tast

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Source: Consultant, 2023 Figure 2.2.1-5 Population distribution b Source: Consultant, 2023 Figure 2.2.1-6 Population density by

Department of Rail Transport Final Report 2-37 by TAZ in the study area, 2010-2019 TAZ in the study area, 2010-2019

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-38 2) Analysis and Estimation of Future Population (1) Methodology to estimate future population in TAZs The estimation of future population in TAZs is a very crucial process to be used for transportation model so as to propose the most appropriate transportation planning in the study area for the next 20 years. Therefore, it needs to be based on the population projection by accountable and reliable source as it will affect the estimation of future population in TAZs. Population projection by NESDC is considered reliable to be used for planning purposes in Thailand, as It is less than 5% difference when comparing to actual population in 2015 and 2019 as shown in Table 2.2.1-5. Thus, this study use population projection by NESDC available at provincial level, as a control total of future population. Table 2.2.1-5 Comparison of actual population and population projected by NESDC, 2015-2019 Source: NESDC, analyzed by consultant, 2023 According to NESDC’s population forecast by province, the total number of future populations in the study area to be used as the control numbers will be 17,216,708, 17,739,637, 18,076,320, and 18,223,300 in 2025, 2030, 2035, and 2040 respectively. Although the overall number of populations in the study area is slightly increasing, population in Bangkok starts to slightly decrease from 2030 onward, while population in other provinces continues to increase until 2040, the targeted year. These different future population patterns will affect the final distribution of future population in TAZs in each province, which will be described later. The details of NESDC’s population forecast by province in the study area are shown in Figure 2.2.1-7. 2015 2019 2015 2019 2015 2019 Bangkok 8,107,418 8,318,381 8,041,668 8,231,878 0.81% 1.04% Samuth Prakarn 1,918,361 2,075,369 1,926,000 2,069,600 -0.40% 0.28% Nonthaburi 1,463,953 1,583,587 1,458,200 1,582,000 0.39% 0.10% Prathumthani 1,423,739 1,545,064 1,366,400 1,460,000 4.03% 5.51% Pra Nakorn Sri Ayuthaya 864,414 875,248 848,400 843,400 1.85% 3.64% Chacheongsao 754,658 789,154 760,800 806,400 -0.81% -2.19% Nakorn Prathom 975,820 1,028,113 1,000,700 1,079,800 -2.55% -5.03% Samuth Sakorn 726,312 770,253 709,400 752,500 2.33% 2.30% TOTAL population 16,234,675 16,985,170 16,111,568 16,825,578 0.76% 0.94% Actual population Province Forecasted Population by NESDC, 2013 % Difference

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-39 Source: NESDC, collected by constultant, 2023 Figure 2.2.1-7 NESDC’s future population by province in the study area as control total To appropriately distribute future population forecasted by NESDC into TAZs, assumption for future population framework is proposed as shown in Figure 2.2.1-8. Source: Consultant, 2023 Figure 2.2.1-8 Assumptions for future population framework 2010 2015 2019 2025 2030 2035 2040 Bangkok 7,691,376 8,107,418 8,318,381 8,473,166 8,457,222 8,339,722 8,139,919 Samuth Prakarn 1,736,914 1,918,361 2,075,369 2,297,820 2,463,856 2,606,321 2,718,439 Nonthaburi 1,304,042 1,463,953 1,583,587 1,752,583 1,878,227 1,985,617 2,069,743 Prathumthani 1,244,635 1,423,739 1,545,064 1,705,765 1,821,187 1,918,559 1,994,189 Pra Nakorn Sri Ayuthaya (65.69%) 904,219 975,820 1,028,113 1,115,518 1,185,399 1,246,645 1,294,987 Chacheongsao (55.03%) 647,285 726,312 770,253 830,648 874,292 910,538 937,557 Nakorn Prathom 558,431 567,834 574,950 578,533 574,487 563,482 545,358 Samuth Sakorn 385,753 415,288 434,271 462,676 484,968 505,436 523,108 TOTAL 14,472,655 15,598,725 16,329,989 17,216,708 17,739,637 18,076,320 18,223,300 - 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 14,000,000 16,000,000 18,000,000 20,000,000

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-40 According to Figure 2.2.1-8, there are 2 development factors considered in future population framwork as follows: • New large urban development projects considered to have larger impact on population growth at provincial level than at TAZ level, therefore is subtracted from the total provincial population • Future railway stations considered to have impacts on population growth at subdstrict level rather than at just TAZ they are located Based on the above assumptions, 3 steps to estimate future population to TAZs are proposed to distribute NESDC population forecast at provincial level to sub-district and finally to TAZ level in 4- future-year periods as shown in Figure 2.2.1-9. The details for each step are described below. Step 1: Population by province, being subtracted by population increase from large-scale urban development projects at the expected opening year, to be used as control total of population for each province at 4 periods of 2025, 2030, 2035, and 2040. The details of large-scale urban development projects including building area dedicated for residential uses, projected population, their locations, and the expected opening year are shown in Figure 2.2.1- 10. These population increases are based on the assumption that only 70% of all planed units are occupied and the 1st phase accounts for 60% and the rest for 40%. Step 2: Population by sub-district To distribute future population at provincial level from Step 1 into sub-district level, 3 population growth rates are considered as follows: ▪ Population growth rate by sub-district ▪ Additional population growth rate by o Impact of railway development depending on population density based on 2 formulas coming from analysis of additional population growth rate affected by railway stations, that have opened until the year 2016 as shown in Figure 2.2.1-11: ▪ Sub-district with railway station, r = -1E-06x + 0.0188 ▪ Sub-district without railway station, r = -1E-06x + 0.0141 r= Growth Rate, x= Population Density o Comprehensive Plan For Sub-district without railway station for each period, green area designated in comprehensive plan is considered as follows (as shown in Figure 2.2.1-12): ▪ > 75% Green Zone: r’=0*r (around 60% of sub-district without railway station, which is not suitable for urban development, so should not have population increase) ▪ Around 50% Green Zone: r’=0.5*r ▪ < 25% in Green Zone: r’=1*r

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-41 For each period, the combination of population growth rate by sub-district and additional growth rate from formulas and green area calculation above is used as the estimated population growth rate to calculate future population in each sub-district. The sums of furture population in sub-districts are then proportionately adjusted to fit with control population number by province. The population growth rate by subdistrict is then recalculated to be used as population growth rate for the next period. The same process is then applied for all 4 periods. Step 3: Population by TAZ To distribute future population in sub-districts from Step 2 into TAZs, 2 factors are considered as follows: ▪ Population growth rate by TAZ from base-year trend be applied to calculate the future population in TAZ, of which the sum is then adjusted to fit with sub-district population in Step 2, ▪ Expected population increase in each urban development project be added in the TAZ it’s located to become the final distribution of future population in TAZ. The final population in each TAZ is then used to recalculate the growth rate by TAZ to be used as growth rate for the next period. The same process is then applied for all 4 periods.

Department of Rail Transport Final Report 2-42 Source: Consultant, 2023 Figure 2.2.1-9 Framework for fut

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) ture population distribution

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-43 Source: Complied by consultant, 2023 Figure 2.2.1-10 New Population Increase from large-scale urban development projects in Step 1 Source: Consultant, 2023 Figure 2.2.1-11 Additional growth rate by density from formulas for sub-district with and without railway station in Step 2

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-44 Source: Consultant, 2023 Figure 2.2.1-12 Additional population growth rate based on green area designated in comprehensive plan for sub-district without railway station in Step 2 (2) Results of Future Population in the Study Area Followig the 3 steps framework to prepare future population, the results of future population distribution by TAZ in the study area in 4 targeted years of 2025, 2030, 2035, and 2040 are shown in Figure 2.2.1-13 and Figure2.2.1-14 respectively. Based on population distribution by TAZ for the next 20 years, when comparing with base-year distribution, the results show that in general, the study area will accommodate more population. However, it is the suburb area of Bangkok and the vicinities, which will experience population increase while the central area of Bangkok will not. However, the trend of population density by TAZ, 2025-2040, shows that the TAZs with high population density (higher than 10,000 persons/sq.km.) will still be concentrated in the central area of Bangkok although will have dispersed around more toward the vicinities in later years. The number of TAZs with population density higher than 4,000 persons/sq.km. will increase covering wider area surrounding the center in all direction and continuing to the surrounding provinces. In addition, the areas with population density between 2,000-4,000 persons/sq.km. will also increase in the similar pattern. These results of future population in conjunction with future students and 3 employment sectors will affect the future transportation planning in the study area and be crucial data to be applied for transportation model.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-45 Source: Consultant, 2023 Figure 2.2.1-13 Distribution of future population by TAZ in the study area, 2025-2040 Source: Consultant, 2023 Figure 2.2.1-14 Future population density by TAZ in the study area, 2025-2040

