Varunraj Valsaraj, Kara Kockelman, Jennifer Duthie, and Brenda Zhou University of Texas at Austin. Original Version: September 2007.

Transcription

1 FORECASTING EMPLOYMENT & POPULATION IN TEXAS: An Investgaton on TELUM Requrements Assumptons and Results ncludng a Study of Zone Sze Effects for the Austn and Waco Regons Varunraj Valsaraj Kara Kockelman Jennfer Duthe and Brenda Zhou Unversty of Texas at Austn Orgnal Verson: September 2007 Abstract The FHWA s publcly avalable Transportaton Economc and Land Use Model (TELUM) predcts the future spatal dstrbutons of employment and households usng Putman s Integrated Transportaton Land Use Package (ITLUP) equatons. TELUM was used here to generate the employment and household locaton forecasts for the Austn and Waco regons by dstrct. Whle reasonably well documented TELUM remans somethng of a black box n that the research team could not duplcate ts parameter predctons or ts forecasts. It also s restrctve n applcaton requrng applcaton at the dstrct level rather than any zone sze (such as the more common and smaller traffc analyss zones [TAZs]). The research team developed ts own open source Matlab code whch wll be referred to as Gravty Land Use Model (G-LUM). G-LUM s based on Putman s documentaton of ITLUP equatons as well as Calper s own (not yet publcly avalable) ITLUP user manual. Ths was done n order to provde transparency try to corroborate TELUM s results and overcome TELUM s zone sze restrctons. Parameters for all ITLUP equatons (fve for each household type fve for each employment type and 19 for the land consumpton model) are estmated by solvng a non-convex non-lnear optmzaton problem whch maxmzes the entropy and thus the lkelhood of the data. In such cases the soluton algorthm can get trapped at a local optmum so our code solves the calbraton problem usng dfferent startng assumptons on parameter values thus reducng the chance of non-globally optmal solutons. TELUM does not address ths ssue. The estmaton results of our code dffer from those of TELUM and yeld hgher entropy values. An analyss of the two models forecasts from 2005 through 2030 (n 5- year ncrements) for the Austn and Waco regons s presented here. TELUM s employment and household predctons dffer sgnfcantly from those of the G-LUM code for the Austn regon. In the case of Waco many smlartes exst n the employment forecasts across the models but household forecasts dffer consderably. Such dstnctons engender analyst hestaton n pursung the use of already compled code such as TELUM s. More transparency s needed to deduce the source of such dstnctons. The nfluence of zone sze on the forecast produced by the ITLUP equatons also was nvestgated n ths study. Future forecasts of the spatal dstrbuton of employment and households by TAZ were obtaned by usng our own code for the Austn and Waco regons. These forecasts were aggregated by dstrcts and then compared wth the dstrct-based forecasts. The comparson showed some stark dfferences. For example n the case of Waco forecasts by

2 dstrct showed more total employment n the eastern and western parts whle forecasts by TAZ showed more total employment n southern parts of the regon. Also the spatal dstrbuton of low ncome households n Austn was completely dfferent for dstrct- and TAZ-based forecasts. Ths report contans detaled descrptons and llustratons of applyng both the TELUM and G- LUM to the three-county Austn regon and the Waco regon. The report begns wth background on the ITLUP model and then results from calbraton are dscussed as well as results from model runs. A summary of fndngs ncludng advantages and drawbacks of the model concludes the report.

3 Table of Contents 1. Introducton Sub-models & Data Requrements EMPLOC RESLOC LUDENSITY Calbraton Austn Metropoltan Regon Implementaton Base Year and Lag Year Data Basc Employment Retal Employment Servce Sector Employment Total Employment Low Income Households Below Average Income Households Above Average Income Households Hgh Income Households Dstrct Implementaton Calbraton Results Comparson of TELUM & G-LUM Forecasts TAZ Implementaton Calbraton results G-LUM Forecast by TAZs Waco Metropoltan Regon Implementaton Base Year and Lag Year Data Basc Employment Retal Employment Servce Employment Total Employment Low Income Households Below Average Income Households Above Average Income Households Hgh Income Households Dstrct Level Implementaton Calbraton Results Comparson of TELUM and G-LUM Forecasts TAZ Level Implementaton Calbraton Results G-LUM Forecasts by TAZs Our Experence wth TELUM Advantages of TELUM Drawbacks of TELUM... 95

4 7. Conclusons REFERENCES Appendx B : G-LUM code Lst of Fgures Fgure 1: Block dagram of G-LUM Fgure 2: Three-county Austn metropoltan regon Fgure 3: Spatal dstrbuton of basc employment n base and lag years for the three-county Austn regon Fgure 4: Spatal dstrbuton of retal employment n base and lag years for the three-county Austn regon Fgure 5: Spatal dstrbuton of servce sector employment n base and lag years for the threecounty Austn regon Fgure 6: Spatal dstrbuton of total employment n base and lag years for the three-county Austn regon Fgure 7: Spatal dstrbuton of low ncome households n base and lag years for the threecounty Austn regon Fgure 8: Spatal dstrbuton of below average ncome households n base and lag years for the three-county Austn regon Fgure 9: Spatal dstrbuton of above average ncome households n base and lag years for the three-county Austn regon Fgure 10: Spatal dstrbuton of hgh ncome households n base and lag years for the threecounty Austn regon Fgure 11: TELUM forecast by dstrct for basc employment for the three-county Austn regon Fgure 12: G-LUM forecast by dstrct for basc employment for the three-county Austn regon Fgure 13: TELUM forecast by dstrct for retal employment for the three-county Austn regon Fgure 14: G-LUM forecast by dstrct for retal employment for the three-county Austn regon Fgure 15: TELUM forecast by dstrct for servce employment for the three-county Austn regon Fg 16: G-LUM forecast by dstrct for servces employment for the three-county Austn regon Fgure 17: TELUM forecast by dstrct for total employment for the three-county Austn regon Fgure 18: G-LUM forecast by dstrct for total employment for the three-county Austn regon32 Fgure 19: TELUM forecast by dstrct for low ncome households for the three-county Austn regon Fgure 20: G-LUM forecast by dstrct for low ncome for the three-county Austn regon Fgure 21: TELUM forecast by dstrct for below average ncome households for the threecounty Austn regon Fgure 22: Matlab code forecast by dstrct for below average ncome households for the threecounty Austn regon... 36

5 Fgure 23: TELUM forecast by dstrct for above average ncome households for the threecounty Austn regon Fgure 24: G-LUM forecast by dstrct for above average ncome households for the three-county Austn regon Fgure 25: TELUM forecast by dstrct for hgh ncome households for the three-county Austn regon Fgure 26: G-LUM forecast by dstrct for hgh ncome households for the three-county Austn regon Fgure 27: TELUM forecast by dstrct for densty of total employment for the three-county Austn regon Fgure 28: G-LUM forecast by dstrct for densty of total employment for the three-county Austn regon Fgure 29: TELUM forecast by dstrct for densty of total households for the three-county Austn regon Fgure 30: G-LUM forecast by dstrct for densty of total household for the three-county Austn regon Fgure 31: G-LUM code forecast by TAZ for basc employment for the three-county Austn regon Fgure 32: G-LUM forecast by TAZ for total employment for the three-county Austn regon.. 49 Fgure 33: G-LUM forecast by TAZ for low ncome households for the three-county Austn regon Fgure 34: G-LUM forecast by TAZ for hgh ncome households for the three-county Austn regon Fgure 35: G-LUM forecast by TAZ for densty of total employment for the three-county Austn regon Fgure 36: G-LUM forecast by TAZ for densty of total household for the three-county Austn regon Fgure 37: Waco metropoltan regon Fgure 38: Spatal dstrbuton of basc employment n base and lag years for the Waco regon 56 Fgure 39: Spatal dstrbuton of retal employment n base and lag years for the Waco regon 56 Fgure 40: Spatal dstrbuton of servce employment n base and lag years for the Waco regon Fgure 41: Spatal dstrbuton of total employment n base and lag years for the Waco regon.. 57 Fgure 42: Spatal dstrbuton of low ncome households n base and lag years for the Waco regon Fgure 43: Spatal dstrbuton of below average ncome households n base and lag years for the Waco regon Fgure 44: Spatal dstrbuton of above average ncome households n base and lag years for the Waco regon Fgure 45: Spatal dstrbuton of hgh ncome households n base and lag years for the Waco regon Fgure 46: TELUM forecast by dstrct for basc employment for the Waco regon Fgure 47: G-LUM forecast by dstrct for basc employment for the Waco regon Fgure 48: TELUM forecast by dstrct for retal employment for the Waco regon Fgure 49: G-LUM forecast by dstrct for retal employment for the Waco regon Fgure 50: TELUM forecast by dstrct for servce employment for the Waco regon... 69

