a decision support indices set (de.s.i.s.): a primary ... · “agio oros” is a religious area...

A DEcision Support Indices Set (DE.S.I.S.): a primary quantitative evaluation tool for road network sustainability

G. A. Achilleos1 & A. Tsouchlaraki2 1National Technical University of Athens, Greece 2Technical University of Crete, Greece

Abstract

The main purpose of this research is to build an indices set, which can be embodied within a Decision Support System for road network infrastructure evaluation. Developing the urban transportation networks, it is obvious that the thorough study of the regional transportation networks is essential. What we plan for the urban areas infrastructure should be interrelated with the regional areas infrastructure in order to work in tandem. This indices set (DEcision Support Indices Set – DE.S.I.S.) is based on a certain database, and will adjust according to the data contained within this database. Should someone want to apply the DE.S.I.S. on a different database, the only thing he has to do is to re-calculate the set. The DE.S.I.S. will quantify, classify and compare the spatial “demand” for road networks and the spatial “offer” of the road network, considering mainly the population distribution within the administrative units (in this particular case, the regions). From that comparison, an evaluation of the road network will take place. GIS tools are remarkably useful for this purpose. The study area for the DE.S.I.S application is defined as the continental part of Greece. Concerning all the road network categories that exist, only the high-level ones are examined. Keywords: infrastructure, road network, evaluation, demand, offer, GIS, Decision Support System, index.

1 Introduction

The infrastructure networks are under a continuous improvement, in every society. In Greece, although transportation infrastructure gets more synchronized every day, the low level of road network service is still present in certain regions of the country. Although, the urban transportation systems are thoroughly

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designed to serve the urban population, in some cases the connection to the broader transportation systems is inadequate. There are lots of broad scale construction projects in progress (i.e. Egnatia project, Attiki Odos project, Rio – Antirio Bridge, etc.) and much more in schedule to be done. The mountainous character of Greece in combination with the hundreds of islands that exist, make things more difficult as projects need more time and money to finish. Certainly, a rapid development of the road network cannot be expected but as time passes social and economical conditions change, land uses change and new needs appear. The question of “how well the offered infrastructure of road network covers the demand”, seems that will never stop to exist.

A quantitative evaluation methodology, not only for road networks, but also for all infrastructure categories, has not been developed yet. The large number of factors that have to be considered in addition to the various interactions that exist between them, make the evaluation procedure a very complicated problem [1,2,3]. A few years ago there was a research project in the Section of Geography and Regional Planning of NTUA about infrastructures [2]. Two hundred indices were designed in that research project, as an attempt to describe all possible factors that affect infrastructures. Unfortunately, it was not able to build an evaluation model.

As it concerns the Greek road network, most of the evaluation approaches that exist in Greek bibliography, are limited in a certain Greek area and most of the cases are further more limited in a certain field of study (traffic volumes, accidents, etc) [2]. Someone, can easily find remarks in papers about the quality of the Greek road network but most of them have a descriptive character. Usually criticism is done without using any quantitative method [3,4].

Factors such as population distribution, economical activities, land uses, relief morphology, monuments, interrelations between the country’s regions, national and social security factors etc. certainly affect the development of the road network in a different way, but again, the examination of all these factors in combination, is very difficult considering that each of them depends on many other variables [5,6,7,8,9].

Specialists usually are called, to decide on the policy to be followed and the actions to be taken, as it concerns the sustainable design of the road network infrastructure. Their decision is based on their experience and it is a result of thoughts, taking into account the available data. The complexity of thinking, shows a more sophisticated and resulting way to do so, the Decision Support Systems (DSS) 10, based on a Geographical Information System (GIS) [11,12,13,14].

The DSS, as a set of a user interface software department, a model selection department and a database department, really help the specialists to take their decisions, more safely and more objectively. Their decisions are based on models, doing the hard work for them, providing them with answers to their questions, that can be modified in seconds and the procedure for scenarios building looks like what it is said: “a piece of cake”.