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-46 2.2.1.3 Employment 1) Analysis and estimation of base-year employment The employment data used for employment analysis that affects trip behaviors in this study is classified into 3 economic sectors, which are agricultural, industrial, and service sectors. The data sources of these 3 employment sectors rely mostly on statistic employment data from National Statistical Office (NSO) and GIS based data such as existing land uses and building uses from Department of City Planning and Urban Development, BMA (CPUD) for Bangkok and land uses from Land Development Department (LDD) for the vicinities as shown in Table 2.2.1-6. Table 2.2.1-6 Data characteristics and sources used for base-year employment in the study area Available Data Level Source Remarks Employment by sector (registered & nonregistered) (2011, 2015 & 2019) Province National Statistical Office (NSO) Statistic data used as control number for 3 employment sectors Building Uses (Bangkok) (2015) TAZ Department of City Planning and Urban Development, BMA (CPUD) GIS based data with x,y coordiates Land Uses (Bagnkok & Vicinities) (varies 2015-2021) TAZ Land Development Department (LDD) GIS based data with x,y coordiates Industrial Employment (registered only) (2015 & 2019) TAZ Department of Industrial Works (DIW) Statistic data and GIS based with x,y coordiates Source: Consultant, 2023 However, some details of employment sub-categories related to the above 3 employment secotrs from both statistic and land use data need to be integratedly adjusted to fit with one another at all level of planning data analyses as shown in Table 2.2.1-7 and Figure 2.2.1-15 respectively. For examples, the employment in transportation and storage, categorized as service sector employment by NSO, is switched to industrial sector, while that in construction and wholesale is switched from industrial to service. In addition, there is limitation of land use data from LDD to be used for employment analysis, especially in service sector. This is because land use data is collected and categorized as one use on each land plot. If there is only one small service building on a large plot, the whole plot is categoried as service land use. Agricultural and industrial land uses are not as much affected by this limitation. Therefore, methodology to estimate base-year employment in TAZs for 3 sectors will be different and so be described separatedly.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Table 2.2.1-3 The number of employments by seSource: NSO, adjusted to fit with land use catagories by consultant, 2023 Source: Land Development Department (LDD), varies 2015-2021 Figure 2.2.1-15 Land use classification for 3 econoSECTOR กทม. สมทุรปราการ นนทบุรี ปทมุธานพีระนครศรอียธุยฉาะเชงิเทรา นครปฐม สมทุรสาคร กทม. สมทุรปราการ นนทบุรีTOTAL 3,863,860 778,552 521,614 492,460 427,591 405,415 584,663 361,331 5,298,088 1,291,064 891,41417,565 24,870 19,577 45,722 68,936 126,045 143,597 37,801 40,930 14,311 28,3641. Agriculture, forestry and fishing 17,565 24,870 19,577 45,722 68,936 126,045 143,597 37,801 40,930 14,311 28,3641,043,517 442,712 135,026 212,461 191,696 137,625 177,481 202,430 1,582,333 745,677 240,0212. Mining and quarrying 1,869 1,242 0 0 703 0 0 1,994 5,453 918 919 3. Manufacturing 733,291 384,290 97,986 183,464 167,456 119,858 160,110 177,740 1,069,903 642,969 170,4854. Electricity, gas, steam and air conditioning supply 7,226 1,239 8,678 578 2,272 650 1,216 645 18,988 1,223 11,7745. Water supply; sewerage, waste management and remediation activities 13,388 853 338 839 2,523 1,648 1,066 1,611 12,875 1,327 1,9648. Transportation and storage 287,743 55,088 28,024 27,580 18,742 15,469 15,089 20,440 475,115 99,241 54,8782,802,778 310,970 367,011 234,277 166,959 141,745 263,585 121,100 3,674,825 531,076 623,0306. Construction 175,522 22,840 23,731 24,435 23,024 15,284 29,632 15,621 266,585 52,269 66,1047. Wholesale and retail trade; repair of motor vehicles and motorcycles 925,147 98,318 112,643 77,444 56,303 50,668 106,947 51,072 1,186,775 181,896 189,3459. Accommodation and food service activities 547,160 59,458 33,217 45,323 22,659 32,139 38,177 24,559 541,528 87,732 73,81510. Information and communication 75,760 2,093 15,789 4,849 786 182 3,508 339 131,398 9,780 23,52811. Financial and insurance activities 135,596 6,242 19,177 5,138 3,041 2,263 3,920 1,431 220,510 15,188 32,30112. Real estate activities 50,695 6,784 2,520 4,621 933 835 2,359 428 92,818 18,053 10,79413. Professional, scientific and technical activities 135,734 6,379 11,300 1,785 446 292 5,722 1,015 180,230 9,773 32,67014. Administrative and support service activities 142,084 26,115 14,358 13,209 9,157 8,174 8,057 3,559 222,953 47,869 22,22015. Public administration and defence; compulsory social security 148,861 20,904 62,745 22,201 20,734 9,905 20,273 5,349 212,173 23,645 69,32916. Education 121,419 18,728 27,745 12,973 13,374 8,276 16,538 3,398 166,853 18,451 36,15217. Human health and social work activities 75,579 7,766 12,227 7,548 5,731 4,831 11,727 6,427 118,798 14,809 22,52618. Arts, entertainment and recreation 28,550 11,576 3,798 6,997 2,827 1,533 3,422 2,017 40,623 8,663 3,84719. Other service activities 127,809 16,431 14,348 6,981 6,205 5,990 11,016 4,822 141,855 29,267 26,08820. Activities of households as employers; undifferentiated goods and services-producing activities of households for own use 94,248 4,039 9,837 773 1,739 1,373 2,287 1,063 101,600 6,287 11,30721. Activities of extraterritorial organizations and bodies 3,762 0 0 0 0 0 0 0 1,930 0 0 22. Unknown 14,852 3,297 3,576 0 0 0 0 0 48,200 7,392 3,003In service land uses 2,514,394 280,794 329,867 209,069 142,196 125,088 231,666 104,416 3,256,510 465,129 542,615In other land uses 288,384 30,176 37,144 25,208 24,763 16,657 31,919 16,684 418,315 65,948 80,4152011

Department of Rail Transport Final Report 2-47 ector by province in the study area, 2010-2019 omic sectors in the study area 2015 and 2019 ปทมุธานีพระนครศรอียธุยา ฉะเชงิเทรา นครปฐม สมทุรสาคร กทม. สมทุรปราการ นนทบุรี ปทมุธานีพระนครศรอียธุยา ฉะเชงิเทรา นครปฐม สมทุรสาคร 900,999 497,447 425,127 640,029 686,687 5,270,383 1,352,893 949,273 935,855 501,017 435,828 678,701 705,226 59,053 47,194 106,607 112,059 20,665 18,168 21,018 25,417 45,071 46,309 87,371 122,557 59,333 59,053 47,194 106,607 112,059 20,665 18,168 21,018 25,417 45,071 46,309 87,371 122,557 59,333 370,357 240,441 144,595 248,717 458,711 1,488,880 742,868 243,693 345,309 234,603 172,187 274,008 441,203 839 580 628 294 5,616 1,528 408 325 317 1,660 240 361 0 311,567 213,818 127,282 227,075 428,088 958,360 612,867 164,749 262,869 207,218 153,200 253,230 411,439 1,336 2,106 1,279 1,919 144 21,590 1,429 8,238 2,242 1,559 2,309 1,004 1,289 1,271 661 768 522 441 26,565 2,486 1,734 2,552 1,716 2,875 829 1,281 55,344 23,277 14,638 18,908 24,422 480,838 125,678 68,649 77,330 22,450 13,565 18,584 27,195 471,589 209,812 173,926 279,253 207,311 3,763,335 589,008 680,162 545,474 220,105 176,270 282,137 204,691 49,987 29,146 22,099 25,363 18,467 300,488 50,767 62,670 69,350 30,934 27,886 27,372 21,579 162,204 62,419 58,044 115,096 86,043 1,237,165 196,354 204,477 208,094 74,687 57,604 115,105 82,812 70,497 23,323 32,506 51,417 37,256 549,843 117,757 79,417 71,714 35,717 27,356 49,199 36,646 9,013 1,081 794 1,757 2,138 104,175 6,288 19,500 11,879 1,432 275 1,214 1,240 13,535 3,891 3,443 5,068 6,166 209,130 17,079 40,008 19,937 5,935 2,613 6,150 4,738 5,343 1,737 991 1,982 4,100 99,648 11,915 16,397 10,312 3,615 359 2,893 3,887 17,329 1,720 5,083 3,839 4,715 183,393 19,778 31,715 18,277 788 2,148 5,130 4,034 20,737 7,990 6,693 5,392 9,377 228,255 46,591 33,906 23,614 5,202 6,611 11,499 7,671 38,389 34,743 16,168 17,660 11,322 218,060 29,926 72,964 31,047 26,974 16,438 16,210 9,028 27,619 17,482 9,266 24,338 6,264 162,133 30,187 34,293 26,727 14,509 11,578 19,149 10,315 20,718 9,290 6,052 8,118 7,690 95,650 14,776 26,436 15,188 6,311 6,964 9,193 8,192 9,043 4,250 4,213 5,885 2,987 43,445 8,844 9,221 14,810 3,802 4,157 4,884 3,600 21,670 9,648 7,667 11,384 9,135 180,960 26,128 33,254 17,584 8,720 10,151 12,019 9,120 4,839 1,641 907 1,956 1,653 92,465 6,062 8,251 6,268 1,479 631 2,120 1,688 0 0 0 0 0 2,538 328 531 0 0 0 0 0 667 1,451 0 0 0 55,990 6,227 7,124 672 0 1,501 0 140 416,097 177,574 150,919 251,934 187,191 3,311,855 525,625 601,586 469,184 187,692 146,252 252,645 181,284 55,493 32,238 23,006 27,318 20,120 451,480 63,383 78,576 76,290 32,413 30,018 29,492 23,407 2015 2019

