using gis for regional t

8/2/2019 Using GIS for Regional t

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U S I N G G I S F O R R E G I O N A L T R A N S P O R T A T I O N P L A N N I N G I NS O U T H E R N C A L I F O R N I AJohn S utton, Ph.D.

Director, Transportation PlanningGIS/Trans, Ltd.

1. INTRODUCTIONI.I Regiona l Plann ing in Southern CaliforniaSouthe m C al i fornia is one of the largest urbanized regions of the world and ex tendsover 39171 square miles with a total population of over 15 mill ion. The Sout hernCal i fornia Associat ion of Governments (SCAG) is the regional transportat ionplann ing agency for 188 cities ranging in size from the City of Los Angele s (3.5mill ion population) to small communities with fewer than 50,000 people. These aregrouped into 11 subregions, 6 counties (Imperial , Los Angeles, Orange, Riverside,San Bemardino and Ventura) , and 5 Transportat ion Commissions, such as OrangeCoun ty Transportation Authority. The reg ion is i l lustrated in Figure 1.The SCAG region faces some o f the worlds most di ff icult t ransportat ion problems,including poo r air quali ty l inked to vehicle emissions, increasing traffic congestio n onthe freeways, low transit uti l ization and low density urban sprawl. Transportationperformance i s measured by Level Of Service (LOS) and vehicle mi les traveled(VMT). The former provides a measure of highway congestion ranging from LOS A,no congestion, to LOS F w hich indicates severe congestion wi th the highw ayoperating at >90% capacity. The 1993 Regional Com prehe nsive Plan (RCP)estimated that in 1990 m ore than 50% of the freeways were operating at LOS E & Fduring the peak hours and that the region was fail ing to meet federal ly mandated ai rquali ty goals. The VM T statistics measu re the increasing distances that auto users arecom mutin g to work - a large part o f the increase in vehicle emissions is attributed notto increasing auto use but to longer distance commuting. The regional plan aims toreduce both VM T and LOS to more acceptable levels by the year 2010.The strategy adopted to accompl ishes this has several elements but two priori typolicies. To encourage travel choice an expansion of regional transit services, bus,regional rai l and metro has b een given top priority; fol lowed by the dev elopment ofHigh Occupancy Veh icle (HOV) o r carpool lanes. The plan cal l s for the designationof 365 mi les of HOV lanes on freeways by 2010 (there are 170 mi les of carpool lanesat present wi th another 50 mi les under construction). HOV or carpool lanes arereserved for autos wi th two or more occupants. The HOV pol icy aims to encourageear pool ing and thereby reduce VMT. Both pol icies, i f successful , would increaseaverage vehicle occupancy, reduce vehicle emissions and ease traff ic congestion.Other pol icies, such as developing low energy vehicles (LEV) and experimenting wi throad pricing, play a suppo rting role. The region expects to spend ove r $50 bil l ion on


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t ransportat ion between 1990 and 2010, wi th the majori ty o f expendi tures going ontransit operating subsidies ($23 bil l ion) follow ed by transit infrastructure ($13 bil l ion)and HOV lanes ($12 bil l ion). New highway infrastructure and improvements toexisting freeways are al located $20 bil l ion but the percentage increase in freewaycapacity is relatively small . Southern California has accepted that there is no way tobui ld a way out of the highway capaci ty problem (too expensive and tooenvironmentally damaging) and instead has adopted al ternate policies of trafficconstraint and travel choice.I t should be noted that whi le the RCP recomm ends these policies, there i s very l i t tledevelopment control to ensure that these plans wi l l be successful . SCAG has noenforcement powers as such and is primari ly a planning and m oni toring agency thatadvises the subregions, counties and cities. The only stick that SCA G is able to wie ldis that unless federal air quali ty mandates and other regulations are met, the regionwill not receive federal aid under the Intermodal Surface Transportation EfficiencyAct, 1991 (ISTEA). This Act mandates Metropoli tan Planning Organizations l ikeSCAG to produce an annual Regional Transportation Improvement Program. Fai lureto prod uce this or mee t targets threatens funding.1.2 The Role of GIS in Regional PlanningAs the regional planning agency, SCAG col lects a large amount of data whichhistorically has be en stored in a variety of databases. These data include the a gency'sdigi tal base map and street network, the transportat ion model networks, US Censusdemographic data including work tr ip origins and destinations by purpose by censustract, employ men t datasets, and 25 land use categories. The agency uti l izes a num berof planning and transportation models to forecast land-use transportat ion dem ands andpredict regional shi fts in the jobs-housing balance. The use of these mo dels and thedata comp ilation efforts required has led to a numb er of "data islands" develop ing inthe agency , with the different teams and sections fai ling to share data and inform ationtechnology. In 1990, the agency purchased a Geographic Information System toprovide digital map ping and to centralize the spatial datasets. In 1994 i t was realizedthat this had only been partial ly successful . Consultant GIS/Trans Ltd. was hired toreview the agency's needs and develop an enterprise approach toward the integrationof the land use and transportat ion data and the GIS. The "Long-Range StrategicWor kplan for Transportation-Related GIS" was delivered in the fourth quarter of1994 and has guided subsequent GIS developments. Key aspects of theimplem entation plan include:1 Referencing the transportat ion and planning data in the same base map2 Centralizing the data in one database manageme nt system3 Desig ning the database to mee t user application needs4 Deve loping Graphic User Interfaces to al low easier access to the data andapplications by non-tech nical users5 Imple ment ing a cl ient-server compu ting architecture - UN IX worksta tion fi le