The main purpose of this research is to build an indices set, which can be embodied within a DSS for road network infrastructure evaluation. This indices


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set (DEcision Support Indices Set – DE.S.I.S.), will be based on a certain database and will adjust on the data of this database [15,16]. In case someone wants to apply the DE.S.I.S. on a different database, the only thing he has to do is to re-calculate the set. The DE.S.I.S., will quantify, classify and compare the spatial “demand” for road network and the spatial “offer” of the road network, considering mainly the population distribution within the administrative units (in this certain case, the regions). From that comparison, an evaluation of the road network will take place. GIS tools are remarkably useful for this purpose. The study area for the DE.S.I.S. application, is defined by the continental part of Greece. Concerning all the road network categories that exist, only the high-level ones are examined: High Speed Motorways (HSM), National Highways (NH) and Main Country Road Network (MCRN) (map 1). Second class country road network is not examined, as it is of very local interest and of very low quality, too.

Map 1: Main road network Map 2: The 39 regions of the and main towns. continental Greece.

2 Designing the DSS indices set DE.S.I.S.

The analysis procedure is divided into three parts. Respectively, each part refers to demand analysis, offer analysis and road network evaluation.

2.1 DE.S.I.S. demand analysis

The term “demand” refers to the possible need of a region for high-level road network. Two indices are designed for this purpose considering that demand straightly depends on the population living in a region. These two indices are weighted by the area of each region, in order for results to be comparable (equations 1, 2).

D1 = Population / Area (1)

D2 = Number of Main Towns / Area (2)

The DE.S.I.S. final evaluation index for demand is defined by the addition of the standardized D1 and D2 (equation 3).


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D = D1’ + D2’ (3) where: D = demand index, D1’, D2’ = standardized D1, D2

As it has already be mentioned before, the needs of a region for high-level road network is a function of a broader range of factors such as economy, tourism, interrelations between regions, land uses, transportation means, number of vehicle of every region, number of households of every region etc. In order to simplify the problem, it is accepted that the road network must cover at least the needs of the residents in a region. This leads to the decision rules, saying that, “the more the population, the more the needs” and also “the more the towns, the more the needs”.

2.2 DE.S.I.S. offer analysis

The term “offer” refers to the ability of the existent road network to cover the needs of the residents. Four indices are designed for this purpose, considering that offer depends straightly on the length of the road network that exists in a region. These four indices are also weighted using the area (equations 4, 5, 6, 7).

F1 = Length of HSM in a region / Area (4)

F2 = Length of NH in a region / Area (5)

F3 = Length of MCRN in a region / Area (6)

F4 = Length of all roads in the distance zone of 3km from the towns / area (7)

The final DE.S.I.S. offer index is calculated by the addition of the standardized Fi (equation 8).

F = F1’ + F2’ + F3’ + F4’ (8) where: F = demand index, Fi’ = standardized Fi

The three categories of road network are examined separately because each of them corresponds to a different quality of road construction (F1, F2, F3). HSM are wider and better designed than NH and NH are wider and better designed than MCR. The index F4 is an approach to describe the spatial distribution of the road network. Here it is accepted that, “the more length of road network within the near zone of the main towns (3 km), the more percentage of the demand is covered by this road network”.

2.3 Evaluation of road network: The DSS indices set DE.S.I.S.

The evaluation of the road network, using the DE.S.I.S. indices set, presupposes that the results of demand and offer analysis are comparable. For this reason, indices D and F are standardized and the difference between them gives the DE.S.I.S. final index “V”, according to which the comparison and evaluation can take place.


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V = D’ – F’ (9) where: D’, F’ = standardized D, F

This indices set (DE.S.I.S.), obviously is a function of the database that is used. If someone wants to recalculate the DE.S.I.S. in another country, or in another time in the same country, then the results will not be the same, due to the fact, that these indices are database related. Their estimation is not absolute, but it is relative to the data that are used for.