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-48 According to the employment data from NSO, the number of emplolyment during 2010–2019 has dramaticly increased in all 3 sectors for all 8 provinces. The growth trend is more obvious between 2010-2015 than between 2015-2019. The service sector contains the highest numbers of employment, accounting for more than 50% of all employment experiencing in all provinces. When comparing province by province, Bangkok has the highest number of employments in all 3 periods and is seconded by Samuth Prakarn. The third ranking has switched back and forth between Nonthaburi, and Prathumthani over the same periods, while Chacheongsao always ranks eight. According to 3 land use types synchronized with NSO’s 3 employment sectors, most of service land use (commercial land use category) is concentrated inside the outer ring road (Motorway No. 9), considered as urbanized area covering Bangkok, Nonthaburi, Samut Prakarn and Pathumthani. The rest are concentrated in the urbanized areas as growth poles of Nakhon Pathom, Samut Sakhon and Phra Nakhon Si Ayutthaya, which normally considered as agricultural provices. (1) Methodology to estimate base-year employment in TAZs • Agricultural Employment The base-year agricultural employment data from NSO, provided at provincial level is allocated to TAZs by applying the ratio of agricultural land use of each TAZ to that of each province it’s located as shown in Figure 2.2.1-16. Source: Consultant, 2023 Figure 2.2.1-16 Estimation framework for base-year employment by TAZ in agricultural sector • Industrial Employment The National Statistical Office (NSO) provide overall number of industrial employments by province. This data includes both registered and non-registered ones. While the Department of Industrial Works (DIW) provides registed industrial employment with location coordinates. So, this data can be allocated to TAZs directly without any estimation. However, the non-registered industrial employment requires estimation similar to that of agricultural sector framework in terms of using the ratio of industrial land use of each TAZ to that of province it’s located. These 2 sets of data combined will provide the estimated total number

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-49 of industrial employment by TAZ. The detail of the estimation framework for industrial employment is shown in Figure 2.2.1-17. Source: Consultant, 2023 Figure 2.2.1-17 Estimation framework for base-year employment by TAZ in industiral sector • Service Employment The estimation framework for service employment is more complicated than that of agricultural and industrial employment. As mentioned before, the land use data for service uses are collected very roughtly covering the whole land plot. For vicinities, this level of data is practically acceptable as most of buildings are not high. But it becomes problematic for metropolitan city like Bangkok, where there are many high-rise buildings many service employment located. So for Bangkok building use is more appropriate. However, it is available for 2015 only. To be able to find the best estimation, 3 different levels of GIS land use data are applied in the assumptions for base-year employment framework as shown in Figure 2.2.1-18. Source: Consultant, 2023 Figure 2.2.1-18 Estimation framework for base-year service employment by TAZ The service employment data by NSO will be used as control number for each province. And this total number will be allocated into service land use and in other land use areas. To be able

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-50 to distribute the in service land use area, 3 different approaches of using GIS data are appropriately applied for 8 provinces (as shown in details in Figure 2.2.1-19) as follows: For Bangkok The service employment by province in 2015 is divided into service land use and in other uses groups. In service land use group, the ratio of building floor area in service uses (by CPUD) of each TAZ to that of Bangkok is used to distribute service employment into TAZs. While in other land uses group, the population ratio of TAZ is used instead. The results of the two group are then combined to be the total of service employment for each TAZ. For Nonthaburi, Prathum Thani, Chacheongsao and Phra Nakorn Sri Ayuthaya For provinces outside of Bangkok, no building floor area is available. Only land use data by LDD is available. However, for these provinces, the accuracy of data is acceptable enough to be used in detail level of sub-district. Thus, it takes several steps to distribute total employment into TAZ. Firstly, the total number of service employment is distributed into district level by using ratio of working age population by district. The number of service employment by district is then be divided into 2 groups, which are in service land use and in other land uses. For in service land use group, the service employment by district is distributed into sub-district by using ratio of service land use area by sub-district. It then be allocated further into TAZ by using population ratio by TAZ. For other land uses group, the distribution from district to TAZs is done by using population ratio by TAZ to that by district. For Nakorn Prathom and Samuth Sakorn Similar to the second group, only land use data by LDD is available. However, for these provinces, the accuracy of data is less acceptable, therefore, is used in district level. After dividing service employment by province into 2 groups, the ratio of service land use by district is used to distribute service employment in service land use group into district. While in other land uses group, the ratio of population by district is used. Then the ratio of population by TAZ is used to distribute service employment from district into TAZs.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-51 Source: Consultant, 2023 Figure 2.2.1-19 Estimation framework for base-year employment by TAZ in service sector

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-52 (2) Results of base-year employment in the study area Following the estimation frameworks above, the result of base-year employment are divided into 3 sectors as follows: • Agricultural Employment According to the provincial employment data by National Statistical Office (NSO) as shown in Table 2.2.1-8, it shows that the total number of agricultural employments in the study area has slightly increased from 331,203 in 2015 to 340,782 in 2019 at the increase rate of 0.72% per year. However, when looking at provincial level, the data shows that 5 out of 8 provinces in the study area, considered as urbanized areas, have experienced a decrease in agricultural employment, especially Bangkok with the annual decrease rate of 18.38 %. While the amount of agricultural employment has increased in vicinities such as Samuth Prakarn, Nakorn Prathom, and Samuth Sakorn. Table 2.2.1-8 Base-year employment in agricultural sector by province in the study area, 2015-2019 Province Employment in Agriculture (person) Annual 2015 2019 Growth Bangkok 40,930 18,167 -18.38% Samuthprakarn 14,310 21,018 10.09% Nonthaburi 28,364 25,417 -2.71% Pathumthani 59,053 45,071 -6.53% Pra Nakorn Sri Ayuthaya (in study area) 25,884 24,764 -1.10% Chacheongsao (in study area) 29,938 24,455 -4.93% Nakornpathom 112,059 122,557 2.26% Samuth Sakorn 20,665 59,332 30.17% TOTAL in Study Area 331,203 340,782 0.72% Source: NSO, compiled by consultant, 2023 When distributing the agricultural employment into TAZs as shown in Figure 2.2.1-20 and Figure 2.2.1-21, the results show that in 2015 most of the agricultural employment are concentrated in the vicinities, especially Nonthaburi, Prathumthani, and Pra Nakorn Sri Ayuthaya. In addition, only suburban areas of Bangkok such as Bangkhuntian and Nongchok districts, where agricultural lands can still be seen, have high agricultural employment density in 2015 but the density has decreased in 2019. While Samuth Sakorn, where fish farming is highly concentrated, is the only province, which has experienced an increase trend in agricultural employment density from 2015 to 2019.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-53 Sources: Consultant, 2023 Figure 2.2.1-20 Estimated distribution of gricultural employment by TAZ in the study area, 2015 and 2019 Sources: Consultant, 2023 Figure 2.2.1-21 Estimated agricultural employment density by TAZ in the study area, 2015 and 2019 • Industrial Employment After following the estimation framework mentioned earlier, the results show that the total number of industrial employments in the study area has slightly decreased from 3,975,658 in 2015 to 3,871,688 in 2019, at the annual rate of -0.66% as shown in Table 2.2.1-9. When looking at the result by province, only Nonthaburi, Chacheongsao (in study area), and Nakorn Prathom has experienced a slight increase. Nakorn Prathom has the highest growth rate of 2.45% per year. In general, there are more industrial employment in other industrial businesses than registered business with Department of Industrial Works (DIW).

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-54 Table 2.2.1-9 Industrial employment by province in the study area, 2015-2019 Province 2015 2019 Annual Growth Rate Employment in registered business (DIW)* Employment in other industrial businesses TOTAL Employment in Industrial Sector** Employment in registered business (DIW)* Employment in other industrial businesses TOTAL Employment in Industrial Sector** Bangkok 528,339 1,053,993 1,582,332 500,372 988,508 1,488,880 -1.51% Samuthprakarn 493,906 251,771 745,677 468,262 274,606 742,868 -0.09% Nonthaburi 82,586 157,435 240,021 75,730 167,963 243,693 0.38% Prathumthani 228,252 142,105 370,357 235,685 109,624 345,309 -1.74% Pra Nakorn Sri Ayuthaya (in study area) 195,153 12,453 207,606 207,184 - 207,184 -0.05% Chachoengsao (in study area) 119,280 2,957 122,237 106,242 22,301 128,543 1.27% Nakornpathom 161,746 86,971 248,717 171,307 102,701 274,008 2.45% Samuthsakorn 325,562 133,149 458,711 351,088 90,114 441,202 -0.97% TOTAL (study Area) 2,134,824 1,840,834 3,975,658 2,115,870 1,755,818 3,871,688 -0.66% Sources: Analyzed by consultant, 2023 * Department of Industrial Works (DIW), compiled by consultant, 2023 ** National Statistical Office (NSO), compiled by consultant, 2023 When distributing into TAZs by using the ratio of industrial land uses as shown in Figure 2.2.1-22, the result is similar in that the vicinities have higher number of industrial emjployments especially Nakorn Prathom, Samuth Prakarn, Chacheongsao and Pra Nakorn Sri Ayuthaya, where many factories are concentrated. However, to be more accurately comparable, the industrial employment density by TAZ is mapped as shown in Figure 2.2.1-23. It shows very small differences in densities between the 2 periods, a little lesser density in the central area of Bangkok and a little higher density in some part of Samuth Sakorn and Phra Nakorn Sri Ayuthaya. Sources: Consultant, 2023 Figure 2.2.1-22 Estimated distribution of industrial employment by TAZ in the study area, 2015 and 2019