server wi th workstat ion and PC cl ients6 Training of staff in the interfaces, applications and GIS data man agem ent


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An early task in the workplan was to develop the SCAG Geographic Data In terface(SGDI) - i tem 4 on the l i s t above. The SGDI provides a user- fr iendly in terface toal low the p lann ers to access , query , d isp lay , analyze and p lo t the t ransporta t ion andplannin g data a t d i fferent levels of representa t ion , including census b lock and t rac t ,t raff ic analysis zones (T AZs), c i t ies, subregional s ta t is t ica l area, co unty and the wh olereg ion . An example o f t he SGDI i s s hown in F igu re 2. The fo l lowing sec t ions focuson the in terface and in tegra t ing the t ransporta t ion data in the base map used forregis ter ing the o ther datasets ( i tem 1 above).

2. U S I N G G I S I N T R A N S P O R T A T I O N N E T W O R K A N A L Y SI S2.1 GIS Network Data Representat ion and GIS-T Extens ionsWh ile there i s a growin g level of u t il iza t ion of GIS in t ransporta t ion (GIS-T), acom prehen sive GIS-T req ui res that a l l network representa t ions of t ransporta t ion datacan be cross- referenced to a s ingle base map. This requi rement i s rare ly met int ransporta t ion agencies where d i fferent appl ica t ions adopt d i fferent scales andmeth ods for t ransporta t ion data representa t ion . An examp le i s il lust ra ted in F igure 3 .In t h i s case , taken f rom Orange Coun ty , t he SC AG t ranspor ta t ion mode l ne twork i scoded as an abst rac t representa t ion of anode, bnode pai rs jo ined by pai rs of l inks(anode-bnode, bnode-anode) that overlay each o ther . The model network i s coded tope r fo rm ne twork a ss ignmen t s and can rep resen t ne twork connec t iv i ty i n any wayuncons t ra ined by geographical considera tions. For examp le , in F igure 3 the H OVlanes are represented by l ines that are separa te from the mai n freeway and conne ctedto the freeway in tersect ions by dummy l inks. In rea l i ty , the HOV lanes are reservedlanes on the freeway next to the median . The actual s t reets are a lso depic ted in themap which show the extent of the d i fferences. In th is case the d i fferences are not a l lt ha t g rea t bu t i n m ore m oun ta inous te r ra in such a s i n no r th Los Ange les o r V en tu racount ies the model network cuts through mounta ins and are d i ff icul t to t race orassocia te with actual arterials.The t ransporta t ion model network i s an ext reme example of the spat ia l d i fferenceswi th underly ing geography. However, for t ransporta t ion p lanning purposes thedep ic tion o f t he mode l ne twork on rea l- s tree ts has a numb er o f mer i t s , d i scussedbe low, and i s be ing reques t ed by more agenc ies who have begun to use GIS fo rt ransporta t ion p lanning (Sut ton , 1995). GIS were not designed for t ransporta t ionnetwork analyse s but there are a num ber of ways to adapt the GIS capabi li t ies fort ransporta t ion purpos es (Vondero he e t a l, 1993). A n um ber of extensio ns to GIS arenow being provided by v endors to enhance the GIS-T capabi l it ies. Speci f ica l ly :