6 Fgure 51: G-LUM forecast by dstrct for servces employment for the Waco regon Fgure 52: TELUM forecast by dstrct for total employment for the Waco regon Fgure 53: G-LUM forecast by dstrct for total employment for the Waco regon Fgure 55: G-LUM forecast by dstrct for low ncome households for the Waco regon Fgure 56: TELUM forecast by dstrct for below average ncome households for the Waco regon Fgure 57: G-LUM forecast by dstrct for below average ncome households for the Waco regon Fgure 58: TELUM forecast by dstrct for above average ncome households for the Waco regon Fgure 59: G-LUM forecast by dstrct for above average ncome households for the Waco regon Fgure 60: TELUM forecast by dstrct for hgh ncome households for the Waco regon Fgure 61: G-LUM forecast by dstrct for hgh ncome households for the Waco regon Fgure 62: TELUM forecast by dstrct for densty of total employment for the Waco regon Fgure 63: G-LUM forecast by dstrct for densty of total employment for the Waco regon Fgure 64: TELUM forecast by dstrct for densty of total household for the Waco regon Fgure 65: G-LUM forecast by dstrct for densty of total household for the Waco regon Fgure 66: G-LUM code forecast by TAZ for basc employment n Waco regon Fgure 67: G-LUM forecast by TAZ for total employment n Waco regon Fgure 68: G-LUM forecast by TAZ for low ncome households n Waco regon Fgure 69: G-LUM forecast by TAZs for hgh ncome households n Waco regon Fgure 70: G-LUM forecast by TAZs for densty of total employment n Waco regon Fgure 71: G-LUM forecast by TAZs for densty of total households n Waco regon... 94

7 Lst of Tables Table 1: DRAM parameters calbrated usng TELUM for Austn dstrcts Table 2: EMPAL parameters calbrated usng TELUM for Austn dstrcts Table 3: LANCON parameters calbrated usng TELUM for Austn dstrcts Table 4: RESLOC parameters calbrated usng G-LUM for Austn dstrcts Table 5: EMPLOC parameters calbrated usng G-LUM for Austn dstrcts Table 6: LUDENSITY parameters calbrated usng G-LUM for Austn dstrcts Table 7: EMPLOC parameter R 2 values usng G-LUM for Austn dstrcts Table 8: RESLOC parameter R 2 values usng G-LUM for Austn dstrcts Table 9: Weghted EMPLOC parameter R 2 values usng G-LUM for Austn dstrcts Table 10: Weghted RESLOC parameter R 2 values usng G-LUM for Austn dstrcts Table 11: EMPAL parameter R 2 values usng TELUM for Austn dstrcts Table 12: DRAM parameter R 2 values usng TELUM for Austn dstrcts Table 13: Weghted EMPAL parameter R 2 values usng TELUM for Austn dstrcts Table 14: Weghted DRAM parameter R 2 values usng TELUM for Austn dstrcts Table 15: RESLOC parameters calbrated usng G-LUM for Austn TAZs Table 16: EMPLOC parameters calbrated usng G-LUM for Austn TAZs Table 17: LUDENSITY parameters calbrated usng G-LUM for Austn TAZs Table 18: EMPLOC parameter R 2 values usng G-LUM for Austn TAZs Table 19: RESLOC parameter R 2 values usng G-LUM for Austn TAZs Table 20: Weghted EMPLOC parameter R 2 values usng G-LUM for Austn TAZs Table 21: Weghted RESLOC parameter R 2 values usng G-LUM for Austn TAZs Table 22: DRAM parameters calbrated usng TELUM for Waco dstrcts Table 23: EMPAL parameters calbrated usng TELUM for Waco dstrcts Table 24: LANCON parameters calbrated usng TELUM for Waco dstrcts Table 25: RESLOC parameters calbrated usng G-LUM for Waco dstrcts Table 26: EMPLOC parameters calbrated usng G-LUM for Waco dstrcts Table 27: LUDENSITY parameters calbrated usng Matlab for Waco dstrcts Table 28: EMPAL parameter R 2 values usng TELUM for Waco Dstrcts Table 29: DRAM parameter R 2 values usng TELUM for Waco Dstrcts Table 30: Weghted EMPAL parameter R 2 values usng TELUM for Waco Dstrcts Table 31: Weghted DRAM parameter R 2 values usng TELUM for Waco Dstrcts Table 32: EMPLOC parameter R 2 values usng G-LUM for Waco Dstrcts Table 33: RESLOC parameter R 2 values usng G-LUM for Waco Dstrcts Table 34: Weghted EMPAL parameter R 2 values usng TELUM for Waco Dstrcts Table 35: Weghted DRAM parameter R 2 values usng TELUM for Waco Dstrcts Table 36: RESLOC parameters calbrated usng G-LUM for Waco TAZs Table 37: EMPLOC parameters calbrated usng G-LUM for Waco TAZs Table 38: LUDENSITY parameters calbrated usng G-LUM for Waco TAZs Table 39: EMPLOC parameter R 2 values usng G-LUM for Waco TAZs Table 40: RESLOC parameter R 2 values usng G-LUM for Waco TAZs Table 41: Weghted EMPLOC parameter R 2 values usng G-LUM for Waco TAZs Table 42: Weghted RESLOC parameter R 2 values usng G-LUM for Waco TAZs... 87

8 1. Introducton The spatal dstrbutons of employment and households of the regon are essental nputs to predct the travel tme n a regon. Travel tme n turn nfluences employment and household locatons n the future. Measures such as the total tme spent by all users travelng n a network are used as ndcators of congeston and hence these measures are used to gauge the effectveness of transportaton polces. So t s necessary to develop a model that can make good forecast of the locatons of employment and household to predct the travel tme accurately n the future. The focus of ths study s to analyze the employment and household locaton forecast gven by the ITLUP equatons proposed by Dr. Putman. The ITLUP equatons were mplemented usng the TELUM software developed jontly by New Jersey Insttute of Technology and S.H. Putman Assocates and also by a code developed ndependently by our team usng Matlab referred as Gravty Land Use model (G-LUM). G-LUM was developed to overcome restrctons mposed by TELUM and also to valdate TELUM s results. TELUM can be used to predct the mpact of a planned transportaton polcy on the land use pattern of a regon n both the short- and long-term. TELUM uses the regonal resdental and employment data from the current and lag years and base year land cover data to forecast the future regonal land use patterns. Professor Stephen H. Putman developer of TELUM proposed the ITLUP equatons n early 1970s and used them to demonstrate the mportance of the lnkage between transportaton polcy and land use. ITLUP has snce been appled to more than twenty metropoltan areas n the Unted States (User Manual: TELUM 2005). The ITLUP equatons have been extensvely revsed and updated snce the ntal work partcularly n lght of the substantal advancement n computer technology over the past two decades. Specfcally Geographcal Informaton Systems (GIS) have been developed and are now popular among planners. In 1997 METROPILUS a new land use modelng tool was developed by Putman. The entre modelng system along wth Graphcal User Interface (GUI) was embedded n the ESRI s ArcVew GIS operatng envronment. It contaned several models for locaton analyss and t could perform data analyss statstcal analyss and dsplay mappng of the output. In 1999 Professor Putman began retoolng METROPILUS as a land use component of Transportaton Economc Land Use System (TELUS). The TELUS Land Use Model or TELUM can predct the locaton and the growth of the resdental and nonresdental development for up to 30 years based on the analyss of current year and a lag year resdental and nonresdental development the locatons of transportaton mprovements and congeston n the system. TELUM and G-LUM were used to generate the employment and household forecast at the dstrct level for Travs Hays and Wllamson countes of Austn. The traffc analyss zones (TAZs) of Austn do not satsfy the zonal requrements of TELUM due to restrctons on the sze of zones. G-LUM doesn t mpose any such restrctons. The objectves of ths study are threefold: ) Implement TELUM for Austn and Waco and provde a detaled account of our experence workng wth the software.