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-55 Sources: Consultant, 2023 Figure 2.2.1-23 Estimated industrial employment density by TAZ in the study area, 2015 and 2019 • Service Employment Based on the estimation framework mentioned earlier, the total number of service employments in the study area has slightly decreased from 6,023,482 in 2015 to 6,311,461in 2019, at the annual rate of 1.17% as shown in Table 2.2.1-10. Only Samuth Sakorn experiences the slightly decrease in service employment. Bangkok is considered the largest concentration of service employment in the study area as expected with the service employment of 3,763,335, accounting for 59.62 %. Table 2.2.1-10 Service employment by province in the study area, 2015-2019 Province 2015 2019 Annual Growth Rate Employment in Service Land Use Employmen t in Other Land Uses TOTAL Service Employment* Employment in Service Land Use Employmen t in Other Land Uses TOTAL Service Employment* Bangkok 3,256,510 418,315 3,674,825 3,311,855 451,480 3,763,335 0.60% Samuthprakarn 465,129 65,948 531,076 525,625 63,383 589,008 2.62% Nonthaburi 542,615 80,415 623,030 601,586 78,576 680,162 2.22% Pathumthani 416,097 55,493 471,589 469,184 76,290 545,474 3.71% Pra Nakorn Sri Ayuthaya (in study area) 136,277 18,669 154,946 144,490 18,757 163,246 1.31% Chacheongsao (in study area) 68,819 12,632 81,452 66,906 16,502 83,409 0.60% Nakornpathom 251,934 27,318 279,253 252,645 29,492 282,136 0.26% Samuthsakorn 187,191 20,120 207,311 181,284 23,407 204,690 -0.32% TOTAL in Study Area 5,324,572 698,910 6,023,482 5,553,575 757,886 6,311,461 1.17% Sources: Analyzed by consultant, 2023 * National Statistical Office (NSO), compiled by consultant, 2023 When distributing the total number of service employments by province into TAZs according to the estimation framework, the results are shown in Figure 2.2.1-24. Large TAZs in Nakorn Prathom, Phra Nakorn Sri

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-56 Ayuthaya and Chacheongsao and smaller TAZs in Samuth Prakarn and Samuth Sakorn have high numbers of service employment. Sources: Consultant, 2023 Figure 2.2.1-24 Estimatied distribution of service employment by TAZ in the study area, 2015 and 2019 However, to be more accurately comparable, the service employment density by TAZ is mapped as shown in Figure 2.2.1-25. The areas with higher service employment density are concentrated inside the outer ring road (Motorway No.9), covering the central area of Bangkok and continuing to Nonthaburi, Prathumthani and Samuth Prakarn. The rest is concentrated in the urbanized area of Samuth Sakorn and Nakorn Prathom. Parts of Pra Nakorn Sri Ayuthaya and Chacheongsao within the study area have service employment density lower than 1,000 persons/sq.km. While the central area of Bangkok has service employment density of more than 10,000 persons/sq.km. and spreaded out to the surrounding with lesser density. This pattern is quite similar to population. In 2015, there are 4 TAZs with service employment density higher than 150,000 persons/sq.km., while the number has increased to 7 in 2019. These TAZs are located in Bangkok. Sources: Consultant, 2023 Figure 2.2.1-25 Estimated service employment density by TAZ in the study area, 2015 and 2019

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-57 2) Analysis and Estimation of Future Employment (1) Methodology to estimate future employment in TAZs Due to the limitation and difference of employment data available in 3 sectors by TAZ l, different framework to estimate future employment is necessary in order to provide reliable and acceptable numbers used for transportation planning purposes. The first step is to find the acceptable and reliable control number or growth rate of future employment by province, but there is no such data available for all 8 provinces. Therefore, several related data sets are used as shown in Table 2.2.1-11 and two different procedures are proposed (as shown in Figure 2.2.1-26 as follows: • Bangkok and 5 vicinities The Department of Public Works and Town & Country Planning (DPT) has completed the latest Bangkok Metropolitan Region Plan (BMR Plan) covering Bagnkok and 5 vicinities (Nonthaburi, Samuth Prakarn, Prathumthani, Nakorn Prathom, Samuth Sakorn). The plan includes the forecast of employment by sectors from 2020-2037 to be used for future land use plan. Thus, this study applies the annual growth rate of the forecasted employment of this plan during 2020-2037 and extend the growth rate for the last 5 years (2032- 2037) to be used for 2038-2040. • Phra Nakorn Sri Ayuthaya and Chacheongsao These 2 provinces are outside of BMR plan, thus do not have controlled employment growth rate to be used. The growth rate of NESDC’s working age population forecast (25-59 years old) is an acceptable alternative to be used for total employment. It is then distributed to 3 sectors by using annual growth rate of each sector from 2015-2019 trend and is adjusted to meet the proportion ratio. Table 2.2.1-11 Available data for future employment estimation by province Available Data Level Source Remarks Employment by Sector (2017-2037) BMR plan (BKK & Vicinities) Province DPT • Use as control growth rate • Available for BKK and 5 surrounding provinces Population Forecast: Working age group (25-59 years old) (2010-2040) Province NESDC • Use as control number /control growth rate • Use for Ayuthaya & Chacheongsao employment forecast Source: Complied by consultant, 2023

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-58 Sources: Consultant, 2023 Figure 2.2.1-26 Framework for future employment by province by sector The next step is to distribute employment by sector from provincial level to TAZs. Two different frameworks are proposed for 3 employment sectors as follows. • Agricultural and Industrial Employment For Agricultural and industrial employment, which is simple comparing to service employment, using the trend of employment growth rate by TAZ is sufficient to distribute the provincial numbers of future employment directly into TAZs. However, the resulting numbers are then be proportionately adjusted to fit with the control total by province. The details of the estimation framework for agricultural and industrial employments are shown in Figure 2.2.1-27. Sources: Consultant, 2023 Figure2.2.1-27 Estimation framework for future employment by TAZ in agricultural and industrial sectors • Service Employment It takes several steps to distribute future employment into TAZs as shown in Figure 2.2.1-28. The details for each step are described below.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-59 Sources: Consultant, 2023 Figure 2.2.1-28 Estimation framework for future employment by TAZ in service sector Step 1: Service employment by province The impact of large urban development projects on service employment is at provincial level, therefore, the increase of service employment from them are substracted from the total numbers at the expected opening year. The resulting numbers are used as control total of service employment for each province at 4 periods of 2025, 2030, 2035, and 2040. The details of large-scale urban development projects including building area dedicated for service uses, projected service employment, their locations, and the expected opening year are shown in Figure 2.2.1-29. Source: Complied by consultant, 2023 Figure 2.2.1-29 New service employment increase from large-scale urban development projects Step 2: Service employment by sub-district To distribute future service employment at provincial level from Step 1 into sub-district level, the trend growth rate by sub-district (2015-2019) is applied to calculate future service employment in each sub-district. The sums of furture service employment in sub-districts are then proportionately adjusted to fit with

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-60 control service employment number by province. The service employment growth rate by sub-district is then recalculated to be used as service employment growth rate for the next period. The same process is then applied for all 4 periods. Step 3: Service employment by TAZ To distribute future service employment in sub-districts from Step 2 into TAZs, the ratio of service employment by TAZ is applied to calculate the future service employment in TAZ, of which the sum is then adjusted proportionally to fit with sub-district service employment in Step 2. In addition, the expected service employment increase in each urban development project is added in the TAZ, where it is located to become the final distribution of future service employment in TAZ. The final service employment by TAZ is then used to recalculate the growth rate by TAZ to be used as growth rate for the next period. The same process is then applied for all 4 periods. (2) Results of future employment in the study Area Following the framework for future employment by province by sector in Figure 2.2.1-26, the result is shown in Figure 2.2.1-30. Source: Analyzed by consultant, 2023 Figure 2.2.1-30 Future employment by province in the study area The overall number of employment will increase from 10,523,930 in 2019 to 11,442,399, 12,668,090, and 12,511,895 in 2025, 2030, and 2035 respectively and then decrease to 11,515,319 in 2040. The total number by province show similar trend. When focusing on employment sector by province as shown in Figure 2.2.1-31, the result shows that most provinces will experience the increasing ratio of service employment 2011 2015 2019 2025 2030 2035 2040 TOTAL Employment Bangkok 3,863,860 5,298,088 5,270,383 5,751,526 6,495,727 6,517,526 6,076,224 Samuthprakarn 778,552 1,291,064 1,352,893 1,434,877 1,464,242 1,348,092 1,167,188 Nonthaburi 521,614 891,414 949,273 1,032,422 1,174,697 1,218,555 1,188,078 Prathumthani 492,460 900,999 935,855 1,038,435 1,153,841 1,101,351 960,500 Pra Nakorn Sri Ayuthaya (in study area) 326,323 388,436 395,194 385,144 371,587 357,097 337,200 Chachoengsao (in study area) 239,538 233,627 236,406 246,748 250,169 251,030 254,423 Nakorn prathom 584,663 640,029 678,701 785,929 895,972 882,318 794,228 Samuthsakorn 361,331 686,687 705,225 767,318 861,855 835,926 737,477 Total 7,168,341 10,330,343 10,523,930 11,442,399 12,668,090 12,511,895 11,515,319 - 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 14,000,000