Line ar Referenc ing - the abi l i ty to locate fea tures a long a h ighway or o thernetwor k wi th reference to a kno wn star t poin t and/or end point .Dynam ic Segm en ta t ion - the abi l i ty to a t t r ibute networks independent ly of thennderly ing topology, for example where a fea ture begins mid-arc and e nds mid -arcConflat ion - the merging or fusion of a source network a t t r ibutes wi th a targetne twork geomet ry


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Linear referencing a l lows features to be cross- referenced to mi leposts /k i lom eterpostsor o ther geographic cont ro l poin ts . So when the pol ice accident report records theaccident . . . "On Highway 10, I00 meters af ter k i lometerpost 291" . . i t can beautomat ica l ly geocoded wi thout knowing the ac tual geographic coordinates or o therl inear a t t r ibutes (such as s t reet name or in tersection). Dynam ic seg mentat io n hasproven to be especia l ly useful in many network representa t ion s i tuat ions, inc ludingt ransporta t ion model netw ork in tegra tion . Dyna mic seg menta t ion a l lows an ar t if ic ia l" route" to be defined as an overlay on the network ( th is route can be a rea l -worldroute, s uch as 1-10 or a transit route, but is coded as a separ ate feature). The G IS routeis a "v i r tual network" that has no topology a nd can therefore be code d mu ch mor eflexibly than a l ink-node network. At t r ibutes can be l inearly referenced to s tar t or endanywh ere a long the route independent ly of the underly ing network. In th is schem a,l inear referencing i s mandated , o therwise the locat ion of a t t r ibutes a long the routewou ld not be cros s- referenced wi th the underly ing network and therefore could not bemapp ed. Th us, dyn amic segm entat ion and l inear referencing go together .Network confla t ion a lso benefi t s from l inear referencing. For example , where twonetworks wi th d i fferent geometries have the sa me st reet nam es, the spat ia l ly imprecisegeometry can be corrected by a t t r ibute matching of l inear fea tures . Where l ineara t t r ibutes are absent , spat ia l matching o f nodes i s as sis ted by cal ibra tion o f l inearmea sure men ts a long the network. Al l three techniques are u t i l ized by SC AG as part ofthe data in tegra t ion in GIS for t ransporta t ion p lanning process .2 .2 N e t w o r k C o n f l a t i o n o f t h e T r a n s p o r t a t i o n M o d e l N e t w o r k a n d

S treet C en ter l in e F i l eThis sect ion focuses on the in tegra t ion (confla t ion) of the t ransporta t ion modelnetwo rks (h igh way and t ransit networks) and the s t reet centerl ine f i le in the GIS. Thenetwork in tegra t ion involves a numbe r of the data convers ion s teps. These aredescribed below. Once the networks are in tegra t ion in the GIS they can be used inma ny t ransporta t ion p lanning exerc ises , inc luding evaluat ing local t raff ic imp acts o fp lanned developments , a i r qual i ty and o ther envi ronmental effec ts . The d isplay ofmodel resul t s on the ac tual s t reets i s a powerful medium for conveying t raff icfo recas t s, and makes t he re su lt s more m ean ing fu l fo r pol i cy makers and non-technical audiences.The w ork f iow o f t he p roj ec t i s summar i zed in F igu re 4 . The SCA G t ranspor ta t ionmode l i s based on TRANP LAN, the mos t w ide ly used t ranspo r t a t i on demandfo recas t ing mode l i n t he USA. The agency wi shed to i n t eg rat e t he mode l ne tworkwith i t s base map (Tho mas Brothers Maps Inc . ) for a num ber of reasons. F irs t ly , asment ioned above, for mapping and publ ic presenta t ion purposes having the t raff icforecasts d isp layed on actual s t reets makes more sense for non- technical audiences,whether pol i t ic ians or lay people . Second, in tegra t ing the t ransporta t ion model datawi th o ther network data and p lanning data would enhance considerably the types ofspat ia l da ta analyses that could be performed in the GIS. Third ly , on ce confia ted , themode l ne tworks can be ed i t ed and managed in t he GIS env i ronmen t by the mode le rs.Mod i fy ing the mode l ne tworks i s a l so m ade eas ie r because t he p l anners can v i sua l i ze