9 ) Develop a code (G-LUM) that overcomes the restrctons of TELUM and also valdate the TELUM results. ) Examne the nfluence of zone sze on the forecast generated usng G-LUM equatons. 2. Sub-models & Data Requrements TELUM conssts of three sub-models namely EMPAL DRAM and LANCON. The correspondng sub-models n G-LUM are referred to as EMPLOC RESLOC and LUDENSITY. The equatons nvolved n each of three sub-models are presented and dscussed n Appendx A. Calbraton determnes the value of parameters that generate the best forecast for the base year based on the lag year data. Calbraton of G-LUM s dscussed n detal n the next secton. Forecasts are generated n tme ncrements of fve years. A tme step begns wth the executon of the EMPLOC model followed by RESLOC and then LUDENSITY. The flowchart n Fgure 1 ndcates the steps nvolved n G-LUM. G-LUM wll be descrbed n ths secton and a note wll be made where TELUM dffers. Base Year Data Lag Year Data Calbraton Emp locaton forecast TELUM- EMP HH locaton forecast TELUM- RES Land use forecast LANCON Next tme perod Base Year Data Lag Year Data Calbraton Emp locaton forecast EMPLOC

10 HH locaton forecast RESLOC Land use forecast LUDENSITY Next tme perod Fgure 1: Block dagram of G-LUM 2.1 EMPLOC EMPLOC forecasts the future spatal dstrbuton of employment and was developed based on the EMPAL model of ITLUP. EMPLOC does not have a lmt on the number of employment sectors allowed but EMPAL requres a mnmum of four and can ncorporate up to eght employment sectors. The forecast of employment locaton of a type n a tme perod n a zone s based on four factors (Putman 2005): ) The employment of that type n all zones n the prevous tme perod ) Populaton of all types n all zones n the prevous tme perod ) Total area per zone for all zones and v) Zone to zone travel cost EMPLOC also requres the projected total employment of regon for each employment category n all the forecast years. These control totals are used to normalze the output produced by EMPLOC. 2.2 RESLOC RESLOC developed based on the DRAM model of ITLUP forecasts the future resdental development. RESLOC requres the classfcaton of households nto 4-5 groups usually based on ncome. The future locaton of a resdent of a specfed type n a zone n a tme perod s based on (Putman S.H 2005): ) Number of resdents of all types n all zones n the prevous tme perod ) Quantty of land used for resdental purposes n that zone at prevous tme perod ) Percentage of developable land n that zone that has already been developed n a prevous tme perod v) Quantty of vacant developable land n that zone at a prevous tme v) Zone to zone travel cost n the current tme perod v) Employment of all types n all zones n the current tme perod RESLOC does not ask the user to explctly nput the number of households n each category for the forecast years and nstead t computes the control totals for each household category n each forecast year based on followng nputs: ) Total populaton of the regon n each forecast year

11 ) Total employment n the regon for all categores n forecast years ) Average number of employees n each household category v) Matrx of Employment by household type n the base year 2.3 LUDENSITY LUDENSITY computes the land consumpton n all zones based on the demand for land for employment and resdental purposes n each zone and the developable (supply) land n that zone. LUDENSITY requres the followng nputs: ) Total land area n all zones ) Usable land n all the zones ) Unusable land n all the zones v) Land used for basc employment n all the zones v) Land used for commercal employment n all the zones v) Resdental land n all the zones v) Land used for street and hghways for all the zones v) Vacant developable n all the zones

12 3. Calbraton The calbraton process nvolves fttng the G-LUM equatons to the data of the regon. The better the ft of the model the more relable are the forecasts. In EMPLOC and RESLOC fve parameters have to be determned for each employment and household type respectvely. The LUDENSITY model requres nneteen parameters to be determned emprcally. Calbraton s an mportant step n G-LUM snce the forecast can vary sgnfcantly across dfferent combnaton of parameter values. Calbraton entals generatng a base year forecast from the lag year data usng the G-LUM equatons. The parameters that generate the best base year forecast (.e. the forecast the most closely matches realty) are used to forecast the employment and household spatal dstrbutons n the future. The parametrc values of G-LUM are typcally determned by solvng an optmzaton formulaton. The standard multple regresson technques cannot be used to estmate the parameters of RESLOC and EMPLOC snce the equatons are non-convex nonlnear and the regonal data may not be normally dstrbuted. The equatons n the LUDENSITY model become lnear equatons f we take logarthm on both sdes. So the parameters of LUDENSITY can be determned usng lnear regresson. The goodness of ft measure also has a sgnfcant nfluence n selectng the parametrc values. Two commonly used goodness of ft crtera are R 2 and measures of lkelhood. It has been shown by (Putman 1983) usng R 2 tends to produce a flat surface close to the local optmum. In comparson use of the lkelhood crtera generates a steeper surface close to the local optmum. So G-LUM uses the entropy based log lkelhood functon as the goodness of ft crtera. CALIBTEL s the procedure used by TELUM to determne the parametrc values n the DRAM and EMPAL sub-models. CALIBTEL and G-LUM uses a gradent search technque to solve the optmzaton formulaton. Lnear regresson s used to determne the parameters n LUDENSITY sub-model. TELUM does not allow users to fne-tune ts parameters (evdently to avod overtnkerng and msuse of the software) so further calbraton smply s not feasble. For employment and households dstrbuton TELUM and G-LUM solves the followng entropy maxmzaton formulaton to determne the parametrc values of ITLUP and G-LUM equatons. Ths formulaton s consstent wth the theory gven n Putman (1983). max N ln Nˆ s. t. I I N = I ( ) Nˆ where I s the set of all zones estmated value (of jobs or households) n zone. N s the count (of jobs or populaton) n zone and (1) Nˆ s the The constrant n (1) ensures that the sum of the projected values s the sum of actual values. If the above constrant s not mposed then the objectve may blow up. The above constrant can be mposed by normalzng all the predcted values by the rato of sum of actual value to the sum of the predcted values. Hence we can use an unconstraned optmzaton technque to solve the

13 above formulaton provded we calculate the objectve functon after normalzng the predcted values. G-LUM (detaled n Appendx B) solves the above formulaton usng a bult-n optmzaton program based on the Nelder-Mead method. The G-LUM equatons are non-lnear n nature so there s always a chance of the program gettng stuck at a local mnmum. In order to overcome ths problem we have solved the above optmzaton formulaton wth multple startng ponts. The set of parameters that yelded the lowest objectve functon value was chosen for mplementaton. The effects of parameters that nfluence the household and employment spatal dstrbutons but are not ncorporated nto G-LUM are captured n resduals. Resduals are computed as the dfference between the actual data of the base year and the predctons generated by G-LUM for the base year usng the lag year data. TELUM allows users to meet base year targets by retanng all resduals and addng these back n to the estmates (essentally as a sute of fudge factors one per zone per job and household category). The effect of these s sad to dmnsh but users do not know to what extent these values actually dmnsh. The G-LUM code the team has developed assumes a 20% reducton n these resduals every 5 years.

14 4. Austn Metropoltan Regon Implementaton TELUM and G-LUM have been used to generate the employment and household forecast for the Travs Hays and Wllamson countes of the Austn metropoltan regon (Fg 2). Wllamson County s located n the north whle Hays County s n the south of regon. Travs County s n between Hays and Wllamson Countes. The cty of Austn s stuated close to the center of Travs County. The three countes n total have 109 dstrcts or 1074 TAZs. G-LUM produces forecasts both by dstrct and by TAZ whle TELUM generates forecasts only by dstrct. Fgure 2: Three-county Austn metropoltan regon The employees n the three-county regon were classfed nto the followng categores: ) Basc employment (Bas) ) Servces employment (Serv) ) Retal employment (Ret) v) Arport employees (Ar) v) Employees n colleges (ED1) v) Employees n school (ED2) The households were classfed as: ) Low ncome (Low): Annual ncome less than $25000 ) Below average (BAvg): Annual ncome between $25000 to $40000 ) Above average (AAvg) Annual ncome between $40000 to $75000 v) Hgh ncome (Hgh): Annual ncome more than $ was chosen as the base year for mplementaton. Snce TELUM makes predctons n fve year ncrements data from year 2000 was used for calbraton. The employment data and the total number of households n each zone were obtaned from the Captal Area Metropoltan Plannng Authorty (CAMPO). The households were then dvded nto the above mentoned

15 ncome categores based on year 2000 Census data. It must be noted that TELUM requres household data by type only for the base year whle the total number of households n a zone s enough for the lag year. The land cover data for 2005 was obtaned from the Captal Area Councl of Governments (CAPCOG). The forecasts were generated by the TELUM and G-LUM codes usng travel tmes from the base year The travel tmes are not updated based on the forecast of the prevous teraton. 4.1 Base Year and Lag Year Data Basc Employment Fgure 3: Spatal dstrbuton of basc employment n base and lag years for the threecounty Austn regon The basc employment s hgh n the cty Austn and ts surroundng zones n Some zones n Hays County and most of the zones n the outskrts of the cty wtnessed an ncrease n the basc employment from 2000 to 2005.

16 4.1.2 Retal Employment Fgure 4: Spatal dstrbuton of retal employment n base and lag years for the threecounty Austn regon Retal employment was concentrated manly n the Austn cty area n 2000 and ts magntude reduces as we move away from the cty. The growth n retal employment from 2000 to 2005 s agan manly n the outskrts of the cty. A couple of zones n Hays County also regstered a hgh ncrease n the retal employment.