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-61 up to the point where it overcomes the other 2 sectors in 2040, except for Samuth Sakorn, where industrial employment will still dominate. Samuth Prakarn, Phra Nakorn Sri Ayuthaya and Chacheongsao, where currently dominated by industrial employment, will be defeat by service employment in the future. While agricultural employment plays a very small role in employment as expected, and even gradually declines its proportion in the future. Source: Analyzed by consultant, 2023 Figure 2.2.1-31 Distribution of employment by sector by province in the study area Based on estimation framework for future employment by TAZ in 3 sectors, the results are explained in 3 sectors as follows: • Agricultural Employment The distribution and density of future agricultural employment by TAZ are shown in Figure 2.2.1-32 and Figure 2.2.1-33 respectively. The results show that all provinces will have gradually fewer agricultural employments in the future. The average density of agricultural employment will decrease from 35 persons/sq.km. in 2019 to 33, 31, 28, and 25 persons/sq.km. in 2040. The main areas where agricultural employments are concentrated at the density higer than 2,000 persons/sq.km. are mostly in Samuth Sakorn, where many fish farmings are located. Employment 2025 Employment 2030 Employment 2035 Employment 2040 Agricultural Industrial Service Total Agricultural Industrial Service Total Agricultural Industrial Service Total Agricultural Industrial Service Total Bangkok 16,348 1,329,590 4,405,589 5,751,526 14,591 1,169,704 5,311,432 6,495,727 12,710 995,631 5,509,185 6,517,526 10,963 829,749 5,235,512 6,076,224 Samuthprakarn 22,502 760,777 651,597 1,434,877 21,558 703,406 739,278 1,464,242 19,469 612,658 715,964 1,348,092 17,214 517,780 632,195 1,167,188 Nonthaburi 22,980 209,923 799,519 1,032,422 20,612 182,447 971,639 1,174,697 17,991 153,694 1,046,870 1,218,555 15,540 126,924 1,045,615 1,188,078 Prathumthani 41,603 383,930 612,903 1,038,435 37,484 423,565 692,792 1,153,841 32,755 394,322 674,274 1,101,351 28,303 329,632 602,565 960,500 Pra Nakorn Sri Ayuthaya (in study area) 21,969 195,814 167,360 385,144 19,568 183,859 168,161 371,587 17,336 171,705 168,057 357,097 15,069 157,338 164,793 337,200 Chachoengsao (in study area) 14,075 125,451 107,222 246,748 13,174 123,782 113,213 250,169 12,186 120,704 118,140 251,030 11,370 118,714 124,339 254,423 Nakorn prathom 120,529 322,311 343,089 785,929 112,504 387,803 395,665 895,972 100,690 397,174 384,454 882,318 88,643 365,616 339,969 794,228 Samuthsakorn 63,054 505,475 198,789 767,318 62,196 595,775 203,883 861,855 58,229 591,347 186,350 835,926 53,352 524,681 159,444 737,477 Total 323,061 3,833,271 7,286,067 11,442,399 301,686 3,770,341 8,596,063 12,668,090 271,366 3,437,236 8,803,294 12,511,895 240,452 2,970,435 8,304,432 11,515,319 Province

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-62 Sources: Consultant, 2023 Figure 2.2.1-32 Distribution of future agricultural employment by TAZ in the study area, 2025-2040 Sources: Consultant, 2023 Figure 2.2.1-33 Future agricultural employment density by TAZ in the study area, 2025-2040

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-63 • Industrial Employment The distribution and density of future industrial employment by TAZ are shown in Figure 2.2.1-34 and Figure 2.2.1-35 respectively. The results show that the number of industrial employments will continue to slightly reduce in all provinces until 2040. The average density of industrial employment will decrease from 370 persons/sq.km. in 2019 to 366, 360, 328, and 284 persons/sq.km. in 2040. It is clearly seen in Figure 2.2.1-35 that in 2040 the main areas where industrial employments most concentrated will be mainly on the western side of the study area in Samuth Sakorn and Nakorn Prathom and some small areas dispersed in other provinces. While most of the areas including the central area of Bangkok and the eastern side of the study area will have industrial employment density of lower than 500 persons/sq.km., except for areas where industrial estate located. Sources: Consultant, 2023 Figure 2.2.1-34 Distribution of future industrial employment by TAZ in the study area, 2025-2040

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-64 Sources: Consultant, 2023 Figure 2.2.1-35 Future industrial employment density by TAZ in the study area, 2025-2040 • Service Employment The distribution and density of future service employment by TAZ are shown in Figure 2.2.1-36 and Figure 2.2.1-37 respectively. The total number of service employment will increase from 7,286,067 in 2025 to 8,596,063, 8,803,294 in 2030 and 2035 respectively and then decrease to 8,304,432 in 2040 similar to the overall employment trend. The average density of service employment will increase from 602 persons/sq.km. in 2019 to 691, 809, and 826 persons/sq.km. in 2025, 2030, and 2035 respectively and then decrease to 778 persons/sq.km. in 2040. The most concentrated service employment areas will continue to be inside the outer ring road, the urbanized area of Bangkok Metropolitan Rigion (BMR) and will disperse along main roads to vicinities, especially Nonthaburi, Prathumthani and Samuth Prakarn. When comparing by TAZ, in 2040, there are 10 TAZs, which have service employment greater than 100,000 persons and 6 of them are located in Bangkok, including TAZ 755, 149, 766, 751, 802, and 147. Amoung them, TAZ 755 located in Thanon Pyathai Sub-district, Rachthewi District, considered as part of CBD of Bangkok has the highest number, with more than 350,000 persons expected in all 4 periods. The other 4 TAZs, including TAZ 1564, 1563, 1170, 1167 are in Prathuthani and Samuth Prakarn.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-65 Sources: Consultant, 2023 Figure 2.2.1-36 Distribution of future service employment by TAZ in the study area, 2025-2040 When service employment densities are compared, in general over the 4 periods from 2025 to 2040, the overall density pattern stay mostly the same except for some TAZs with obvious increases in density after 2025. However, some areas start to see a decline in density after 2030 responding to the overall declining trend. In 2040, there will be around 40 TAZs with service employment density higher than 50,000 persons/sq.km., and most of them are located in Bangkok. Some are expected to be dispersed to the surrounding provinces such as Prathumthani and Samuth Prakarn. This number has increased from 29, 36, in 2025, and 2030 respectively, but decreased from 42 in 2035, the highest year. It is also expected that in 2040 there will be 10 TAZs with service employment density higher than 150,000 persons/sq.km., 5 TAZs increase from 2019, and . They all are located in Bangkok.

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-66 Sources: Consultant, 2023 Figure 2.2.1-37 Future service employment density by TAZ in the study area, 2025-2040 2.2.1.4 Number of Students 1) Analysis and Estimation of Base-year Student The areas where shools are concentrated can affect the surrounding traffic especially during shool pick up hours. This is therefore the crucial data to be considered for transportation planning and is another factor used for transportation model. Within the study area, there are only 2 sources of data available on number of students, which are as follows: • National Education Information System (NEIS) for students lower than higher education level (including kindergarten, primary school, secondary school, high school) • Ministry of Higher Education, Science, Research and Innovation (MHESRI) for college and university level. (1) Methodology to estimate base-year students in TAZs The above student data are statistic data based on school locations (location-based), which can be spatially joined in GIS to allocate the exact number of students in TAZs. However, it is found that only the school data of 2015 has x, y coordinates, which can be joined in GIS. Due to this limited data available, only 2015 data can be only base-year for students. Thus, it requires student estimation for year 2019 to be able to calculate the student growth trends used for future student distribution.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-67 The assumptions for student estimation in 2019 are as follows: • Student distribution will be the same as of 2015 • The increase/decrease of students in TAZs are in line with population growth in TAZs Based on the above assumptions, the ratio of 2015’s actual students to NESDC’s 2015 student age population (age 5-24 years old) is calculated. It is then multipied to NESDC’s 2019 student age population to get the estimated number of students in 2019. (2) Results of base-year employment in the study area The actual and estimated students by province are shown in Table 2.2.1-12. The distribution of students by TAZ and student density by TAZ are shown in Figure 2.2.1-38 and Figure 2.2.1-39 respectively. The results show that the overall number of students decreases from 3,158,259 in 2015 to 2,993,640 in 2019, responding to the same ratio of the decrease trend of student age population. Bangkok has the ratio of 2015 students to NESDC’s 2015 student age population of 115.22%. This implies that Bangkok accommodates more students than its student age population from the vicinities. While Samuth Prakarn, with ratio of actual students to that of student age population of only 54.02%, does not provide enough shools to accommodate its student age population. When looking at the student density, the results show that in both periods, the area with high student density are concentrated in the central area of each province similar to population density. Bangkok has still covered most of the TAZs with high student density. This is due to the fact that there are many famous schools located in Bagnkok. TAZ 117, is for an example, located in Hua Mark Sub-district, Bang Kabi District, has the highest number of students of 262,529 in 2019. It is where several primary and secondary schools and Ramkamhaeng University are located. It is also considered as the densest TAZ of students in the study area. Table 2.2.1-12 Base-year Students by province in the study area in 2015 and 2019 Province NESDC’s Student Age Group (5-24 years old) * % of 2015 students to NESDC’s 2015 student age population Actual students** Estimated students*** 2015 2019 2015 2019 Bangkok 1,592,500 1,495,900 115.22% 1,834,912 1,723,607 Samuthprakarn 410,619 394,316 54.02% 221,829 213,022 Nonthaburi 313,355 300,878 86.85% 272,162 261,325 Prathumthani 304,748 293,559 93.95% 286,302 275,790 Pra Nakorn Sri Ayuthaya (in study area) 142,315 136,993 98.79% 140,591 135,333 Chacheongsao (in study area) 102,125 103,915 90.78% 92,711 94,336 Nakornpathom 208,871 195,340 106.12% 221,648 207,289 Samuthsakorn 155,465 146,347 56.67% 88,104 82,937 TOTAL 3,229,997 3,067,247 97.78% 3,158,259 2,993,640 Source: * NESDC, complied by consultant, 2023 ** National Education Information System (NEIS) and Ministry of Ministry of Higher Education, Science, Research and Innovation (MHESRI), and compiled by the consultant, 2023 *** Calculated by consultant, 2023