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the s t reets to be u sed in the mode l network. Fourth ly , sharing data wi th o ther agenciesin the region would bene fi t f rom the one uni form data envi ronm ent . Other agencies inthe region a lso s tandardize on Thomas Brothers Maps s t reet centerl ine f i les andassocia ted data , and the majori ty a lso u t i lize ARC/IN FO GIS a nd ArcView software ,so once the data i s spat ia l ly referenced in the s tandard GIS o n the s tandard base m ap,data sha ring i s made s igni f icant ly easier .F igure 4 shows that the network in tegra t ion process proceeded through a number ofsteps. F i rs t ly , the TRANPLAN model network and a t t r ibute data had to be convertedin to A RC/ IN FO fo rma t. Th i s w as accompl i shed us ing spec ia l convers ion p rog rams .The mode l n e tworks were t hen eon f la t ed us ing the GIS /Trans GIS/T-Conflate oolbox,whi ch conta ins prog rams to perform the a t tr ibute and spat ia l confla t ion automat ica l ly(Brown et a l , 1995). Tradi tional ly , da ta confla t ion has been a labor in tensive and t imecon sum ing process , requi r ing a lo t of qual i ty cont rol . Th e GIS/T-Conflate toolsau tomate be tween 70% and 90% o f t he ma tch ing p rocess w i th spec i al ma tch ingalgori thms. The con fla t ion of the base year mod el network (33 ,776 l inks, 12 ,122nodes) to the GIS s t reets (118,000 ares , 87 ,000 nodes) was performed in less than twomonths. The four networks that were confla ted (see Table 1) were completed inapproxima tely s ix months. Subsequent ly , the modelers have confia ted f ive addi t ionalnetwo rks in the GIS ( these were m odifica t ions of the orig inal networks) in less thanone mon th .Fo l lowing the con f l at i on o f t he h ighways and the t rans i t ne tworks , t he work p rog ramproceeded to pro gram specia l network edi t ing tools in the GIS. Th ese are used to edi tthe dyna mic segm entat ion routes that are created by the model eo nfla t ion process . I twas decided to proceed in th is way as routes provide a robust metho d to represent themodel l inks. Thus, one model l ink equals one route in the GIS. The many- to-onerela t ionship between the GIS s t reets and the model l ink i s managed by the GISdynamical ly . There are severa l addi t ional advantages to th is method. F i rs t ly , theedi t ing of the routes i s preferable to edi t ing the underly ing base map (which i s s ta t icbetween map updates) . Adding, dele t ing , modifying routes/model l inks i saccompl i shed us ing the cu rso r and the map d i sp l ay : fo r example when add ing a newl ink to the mod el , the u ser s im ply poin ts to the m ap st reet (s) requi red and the toolsautomat ica l ly convert the s t reet (s) to a route and add i t to the route-system . Secondly ,the routes are format ted as a s t ra ight forward table that can be easi ly read by theTRANPLAN model (recal l tha t the GIS routes are non- topological so there are noissues of spat ia l in tegri ty to handle) . Thi rd ly , the route a l lows a t t r ibute data to bel inearly referenced w hich i s a great help for represent ing t ransi t l ines . Transi t l ines arean addi t ional netwo rk fea ture that l ie on top o f t ransi t routes in the t ransporta t ionmodel . D epic t ing these as l inear fea tures (or linear "events") in the GIS me ans that theroute tables and associa ted t ransi t l ine tables can be managed automat ica l ly by thedynamic segmen ta t ion p rog rams . Trans i t li nes can be ed i ted j u s t a s eas i ly a s h ig hwayfeatures and cross- referenced to the underly ing s t reets.Hav ing accompl i shed the ne twork in teg ra tion in t he GIS , t he f i na l ta sk was t o m akethe resul t s accessib le to a wide ran ge of users in the agency. This was acc ompl is hedus ing ArcView as t he GUI fo r c rea ting the SGDI. The SGDI a l lows use rs t o accessthe da t a t h rough pu l l - down menus and o the r Windows l i ke func t ions . The SGDI


