a signal, so when the device is first turned on the user will have to wait until a signal is detected.

  • Indoors–the device looses its signal when indoors so when the signal is lost at a certain location it will be assumed that the user is indoors.

  • Battery life–the manual indicates that the device can get up to 14 hours of usage on two AA batteries. Rechargeable batteries do not have enough power to keep the GPS device running throughout an entire day. Non-rechargeable batteries will be replaced when they are running low.

Table 1  Observational Instruments

Table 1 Observational Instruments

SECTION 4. Observational study

4.1 Digital breadcrumb

Figure 1  —Participant with Magellan GPS Device

Figure 1 —Participant with Magellan GPS Device

An observational study was carried out to gain knowledge about the sensitivity of location information. This study involved a civilian participant who had their daily movements tracked from Monday 15th August 2005 to Sunday 28th August 2005. The participant is a 21 year old university student who works part-time and owns a vehicle. Each day during the two weeks of the study the participant carried a Magellan Meridian Gold handheld device either in a carry bag or pocket (see figure 1). The GPS device was setup to collect location data every three seconds. At the end of each day this data was uploaded into GIS software “DiscoverAus Streets & Tracks” which was used to save and analyze the data. Throughout the entire study the observer stayed in the area of Wollongong, NSW, Australia.

A great deal of information was found out about the observer by tracking them over an extended period of time. From data coordinates it is easy to deduce information such as where the participant is located at a given point in time and the speed at which they are traveling. However, more invasive personal data, such as where the participant lives, his workplace and social activities can also be found. It is also possible to create detailed profiles about the participant based on his daily travel routines. For instance, the speed at which the participant is traveling can indicate the form of transport they are using. How long they spend at a location can determine the type of activities the participant is also engaged in.

Figure 2 shows the participant's movements on day 10 of the study (24th August 2005). On this day the participant traveled from their home to the University of Wollongong, and then to their place of work. This day is typical of other weekdays in the study as the most common locations traveled were to the participant's home, University and workplace. The user's daily track movements are indicated by the thicker lines (two closed loops connected by a highway). With the GIS software it is possible to play the participant's movements in real time, to get a step-by-step and magnified view of their whereabouts. Roads, highways, train tracks and trails are clearly presented in the map. Key locations, street names and suburb names are also shown on the map. Even more data could be gathered manually or purchased to overlay onto the current details. It would be interesting also to show intersecting trails of other members of the family during the same study period. Different types of “families” or “groups” would have different types of profiles, some lending themselves to greater location movement than others, with communities-of-interest (CoI) varying widely from local, national and international travel.

Figure 2 —Participant Track Data for the Study Period

4.2 Graphical travel logs

Graphical analysis of track data also gives indications of a person's travel habits and behavior, providing that all the data is accurate and free from errors. The following graphs (figures 3–6) are meaningful representations of speed, time, distance, and elevation data collected by the GPS.

Figure 3  Time/Speed Graph: indicates speed at a specific time, when a person is traveling from one place to another, and how long the person spends at a given location.

Figure 3 Time/Speed Graph: indicates speed at a specific time, when a person is traveling from one place to another, and how long the person spends at a given location.

Figure 4:  Distance/Speed Graph indicates speed at a specific point in a journey, and whether a person is in a vehicle or walking (i.e. form of transport).

Figure 4: Distance/Speed Graph indicates speed at a specific point in a journey, and whether a person is in a vehicle or walking (i.e. form of transport).

Figure 5:  Time/Distance Graph indicates the length of time a person stays at a location, the length of time a person is on the move, and the number of places a person travels to.

Figure 5: Time/Distance Graph indicates the length of time a person stays at a location, the length of time a person is on the move, and the number of places a person travels to.

Figure 6:  Distance/Elevation Graph indicates a person's location by comparing the elevation patterns with other data.

Figure 6: Distance/Elevation Graph indicates a person's location by comparing the elevation patterns with other data.

 

SECTION 5. GPS tracking issues

5.1 Accuracy

Although not perfect in terms of accuracy of a given location fix, the GPS is generally perceived by civilians as being close to perfect. However, on several occasions in the observational study substantial errors occurred. Over the two weeks of the observational study there were six significant signal dropouts. During a signal dropout a person's location is not known. All of these dropouts occurred while the participant was traveling by car. It is likely that the GPS receiver was not positioned well enough to gain an accurate signal or traditional natural/physical factors affected the device. This kind of signal dropout could be costly in a real life scenario if a person's location was mandatory. There were also five significant speed miscalculations during the study. Speed is found by calculating the distance traveled between two points within a given time period. For example, on day 13 of the observational study the tracking information indicated a speed of 600 km/h whilst in a moving vehicle. This was found by calculating the time and location differences between two subsequent tracking points. The collected GPS data indicated the participant had traveled 0.0479884332997 kilometres in 5 seconds.

Table 3  Summary of Geolocation Trail Data

Table 3 Summary of Geolocation Trail Data

5.2 Editing track data

The GPS device used to collect location data stored tracking nodes which recorded location and time data every 3 seconds. GIS software was then used to create an entire track by joining each tracking node. However, the software also grants the user the option to add and edit tracking nodes. This feature is included to assist in navigation but could be used for other covert reasons. The use of GPS location data is surprisingly considered legitimate evidence in legal trials [12]. It is possible to convict an innocent man of a crime they did not commit by editing track data to falsify evidence. Stringent security and validation checks need to be set in place if authorities plan to use GPS track data as valid evidence in a court trial.

5.3 User travel behavior

An analysis of the track data has shown that the participants' daily movements are quite similar each week (compare figures 7 and 8, 9 and 10) and is a reflection of their daily routines and behavior. The observer took the exact same travel route whenever they traveled to a known location, like home or work, even though there are alternate routes-reflecting how habitual some humans are. The track data also reflects the participant's behavior when they are running late for a meeting or deadline (i.e. the participant accelerated their speed while walking/driving). This kind of information can be used to create intelligent systems which can observe what a person is doing and then alert systems when their behavior is out of the ordinary.