3 Road network demand and offer analysis using DE.S.I.S.

In each part of the analysis, indices are designed and applied on the 36 continental Greek regions (map 2). It must be mentioned here that the regions of Attiki, Thessaloniki and Agio Oros are not included within the research although they belong to the continental part of Greece, due to the extreme values they present in the analysis. These regions are special cases. Attiki and Thessaloniki are very populated areas as they consist the two main capitals of Greece and “Agio Oros” is a religious area where the development of road network is prohibited. These regions are light colored in the following classification maps and are marked with the codes 37, 38, 39 respectively (map 2).

3.1 Demand analysis

Data and results, concerning the application of DE.S.I.S. for Demand analysis, are presented in Tables 1 and 2 (tables 1, 2).

The small value of the coefficient of correlation between D1 and D2 (rxy = 0.317) shows that these two indices are almost independent, although someone would expect the opposite. This is easily explained, as there are towns more populated and towns less populated, and therefore, “more population does not necessary means more towns”.

The 36 regions are classified in 3 classes, according to the demand index “D”, using k-means cluster analysis (map 3). Eight regions belong to the first class having small demand values, nineteen regions to the second class having medium demand values and also nine regions to the third class having large demand values.

3.2 Offer analysis

The final results for the offer analysis, using the DE.S.I.S., are presented in Tables 1 and 2 (tables 1, 2).

It is shown from Table 2, that there is a differentiation between regions. There are regions depended mostly on the first category of road network (Korinthias, Pierias, Ilias) and regions depended mostly on the third category (Etoloakarnanias, Evritanias, Evias etc). Indices F1, F2, F3 are almost independent and it can be concluded that the existence of a certain road category does not necessary presupposes the existence of the others.


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Table 1: Demand and offer analysis data.

code Region Populat Area Towns HSM NH MCRN N3km 1. Etoloakarnanias 228.180 5.514 5 0 121 285 33 2. Viotias 134.108 3.124 3 54 101 0 12 3. Evias 208.408 3.581 7 0 4 231 33 4. Evritanias 24.307 2.06 2 0 0 1 0 5. Fthiotidas 171.274 4.481 5 132 116 0 26 6. Fokidas 44.183 2.146 3 0 95 58 11 7. Argolidas 97.636 2.243 3 30 95 15 15 8. Arcadias 105.309 4.449 5 20 153 144 31 9. Ahaias 300.078 3.177 5 93 0 136 15 10. Ilias 179.429 2.651 4 63 53 41 8 11. Korinthias 141.823 2.275 4 87 28 31 9 12. Lakonias 95.696 4.024 7 0 112 165 38 13. Messinias 166.964 3.045 7 0 146 105 30 14. Artas 78.719 1.55 1 0 20 35 5 15. Thesprotias 44.188 1.642 4 0 58 0 9 16. Ioanninon 158.193 5.048 4 0 180 39 16 17. Prevezas 58.628 0.978 1 0 83 9 7 18. Karditsas 126.854 2.599 3 0 46 24 7 19. Larissas 270.612 5.565 5 72 131 85 22 20. Magnisias 198.434 2.547 2 55 48 53 7 21. Trikalon 138.946 3.35 2 0 77 102 10 22. Grevenon 36.796 2.332 1 0 45 0 5 23. Dramas 96.554 3.44 3 0 32 124 12 24. Imathias 139.934 1.733 3 42 94 0 8 25. Kavalas 135.937 1.584 3 0 134 64 13 26. Kastorias 52.685 1.693 2 0 14 68 12 27. Kilkis 81.710 2.643 2 38 0 96 5 28. Kozanis 150.386 3.657 4 0 156 52 19 29. Pellas 138.761 2.481 3 0 79 50 16 30. Pierias 116.763 1.816 3 63 0 25 10 31. Serron 192.828 3.872 4 0 138 168 28 32. Florinas 53.147 1.926 2 0 50 39 10 33. Halkidikis 93.653 2.809 4 0 60 248 18 34. Evrou 143.752 3.962 6 0 172 40 29 35. Xanthis 91.063 1.697 2 0 35 76 14 36. Rodopis 103.190 2.44 2 0 81 19 13

There is a small correlation between indices F3 and F4 (rxy = 0.456). This

indicates that, the third category of road network mostly exists within the near zone, of the main towns.