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provides a user- fr iendly envi ronmen t for perform ing data query , analysis and p lo t t ingfunct ions. The SGDI is being insta l led on users desk- tops and l inked to a h ighperforming IBM RISC worksta t ion f i leserver . The GIS database to ta ls nearly 20gigabytes of spat ia l and a t t r ibute data , so repl ica t ing th is on the PC is not onlydupl ica t ive but impract icable g iven current PC technology.As Figure 4 i l lust ra tes , the GIS-TRANPLAN integra t ion i s not a one-way but a two-way p rocess . The GIS manages t he da t abase and pe r fo rms ed i t i ng and mapp ingfunc t ions wh i l e TRA NP LA N does wha t i t does bes t , wh ich i s to pe r fo rm the ne tworkass ignmen t and o the r mode l ing func t ions . The p rocess means t ha t t he ne tworks can bebu i l t e i the r in t he GIS o r i n T RA NP L AN and too ls a re ava i lab l e t o man age wh icheverprocess i s preferred . H owever, i t i s preferable once the network s have be en c onfla tedto edi t these in the GIS o therwise the networks have to be reconfla ted .F igu re 5 shows the ease by wh ich da t a l aye rs o r t hemes can be d i sp l ayed in t hein terface . I t shows the confla ted model networks correct ly fo l lowing the s t reets andcrossing the correct land uses . Previous a t tempts to analyses spat ia l da ta have fa i leddue to the m is-speci f ica t ion of the data in geographic space. The c omplet ion o f thenetwork in tegra t ion wi th the o ther t ransporta t ion and p lanning data has been widelywelcomed by SCAG and o the r agenc ies i n t he reg ion . These in t end to u se t heconfla t ion tools and in tegra ted mode l networks in thei r own pla nning projects .

3 C O N C L U S I O N : B E N E F I T S A N D I S S U ES

The use o f GIS in SC AG i s gene ra lly rega rded a s be ing ve ry success fu l, bo th i n t e rmsof organiz ing the database for mapping and l inking the t ransporta t ion modelsdynam ical ly to the GIS. Th e GIS is p laying a const ruct ive ro le in regionalt ransporta t ion p lanning, help ing the p lanners to analyze the impact of d i fferentpol ic ies, and p lo t t ing the resul t s of t raff ic forecasts on rea l s t reet maps . Issues thatarose in the project which requi re further research and developm ent , and wh ich poin tto the need for advances in GIS technology and GIS-T techniques, inc lude thefol lowing:1._Data conversion between GIS and transportation models - a l though the convers ionbetwe en the two environ ments was successfu l ly achieved, the convers ion re l ies uponthe model being able to read the GIS data . A specia l API (Appl ica t ion ProgramInterface) had to be wri t ten by the model developers - Urb an Analysis Group - toenable the mod el to correct ly read the route tables . The rou te tables do not conta in an yspat ia l da ta , suc h as shape poin ts . Even so , a less on to be learn t i s tha t in design ing theAPI the abi l i ty to read data from a GIS database such as INFO or Oracle should beconsidered e arly on in the des ign process .One q uest ion that has been ask ed of the project approach i s wh y i t was not considereddeve lop ing the mode l ne twork in a GIS su ch a s TransCAD, wh ich p rov ides mod e l ingcapabi li t ies . T his opt ion was considered a t the outse t of the project . Whi let ransporta t ion network mode l ing a lgori thms have been developed in GIS, including inTransCAD and ARC/ INFO ( Lewis e t a l , 1992) t hese have no t a lways been