Figure 7:  Time/Speed Graph (17 August 2005)

Figure 7: Time/Speed Graph (17 August 2005)

Figure 8:  Time/Speed Graph (24 August 2005)

Figure 8: Time/Speed Graph (24 August 2005)

Figure 9:  Distance/Speed Graph (17 August 2005)

Figure 9: Distance/Speed Graph (17 August 2005)

Figure 10:  Distance/Speed Graph (24 August 2005)

Figure 10: Distance/Speed Graph (24 August 2005)

Substantial similarities can be seen between like graphs, one week to the next. Both sets of time/speed graphs indicate the participant traveled on four occasions during the same day of the week, in consecutive weeks. The distance/speed graph shows similar patterns of traveling speed. In fact, the graphs of every single weekday were almost identical one week to the next, typical of a university student pattern of behavior. The weekends did not vary that much either- an opportunity to go to work, take a break for some socializing, and return home for further study.

5.4 Detail of GIS

The GIS software used, provided details on the roads, highways and the location of major landmarks but did not show any building data. There are however, databases like MapInfo's MapMarker or the Australian Geographical National Address File (G-NAF) that could be coupled with a telemarketing list to provide a rich background layer. In this project, little could be deduced from the user's location at certain longitude and latitude coordinates (apart from what the user provided) because the supporting database was absent. The level of detail in a GIS could be made scalable to correspond with its application context. In applications which require high resolution detail, the GIS could be setup to display roads, buildings and landmarks. Conversely, if little detail is needed it could show the user's location in relation to important landmarks.

5.5 User awareness

Several days into the study the user indicated that it was easy to forget about the fact they were being tracked or observed (see section 6). Any activity that is carried out at length could easily become routine. By the end of the study the user was not concerned about being tracked but was more concerned about having to carry the device around. If GPS were to be enforced on parolees as a deterrent to crime, the participant felt it might lose effectiveness as a tool in the longer term.

5.6 Outcomes of the observational pilot study

This pilot study provided a practical perspective to the process of GPS tracking and proved that it can be accomplished with relative ease. The evidence suggests that tracking a person over an extended period of time is an invasion of privacy as GPS applications can track every detail of a person's movements. The probability of inaccuracies and the possibility of editing data poses questions about the reliability of such information. The effectiveness of GPS tracking in deterring crime may not be as great as first thought because the user may become blasé about its presence.

SECTION 6. Participant diary entries-narrative

This section is taken verbatim from the participant's diaries made between Monday 15th August 2005 and Sunday 28th August 2005. It is important to highlight some of the end-user perceptions and attitudes towards the basic GPS tracking application.

Day 1: Monday 15th August 2005

Today was the first day of tracking. Throughout the day I was very conscious of the device I was carrying. Every time I left for a new location I would check if the device was working and if I was getting an accurate reading. A person being tracked would not be too concerned whether their receiver was working or not. Although a parolee with a faulty tracking device may face immediate repercussions.

Day 2: Tuesday 16th August 2005

It would seem that my primary objective is to simply carry the device, not to track my movements. I rarely think what someone else would think. In fact, I am in a different state of mind when I am downloading and looking over the waypoints I collected that particular day. Most of the time when I am traveling from place to place I am concerned about whether the device is working, how much battery life I have left, if a signal has been picked up.

Day 3: Wednesday 17th August 2005

Running late for a meeting today I noticed that I was traveling faster than normal. Not just when I was driving but my walking pace was very fast. This behavior was projected through my physical movements which were picked up in the GPS receiver. From this experience it could be possible to create user profiles on a person being tracked. For example, analyzing the walking speed can reveal an approximate walking span and from that the approximate height of the person can be deduced. This idea may seem farfetched and outlandish but it would be an interesting experiment to conduct one day.

Day 4: Thursday 18th August 2005

A thought occurred to me while I was driving to the RTA to do my driving test for my full license. What if all cars carried a GPS or similar LBS device on board and two cars were involved in a car accident. The Driver Qualification Handbook indicates that three most common types of crashes by new drivers involve two cars in rear-end collisions, adjacent collision when turning corners and opposite collisions when turning corners. A GPS could be used to reveal what exactly happened in an accident like which person hit first and which person was traveling the fastest. If cars were being tracked there could be rules set out to provide automated emergency responses. For example, if the speed of a vehicle decelerated at an alarming rate, e.g., from 100 km/h to 0 km/h in less than a few seconds, it would be fair to say that the vehicle was involved in an accident.

Day 5: Friday 19th August 2005

While analyzing today's tracking data I have noticed that the device sometimes loses a signal when I am driving. This is most likely due to the poor placement of the receiver. If a GPS device was used to track a person, the placement of the receiver would be very important. Parolees often have GPS devices placed around their ankles leaving it very low on the body and unable to get the best signal. I think receivers need to be placed higher up on the body to ensure continuous and accurate readings.

Day 6: Saturday 20th August 2005

The mapping software I used to download my tracking data gives the option to add and edit way points or tracking nodes. It would be easy to frame a person by editing the location data and disproving any alibi they may have. I wonder about the reliability of location data collected from GPS devices alone.

Day 7: Sunday 21st August 2005

After a week of tracking I have voluntarily decided to extend the study period of personal tracking so that I will have more data to analyze. I am not concerned about tracking my movements for another week. In fact, I am eager to continue this study to get more data and to make weekly profile comparisons possible.

Day 8: Monday 22nd August 2005

I am beginning the second week of tracking today and my awareness level of the tracking of my own movements has dulled. Throughout the day I do not consciously think of myself as being tracked. At times I may check if the device is working correctly but I am not concerned about the data the device is collecting about me. I can now say that after eight days of tracking, I am used to the process, even though it is such an abnormal activity.

Day 9: Tuesday 23rd August 2005

After replacing the batteries in the device with a fresh set I have noticed the device picks up a signal much quicker than it did with a used set of batteries. This makes sense to me; the more power the device has the better it will work. However, this has ramifications for people being tracked, especially prisoners on parole who have to recharge the batteries each day.