17 4.1.3 Servce Sector Employment Fgure 5: Spatal dstrbuton of servce sector employment n base and lag years for the three-county Austn regon Servce sector employment s unformly dstrbuted across Travs County wth the magntude beng hgher n the cty. The major growth areas were zones n Travs County located away from the cty. Interestngly some zones n the cty and ts outskrts wtnessed a decrease n the servce employment Total Employment Fgure 6: Spatal dstrbuton of total employment n base and lag years for the threecounty Austn regon The total employment s at ts maxmum n the cty of Austn and then reduces as we move away from the cty. An nterestng trend that was observed from 2000 to 2005 s that the zones wth

18 hgh total employment n the cty have reduced whle total employment n zones located n the outskrts of the cty has ncreased Low Income Households Fgure 7: Spatal dstrbuton of low ncome households n base and lag years for the threecounty Austn regon There are a large number of low ncome households close to the cty. These are lkely to be students at the Unversty of Texas and other nsttutons. The number of low ncome households n the outskrts of the cty has ncreased consderably from 2000 to Ths may be because low ncome households prefer to stay n outskrts of cty due to the low cost of lvng Below Average Income Households Fgure 8: Spatal dstrbuton of below average ncome households n base and lag years for the three-county Austn regon

19 Ths category of household s densely populated n the zones close to cty and the densty reduces as we move away from cty. A szeable populaton of these households s located n Hays County. There has been an ncrease n the number of below average households n a couple of zones n the outskrts of the cty between 2000 and 2005 but no major changes have occurred n the spatal dstrbuton of ths category of households Above Average Income Households Fgure 9: Spatal dstrbuton of above average ncome households n base and lag years for the three-county Austn regon Most of the zones n Travs and Hays County have a number of above average ncome households. These households have ncreased n a couple of zones n the Austn cty and also n a number of zones n the outskrts of the cty. There were no major changes n the spatal dstrbuton of these households n Wllamson and Hays countes between 2000 and 2005.

20 4.1.8 Hgh Income Households Fgure 10: Spatal dstrbuton of hgh ncome households n base and lag years for the three-county Austn regon Hgh ncome households are manly concentrated on the outskrts of the cty and ther number n these zones contnued to ncrease from 2000 to Hays and Wllamson countes also has a szeable number of hgh ncome households. However dstrbuton of these households n the countes has not changed much between the years 2000 to Dstrct Implementaton ITLUP equatons were mplemented at the dstrct level to generate employment and household forecasts from 2010 to 2030 usng both the TELUM and G-LUM codes. The calbraton results and the maps ndcatng the spatal dstrbuton of the forecast gven by the TELUM and G-LUM codes s gven below Calbraton Results The values of parameters n the sub-models determned usng TELUM and G-LUM developed are presented below. The entropy value s the measure of the goodness of ft of the model used n both the models. In order to make a comparson of the goodness of ft of parameters calculated by TELUM and G-LUM the entropy values are also dsplayed. The equatons correspondng to these parameters can be found n the Appendx A TELUM calbraton results The readers are referred to the Appendx A for an explanaton of each of these parameters.

21 Table 1: DRAM parameters calbrated usng TELUM for Austn dstrcts Parameters Low-HH BAvg-HH AAvg-HH Hgh-HH η α β q r s B (HHtypeLow) B (HHtype BAvg) B (HHtypeAavg) B (HHtypeHgh) Entropy 8.15E E E E+06 Table 2: EMPAL parameters calbrated usng TELUM for Austn dstrcts Parameters Basc Retal Serv Ar College ED1 ED2 λ α β a b Entropy 1.78E E E E E E E+06 Table 3: LANCON parameters calbrated usng TELUM for Austn dstrcts Parameters Resdental Industry Commercal Constant PerDev PerBas PerComm PerLI PerHI Developable Entropy 3.35E E E+05

22 Matlab code parameters Table 4: RESLOC parameters calbrated usng G-LUM for Austn dstrcts Parameters Low-HH BAvg-HH AAvg-HH Hgh-HH η α β q r s B (HHtypeLow) B (HHtype BAvg) B (HHtypeAavg) B (HHtypeHgh) Entropy 9.30E E E E+06 Table 5: EMPLOC parameters calbrated usng G-LUM for Austn dstrcts Parameters Basc Retal Serv Ar College ED1 ED2 λ α β a b Entropy 1.79E E E E E E+06 Table 6: LUDENSITY parameters calbrated usng G-LUM for Austn dstrcts Parameters Resdental Industry Commercal Constant 1.13E PerDev PerBas PerComm PerLI PerHI Developable Entropy 3.53E E E+05 The entropy value of the parameters calculated by G-LUM s greater than the parameters computed by TELUM n all the cases. So parameters computed by G-LUM are lkely to gve

23 more accurate predctons than TELUM usng ITLUP equatons for the three-county Austn regon Comparson of TELUM & G-LUM Forecasts A comparson of the outputs produced by TELUM and G-LUM s presented n ths secton. The spatal dstrbutons of three man employment classes and total employment along wth the spatal dstrbutons of all the four household classes n the forecast years produced by TELUM and G-LUM are dscussed here R 2 and weghted R 2 values The R 2 value and the weghted R 2 value for all the employment and household types n the forecast years are also calculated. The R 2 value s an ndcator of the dfference n the spatal dstrbuton of the forecast year and the base year. Table 7: EMPLOC parameter R 2 values usng G-LUM for Austn dstrcts Years Basc Retal Servces Ar ED1 ED Table 8: RESLOC parameter R 2 values usng G-LUM for Austn dstrcts Years Low BAvg AAvg Hgh Table 9: Weghted EMPLOC parameter R 2 values usng G-LUM for Austn dstrcts Years Basc Retal Servces Ar ED1 ED

24 Table 10: Weghted RESLOC parameter R 2 values usng G-LUM for Austn dstrcts Years Low BAvg AAvg Hgh Table 11: EMPAL parameter R 2 values usng TELUM for Austn dstrcts Years Basc Retal Servces Ar ED1 ED Table 12: DRAM parameter R 2 values usng TELUM for Austn dstrcts Years Low BAvg AAvg Hgh Table 13: Weghted EMPAL parameter R 2 values usng TELUM for Austn dstrcts Years Basc Retal Servces Ar ED1 ED Table 14: Weghted DRAM parameter R 2 values usng TELUM for Austn dstrcts Years Low BAvg AAvg Hgh

25 Forecast from 2010 to 2030 Ths secton presents the mapped output produced by TELUM and G-LUM and a dscusson on these results. The forecast are produced n ncrements of fve years. The zones have been classfed nto four classes based on the number of employment and household types present n that zone. Each class s assgned a dfferent color. Basc employment Fgure 11: TELUM forecast by dstrct for basc employment for the three-county Austn regon TELUM predcts that the basc employment wll ncrease n almost all the zones n the threecounty regon. The basc employment s predcted to be hgh n the outskrts of the Austn cty partcularly n the zones west of the cty by 2030.

26 Fgure 12: G-LUM forecast by dstrct for basc employment for the three-county Austn regon G-LUM on the other hand predcts that the dstrbuton of basc employment would be hgh n central Austn. The majorty of growth areas are located close to the cty and only a few zones n Hays and Wllamson countes are predcted to experence a hgh ncrease n basc employment.

27 Retal employment Fgure 13: TELUM forecast by dstrct for retal employment for the three-county Austn regon Almost all zones n Travs County are predcted by TELUM to experence a huge ncrease n retal employment. By 2030 the outskrts of the cty are forecasted to have hgh numbers of retal employment. Some of the zones n Hays and the Wllamson countes are also predcted to wtness a large ncrease n retal employment.

28 Fgure 14: G-LUM forecast by dstrct for retal employment for the three-county Austn regon G-LUM also predcts a huge ncrease n the retal employment n the outskrts of the cty. However the spatal dstrbuton of the retal employment predcted by both G-LUM and TELUM are substantally dfferent. G-LUM forecasts that the west of the cty wll become hgh retal employment whle TELUM on the other hand predcts the retal employment to ncrease manly east of cty. The forecast of retal employment n Hays and Wllamson countes by TELUM matches wth G-LUM predctons.

29 Servces employment Fgure 15: TELUM forecast by dstrct for servce employment for the three-county Austn regon Servce sector employment s predcted by TELUM to be hgh n dstrcts located to the north of the cty by A couple of zones to the south of cty and n Hays County are also predcted to experence huge ncrease n servce employment. The zones n Wllamson County are predcted to have only small changes n servce employment.

30 Fg 16: G-LUM forecast by dstrct for servces employment for the three-county Austn regon G-LUM predcts central Austn to have hgh levels of servce employment by 2030 but TELUM forecasts ths growth to happen north of the cty center. The G-LUM predctons and TELUM predctons are nearly the same for the zones n the Hays County. However ther predctons dffer sgnfcantly for the Wllamson County. G-LUM forecasts that there wll be a sgnfcant ncrease n the levels of servce employment for zones n Wllamson County but TELUM predcts only small ncreases n servce employment for these zones.