The 36 regions are classified in 3 classes according to the final offer index “F”, using k-means cluster analysis (map 4). There are five regions in the first class having very small offer values, sixteen regions in the second class having medium offer values and finally fifteen regions in the third class having large offer values.


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Table 2: Descriptive measures of demand and offer indices.

INDEX D1 D2 D F1 F2 F3 F4 F Mean 45.722 1.245 0.000 5.290 7.330 23.920 27.570 0.000

Std Dev 19.769 0.469 1.623 2.300 11.890 20.310 20.210 1.950 Min 11.800 0.429 -3.255 0.000 0.000 0.000 0.000 -5.433 Max 94.453 2.436 3.412 9.852 38.242 88.288 84.867 4.286

Map 3: Demand classification Map 4: Offer classification map. map.

4 Evaluation of road network

The road network evaluation results, after the application of the DE.S.I.S. indices set, can be seen in Table 3 (table 3).

The results are classified once more, in three categories according to DE.S.I.S. index V (map 5). There are eight regions in the first class having more offer than demand, eighteen regions in the second class having their offer size, considerably equal to their demand size and ten regions in the third class having less offer than demand (table 3).

These results, in combination with the large correlation between D and F (rxy = 0.644), can lead to the conclusion that according to the factors examined, the way that the road network has been developed in Greece, corresponds satisfactory to the population’s demand.

Some further parameters that could be used to determine the criterion of DEMAND, are the quality of service, the coverage of the economic, social, interregional activities. Such an approach can be the subject of an inter-scientific analysis group.

5 Conclusions: general remarks

Concerning the infrastructure evaluation [2,3,5], there is a serious difficulty for finding measuring techniques, simple or complicated, in order to have an objective evaluation. The existence of such techniques surely would have been a serious tool for designing the development and the regional policy of that country.


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Table 3: Evaluation results.