Day 10: Wednesday 24th August 2005

It has occurred to me that the pervasiveness of GPS tracking depends on the complexity and detail of the GIS being used. The more information being displayed on a GIS such as landmarks, roads, side streets, the more information about the person's movements are available. When I analyze my own movements at the end of the day, I find myself sequentially and systematically recollecting where I went, and reevaluating my motives for being there.

Day 11: Thursday 25th August 2005

I have noticed that so far my data is fairly ‘static’, based on my weekly and daily routines. For example, I regularly travel to University and my workplace at the same time and day each week. I could also make the assumption that many people have stringent daily routines, especially people that are currently being tracked using GPS. Intelligent systems could be developed to monitor these movements automatically. The system could analyze a person's movements over a week or two and develop a personalized information system that would create user profile based on their activities.

Day 12: Friday 26th August 2005

No entry.

Day 13: Saturday 27th August 2005

The entire process of tracking my movements has become a habit. I can imagine it would be similar for any person who has to have their movements tracked. I am relieved the entire process is drawing to a close mainly because I do not have to carry around the GPS device anymore. This is not on account of the bulkiness or weight of the device (it only weighs 233 grams)- but my relief comes from the knowledge that I do not have to worry about being attached to this gadget both physically and mentally.

Day 14: Sunday 28th August 2005

Today is the final day of this study. I did not track my movements today because I stayed at home. Looking back at the previous weeks I did make an effort to travel a lot so I would have a substantial amount of data to analyze. I wonder if this will have an opposite effect on a person being tracked by a second party. Would they travel less? Would a teenager being tracked still visit places his/her parents thought of disapprovingly?

SECTION 7. Towards überveillance

Dataveillance is defined as the “systematic use of personal data systems in the investigation or monitoring of the actions of one or more persons” [13]. M. G. Michael [14] has spoken of an emerging-überveillance-above and beyond almost omnipresent 24/7 surveillance. The problem, he has gone on to say, is that in human terms at least, “omnipresence will not always equate with omniscience, hence the real concern for misinformation, misinterpretation, and information manipulation.” In the case of the civilian participant observed in this study we cannot assume everything based on his/her location. Being located in the bounds of the “home” does not mean that the participant has gone to sleep or is inactive; while he/she is at “university” it does not mean they are studying or in class; going to “work” (which happens to be a gymnasium) does not mean the civilian is working out; visiting the location of the “unibar” does not mean the civilian was drinking anything but cola; a “signal dropout” does not presume the civilian did not take a detour from their normal route; and a “speed miscalculation” does not necessarily mean the civilian was not speeding, they may have been in an alternate mode of transportation like an airplane, train or speedboat. Thus while location can be revealing, it can also be misleading. It is important that end-users of location based services, save for law enforcement, be able to “opt-out” of being tracked, rendering themselves “untraceable” for whatever reason. Being untraceable does not mean that one is doing something wrong, it is one's right to be “left alone”, and LBS policies need to ensure these safeguards are built in to their applications. Being tracked by multiple “live” devices will also become an issue for the future. What is the true location of a person who is tracked by more than one device-the notion of moving and stationary association confidences is important here [15].

SECTION 8. Conclusion

Tracking is very invasive so care must be taken to ensure that only essential information about that person is revealed. Levels of privacy can be controlled by incorporating intelligent systems and customizing the amount of detail in a given geographic information system. If these types of measures are enforced GPS tracking can be used in an ethical manner which is beneficial to the person being tracked, not detrimental.

GPS is an effective technology and it can potentially save lives, however many current applications are not suited to it. Many groups of people rely heavily on the technology even though it is prone to inaccuracies and unreliable at times. Technological convergence may correct some of these issues but a real problem is posed if the GPS network is solely relied upon. It should be remembered that as we build more and more mission-critical applications that rely upon GPS, that the US government can shut down parts of the system in times of crisis, in addition to having already existing problems maintaining their satellites. When using any form of GPS tracking device, backup systems need to be implemented, and a Murphy's Law type mentality needs to be encouraged: If the GPS can fail, it will fail!

These findings apply to all parties which track the movements of others. These groups include police responsible for law enforcement, parole officers, caretakers of dementia patients, parents who want to track their children and employers who track their employees. These groups need to ensure that the tracking of people is done in a just and ethical fashion. It is up to the trackers to ensure that the tracking of another human is done in a way which is beneficial to the person involved and the wider community.

SECTION 9. Further research

The next phase in this research is to carry out a group observational study. The observational study in this paper was limited to a single participant but it would be interesting to track the movements of a group of people. A study like this could be used to investigate whether detailed portfolios can be created from anonymous participants based on their travel patterns. Another aim could be to create an intelligent system that would collect and analyze the movements of people automatically. In addition to an observational study several people who have had GPS tracking imposed on them could be interviewed to ascertain the emotional and psychological consequences of having a GPS tracking device attached 24/7 for long periods of time.