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-68 Source: Consultant, 2023 Figure 2.2.1-38 Distribution of students by TAZ in the study area in 2015 and 2019 Source: Consultant, 2023 Figure 2.2.1-39 Student density by TAZ in the study area in 2015 and 2019 2) Analysis and Estimation of Future Students (1) Methodology to estimate future students in TAZs As mentioned earlier that only the school data of 2015 has x, y coordinates, therefore, it can be accurately shown at TAZ level. And it requires estimation for year 2019 to be able to calculate the student growth trends used for future student distribution. The same estimation framework is applied for future students under the assumptions that student distribution will be the same as of 2015 and the increase/decrease of students in TAZs are in line with population growth in TAZs for each period. The details of the estimation framework are as shown in Figure 2.2.1-40.

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-69 Source: Consultant, 2023 Figure 2.2.1-40 Estimation framework for future students by TAZ in the study area, 2025-2040 The details for each step are described below. • The ratio of 2015’s actual students to NESDC’s 2015 student age population (age 5-24 years old) is used to be multipied to NESDC’s 2025 student age population to get the estimated number of students in 2025. • The differences numbers of students between 2025 and 2019 will then be distributed by population growth rate by TAZ between 2019-2025 (2) Results of future students in the study area Based on the above framework, the results of total future and base-year students are shown in Figure 2.2.1-4. Overall number of stuents will continue to decline from 2019 until 2040 according to the decline of student age population forecasted by NESDC for the same periods. The number of students in the study area decreases from 2,993,640 in 2019 to 2,918,960, 2,858,543, 2,784,070, and 2,458,130 in 2025, 2030, 2035, and 2040 respectively. It is noted that the decline is more obvious from 2035 to 2040, similar to that of population. And all provinces in the study experience the same declining trend.

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-70 Source: Consultant, 2023 Figure 2.2.1-41 Future students by province in the study area When distributing future student numbers of all 4 periods into TAZ as shown in Figure 2.2.1-42, the distribution patterns are quite the same. The TAZs with number of students higher than 20,000 are mostly located in Bangkok and the rest are spreaded out into Nonthaburi, Prathumthani, Samuth Prakarn, and Nakorn Prathom. TAZ 117 will still have the highest number of students in the future, although gradually decline from 257,787 in 2025 to 254,481, 250,181, and 213,379 in 2030, 2035, and 2040 respectively. The stuent density maps as shown in Figure 2.2.1-43 explain a clearer concentration of students. In overall, the density pattern will stay mostly the same for 4 periods. Bangkok will have student density of 221,396, 218,557, 214,864, and 183,257 students /sq.km. in 2025, 2030, 2035, and 2040 respectively. This is due to the decline trend of student age population in all provinces. Most of TAZS with student density of higher than 1,000 students/sq.km. are located inside the outter ring road. And Bangkok will still have the most concentration of students in the study area. In 2025 there will be 48 TAZs with student density higher than 20,000 students/sq.km, decresing from 68 in 2019. All of them are still located in Bangkok. While in 2030, 2035, and 2040, the number will reduce to 27. 2015 2019 2025 2030 2035 2040 Bangkok 1,834,912 1,723,607 1,693,650 1,668,301 1,636,154 1,388,542 Samuthprakarn 221,829 213,022 206,993 202,581 196,515 183,777 Nonthaburi 272,162 261,325 253,823 248,282 240,698 224,958 Prathumthani 286,302 275,790 267,218 260,403 251,562 234,443 Pra Nakorn Sri Ayuthaya (in study area) 140,591 135,333 124,684 113,977 103,063 92,782 Chacheongsao (in study area) 92,711 94,336 96,707 98,139 99,422 95,173 Nakornpathom 221,648 207,289 197,391 191,450 184,636 171,966 Samuthsakorn 88,104 82,937 78,495 75,409 72,018 66,490 TOTAL 3,158,259 2,993,640 2,918,960 2,858,543 2,784,070 2,458,130 - 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-71 Source: Consultant, 2023 Figure 2.2.1-42 Distribution of future students by TAZ in the study area, 2025-2040 Source: Consultant, 2023 Figure 2.2.1-43 Future student density by TAZ in the study area, 2025-2040

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-72 2.2.2 Household income The National Statistical Office, Ministry of Digital Economy and Society reported the average monthly income per household from the Household Socio-Economic Survey, it was found that the study area had an average household income about 34,343 baht per month in 2021 with an average growth for the past 10 years of 2.31% per year. Pathum Thani province was the area with the highest growth and Nonthaburi was a highest average household income at present as detailed in Table 2.2.2-1. Table 2.2.2-1 The average monthly household income of study area in 2011-2021 Province Average monthly household income (baht) Average growth 2011 2013 2015 2017 2019 2021 rate Bangkok 48,951 49,191 45,572 45,707 39,459 40,201 -1.95% Samut Prakan 23,798 29,575 25,457 28,712 24,729 32,914 3.30% Nonthaburi 35,120 30,664 36,884 40,861 37,502 41,129 1.59% Pathum Thani 21,616 33,461 41,057 41,484 46,978 39,507 6.22% Nakhon Pathom 22,955 30,856 40,347 32,761 34,436 38,788 5.39% Samut Sakhon 20,850 23,658 29,347 25,446 23,443 27,591 2.84% Phra Nakhon Si Ayutthaya 22,302 26,482 28,379 28,778 30,590 31,416 3.49% Chachoengsao 23,031 34,548 27,555 26,062 22,875 23,196 0.07% Average on Study Area 27,328 32,304 34,325 33,726 32,502 34,343 2.31% Source: The Household Socio-Economic Survey from National Statistical Office, Ministry of Digital Economy and Society, compiled by the consultant, 2023 Forecast of average monthly household income The average household income was collected based on the total income of the households. Therefore, the average monthly household income forecast must be considered in accordance with the changing trend of the Thai economy in the future that tends to increase continuously and coupled with the historical trend of change in average household income in the study area. This causes the higher level on average monthly household income of the study area by an average growth rate at 2.10% per year as shown in Table 2.2.2-2. Table 2.2.2-2 The forecasting results of monthly household income of study area in 2027-2047 Province Average monthly household income forecast (Baht/month) Average 2027 2032 2037 2042 2047 growth rate Bangkok 42,900 47,100 52,000 57,300 63,100 1.95% Samut Prakan 26,900 29,500 32,400 35,600 39,100 1.89% Nonthaburi 40,900 44,900 49,400 54,300 59,700 1.91% Pathum Thani 52,100 57,900 64,500 71,900 80,000 2.17% Nakhon Pathom 38,200 42,200 47,000 52,200 57,900 2.10% Samut Sakhon 25,300 27,500 30,000 32,800 35,700 1.74% Phra Nakhon Si Ayutthaya 34,500 38,600 43,400 48,700 54,600 2.32% Chachoengsao 26,300 30,000 34,400 39,300 45,000 2.72% Average on Study Area 35,900 39,700 44,100 49,000 54,400 2.10% Source: Forecasted by the consultant, 2021

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-73 2.2.3 Number of households and household size According to the 2010 Population and Housing Census by the National Statistical Office, Ministry of Digital Economy and Society found that the study area had approximately 5,643,356 households which Bangkok was the province with the largest number of households about 2,881,752 households, accounting for 51% of the total number of households in the study area. The overall study area was an average household size about 2.9 people per household. In comparative with 2000, it represented an increased in the number of households at an average growth rate of 5.84% per year and a smaller change in household size, it shown the changing of family pattern from extended family to nuclear family and single family as detailed in Table 2.2.3-1. Table 2.2.3-1 Number of households and household sizes in 2000 and 2010 Province Number of households (households) Average growth rate Average household sizes (people/household) 2000 2010 2000 2010 Bangkok 1,743,752 2,881,752 5.15% 3.6 2.9 Samut Prakan 319,939 646,407 7.29% 3.2 2.8 Nonthaburi 234,671 473,689 7.28% 3.5 2.8 Pathum Thani 196,777 519,047 10.19% 3.4 2.6 Nakhon Pathom 210,165 286,312 3.14% 3.9 3.3 Samut Sakhon 136,846 327,953 9.13% 3.4 2.7 Phra Nakhon Si Ayutthaya 192,418 307,760 4.81% 3.8 2.8 Chachoengsao 165,425 200,436 1.94% 3.8 3.6 Study Area 3,199,993 5,643,356 5.84% 3.6 2.9 Source: The 2000 and 2010 Population and Housing Census by National Statistical Office Forecast of household number and household sizes From the change trend of household number and household size, it was analyzed together with the average household size according to registered household size by Department ofProvincial Administration which is the only empirical source of current data can be concluded that the study area will continue to increase of the number of households while the average household size will likely continue to small in the future. The study area will have approximately 8,139,000 households in 2027, increasing at a rate of average 1.62% per year until 2047 that will be approximately 11,224,000 households with a small average household size to 2.06 people per household as the forecasted results in Table 2.2.3-2 and Table 2.2.3-3.