31 Total Employment Fgure 17: TELUM forecast by dstrct for total employment for the three-county Austn regon The total employment s predcted to ncrease n almost all the zones n the three-county regon. In partcular total employment n the zones north of Austn cty and zones located n the cty and n the outskrts of the cty s predcted to ncrease rapdly.

32 Fgure 18: G-LUM forecast by dstrct for total employment for the three-county Austn regon G-LUM on the other hand predcts a more unform ncrease n the total employment. The hgh employment zones are located n the cty center and to the north of the cty. The major dfference n the forecasted spatal dstrbuton of G-LUM and TELUM s n the zones of Wllamson County. TELUM predcts only small ncreases n total employment n most of the zones of Wllamson County. G-LUM on the other hand predcts substantal ncreases n the total employment n almost all the zones n the Wllamson County.

33 Low ncome households Fgure 19: TELUM forecast by dstrct for low ncome households for the three-county Austn regon TELUM predcts the number of low ncome households to ncrease n most of the zones. A large number of these households are predcted to be located n zones close to Austn cty center and to the west of the cty. Some zones n Hays and Wllamson countes are also predcted to have a hgh number of low ncome households by 2030.

34 Fgure 20: G-LUM forecast by dstrct for low ncome for the three-county Austn regon The G-LUM forecast matches the TELUM forecast for most of the zones n Travs and Hays countes. In Wllamson County G-LUM predcts small changes n the number of low ncome households. TELUM on the contrary predcts a large ncrease n the number of low ncome households here.

35 Below average ncome households Fgure 21: TELUM forecast by dstrct for below average ncome households for the threecounty Austn regon Below average ncome households are predcted to ncrease n most of the zones n the threecounty regon by TELUM. Zones close to cty center and to the west along wth a couple of zones n Wllamson and Hays countes are predcted to have a hgh number of these households by 2030.

36 Fgure 22: G-LUM forecast by dstrct for below average ncome households for the threecounty Austn regon G-LUM also forecasts the below average ncome households to be concentrated n zones to the west of cty and n some zones n Hays County. However the predctons from G-LUM are sgnfcantly dfferent from the TELUM predctons for zones n Wllamson County and zones located to the east of the cty. TELUM predcts the number of below average ncome households n these zones to be much hgher than the G-LUM predctons.

37 Above average ncome households Fgure 23: TELUM forecast by dstrct for above average ncome households for the threecounty Austn regon The number of above average ncome households s also predcted by TELUM to ncrease n most of the zones. A large number of above average households are predcted by TELUM to be located to west and north of Austn cty n 2030.

38 Fgure 24: G-LUM forecast by dstrct for above average ncome households for the threecounty Austn regon The forecast of spatal dstrbuton of the above average ncome households by G-LUM matches the TELUM forecast for most of the zones n Travs County. G-LUM predcts a couple of zones n Hays County to have large number of these households but TELUM does not. G-LUM also predcts small changes n the number of above average ncome households n Wllamson County but TELUM on the other hand predcts sgnfcant change n the number of above average ncome households n these zones.

39 Hgh ncome households Fgure 25: TELUM forecast by dstrct for hgh ncome households for the three-county Austn regon A large number of hgh ncome households are predcted by TELUM to be located n central Austn some zones to the west of Austn cty and n a couple of zones n Hays County by TELUM also predcts the number of hgh ncome households to ncrease n most of the zones.

40 Fgure 26: G-LUM forecast by dstrct for hgh ncome households for the three-county Austn regon The predctons of the spatal dstrbuton of the hgh ncome households of G-LUM are nearly the same as the TELUM predctons. The dfference s agan n some zones of Wllamson County where TELUM predcts the number of hgh ncome households to be more than the G- LUM predctons.

41 Densty Varaton n Forecast Years Densty of a zone s the rato of the number of jobs or households of a partcular type present n the zone to the total land area of that zone. The densty varaton across the three county regon predcted by TELUM and G-LUM durng the forecast years s depcted usng a seres of maps. The zones are classfed nto four classes based on the magntude of the densty of the zone and each class s dstngushed by a dfferent color. Total Employment Fgure 27: TELUM forecast by dstrct for densty of total employment for the threecounty Austn regon The zones wth hgh densty of total employment n 2030 are predcted to be located n Austn cty center and ts outskrts and also n few zones to the east of the cty n the TELUM forecast. The major change across the forecast year s the ncrease n total employment densty n many zones of Wllamson County and also n few zones n the cty and west of Austn.

42 Fgure 28: G-LUM forecast by dstrct for densty of total employment for the three-county Austn regon The G-LUM forecast for total employment densty n the three-county regon has a lot of smlartes wth the TELUM forecast. G-LUM predcts the number of hgh densty zones n Austn cty to be more than TELUM forecast. TELUM predcts the total employment to ncrease n a few zones to west of Austn cty whle G-LUM does not. Both forecasts are smlar for the remanng zones.

43 Total Households Fgure 29: TELUM forecast by dstrct for densty of total households for the three-county Austn regon The hgh densty zones of total households are predcted by TELUM to be located n Austn cty and also n few zones n the outskrts. TELUM predcts that durng the forecast years the total household densty would ncrease n many zones of Wllamson County. A few zones located to north of the cty are also predcted to experence an ncrease n densty.

44 Fgure 30: G-LUM forecast by dstrct for densty of total household for the three-county Austn regon G-LUM predcts the densty of total household to be lower that of TELUM forecasts for a few zones located north of the cty and n Wllamson County. The G-LUM forecast for household densty n the remanng zones of the regon are very smlar to the TELUM forecast Summary TELUM predcts an ncrease n total employment n most of the zones n Travs County whle G- LUM predcts an ncrease only n zones n the Cty of Austn. G-LUM predcts a sgnfcant ncrease n total employment n many zones of Wllamson County but TELUM does not. The spatal dstrbuton of low ncome households and below average ncome households predcted by TELUM s completely dfferent from that of G-LUM. However there were close smlartes between the forecasts of TELUM and G-LUM for above average ncome and hgh ncome households. Hence n general there s a sgnfcant dfference n the spatal dstrbuton of employment and household forecasted by TELUM and G-LUM. The source for such dstnctons s very lkely from the unknown formulaton of LANCON n TELUM. The user manual of TELUM mssed LANCON s specfcaton and G-LUM follows the formulas n Putman s book to create LUDENSITY (1991).

45 4.3 TAZ Implementaton G-LUM was used to forecast the future dstrbutons of employment and households n the Austn regon by TAZ to nvestgate the nfluence of zone sze on predctons generated by the G-LUM equatons. TELUM cannot generate the forecast of Austn regon by TAZ snce the average populaton of a TAZ n the three-county regon s less than The developers of TELUM have concluded that TELUM works best when the average populaton of each zone les between 3000 and Calbraton results The G-LUM results from calbratng RESLOC EMPLOC and LUDENSITY sub-models usng the three-county data by TAZ are presented n ths secton. The entropy correspondng to each set of parametrc values s also dsplayed. Table 15: RESLOC parameters calbrated usng G-LUM for Austn TAZs Parameter Low-HH BAvg-HH AAvg-HH Hgh-HH η 3.47E E E E-08 α β q r s B (HHtypeLow) B (HHtype BAvg) B (HHtypeAavg) B (HHtypeHgh) Entropy 6.66E E E E+05 Table 16: EMPLOC parameters calbrated usng G-LUM for Austn TAZs Parameter Basc Retal Serv Ar College ED1 ED2 λ α β a b 4.07E E E E-07 Entropy 1.46E E E E E E+06

46 Table 17: LUDENSITY parameters calbrated usng G-LUM for Austn TAZs Parameter Resdental Industry Commercal Constant PerDev PerBas PerComm PerLI PerHI Developable Entropy 3.49E E E G-LUM Forecast by TAZs The forecast s generated by G-LUM from 2010 to 2030 n ncrements of fve years. The output generated by the G-LUM s mapped usng Arc GIS for two employment and household categores. The forecast produced by G-LUM s also aggregated to the dstrct level to facltate a comparson wth the forecast generated by G-LUM by dstrct for the three-county regon of Austn. The R 2 and weghted R 2 value of the forecast years for each of the employment and household type are also computed R 2 and weghted R 2 values Table 18: EMPLOC parameter R 2 values usng G-LUM for Austn TAZs Forecast Basc Retal Servces Ar ED1 ED2 Year Table 19: RESLOC parameter R 2 values usng G-LUM for Austn TAZs Forecast Low BAvg AAvg Hgh Year

47 Table 20: Weghted EMPLOC parameter R 2 values usng G-LUM for Austn TAZs Forecast Basc Retal Servces Ar ED1 ED2 Year Table 21: Weghted RESLOC parameter R 2 values usng G-LUM for Austn TAZs Forecast Year Low Inc BAvg Inc AAvg Inc Hgh Inc Forecasts from 2010 to 2030 Ths secton contans the forecasts generated by G-LUM for the three-county regon by TAZs. The TAZs are then aggregated to dstrcts to make a comparson wth the forecasts generated by G-LUM by dstrcts for the same regon. The zones are agan classfed nto four types based on the magntude of employment and household type present n the zone.