References

1. S. Dur, M. Gruteser, X. Liu et al., "Context and Location: Framework for Security and Privacy in Automotive Telematics", Proceedings of the 2nd International Workshop on Mobile Commerce, pp. 25-32, 2002.
2. K. Kayama, I.E. Yairi, S. Igi, "Semi-Autonomous Outdoor Mobility Support System for Elderly and Disabled People", International Conference on Intelligent Robots and Systems, pp. 2606-2611, 2003.
3. Pingali, R. Jain, "Electronic Chronicles: Empowering Individuals Groups and Organisations", IEEE International Conference on Multimedia and Expo, pp. 1540-1544, 2005.
4. R. Cucchiara, C. Grana, G. Tardini, "Track-based and Object-based Occlusion for People Tracking Refinement in Indoor Surveillance", Proceedings of the ACM 2nd International Workshop on Video Surveillance & Sensor Networks, pp. 81-87, 2004.
5. G.M. Djuknic, R.E. Richton, "Geolocation and Assisted GPS" in , IEEE Computer, pp. 123-125, 2001.
6. A. Arora, A. Ferworn, "Pocket PC Beacons: Wi-Fi based Human Tracking and Following", Proceedings of the 2005 ACM Symposium on Applied Computing SAC'05, pp. 970-974, 2005.
7. H-C Wang, J-C Lin et al., "Proactive Health Care Underpinned by Embedded and Mobile Technologies", Proceedings of the Fourth Annual ACIS International Conference on Computer and Information Service, pp. 453-460, 2005.
8. A. Applewhite, "What Knows Where You Are? Personal Safety in the Early Days of Wireless" in Pervasive Computing, IEEE, pp. 4-8, 2002.
9. S. Morris, A. Morris, K. Barnard, "Digital Trail Libraries", Joint ACM/IEEE Conference on Digital Libraries, pp. 63-71, 2004.
10. U. Hengartner, P. Steenkiste, "Access Control to People Location Information", ACM Transactions on Information and System Security, vol. 8, no. 4, pp. 424-456, 2005.
11. C. Robson, Real world research, Melbourne:Blackwell Publishing, 2002.
12. K. Michael, A. McNamee, M.G. Michael et al., "The Emerging Ethics of Humancentric GPS Tracking and Monitoring", International Conference on Mobile Business, 2006.
13. R.A. Clarke, "Information Technology and Dataveillance", Communications of the ACM, vol. 31, no. 5, pp. 498-512, 1988.
14. M.G. Michael, "Consequences of Innovation" in IACT 405/905 Information Technology and Innovation, NSW, Australia:University of Wollongong, 2006.
15. J. Myllymaki, S. Edlund, "Location Aggregation from Multiple Sources", The International Conference on Mobile Management, pp. 131-138, 2002

Keywords

Humans, Global Positioning System, Geographic Information Systems, Computer science, Monitoring, Business, Credit cards, Data privacy, Surveillance, Tracking, artificial intelligence, monitoring, object monitoring, location-based intelligence, GPS, object tracking
 

Citation: Katina Michael, Andrew McNamee, M.G. Michael, Holly Tootell, "Location-based intelligence - modeling behavior in humans",  ISTAS 2006. IEEE International Symposium on Technology and Society, 8-10 June, 2006, USA.

The importance of conducting geodemographic market analysis on coastal areas: a pilot study using Kiama Council

Katina Michael, School of Information Technology and Computer Science, University of Wollongong, NSW, Australia, 2500

Full Citation: Katina Michael, 2003, The importance of conducting geodemographic market analysis on coastal areas: a pilot study using Kiama Council, eds. Colin Woodroffe, Ronald A. Furness, Coastal GIS 2003: an integrated approach to Australian coastal issues, Proceedings of the Workshop, University of Wollongong, 7-8 July 2003, Wollongong Papers on Maritime Policy No 14, pp. 481-496.

Abstract

In February of 2003 Kiama Council launched a preliminary survey to gather community attitudes on the future growth of Werri Beach and Gerringong, NSW (Nelson). The survey focused primarily on what actions Council should take to manage population growth within existing neighbourhoods. This paper aims to support the preliminary survey by proposing that a geodemographic market analysis be conducted to complement the findings of the study published in May 2003 (Wiggins). The use of a Geographic Information System (GIS) can add great value to the strategic decision-making process and it is the recommendation of this paper that GIS should become an integral component of Council’s day-to-day planning function. This type of analysis does not negate the requirement for community participation in local issues rather it enhances the planner’s ability to make more informed decisions using a holistic approach throughout the lifetime of a given project. The findings of this paper indicate that GIS is an important element of any coastal assessment. The process outlined here could be adopted by councils located all along the Australian coastline.

Introduction

Kiama Council covers a surface area of 256 square kilometres. Within its bounds is the rapidly expanding coastal town of Gerringong, located within the post code 2534. Gerringong is known for its picturesque rolling hills, lush evergreen dairy farms, and famous surf beach (Werri Beach), all of which make it a popular holiday destination and ideal for residential settlement. However, so many attractions undoubtedly place pressure on the environment as increasing numbers of tourists visit, and demand for housing continues to rise. Council is left with the challenging task of catering for the diverse range of needs both of the permanent local and temporary populations. This paper will identify the need to conduct geodemographic market analysis using a variety of statistical and spatial sources from different data suppliers, including the Australian Bureau of Statistics (ABS). It will explore how GIS could be applied by Kiama Council to better plan for the future growth of Werri Beach/ Gerringong and Gerroa and finally offer some preliminary findings. Throughout the paper space will also be dedicated to some of the more practical issues that the GIS analyst could be faced with in conducting such a study.

Background

Kiama Council is typical of most local councils. It has a small planning team and a defined annual budget for information technology (IT) requirements. In 2002 the need for Council to invest in a state-of-the-art GIS was investigated and several platforms evaluated. As a result GIS software and support hardware was purchased in 2003 and a newly-established GIS team was formed. Council is actively trying to incorporate GIS into a range of functions because it foresees positive flow-through effects through this type of inter-departmental collaboration. However, in the short-term resource constraints mean that specific applications of GIS pertaining to the planning function may be delayed, in preference to other core council requirements. One of the problems identified by the planning team was actually defining those important applications that would help them do their work more efficiently and effectively. This is a common hurdle that non-GIS professionals face as they are trying to come to terms with the value the software can bring to their organisation and more specifically, to their job role. The very positive attitude the planners have toward one day integrating GIS into their existing processes and practices means that successful implementation is likely. The following pilot study is representative of what is possible in the future.