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-74 Table 2.2.3-2 The forecasting results of household number of study area in 2027-2047 Province Household number forecast (households) Average 2027 2032 2037 2042 2047 growth rate Bangkok 3,935,000 4,229,000 4,495,000 4,743,000 5,010,000 1.21% Samut Prakan 1,029,000 1,167,000 1,306,000 1,446,000 1,604,000 2.24% Nonthaburi 787,000 900,000 1,014,000 1,132,000 1,265,000 2.40% Pathum Thani 857,000 969,000 1,081,000 1,195,000 1,322,000 2.19% Nakhon Pathom 422,000 472,000 521,000 570,000 624,000 1.97% Samut Sakhon 474,000 516,000 555,000 592,000 632,000 1.45% Phra Nakhon Si Ayutthaya 358,000 369,000 376,000 379,000 383,000 0.34% Chachoengsao 277,000 303,000 329,000 355,000 384,000 1.65% Study Area 8,139,000 8,925,000 9,677,000 10,412,000 11,224,000 1.62% Source: Forecasted by the consultant, 2021 Table 2.2.3-3 The forecasting results of household sizes of study area in 2027-2047 Province Household sizes forecast (people/household) Average 2027 2032 2037 2042 2047 growth rate Bangkok 2.40 2.27 2.15 2.04 1.93 -1.08% Samut Prakan 2.49 2.40 2.32 2.23 2.15 -0.74% Nonthaburi 2.42 2.31 2.21 2.11 2.02 -0.90% Pathum Thani 2.25 2.16 2.08 2.01 1.93 -0.76% Nakhon Pathom 2.87 2.75 2.64 2.54 2.44 -0.81% Samut Sakhon 2.49 2.43 2.37 2.31 2.26 -0.49% Phra Nakhon Si Ayutthaya 2.55 2.48 2.40 2.33 2.26 -0.60% Chachoengsao 3.21 3.11 3.01 2.92 2.83 -0.63% Study Area 2.46 2.35 2.25 2.15 2.06 -0.88% Source: Forecasted by the consultant, 2021 2.2.4 Economic conditions Due to the situation of Coronavirus outbreak (COVID-19) from year 2020 to the present, the Office of the National Economic and Social Development Council (NESDC) reported that the Thai economy in the second quarter of 2023 was able to increased by 1.8 percent, decelerated from a rise of 2.6 percent in Q1/2023. It is expected that the Thai economy in 2023 will expand in the range of 2.5-3.0 percent, supported by factors from continually high increase of household expenditure, recovery of tourism sector, and continuously expansion of public and private investments. In consideration of long-term expansion trend or in the past 10 years (2010-2020), it shown that Thailand has an average economic growth rate of 2.03% per year and it is expected to grow up in 2023. In addition, there were some economic disruptions in range of year 2011 and 2014 from the internal factors namely,

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-75 great flood situation and political problem situation respectively, which all affected the country's economic condition (As in Figure 2.2.4-1 and Figure 2.2.4-2) Source: Office of the National Economic and Social Development Council Note: Year 2023 is the NESDC’s projection by growth rate in the range of 2.5-3.0 percent Figure 2.2.4-1 Gross Domestic Product value in 2012-2023 (million Baht) Source: Office of the National Economic and Social Development Council Note: Year 2023 is the NESDC’s projection by growth rate in the range of 2.5-3.0 percent Figure 2.2.4-2 GDP growth rate in 2012-2023 (percent per year) 0 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 GDP (MILLION BAHT) -8.00% -6.00% -4.00% -2.00% 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 GDP GROWTH RATE (%ANNUAL)

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-76 2.2.4.1 Thailand Economic Forecast From the situation of the COVID-19 epidemic that has affects the volatility of the Thai economy, therefore, the analysis was divided into 2 ranges: first, the recovery period from the Covid-19 epidemic situation (year 2023and 2024) and second, the returning to normal situation period (after 2025onwards) as the following details: 1) During years 2023 and 2024 During the recovery period from the Covid-19 epidemic situation, there were Thailand economic forecasting from various organizations as shown in Table 2.2.4-1. Table 2.2.4-1 Projections of the Thai economy's recovery from various agencies Organization Projection World Bank The World Bank is expected the economy will accelerate from 2.6% in 2022 to 3.9% in 2023 mainly due to tourism recovery and rebounding from domestic private comsumption with an improved labor market. Public investment will remain weak due to the long transition towards a new government. Thus, the growth rate in 2024 and 2025 are expected to expand at 3.6 percent and 3.4 percent, respectively. Fiscal Policy Office The Thai economy is expected to expand by 3.6 percent in 2023 (within the range of 3.1 to 4.1 percent), received support factors from the continued expanding of private consumption and tourism sector with a declining inflation rate which stimulate increase consumption. Bank of Thailand The Thai economy was projected to expand by 3.6 in 2023 and 3.8 percent in 2024, driven mainly by tourism and private consumption. Meanwhile, merchandise exports are expected to recover gradually. Office of the National Economic and Social Development Council The Thai economy was projected to expand in range of 2.5-3.0 percent in 2023, supported by favorably growth in private consumption, the continued recovery of the tourism sector as well as the continuous expansion of public and private investment. Source: Compiled by the consultant, 2023 2) After 2025 onwards For 2025 onwards, the Thai economy will begin to return to normal situation by expected that the government sector will implement policies to set the economic growth goals and strategize to develop the economy to be more stable. It is specifying an average growth rate that is at the same level as the average growth rate of GDP in the past period from 2009 to 2019 (before the Covid-19 situation) which is about 3.9% per year. Therefore, both the recovery period from the Covid-19 epidemic situation and the period returning to normal as above, it can be summarized as an assumption for forecasting the Thai economic growth as shown in Table 2.2.4-2 and GDP forecasting result as shown in Table 2.2.4-3. Table 2.2.4-2 Summary of the assumptions on GDP growth rate in Thailand Year 2023 2024 2025 onwards GDP growth rate (Annual %) 3.6% 3.8% On average 3.9% Source: Forecasted by the consultant, 2023

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-77 Table 2.2.4-3 Forecast of Thai GDP during 2027-2047 2027 2032 2037 2042 2047 Average growth rate GDP (Million Baht) 13,254,000 16,117,000 19,598,000 23,831,000 28,979,000 3.99% Source: Forecasted by the consultant, 2023 2.2.4.2 The forecast of economic conditions in study area For the forecast of economic conditions in study area, it will be used the forecasted GDP to distribute at the study area level according to the ratio method. The forecasted results can be summarized as shown in Table 2.2.4-4, which can be seen that the study area will have an average overall economic expansion of 3.74% per year and each province having an average growth rate of not less than 2.50% per year. Table 2.2.4-4 The forecasting results of GPPs in study area during 2027-2047 Province GPPs Forecast (Million Baht) Average 2027 2032 2037 2042 2047 growth rate Bangkok 4,748,000 5,724,000 6,897,000 8,304,000 9,992,000 3.79% Samut Prakan 594,000 720,000 873,000 1,058,000 1,281,000 3.92% Nonthaburi 323,000 386,000 461,000 551,000 657,000 3.61% Pathum Thani 356,000 421,000 496,000 585,000 689,000 3.36% Nakhon Pathom 295,000 360,000 440,000 537,000 654,000 4.06% Samut Sakhon 348,000 404,000 469,000 544,000 631,000 3.02% Phra Nakhon Si Ayutthaya 372,000 421,000 477,000 540,000 611,000 2.51% Chachoengsao 372,000 468,000 588,000 739,000 927,000 4.67% Study Area 7,408,000 8,904,000 10,701,000 12,858,000 15,442,000 3.74% Source: Forecasted by the consultant, 2023