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successful , especia l ly on large networks. A second considera t ion was the s ize of thedatasets and the c l ien t - server archi tec ture configura t ion which requi res a morepowerful database engine and f i leserver performance than i s current ly avai lable on aPC GIS p la t form. Further , SCA G wis hed to remain wi th the t ransporta t ion model thatthey had developed and d id not wish to recode i t in another package. Even i fTransCAD and i t s m ode l ing t oo l s had been used , t he ne tworks wou ld s t i l l haveneeded confla t ing and TransCAD has no tools for performing th is a t th is t ime. Whi lecoding t ransporta t ion model networks remains a v iable opt ion for some appl ica t ions,there i s a larger nee d to l ink GIS to o ther t ransporta tion software .2 . R o u t e - s y s t e m s d a t a m o d e l - The rou t e - sys t em s p roved t o be a robus t m e thod fo rspec i fy ing t he h ighw ay and t rans it da ta . However , dynam ic segm en ta t i on invo lves acons ide rab l e am oun t o f ove rhead in m anag ing t he re l a t i onsh ip be tween the rou t etables and the underly ing arc a t t r ibute tables . This i s not a problem when edi t ingindiv idual routes , but re- indexing over 33 ,000 routes fo l lowing a mini -confia t ion of am od i f i ed ve rs ion o f t he m ode l ne twork t akes seve ra l hou rs t o com pu te even on apowerful worksta t ion . The computer processing i s in tensive because of the need forthe GIS to m ainta in data in tegrity and topology. The dyn amic seg menta t ion datamodel was not designed to handle these many routes . I t i s possib le to speed-up theda t a p rocess ing by p ro g ram m ing o r pe r fo rm ba t ch runs bu t t hese ex t ens ions are no tideal and not fu l ly supported by the core data model , so the user has to in tervene inthe process .3 . N e t w o r k d i r e c t i o n a li t y a n d s h a p e - GIS networks are coded as two-way l inks incont rast to model networks that are dupl ica t ive one-way l inks. The routes havedi rect ionali ty bui l t in thro ugh l inear referencing , but i f GIS arcs had d i rec t ional ity l ikemod el networks (and the tools to mana ge the topology) the mod el network in tegra t ionand d i sp l ay o f re su l t s cou ld be accom pl i shed by o the r m e thods o the r t han hav ing t ogenera te routes u t i l iz ing dynamic segmenta t ion . Likewise , i f t ransporta t ion modelscould incorporate shape poin ts , then a many- to-one correspondence could be ach ievedby d i rec t confla t ion of the corresponding networks. Transporta t ion model developershave sho wn re luctance to incorporate geographic coordinates or o ther spat ial fea turesin to t he i r m ode l ing pa rad igm . The Urba n Ana lys i s Group a re one o f t he f i rs t m ode ldevelopers to recognize the potent ia l of GIS in t ransporta t ion model ing .Despi te some problems in opt imizing the data conversion , the pro ject i s judged tohave brought substant ia l benefi t s to the agency. The to ta l cost to the agency of theGIS development effort ( including cont ractors as wel l as hardware and softwarepurcha ses) i s es t imated a t over $500,000. This est ima te does not include the GIS s taffem ployed by t he agency t o m anage t he da t a and t he GIS p rog ram . GIS requ i rescom prehens ive de s ign and im p lem en ta t i on p l ann ing . Mos t success fu l GIS a re m u l t i -year effort s tha t evolve wi th experience and increased knowledge. The technology i sa lso advancing and becoming more user- fr iendly . GIS i s an excel len t toolbox foradding valu e to the p lann ing process . The benefi t s are d i ff icul t to quant i fy but includereduced costs for mapping , better database design and eff ic iencies in data processing ,bet ter product iv i ty amo ng sta ff who a lso benefi t f rom being able to perfor m dataanalyse s that were a l l but im possib le before the GIS arr ived . GIS i s a su bstant ia l


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investment that requires comm itment and vision. The b enefi t s can accrue quickly buta long term view is needed to see the investment ful ly pay-off .One final note. The success of the GIS dev elopment program in SCAG has led to theextension of GIS data sharing on the Internet. The SCAG Access project i s instal lingArc View and the SGDI datasets in all the cit ies in the region, with special interfacesto allow u sers to dial into the cit ies and get access to plannin g and transpo rtation data.The aim is to take the data sharing concep t betw een cit ies one-stage further - plannersno longer have to request data, they just dial up and ext ract what they need. Al l oneneeds i s a copy of ArcView and the Access password. At this t ime the project i sl imited to cit ies but potentially in the future anyone with the fight software couldaccess the l ibraries o f data and dow nload them.

A C K N O W L E D G M E N TThe examples ci ted in the paper come from the GIS network - mode l integrat ionproject sponsored by the Southern Cal i fornia Associat ion of Governments, LosAngeles.

RE FERENCE S

Brow n, J. , Rao, A., and J Baran. (1995) Autom ated GIS Conflation: Coverage Upda teProblems and Solut ions, Proceedings o f the 199 5 Geographic Information Systemsfo r Transportation Symposium (GIS-T),AASH TO, Washington, D.C.Lewis, S. and Bailey, M. (1992) Creating a Municipal GIS for Transportation,Transportation Research Record, No. 1364, Transportation Research Board,Washington D.C.Sutton, J.C. (1995) The Role of GIS in Regional Transportation Planning,Proceedings o f the Fifth Transportation Planning Methods Applications Conference,Vol. II, Transportation Research Board, Washin gton D.C.Von deroh e, A.P., Travis, L. , Smith, R.L., and Tsai, V. (1993) Adaptation o fGeographic Information Systems or Transportation, Report 359, NCHRP, Nat ionalAca dem y Press, Washin gton, D.C., 1993.


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Table 1 . Transportat ion Model and GIS Network s Conflat ion Stat is t ics

1990 Highway1990 Transit2010 Highway2010 Transit

TRANPLANModel Networkl ,inks Nodes

33,776 12,12231,000 10,60936,067 13,19132,359 10,928

GIS Street CenterlineFileArcs Nodes118,000 87,000108,000 80,000126,000 94,000113,000 84,000


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Figure 4. GIS and Transportation Model Networks Integration Workflow

ArcView GUI

QueryDisplayAnalyzePlot

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