Methodology

A semi-structured interview was conducted with one of Kiama Council’s strategic planners to ensure that a gap was being filled with the proposed pilot study. The interview was open-ended and probing questions were asked to determine the current state of GIS practice within the planning department in the Council. A subsequent literature review found the link between geodemographic market analysis and coastal issues to be severely lacking. Some of the more relevant publications included Maguire et al. (1991), Grimshaw (1994), Goss (1995) and Birkin et al. (1996). As an outcome of the interview and literature review it was decided to document the high level process required to build a GIS for geodemographic purposes and outline how spatial analysis could be used to aid Council’s strategic planning function. The contribution of this paper is not in its statistical output but in demonstrating the value of GIS for strategic planning in coastal areas. Admittedly one of its limitations is that it does not take into consideration longitudinal trends and patterns, but it does illustrate the power of GIS to represent cross-sectional demographic data.

Process

A work-in-progress custom GIS was created using the MapInfo Professional application with supporting data sets from a variety of suppliers and vintages. The following steps were taken to build the GIS:

(1)  understand the various spatial units of analysis and determine which level(s) of detail are appropriate and useful for Council;

(2)  identify and acquire the separate layers of spatial data required to conduct meaningful research and consider how these could be used in prospective applications (e.g. roads, parks, rivers and other features);

(3)  gather demographic data for residential and business market segments (either internally or externally available to the Council, and of primary or secondary research sources);

(4)  geo-reference demographic data to designated spatial units;

(5)  determine how the custom GIS can be used to shed light on issues of human geography and the environment; and

(6)  conduct geodemographic analysis using structured query language (SQL) and thematic mapping to uncover specific trends and patterns.

Spatial Units of Analysis

Prior to building a GIS for a specific area the planner must be able to identify all those important units of analysis that are relevant and meaningful to the study. Depending on the scope of the study, one may choose to start their analysis at a coarse level of detail, such as a local government area (LGA) unit and work their way down to a census collection district (CCD) level. The top-down approach is to be preferred in large-scale projects like the Comprehensive Coastal Assessment (CCA) initiative proposed by the Department of Infrastructure Planning and Natural Resources. Only in this manner can planners prioritise responses to pressing issues over a variety of locations. What is paramount, independent of the scope of the study is that recognized spatial units are used in the GIS, such as those defined in the Australian Standard Geographical Classification (ASGC) hierarchical list (Castles 1993). In the case of the Kiama Council pilot study, which focused on the post office area (POA) of Gerringong, planners specifically requested the need to use CCD level information, and if possible, to perform an even more granular investigation. This especially posed a challenge to the author, particularly because the public availability of demographic data at the street or dwelling unit (cadastral level) is very limited, save for internal Council intelligence information. Provided that strict controls were placed upon the access and use of the latter, Council would be adhering to Australia’s Information Privacy Principles.

Spatial Layers of Information

The three categories of layers in the pilot study included: natural features, non-natural features and government-defined spatial boundaries. The vector layers are represented as region, line or point objects dependent on what they are depicting. Natural features included layers like rivers, lakes, the coastline, parks and reserves, while non-natural features included layers like roads, bridges, railways, residential and business dwellings, and public amenities. As a general rule, the more layers of spatial information one can acquire for a particular study, the richer the results. Important to note however, is the scale of the map layer in question, its currency (in terms of lifetime), its quality, and its purpose to a given GIS project.

MapInfo (among many other suppliers, like ESRI) develop and supply spatial layers that proved to be useful in this pilot study. The first are the ASGC administrative spatial boundaries as defined by the ABS in the CDATA2001 product; everything from LGAs to CCDs, including POAs. The second is the detailed road network that is available in the StreetPro® Australia product that contains street addressing and an additional fourteen layers of data. The third is the MapInfo® CadastralPlus product that contains individual land parcels from which centroid longitude and latitude locations can be extracted. And finally the MapMarker® Australia product, which includes an intelligent address parser, and can be used to pinpoint dwelling locations using either internal Council address information or external sources like Brylar’s Australia on Disc (AOD) database. MapMarker’s capabilities differ significantly from the Cadastral spatial layer, in that the former allows for residential and business names to be geo-referenced to a street address (i.e. a longitude and latitude location). Apart from vector-based data, raster data like aerial photographs could also be used to enhance the planner’s perspective of a given problem. Other spatial data, like hardcopy building approval plans could be scanned and geo-referenced, although such a process would be time-consuming and expensive, it would in the longer-term pay for itself.

Demographic Data

There is usually a plethora of demographic data available at high levels of granularity, such as at the statistical local area (SLA) and POA levels. While the data at this level is considered coarse, by most regional Councils, the overall key indicators are helpful in establishing a background setting for the study. There are also two broad categories of demographic data that can be acquired; these are either primary or secondary in nature. In general, secondary data is usually a lot more affordable than primary research data. Examples of secondary data used in this study include: ABS CensusData and the Australian Business Register (ABR). Additional data sources that would prove useful include: the ABS Integrated Regional Database (IRDB), the ABS Socio-Economic Indexes for Areas (SEIFA), Salmat’s MarketFind database and Dun & Bradstreet’s Marketing List. The specific fields of data included in the above-mentioned sources are too many and varied to list, even in a tabular format- the CensusData data source alone would fill several pages. However the demographics can be categorised as pertaining to either the residential or business market segment.

Residential data that can be obtained includes (aggregated down to the CCD level) attributes like: the number of people, the number of household dwellings, resident age and background, the average individual/ household income, the number of employed/ unemployed persons, the qualification level reached by residents and their occupation, housing status and level of ownership. Other residential-specific databases aim at providing predefined target groups based on the level of income earned or other economic or education-based indicators. For example, Salmat’s Marketfind tool distinguishes 24 demographic profile types, ranging from the ‘Prestige’ category to ‘Suburban Welfare’ and also brings together customer lifestyle and attitudes profiles. Specific AC Nielsen data can be added to this as well, if required. Business data that can be obtained (down to the POA level) includes the size of business, in terms of the number of employees or annual turnover amount in dollars. The type of business, based on the Australian and New Zealand Standard Industry Code classification (ANZSIC) can be obtained at either the industry division (17 categories) level or subdivision (53 categories) level. At the individual company level, the industry classification can be acquired (as specified in the Australian Yellow Pages), including full postal address and telephone/ fascimile details, as well as a web site and email address if provided. The Dun and Bradstreet Marketing List also includes a contact name for each company, the line of business, revenue, exact number of employees and more.