48 Basc employment Fgure 31: G-LUM code forecast by TAZ for basc employment for the three-county Austn regon G-LUM predcts that the basc employment n zones n the Cty of Austn would decrease whle the zones stuated east of the cty would experence sgnfcant ncrease. Most of the zones n Hays and Wllamson countes are projected to experence an ncrease n basc employment. In comparson G-LUM predctons by dstrct suggest that ncrease n basc employment would be manly concentrated n the central dstrcts of Travs County.

49 Total employment Fgure 32: G-LUM forecast by TAZ for total employment for the three-county Austn regon The total employment n predctons generated by G-LUM by TAZ s concentrated manly n the central and eastern dstrcts of Travs County and n a few dstrcts to the east of Hays County. The rest of the dstrcts are predcted to experence a unform ncrease n the total employment. On the other hand there s a hgh level of total employment n many dstrcts n central Travs County n G-LUM predctons by dstrct. The predctons are roughly the same for the rest of the dstrcts.

50 Low ncome households Fgure 33: G-LUM forecast by TAZ for low ncome households for the three-county Austn regon By 2030 few zones n central Austn and n Hays County are predcted to have many low ncome households the n G-LUM forecast by TAZs. A sgnfcant number of low ncome households are also predcted n zones to the east of Travs County and also n a few zones n Hays County. The rest of the zones have a low number of low ncome households. Whle n the G-LUM forecast by dstrct there s a hgh number of low ncome households n zones that are n central Travs and Hays countes and also n a few zones n the east and west of Travs County.

51 Hgh ncome households Fgure 34: G-LUM forecast by TAZ for hgh ncome households for the three-county Austn regon The G-LUM predctons by TAZ suggest that hgh ncome households would be located densely n zones n the west of Travs County by The dstrct level G-LUM predctons also produce smlar output. The dfference n the two forecasts le n zones that are n the center of Travs County whch s predcted to have a large number of hgh ncome households n G-LUM predctons by dstrcts. In comparson n the G-LUM predcton by TAZ these zones do not have a hgh number of hgh ncome households.

52 Densty Varaton n Forecast Years The densty varaton n G-LUM forecasts by TAZ from 2010 to 2030 s presented n a seres of maps. Each map represents the spatal dstrbuton of densty across the three-county regon. The zones are classfed nto four classes dependng on the magntude of densty and the classes are assgned dfferent colors. Total Employment Fgure 35: G-LUM forecast by TAZ for densty of total employment for the three-county Austn regon G-LUM predcts that n 2030 the TAZs wth hgh densty of total employment wll be located n the center of Travs County whle the majorty of the remanng TAZs would have smlar employment densty. The employment densty has ncreased durng the forecast n most of the zones n Hays and Wllamson countes that had low employment n the base year.

53 Total Households Fgure 36: G-LUM forecast by TAZ for densty of total household for the three-county Austn regon The hgh densty zones of total households are predcted n the G-LUM forecast by TAZ to be located n the center of Travs County n Most of the zones n Wllamson and Hays countes are predcted to have low household densty. The G-LUM forecast by TAZ does not predct any major change n the spatal dstrbuton of densty of total household durng the forecast years.

54 Summary The spatal dstrbutons of total employment basc employment low ncome households and total households n the Cty of Austn generated usng G-LUM by dstrct and by TAZ are consderably dfferent. So the sze of a zone has a bg nfluence on the predctons usng G-LUM equatons. The TELUM user manual recommends that the ITLUP equatons work best when the sze of the zone s such that the average populaton per zone les between 3000 and However the TELUM user manual does not cte any reference on research conducted examnng the nfluence of sze of the zone on the predcton generated by ITLUP. So t s not clear how these lmts on the zone sze were derved.

55 5. Waco Metropoltan Regon Implementaton The forecast of the spatal dstrbutons of employment and household of the Waco regon generated by TELUM and G-LUM s dscussed n ths secton. G-LUM was also used to generate the forecast of the Waco regon by TAZ to gauge the nfluence of zone sze on the predctons. The base year of mplementaton s 2005 and 2000 was chosen as the lag year snce TELUM generates forecast n fve year ncrements. The nter-zonal travel tme n the year 2005 was used by both TELUM and G-LUM. The travel tme was assumed to reman constant throughout the forecast years. Employment n the Waco regon s categorzed nto the followng types: ) Basc ) Retal ) Servces v) Other types Households n the Waco regon are classfed nto: ) Low ncome ) Below average ncome ) Above average ncome v) Hgh ncome The data for the Waco regon were obtaned from Wlbur Smth Assocates. The dvson of the Waco regon nto dstrcts and TAZs s shown below. The red lne shows the dstrct boundary whle the blue lne shows the boundary of TAZs. Please also note the drecton of orentaton of the map ndcated n top rght corner of the fgure. Fgure 37: Waco metropoltan regon

56 5.1 Base Year and Lag Year Data The spatal dstrbuton of the employment and households by type for the base year (2005) and lagged year (2000) s presented here Basc Employment Fgure 38: Spatal dstrbuton of basc employment n base and lag years for the Waco regon Most of the zones wth dense basc employment are located towards the west of the Waco regon n the base year. There are also a few zones wth hgh basc employment n the center of the regon. There was a reducton n basc employment from 2000 to 2005 n a couple of zones n south of the regon Retal Employment Fgure 39: Spatal dstrbuton of retal employment n base and lag years for the Waco regon The retal employment s stuated mostly n the southern and eastern parts of the Waco regon n the year There are a couple of zones n the north of the regon wth hgh retal employment. Some of the zones on the east sde of the Waco regon experenced a reducton n

57 retal employment whle an ncrease n retal employment was observed n a few zones n the northern and southern parts of the regon n between 2000 to Servce Employment Fgure 40: Spatal dstrbuton of servce employment n base and lag years for the Waco regon The zones wth hgh levels of servce employment are located n the southern and central parts of the Waco regon. There s an almost unform dstrbuton of servces employment for the rest of the zones n the base year. The major change n spatal dstrbuton from lagged year to base year s the ncrease n servces employment n a couple of dstrcts n the south and also a decrease n servces n a few zones n the east Total Employment Fgure 41: Spatal dstrbuton of total employment n base and lag years for the Waco regon In the base year the zones wth large number of total employment were located n the center of the Waco regon and also n a couple of zones n the south. The total employment reduces as we move away from the center of the regon. In comparson n the lagged year 2000 the total employment seems to be unformly dstrbuted n the south and east parts of Waco wth a few

58 zones of hgh employment n the center. In between 2000 and 2005 a reducton n total employment was observed n a few zones stuated to the east and west of the regon Low Income Households Fgure 42: Spatal dstrbuton of low ncome households n base and lag years for the Waco regon The low ncome households are located manly n the east and central zones of Waco regon n the base year. The low ncome households have ncreased n the central and eastern regon of Waco between the base year and lag year. The rest of the zones have wtnessed ether a decrease n the low ncome households or mnor changes Below Average Income Households Fgure 43: Spatal dstrbuton of below average ncome households n base and lag years for the Waco regon The zones wth hgh number of below average ncome households are located n the center of the Waco regon n the base year. It s dstrbuted almost unformly throughout the rest of the Waco regon. The sgnfcant change n the spatal dstrbuton between 2000 and 2005 s the ncrease n below average households n zones n the central Waco regon and ts outskrts.

59 5.1.7 Above Average Income Households Fgure 44: Spatal dstrbuton of above average ncome households n base and lag years for the Waco regon In the base year above average ncome households are concentrated manly n the trangular regon wth ts vertces at the center east and south of the regon. In between 2000 and 2005 the number of above average ncome households have ncreased n ths trangular doman whle at the same tme above average ncome households have reduced n some zones stuated to the east Hgh Income Households Fgure 45: Spatal dstrbuton of hgh ncome households n base and lag years for the Waco regon The hgh ncome households are dstrbuted manly n the southern and eastern zones of Waco. There are a couple of zones wth large number of these households n the center of the regon. There has been a sgnfcant reducton n number of hgh ncome households n almost all the zones except those located center and south of the Waco regon n between the 2000 and 2005.