code D’ F’ V Demand Classes

Offer Classes

Evaluation Classes

1. -0.58 0.399 -0.978 medium (2) high (3) more offer (1) 2. -0.461 -0.377 -0.084 medium (2) medium (2) equal (2) 3. 1.3214 0.915 0.406 high (3) high (3) equal (2) 4. -1.417 -2.791 1.374 low (1) low (1) more demand (3) 5. -0.403 0.423 -0.827 medium (2) high (3) more offer (1) 6. -0.582 0.150 -0.733 medium (2) medium (2) more offer (1) 7. 0.0532 0.514 -0.461 medium (2) high (3) equal (2) 8. -0.846 0.640 -1.487 low (1) high (3) more offer (1) 9. 1.9509 0.599 1.352 high (3) high (3) more demand (3) 10. 1.0312 -0.203 1.234 high (3) medium (2) more demand (3) 11. 1.1922 0.390 0.802 high (3) high (3) more demand (3) 12. -0.034 1.051 -1.085 medium (2) high (3) more offer (1) 13. 1.6685 1.488 0.180 high (3) high (3) equal (2) 14. -0.63 -1.184 0.554 medium (2) low (1) more demand (3) 15. 0.9785 -0.681 1.660 high (3) medium (2) more demand (3) 16. -1.043 -0.994 -0.049 low (1) low (1) equal (2) 17. 0.151 1.185 -1.034 medium (2) high (3) more offer (1) 18. -0.023 -1.518 1.495 medium (2) low (1) more demand (3) 19. -0.365 -0.377 0.012 medium (2) medium (2) equal (2) 20. 0.3992 -0.251 0.650 medium (2) medium (2) more demand (3) 21. -0.984 -0.782 -0.201 low (1) medium (2) equal (2) 22. -2.006 -1.834 -0.171 low (1) low (1) equal (2) 23. -1.04 -0.876 -0.164 low (1) medium (2) equal (2) 24. 1.7303 0.654 1.077 high (3) high (3) more demand (3) 25. 2.1023 2.202 -0.100 high (3) high (3) equal (2) 26. -0.539 0.006 -0.545 medium (2) medium (2) equal (2) 27. -1.103 -0.841 -0.262 low (1) medium (2) equal (2) 28. -0.342 -0.199 -0.143 medium (2) medium (2) equal (2) 29. 0.2711 -0.044 0.315 medium (2) medium (2) equal (2) 30. 1.1136 0.274 0.840 high (3) medium (2) more demand (3) 31. -0.151 0.815 -0.967 medium (2) high (3) more offer (1) 32. -0.836 -0.472 -0.365 low (1) medium (2) equal (2) 33. -0.151 1.404 -1.555 medium (2) high (3) more offer (1) 34. 0.0597 0.190 -0.131 medium (2) medium (2) equal (2) 35. 0.1602 0.697 -0.536 medium (2) high (3) equal (2) 36. -0.666 -0.573 -0.093 medium (2) medium (2) equal (2)

The strategies and the planning that will be followed, are completely

dependent maneuvers with concepts such as OFFER, LACK, DIFFICULTY, FORECASTING, EXTRAPOLATION, concepts that attempt to describe the broader meaning of NEED. The development of the Informatics science, in combination with the tremendous development of technology, gives the researchers and the specialist (decision makers), the push to try and find ways and methodologies, wide approved, which will provide the wanted estimation of a parameter / variable, through the use of computers.


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Map 5: Final classification map. There is even a greater need, referring to the infrastructure of a country, as

the infrastructure is a concept closely dependent and related to other social concepts such as the society itself, civilization, social needs, social welfare. These concepts are very sensitive and fragile in situations of non-equalities, non-equal distributions of goods and offers, non-symmetrical development etc. History has many examples to show (urbanization, immigration, social revolutions).

This certain research, is part of a broader research which attempts to approach the concept of infrastructure, to analyze and evaluate it and attempts to the development of an indices set / model / mechanism to achieve this evaluation. This indices set / model / mechanism will enclose a series of indices (simples or complicated), some models for measuring, extrapolating, forecasting, evaluating, some models of dynamical simulation, some methods and techniques, and all these direct connected to a spatial database, combined within an integrated GIS and a DSS. It will play the role of an Integrated Decision Support System for the promotion of the regional planning and development of the country.

As a first result of the research, dissimilarities seem to exist in Greece, concerning the distribution of the infrastructures. It is still too early to name these dissimilarities as non-equal distribution of infrastructure, or further on, to name them as distinctions. There is a great need for enriching the database with parameters, in order for the research to cover the range of those parameters, influencing and determining the issues of infrastructure of road network and in general the transportation infrastructure.

Such a database, enriched in periodically determined times, could be used for forecasting the DEMAND, the OFFERING difficulties, for “what-if” scenarios application and in general, placed under a DSS environment within a GIS, could compose a powerful tool for Decision Making and Regional Analysis & Planning.

References

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Elladas pros ton 21o aiwna, Eyrwpaiki Etaireia Perifereiakis Episthmhs – Ellhniko Tmhma, Khfisia, 1996 (G.L. - Greek language).

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[7] P. Nijkamp, R. Maggi, I. Masser, Missing Networks in Europe, A Study Prepared by a Team from the European Science Foundation (ESF) Network on European Communications and Transport Activity Research (NECTAR) for the Round Table of European Industrialists, September 1990.

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