As for internal intelligence sources, these were not obtained for the pilot study but it is assumed, that if Council adopted the findings of this paper, that they would be able to use appropriate internal data to further enhance the GIS. The attributes that would be useful, among others, include ratepayer information per dwelling/ land parcel, land-use zoning information (such as residential, commercial, industrial categories), specific building regulation constraints and the number of temporary versus permanent residents (for instance during public and school holiday periods).

Geo-referencing Demographic Data to Spatial Units

One of the fundamental uses of GIS is to bring spatial data together with aspatial data. Potentially this also presents the GIS administrator with one of the greatest challenges- how to integrate two or more sets of aspatial data sources that are not 100 per cent compatible with the designated spatial layers. While the use of ASGC boundaries has been encouraged in this paper, planners should be aware that boundaries like SLAs and CCDs are variable in nature, depending on the growth or decline of a given area over time. For instance, the 1996 and 2001 Australian SLA boundaries differed in number and in name. A SQL statement could easily identify the discrepancies in the spatial layers from year-to-year but this still does not resolve the problem of matching databases of various vintage successfully to base spatial layers. And this is not only a problem limited to ABS-defined boundaries; this same problem is recurrent in natural and non-natural spatial layers. Consider the case where new roads are added to a town as a result of a new housing estate being established, among many other examples. GIS users need to think about how their organisation will overcome ungeocoded records (i.e. those records that remain unlinked using a given primary key), without compromising the overall accuracy of the results. The ideal situation is to continue to upgrade data sources as they become available, although this becomes an expensive exercise and is not always feasible given that some databases do not follow a periodic release schedule. Whatever solution is sought, what is certain is that guidelines need to be drawn and implemented. These guidelines may also vary dependent on the type and size of database being geocoded. Sometimes manual manipulation is plausible, other times it is not. For example, hit rates for the geocoding of telemarketing information to street addresses commonly range between 60-70 per cent of total records dependent on the intelligent addressing product in question and how clean the database being geocoded is (Drummond 1995; Holloway 1998). Checking one hundred ungeocoded street address records manually (one-by-one) may be a manageable exercise, while one hundred thousand would be unacceptable.

Council Applications of GIS

Once a GIS inventory has been created and appropriate data sources geocoded to spatial locations, an organisation can begin to program automated applications, in order of priority. The planning function at Kiama Council has been identified as being made up of mainly routine tasks. GIS applications lend themselves well to such tasks, allowing for automated reports to be generated periodically that show results not only in tabular and graphical views but also in spatial ways as well. The spatial element, in a digital form, can add a lot of value to decision-making processes as it grants the planner an additional perspective to the problem(s) at hand. GIS can also be used for non-routine tasks that require specific inquiries to take place as requested by council members. The applications that may be considered for implementation by Kiama Council are described below.

§  Basic geodemographic profile: defining discrete places within Gerringong which are meaningful to Council planners and extracting demographic data based on these areas, such as “Gerringong Central Business District” (CBD) and “Werri Beach”. The statistics should incorporate both residential and business information over time. Forecasts of these figures should be calculated as well using appropriate types of trend analysis.

§  Re-evaluating land-use zoning development controls: the ability to consider whether a given area should be classified as a particular type of zone (e.g. residential or light industrial).

§  Considering building proposals: Council has the ability to either accept or reject a building proposal based on evidence provided in the GIS (using both raster and vector spatial layers of information). Geographic data such as the area of the dwelling in proportion to the rest of the block, the gradient of the driveway, the aspect the dwelling faces (i.e. energy-saving measures), even the distance between one dwelling and the next, can all be factored in to preserve the local character of the location in question.

§  Calculating the dwelling height: the ability to calculate the heights of existing dwellings within a given area and to determine whether proposed structures meet height restrictions (e.g. careful design of buildings that does not lead to overly dominant structures).

§  Considering residential redevelopment proposals: Council can consider residential subdivision, dual occupancy development, integrated housing and villa homes, based on perspectives offered by the GIS. Additional layers acquired from utilities would also be helpful, including water, sewerage and electricity pipeline locations.

§  Choosing areas suitable for housing development: Council can determine the most suitable location for a new housing estate and comply with current standards without compromising, despite the pressure for more land parcels to be made available to prospective residents on permanent housing waiting lists. The size of the block for instance, should remain as close as possible to the existing average land parcel. Roads and pathways as well as reserves should be intelligently scoped into new housing estate areas. For example, the new Elambra Estate (see figure 1).

§  Approving local business opportunities: considering the needs of local residents and acting according to these needs. For instance, the approval of the Independent Grocer’s Association (IGA) supermarket.

§  Ensuring adequate commercial and industrial floor space: calculating the availability of business floor space for particular types of companies, as increasing numbers of people reside in Gerringong.

§  Protecting the coastal strip: Council can ensure that development within the coastal strip meets all rules and regulations. The distance from the coastline can be measured precisely and appropriate action taken in a given scenario. For example, preserving the character of Werri Beach, despite the obvious opportunities to invest in high-rise apartments, such as on the southern headland.

§  Services to the community: identifying areas where particular services to the community are required and targeting those clients, dependent on the service. For example “meals on wheels”, or the possibility of a local high school or police station. The relocation of Gerringong Primary School to Greta Street is another example.

§  Demand for public amenities: understanding the need for amenities such as public pools, barbecues, toilets and bins in key locations or pathways leading to the beach to ensure that sand loss does not occur. For instance, the decision to rebuild the local surf club and associated bowling club on Pacific Avenue.

§  Catering to increasing traffic pressures: the consideration of adequate parking facilities that meld into the surrounding streetscape.

§  Sewerage and drainage schemes: identifying those residents that are yet to connect to the new Gerringong-Gerroa sewerage scheme and those areas that are prone to flooding after heavy rainfall.