60 5.2 Dstrct Level Implementaton Waco has a total of 44 dstrcts. The employment and household locaton dstrct data for the base year and lag year was obtaned by aggregatng the data avalable at TAZ level. TELUM and G-LUM were used to generate forecast by dstrcts from 2010 to 2030 n fve year ncrements. The calbraton results and the mapped output of the forecast generated by TELUM and G-LUM codes are dscussed n the followng sectons Calbraton Results The parameters of ITLUP equaton computed by TELUM and G-LUM for the Waco regon by calbraton are dsplayed n ths secton. The entropy value whch s a measure of goodness of ft s computed for each set of parameters. TELUM Calbraton Results Table 22: DRAM parameters calbrated usng TELUM for Waco dstrcts Parameters Low-HH BAvg-HH AAvg-HH Hgh-HH η α β q r s B (HHtypeLow) B (HHtype BAvg) B (HHtypeAavg) B (HHtypeHgh) Entropy E E+05 Table 23: EMPAL parameters calbrated usng TELUM for Waco dstrcts Parameters Basc Retal Serv Other λ α β a b Entropy 1.41E E E

61 Table 24: LANCON parameters calbrated usng TELUM for Waco dstrcts Parameters Resdental Industry Commercal Constant PerDev PerBas PerComm PerLI PerHI Developable Entropy 1.26E E E+05 G-LUM code parameters Table 25: RESLOC parameters calbrated usng G-LUM for Waco dstrcts Parameters Low-HH BAvg-HH AAvg-HH Hgh-HH η α β q r s B (HHtypeLow) B (HHtype BAvg) B (HHtypeAavg) B (HHtypeHgh) Entropy 1.13E E E E+05 Table 26: EMPLOC parameters calbrated usng G-LUM for Waco dstrcts Parameters Basc Retal Serv Other Λ Α Β A B Entropy 1.44E E E E+05

62 Table 27: LUDENSITY parameters calbrated usng Matlab for Waco dstrcts Parameters Resdental Industry Commercal Constant E+03 PerDev PerBas PerComm PerLI PerHI Developable Entropy The entropy value of parameters computed by G-LUM s more than TELUM n all the cases. The dfference may be because the soluton algorthm of TELUM got stuck at a local optmum Comparson of TELUM and G-LUM Forecasts The followng secton contans the mapped output of the predctons produced by TELUM and G-LUM for Waco regon by dstrcts. Ths secton also contans a dscusson on these forecasts and how the TELUM forecasts dffer from the G-LUM forecasts R 2 and weghted R 2 values The R 2 and weghted R 2 s an ndcator of change n the spatal dstrbuton of employment and households n the forecast year from that of the base year. Table 28: EMPAL parameter R 2 values usng TELUM for Waco Dstrcts Forecast Basc Retal Servces Other Years

63 Table 29: DRAM parameter R 2 values usng TELUM for Waco Dstrcts Forecast Years Low Inc BAvg Inc AAvg Inc Hgh Inc Table 30: Weghted EMPAL parameter R 2 values usng TELUM for Waco Dstrcts Forecast Basc Retal Servces Other Years Table 31: Weghted DRAM parameter R 2 values usng TELUM for Waco Dstrcts Forecast Years Low Inc BAvg Inc AAvg Inc Hgh Inc Table 32: EMPLOC parameter R 2 values usng G-LUM for Waco Dstrcts Forecast Basc Retal Servces Other Years

64 Table 33: RESLOC parameter R 2 values usng G-LUM for Waco Dstrcts Forecast Years Low Inc BAvg Inc AAvg Inc Hgh Inc Table 34: Weghted EMPAL parameter R 2 values usng TELUM for Waco Dstrcts Forecast Basc Retal Servces Other Years Table 35: Weghted DRAM parameter R 2 values usng TELUM for Waco Dstrcts Forecast Years Low Inc BAvg Inc AAvg Inc Hgh Inc Forecast from 2010 to 2030 The forecast generated by TELUM and G-LUM by dstrcts for the Waco regon n fve year ncrements s gven n ths secton. The dstrcts have been dvded nto four classes based on the number of employment and household type present n the dstrct. Each of these classes has been assgned dfferent colors.

65 Basc Employment Fgure 46: TELUM forecast by dstrct for basc employment for the Waco regon TELUM s predcton for the basc employment dstrbuton for 2030 s that the zones wth hgh basc employment would be located n the center and would radate out n the north-east northwest and south-west drectons. The sgnfcant change predcted between 2010 and 2030 s the reducton n basc employment n a couple of zones n eastern and southern parts of the regon.

66 Fgure 47: G-LUM forecast by dstrct for basc employment for the Waco regon G-LUM forecast for basc employment s very smlar to TELUM s. The dfference between the two forecasts s that the basc employment of a couple of zones n the south-west drecton n TELUM s predcton s more than that of G-LUM s predctons.

67 Retal Employment Fgure 48: TELUM forecast by dstrct for retal employment for the Waco regon The zones wth large retal employment are predcted to be located n the central and northern regon of Waco and also n a few zones n the south n the TELUM forecast. No major changes are predcted n the spatal dstrbuton of retal employment durng the forecast years.

68 Fgure 49: G-LUM forecast by dstrct for retal employment for the Waco regon The G-LUM forecast for retal employment matches the TELUM forecast n almost all the dstrcts. There s no sgnfcant dfference between the two forecasts.

69 Servce Employment Fgure 50: TELUM forecast by dstrct for servce employment for the Waco regon The servce employment s predcted to be concentrated n center and south Waco n 2030 by TELUM. The sgnfcant change durng the forecast years s the reducton n the servces employment n some of the zones located to the east and south-east part of the regon.

70 Fgure 51: G-LUM forecast by dstrct for servces employment for the Waco regon The G-LUM forecast also predcts that the zones wth hgh number of servce employment would be located n center and south of Waco. However unlke TELUM G-LUM does not forecast the decrease n servce employment n zones located to the west and south-east of Waco.

71 Total Employment Fgure 52: TELUM forecast by dstrct for total employment for the Waco regon TELUM forecasts that by 2030 the zones wth hgh total employment would be n the center and radatng n the south and north-west regons of Waco. A couple of zones n north-west regon also have hgh number of total employment n The ncrease n total employment n most of the regons located n the north-west regon of Waco and decrease n total employment n a few zones n east of Waco were sgnfcant changes durng the forecast years.

72 Fgure 53: G-LUM forecast by dstrct for total employment for the Waco regon G-LUM predcts the zones wth hgh employment would be n the center and radatng n the south and north of Waco n The man dfference between the TELUM and G-LUM forecast s that G-LUM does not forecast an ncrease n total employment north-eastern dstrcts of Waco but TELUM does.

73 Low Income Households Fgure 54: TELUM forecast by dstrct for low ncome households for the Waco regon The low ncome households are predcted to be located manly n the central western and northeastern zones of Waco by TELUM n TELUM predcts that durng the forecast years the low ncome households located n central and northern regons of Waco would ncrease.

74 Fgure 55: G-LUM forecast by dstrct for low ncome households for the Waco regon The G-LUM forecast for low ncome households are dfferent from that of TELUM s. G-LUM predcts low ncome households to be located manly n eastern and central zones of Waco by The reducton of low ncome households n the central Waco and ther ncrease northwestern parts of regon s the major predcted change over the forecast years.

75 Below Average ncome households Fgure 56: TELUM forecast by dstrct for below average ncome households for the Waco regon The zones wth large number of below average ncome households are forecasted by TELUM to be located n center and s radatng out towards all the four corners of the Waco regon n There has been a reducton n the below average households n a few zones located n the south and north-west parts of the regon durng the forecast years. Zones n north and eastern parts of the regon are predcted to experence an ncrease n the below average households.

76 Fgure 57: G-LUM forecast by dstrct for below average ncome households for the Waco regon The predctons of G-LUM are consderably dfferent from those produced by TELUM. The below average ncome households are predcted by G-LUM to be located manly n the center and eastern regons of Waco by Contrary to TELUM predctons the below average households have reduced n all zones except those located n the eastern parts of the regon.

77 Above Average ncome households Fgure 58: TELUM forecast by dstrct for above average ncome households for the Waco regon TELUM forecasts sgnfcant changes n the spatal dstrbuton of the above average ncome households across the forecast years. The zones wth hgh number of above average ncome households are predcted to be located n the western and central regons of Waco. Durng the forecast years the zones located n the center and west are predcted to experence an ncrease whle zones n the south of the regon are predcted to wtness a decrease n number of above average ncome households.

78 Fgure 59: G-LUM forecast by dstrct for above average ncome households for the Waco regon In 2030 G-LUM too predcts a large number of above average households n the center and west of Waco. However contrary to TELUM predctons G-LUM predcts that zone located to the south wll wtness an ncrease n the above average ncome households. Many of the above average ncome households are also predcted to be n northern zones of Waco by 2030 n the G- LUM predctons.