§  Sustaining the needs of increasing numbers of visitors and temporary residents: determining whether there is enough temporary housing such as caravan parks and hotels as well as parks and reserves.

§  Affordable housing: determining the mix of housing available and planning for a range of options in terms of affordability.

Figure 1 New housing estate areas: Using the GIS to assess prospective locations for new housing estate areas and planning for development that is in accordance with the local character. For example, Elambra Estate in southern Gerringong comprises of 250 sites with a range of land and house size and style options, including duplex and integrated sites. Elambra Estate is considered to be an environmentally responsible land development project initiated by Kiama Council.

Figure 1 New housing estate areas: Using the GIS to assess prospective locations for new housing estate areas and planning for development that is in accordance with the local character. For example, Elambra Estate in southern Gerringong comprises of 250 sites with a range of land and house size and style options, including duplex and integrated sites. Elambra Estate is considered to be an environmentally responsible land development project initiated by Kiama Council.

Summary Facts and Figures

Reports that have been commissioned by Council, such as those compiled by Wiggins (2003) and ESD (2002) would be aided by the use of a GIS. Not only could qualitative outcomes from the reports be captured spatially for future re-use by Council planners but quantitative data could also be extracted to enhance report outcomes with accurate facts and figures (both current and forecasted). The following is a summary of some of the fundamental cross-sectional data that was captured by the work-in-progress GIS for the post code of Gerringong (2534). The extracted data is shown by unit of analysis and should be considered in light of the GIS applications proposed above. While these figures do not depict clusters of typologies, nor consumer behaviour or attitudinal patterns, they do indicate the vital demographics any planner should be aware of before drilling down further. Only when a planner is comfortable with the high-level numbers, after laying the foundations of a basic GIS, can they fully appreciate the implications of particular geodemographic trends (Schensul 1999).

Post Code Analysis

The post code 2534 covers a surface area of about 86 square kilometers. There are 9 suburbs in the post code including: Gerringong, Gerroa, Werri Beach, Foxground, Toolijooa, Broughton, Omega, Rose Valley and Broughton Village. In 1996, the ABS census recorded 1458 residences and a total population of 4047. According to the ABS ABR, in 1998 there were 145 businesses operating in the post code and in 2001 there were 433 Australian Business Numbers (ABN) registered in the post code.

Collection District Analysis

There are 10 collection districts in post code 2534 which cover a surface area of about 82 square kilometers. The residential and business dwelling count per CCD can be found in a graduated thematic map in figure 2. In 1996, the median age was 40 years old and the median household income was between $500 and $699. Save for the United Kingdom and New Zealand, a very small proportion of persons residing in Gerringong were born outside Australia.

Figure 2 Demographic distribution analysis: Understanding the distribution of residential and business dwellings by Census Collection District (CCD). Above can be seen a graduated thematic map (green dots) overlayed against a ranged thematic map (shades of red). This visual representation allows the planner to consider where there is peak demand for public amenities.

Figure 2 Demographic distribution analysis: Understanding the distribution of residential and business dwellings by Census Collection District (CCD). Above can be seen a graduated thematic map (green dots) overlayed against a ranged thematic map (shades of red). This visual representation allows the planner to consider where there is peak demand for public amenities.

Roads Analysis

There are 129 roads in post code 2534 stretching a total of 80 kilometres in length. Seventy-five percent of residential dwellings are located in 30 roads and streets. Four streets have over 100 residential dwellings each, including Belinda Street, Renfrew Road, Fern Street, and Stafford Street. Forty percent of businesses are located on three roads, including Fern Street, Belinda Street and Rowlins Road. The respective graphs representing these statistics can be found in figure 3.

Figure 3 Targeting populated places: The graphs above depict the density profile of Gerringong by street. Typical of a regional coastal town in Australia, 50 per cent of residential and business dwellings are located in only about 10 per cent of roads. Viewing residential and business counts graphically in order of their prominence, such as in the above line graphs, can help the planner identify areas of peak traffic (both pedestrian and vehicle).

Figure 3 Targeting populated places: The graphs above depict the density profile of Gerringong by street. Typical of a regional coastal town in Australia, 50 per cent of residential and business dwellings are located in only about 10 per cent of roads. Viewing residential and business counts graphically in order of their prominence, such as in the above line graphs, can help the planner identify areas of peak traffic (both pedestrian and vehicle).

Dwelling Analysis

As of 2002 there were approximately 2000 residential dwellings in post code 2534, which equates to approximately 5200 permanent residents. Over 225 businesses are located in the area. Eight-four percent of businesses employ less than 5 employees. Over 50 per cent of business can be categorized as ANZSIC type Construction, Manufacturing or Retail.

Figure 4 Household dwelling distribution: The thematic map above shows the distribution of households by road. The thicker the road segment and darker the shade of red, the more households are located on that street. This thematic map can help planners to strategically place parks, reserves and rest areas in positions that will be utilised by the neighbouring population.

Figure 4 Household dwelling distribution: The thematic map above shows the distribution of households by road. The thicker the road segment and darker the shade of red, the more households are located on that street. This thematic map can help planners to strategically place parks, reserves and rest areas in positions that will be utilised by the neighbouring population.

Conclusion

Local councils are beginning to understand the power of geographical information systems (GIS). While GIS is not a new concept, many councils are only now adopting the technology. Spatial analysis provides a whole new dimension to the strategic planning process that can aid in producing a holistic perspective rather than a piecemeal approach to solving real and anticipated problems. A top-down analysis of a given scenario is always to be preferred to gain a macro to micro perspective, without accidentally omitting pieces of information, important to making a particular decision. Councils located in coastal areas in particular can benefit from using GIS for both human geography and environmental geography issues. Considering both of these aspects together is paramount for the preservation and conservation of a given area. GIS can incorporate both qualitative and quantitative data and capture patterns and trends more readily than any other information system. While this pilot study was cross-sectional in nature (i.e. a snapshot), an ideal study would incorporate a longitudinal view and forecast population growth rates that were sustainable for the area based on Council parameters. The most important outcome of the study was demonstrating the need for Council to quickly adopt GIS into its planning practices. While the cost of acquiring the data sources and spatial boundaries identified throughout this paper would total in excess of one hundred thousand dollars (i.e., for a single user license for the area covered by Kiama Council alone), the investment would have positive long-term implications.

Figure 5 Pinpointing company locations: The MapMarker® Australia product allows for intelligent address matching. In this pilot study, telemarketing business records from Brylar’s Australian on Disc (AOD) product were geocoded to street address locations. Council planners can query individual company records in the GIS or extract data to analyse the various types of businesses that are located in Gerringong. It can also help planners in re-zoning land parcels for re-development based on local business and employment demands.

Figure 5 Pinpointing company locations: The MapMarker® Australia product allows for intelligent address matching. In this pilot study, telemarketing business records from Brylar’s Australian on Disc (AOD) product were geocoded to street address locations. Council planners can query individual company records in the GIS or extract data to analyse the various types of businesses that are located in Gerringong. It can also help planners in re-zoning land parcels for re-development based on local business and employment demands.

References

Birkin, M., Clarke, G., Clarke, M. and Wilson, A. 1996. Intelligent GIS: Location Decisions and Strategic Planning. GeoInformation International, Cambridge.

Castles, I. (ed.) 1993. CDATA91: Data Guide. 1991 Census of Population and Housing. Australian Bureau of Statistics, Canberra.

Drummond, W.J. 1995. Address matching: GIS technology for mapping human activity patterns. Journal of American Planning Association 61: 240-251.

Ecologically Sustainable Design [ESD] (ed.) 2002. The Charrette Report. Kiama Council, New South Wales.

Goss, J. 1995. We know who you are and we know where you live: the instrumentality of geodemographic systems. Economic Geography 71(2): 171-198.

Holloway, G. (ed.) 1998. The Math, Myth & Magic of Name Search and Matching. SearchSoftwareAmerica, Connecticut.

Maguire, D., Goodchild, M., and Rhind, D. 1991. Geographical Information Systems: Principles and Applications. Wiley, New York.

Nelson, P. (ed.) 2003. Preliminary Survey: Community Participation Process, Place-based residential Strategies for the Future Growth of Werri Beach/ Gerringong & Gerroa. Kiama Council, New South Wales.

Schensul, J.J., LeCompte, M.D., Trotter, R.T., Cromley, E.K., and Singer, M. 1999. Mapping Social Networks, and Spatial Data, & Hidden Populations. Sage Publications, London.

Wiggins, D. (ed.) 2003. Final Report: May 2003. Kiama Council Community Participation Process, Place-based Residential Strategies for the Future Growth of Gerringong and Gerroa. Kiama Council, New South Wales.

Suggested Resources for Spatial and Aspatial Data

ABS. 2003. 1353.0 Integrated Regional Data Base (IRDB), Australia. http://www.abs.gov.au/Ausstats/abs%40.nsf/ca79f63026ec2e9cca256886001514d7/b27b00a2b3a79c42ca2568a900143de1!OpenDocument.

ABS. 2003. 1369.0.55.001 Australian Business Register - Counts of ABNs. http://www.abs.gov.au/ausstats/abs@.nsf/0/CCF2C8379B1EC773CA256B87008134D5?Open&Highlight=0,ABR.

ABS. 2003. CadastralPlus — Overview. http://www.mapinfo.com/au/products/Overview.cfm?productid=866.

ABS. 2003. CDATA 2001 – Brochure. http://www.abs.gov.au/websitedbs/D3110124.NSF/24e5997b9bf2ef35ca2567fb00299c59/1bfc550a6d37a700ca256bd600063d37!OpenDocument.

ABS. 2003. Socio-Economic Indexes for Areas 96 (SEIFA). http://www.abs.gov.au/websitedbs/D3110142.NSF/654f973dc0676ad3ca2566ac001ffe93/29ce159bcbb882d3ca2566ad0002229e!OpenDocument.

Data Dependables Data. 2003. Brylar’s Australia on Disc. http://www.australiaondisc.com.au/.

Dun & Bradstreet Australia. 2003. D&B Australian Marketing Lists. http://www.dnb.com/AU/dbproducts/ProdDesc.asp?id=175&ver=481.

MapInfo. 2003. CDATA 2001 - Detailed Base Map — Overview. http://www.mapinfo.com/au/products/Overview.cfm?productid=1675.

MapInfo. 2003. MapInfo Professional® — Overview. http://www.mapinfo.com/au/products/Overview.cfm?productid=1044.

MapInfo. 2003. MapMarker® Australia — Overview. http://www.mapinfo.com/au/products/Overview.cfm?productid=152.

MapInfo. 2003. StreetPro® Australia — Overview. http://www.mapinfo.com/au/products/Overview.cfm?productid=138.

Salmat. 2003. Marketfind. http://www.salmat.com.au/Services/Customer_Contact/CustomerTargeting.html.

Acknowledgements

I would like to thank sales representative Brinda Rabi of MapInfo Australia who supplied free GIS software and associated spatial databases to the Faculty of Informatics at the University of Wollongong for research purposes in 2002. I would also like to thank the University of Wollongong who funded a New Researcher, and Start-up Researcher grant for the Spatial Database National Australia (S-DNA) project to the total value of $7,500 of which this study is a part of. Strategic planner, Peter Nelson, of Kiama Council was also helpful in establishing the scope for this GIS pilot study.

The Auto-ID Trajectory - Publications

During my PhD I was working full-time for Nortel Networks as a senior network and business planner. I did not have much time left over to write papers for conferences or submit to journals. But I did manage to write a number of case studies for a textbook on electronic commerce and as part of my day job present at several global conferences.

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The Auto-ID Trajectory - Chapter Seven: Ten Cases in the Selection and Application of Auto-ID

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