79 Hgh ncome households Fgure 60: TELUM forecast by dstrct for hgh ncome households for the Waco regon TELUM forecast a large number of hgh ncome households n western part of Waco and also n a couple of zone n the center and south-east of Waco. A few zones located n the south and north-east parts of the regon are predcted to wtness decreases n the number of hgh ncome households. The zones that are forecasted to experence an ncrease n hgh ncome households are stuated manly n the north and west of Waco.

80 Fgure 61: G-LUM forecast by dstrct for hgh ncome households for the Waco regon The G-LUM forecast for hgh ncome households s completely dfferent from the TELUM forecast. In the G-LUM forecast the hgh ncome households are predcted to be located manly n the center of the Waco regon and also n a couple of zones n the southern and eastern parts of Waco by The zones located to the west of Waco are predcted to have a very low number of hgh ncome households whch s the exact opposte of TELUM s predcton. The hgh ncome households have reduced n all zones except those located n the eastern part of Waco durng the forecast years.

81 Densty Varaton n Forecast Years Ths secton presents a comparson of TELUM and G-LUM forecasts of the densty of total employment and total households n the Waco regon by dstrct. The zones are classfed nto four classes based on the magntude of densty. Total Employment Fgure 62: TELUM forecast by dstrct for densty of total employment for the Waco regon TELUM forecast that the dstrcts wth hgh denstes of total employment are located n the centre of Waco and radatng n the north-east north-west and south-west drecton n The remanng dstrcts are predcted to have low densty of total employment. The total employment densty has ncrease n a couple dstrcts stuated n the northern parts of the regon durng the forecast years.

82 Fgure 63: G-LUM forecast by dstrct for densty of total employment for the Waco regon The spatal dstrbuton of the densty of total employment predcted by G-LUM matches the TELUM forecast.

83 Total household Fgure 64: TELUM forecast by dstrct for densty of total household for the Waco regon Dstrcts wth hgh densty of total households are located n the center and radatng from center towards the east and western parts of the Waco. The household densty has ncreased n a few dstrcts n eastern parts of Waco whle there has been small varaton of densty n the remanng zones.

84 Fgure 65: G-LUM forecast by dstrct for densty of total household for the Waco regon G-LUM forecast for densty of total household dffer from the TELUM forecast manly n the eastern parts of Waco. TELUM predcts the densty of total households n eastern dstrcts of Waco to be more than G-LUM forecasts. The household densty predcted for the remanng zones are smlar n both forecasts. Summary The TELUM predcton for the spatal dstrbuton of three man employment types of Waco - namely basc retal and servces employment - s very smlar to G-LUM forecasts. However the TELUM forecasts for all household types are completely dfferent from that of the G-LUM forecast. TELUM predcts large ncreases n the number of household for many zones whle G- LUM does not. So the numbers of zones wth hgh number of households n TELUM forecast are much more than that of the G-LUM predctons.

85 5.3 TAZ Level Implementaton G-LUM was used to mplement ITLUP equatons by TAZs for the Waco regon. Ths was done to nvestgate the effect of zone sze on the predctons generated by ITLUP equatons for the Waco regon. Waco has 283 TAZs and total populaton of So the average populaton per TAZ s 755 persons. The average populaton per TAZ of Waco regon falls below the recommended range for the average populaton per zone by TELUM Calbraton Results The parameters obtaned by calbratng G-LUM equatons usng the lag year and base year data of Waco by TAZ s presented n ths secton. The entropy correspondng to the parameters chosen for predcton s also dsplayed. Table 36: RESLOC parameters calbrated usng G-LUM for Waco TAZs Parameters Low-HH BAvg-HH AAvg-HH Hgh-HH Η Α Β Q r s B (HHtypeLow) B (HHtype BAvg) B (HHtypeAavg) B (HHtypeHgh) Entropy 8.39E E E E+05 Table 37: EMPLOC parameters calbrated usng G-LUM for Waco TAZs Parameters Basc Retal Serv Other λ α β a b Entropy 1.10E E E

86 Table 38: LUDENSITY parameters calbrated usng G-LUM for Waco TAZs Parameters Resdental Industry Commercal Constant PerDev PerBas PerComm PerLI PerHI Developable Entropy 1.16E E E G-LUM Forecasts by TAZs The mapped output of the G-LUM forecast for two employment and household types by TAZs for the Waco regon s dsplayed here. The TAZ level forecast generated by G-LUM was aggregated to the dstrct level to facltate a drect comparson wth dstrct level forecast generated by TELUM. The R 2 and weghted R 2 values were also calculated for all the household and employment types R 2 and weghted R 2 values Table 39: EMPLOC parameter R 2 values usng G-LUM for Waco TAZs Forecast Basc Retal Servces Other Years Table 40: RESLOC parameter R 2 values usng G-LUM for Waco TAZs Forecast Years Low Inc BAvg Inc AAvg Inc Hgh Inc

87 Table 41: Weghted EMPLOC parameter R 2 values usng G-LUM for Waco TAZs Forecast Basc Retal Servces Other Years Table 42: Weghted RESLOC parameter R 2 values usng G-LUM for Waco TAZs Forecast Low Inc BAvg Inc AAvg Inc Hgh Inc Years

88 Forecasts from 2005 to 2030 Basc Employment Fgure 66: G-LUM code forecast by TAZ for basc employment n Waco regon Durng the forecast years 2010 to 2030 the basc employment ncreases n zones located n the centre of Waco regon whle n the remanng zones the basc employment ether reduces or has only margnal changes. In comparson the forecast generated by G-LUM for the G-LUM Waco regon by dstrct predcts that n addton to the zones wt hgh basc employment n the center there would be some addtonal hgh basc employment n the west and south-west regons of

89 Waco by The number of low basc employment zones predcted n the forecast by dstrct n the south north and eastern parts of the regon n 2030 s more than those n the forecast by TAZs. Total Employment Fgure 67: G-LUM forecast by TAZ for total employment n Waco regon In the forecast by TAZs the zones wth large total employment are predcted to be located n center of Waco regon and n a couple of zones n the outskrts n In the forecast by dstrct these zones are also located n the same area. The spatal dstrbuton of the two forecasts s smlar except for the fact that n the forecast by dstrcts there are more zones wth low basc

90 employment than n the forecast by TAZs.

91 Low ncome households Fgure 68: G-LUM forecast by TAZ for low ncome households n Waco regon The forecast by TAZ predcts that by 2030 the zones wth a hgh number of low ncome households wll be centrally stuated and radatng n the east and north-west drecton from the center. They are predcted to be dstrbuted almost unformly n the remanng zones. Whle n the forecast by dstrcts zones wth hgh number of low ncome households n 2030 are n the center and n a couple of zones to the east of the regon. A large number of zones wth low ncome households are predcted n the north-west regon of Waco n forecast by dstrct whch are absent n the forecast by TAZs.

92 Hgh ncome households Fgure 69: G-LUM forecast by TAZs for hgh ncome households n Waco regon The hgh ncome households are predcted n 2030 to be stuated manly n the central and eastern parts of Waco regon n the forecast by TAZ. A couple of zones n the south of the regon are also predcted to have a hgh number of hgh ncome households by The remanng zones are forecast to have a medum to low number of hgh ncome households. In comparson n the forecast by dstrcts the hgh ncome households are predcted to be concentrated manly n the center and n a couple of zones north of the regon. The remanng zones are forecasted to have medum to low number of hgh ncome households.

93 Densty Varaton n Forecast Years The varaton n the densty across TAZs n G-LUM predctons of the Waco regon s dscussed n ths secton. The TAZs are classfed nto four classes dependng upon the magntude of densty. Total employment Fgure 70: G-LUM forecast by TAZs for densty of total employment n Waco regon TAZs wth hgh denstes of total employment are predcted n 2030 to be stuated n center and fannng out n south and western parts of Waco. The rest of the zones are predcted to have low densty of total employment. G-LUM doesn t forecast any major change n total employment durng the forecast year other than the reducton of total employment densty n a few zones n south and west of Waco.

94 Total households Fgure 71: G-LUM forecast by TAZs for densty of total households n Waco regon G-LUM forecast zones wth hgh densty of total households to be located manly n central parts of regon. Some zones n south and eastern parts of Waco are predcted to have medum densty of households. The ncrease n densty of households n a couple of TAZs n the eastern part of Waco s the only notceable change that occurred durng the forecast years. Summary The employment and household forecasts made usng G-LUM dffer dependng on whether they are made by dstrct or TAZs. G-LUM forecasts by dstrct predct more total employment n eastern and western parts of Waco than the G-LUM forecast by TAZs. G-LUM predctons for low ncome households and hgh ncome household by dstrct are completely dfferent from forecast TAZs for most of the zones. Thus the sze of zone used for analyss has a sgnfcant nfluence n the spatal dstrbuton forecast generated usng the ITLUP equatons for the Waco regon.