The Study for the Development of a Macro Simulation Model for forecastingthe demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-78 2.2.5 Number of registered vehicles From the statistics of the cumulative number of registered vehicles by province as of July 31st from the Department of Land Transport, the study area had a total of 13,170,846 registered vehicles in 2023, increased by an average growth rate at 4.49% per year from 2010. Bangkok was the province with the highest number and growth rate of the cumulative number of registered vehicles as shown in Table 2.2.5-1. For the type of passenger car and motorcycle, the study area had a total of passenger car and motorcycle approximately 11,563,030 units, representing 82% of all types of registered vehicles in the study area. The number of passenger cars was slightly higher at 53 percent from the number of passenger cars in Bangkok and Nonthaburi provinces that accounted for more passenger cars than motorcycles as in Figure 2.2.5-1. Table 2.2.5-1 The cumulative number of registered vehicles of the study area in 2010 - 2023 Province Cumulative number of registered vehicles (units) Average growth rate 2010 2015 2020 2021 2022 2023 (31 Jul 23) Bangkok 6,444,631 9,018,594 10,971,799 11,244,732 11,617,177 11,863,006 4.81% Samut Prakan 129,496 144,767 162,670 166,790 170,823 173,071 2.26% Nonthaburi 160,428 180,441 189,955 188,146 186,029 185,125 1.11% Pathum Thani 122,992 141,506 175,071 177,777 180,263 181,406 3.03% Nakhon Pathom 369,873 457,268 504,023 510,639 518,617 524,974 2.73% Samut Sakhon 177,276 228,087 244,894 247,795 256,536 263,362 3.09% Phra Nakhon Si Ayutthaya 314,887 409,298 496,186 507,689 523,625 533,258 4.14% Chachoengsao 280,719 372,230 426,248 432,354 441,305 445,013 3.61% Study Area 8,000,302 10,952,191 13,170,846 13,475,922 13,894,375 14,169,215 4.49% Source: The Department of Land Transport, compiled by the consultant, 2023 Source: The Department of Land Transport, compiled by the consultant, 2023 Figure 2.2.5-1 Number of registered vehicles on the study area classified by vehicle type in 2023 - 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 Bangkok Samut Prakan Nonthaburi Pathum Thani Nakhon Pathom Samut Sakhon Phra Nakhon Si Ayutthaya Chachoengsao Bangkok Samut Prakan Nonthaburi Pathum Thani Nakhon Pathom Samut Sakhon Phra Nakhon Si Ayutthaya Chachoengsa o Motorcycle 4,196,763 68,129 54,028 77,965 281,097 220,810 278,343 243,134 Passenger car 5,683,163 21,175 66,496 39,463 93,931 11,297 134,340 92,896

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-79 2.3 Current project information M-MAP and M-MAP2Blueprint and related design projects. (TOR 3.1.1) This part of the study aims to determine the guidelines for the development of the rail mass transit network in Bangkok Metropolitan Region. The consultant gathered information about the number of passengers, project type, routes, station, investment value, including the current project status according to M-MAP and the details presented in the M-MAP2 Blueprint and related design studies which contains the following contents: 2.3.1 Review plans for the development of the rail mass transit system in Thailand Concept of development of rail mass transit system in Thailand. Started to exist since 1972, the Thai government at that time was aware of the problem of traffic and transportation congestion. The government therefore asked the German government to send experts to study. and planning to solve traffic and transportation problems in Bangkok which has suggested that the government has a policy to support public transport as the main and proposed to have a mass rapid transit system to solve traffic problems. The government itself has supported and pushed continuously. In 1979, there was a study of the Lavalin project. which is an elevated train construction project in Bangkok It consists of 3 routes and has a construction plan to be completed in 1986, but the work period is very long. Because it had to wait 11 years after the study of the master plan, the construction contract was signed in 1990. In addition, that same year, the Ministry of Transport signed a concession for a road transport system and an elevated railway project. in Bangkok (Hopewell Project) with Hopewell (Thailand) Co., Ltd. Later in 1992, the Lavalin project was canceled due to the problem of the project owner's investment. along with higher costs in terms of expropriation and relocation of utilities The Lavalin electric train project, which was the hope of the Bangkok people at that time, was destroyed. and in the same year Metropolitan Electricity Authority (Mass Rapid Transit Authority of Thailand or MRTA at present) was established to be responsible for the implementation of the mass rapid transit system in Bangkok and its vicinity. Later in 1994, the Cabinet approved in principle the mass transit master plan in Bangkok According to the Mass Transit Master Plan (MTMP) project developed by the Office of the Land Traffic Management Commission or currently OTP. which proposed to develop a 135 km rail mass transit network within 1995-2011, leading to a study of the Conceptual Master Implementation Plan (CMIP) ) along with a proposal to modify and improve the route from the original master plan. A total distance of 178.9 kilometers in 1996 and later a secondary mass transit system was introduced. It consists of an elevated light rail system and a monorail system to support the mass transit system in Bangkok. (main network) to be effective, which has a total of 11 routes, a distance of 206 km. In 1997, Thailand was facing an economic crisis. and the situation of the Bangkok Mass Transit System (BTS), the Metropolitan Rapid Transit Project The first phase of the Chaloem Ratchamongkhon Line and the Hopewell Rail Mass Transit System Development Project The operation has changed and did not go according

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-80 to the original plan. In addition, the economic situation is not conducive to binding on large investments. causing the implementation of the master plan to halt and finally, the Hopewell project was officially canceled in the year 1998. Later, the Cabinet has assigned the Office of the Land Traffic Management Commission or currently OTP to accelerate the study with the relevant agencies. relevant Therefore, the Urban Rail Transportation Master Plan in Bangkok and Surrounding Areas (URMAP) was born in 2000 to be used as the main master plan for the development of rail mass transit systems in Bangkok based on the projects in the master plan. past and recommending a mass transit network with a total distance of 375 km in a period of more than 20 years. Until 2004, the country's economic status began to show signs of improvement. OTP has implemented a project to convert the Master Plan for Rail Mass Transportation in Bangkok and the Continuing Areas (Bangkok Mass Transit Master Plan - BMT) and the Land Traffic Management Committee has approved the principle of the Mass Rapid Transit System Network, Phase 1, by the year 2009, totaling 7 routes with a total distance of 291 kilometers. However, despite the adherence to the plan according to the resolution of the Land Traffic Management Committee as a guideline for the implementation of the project but with the volatility and uncertainty of political policy. As a result, the mass rapid transit project has to fluctuate from time to time. There has been a change in the concept of investment guidelines. and additional routes from the mass transit system network from 7 routes to 10 routes in 2006. But the project is not ready in terms of the design of the project details. That requires a review of the project's socio-economic suitability, study, plan and design the project in accordance with standard guidelines for general infrastructure planning, such as an alternative analysis. environmental impact analysis and social impacts, etc. It is an opportunity for foreigners to participate in the operation of large government investment projects. The mega-project, also known as Thailand: Partnership for Development, has resulted in the implementation of the master plan not being successful as expected. Later in 2007, there was a plan to expedite the construction of 5 mass transit routes in order to push the rail system that is important for urgent development. In 2008, the government has improved the mass rapid transit network in Bangkok and surrounding areas from the original mass transit network. by adding and improving the route line to extend to the suburban area which has developed rapidly which has a total network of 9 routes with a total distance of 311 kilometers. And later in the year 2010, the Ministry of Transport by the Office of Transport and Traffic Policy and Planning (OTP) has prepared a master plan for the rail mass transit system in Bangkok and its vicinity (M-MAP), which defines the system network. Mass transit by rail in Bangkok and its vicinity over a 20-year period (2010 - 2029), totaling 12 routes, divided into 8 main networks and 4 secondary networks with a total distance of 509 kilometers. According to the M-MAP, the context of urban growth has changed. with more expansion in suburban areas There are many residential and commercial areas along the mass transit route. As a result, the travel patterns of people in Bangkok and its vicinities have changed. Therefore, the Ministry of Transport has coordinated with Japan through the Japan International Cooperation Agency (JICA) together with the OTP to support organizing Make directions and policies for developing a master plan for rail mass transit systems in Bangkok and its vicinities (Contiguous area) Phase 2 (M-MAP2Blueprint). And later in the year 2019, the Cabinet resolved to acknowledge

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-81 the Land Traffic Management Committee on January 22, 2019 regarding the results of the M-MAP2 Blueprint study. Introducing 5 additional network routes. The projects and plans for the development of major rail mass transit systems in the past are shown in Figure 2.3.1-1, with details as follows. Source: Consultant, 2021 Figure 2.3.1-1 The development plan of the rail mass transit system in Thailand

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network Department of Rail Transport in Bangkok Metropolitan Region Phase 2 (M-MAP2) Final Report 2-82 For the development plan of the rail mass transit system in Thailand. The details of each plan are shown in Appendix 2A-1 2.3.2 The rail mass transit system according to the M-MAP plan 2.3.2.1 Network planning concept Analysis and conceptualization of mass transit system planning in Bangkok and vicinities as a whole. The model is considered to be in line with the development of the city according to the concept of the overall city planning and the network according to the previous master plan. To ensure continuity in development, including considering the effects of changes in socio-economic conditions, land use, and changing travel patterns and behaviors and the status of the current development, including projects that have been carried out at present and the project has been approved by the Cabinet The issues mentioned above will affect the main factors that are the framework for planning the development of the mass transit network, which include 1) Overview of the network The mass transit system in Bangkok and its vicinities will consist of intercity and urban services with different levels of travel density. The service route consists of being the main mass transit route, the secondary mass transit route and the auxiliary system route with the system model and vehicle type used in the appropriate mass transit varies. Source: M-MAP, OTP. 2010 Figure 2.3.2-1 Mass transit service model

The Study for the Development of a Macro Simulation Model for forecasting the demand for rail travel and the development of a rail mass transit network in Bangkok Metropolitan Region Phase 2 (M-MAP2) Department of Rail Transport Final Report 2-83 2) Coverage Area and Accessibility Because the rail mass transit system is an infrastructure that requires a lot of investment. It would be difficult to establish a main mass transit system to serve people in all areas. Therefore, the service model of the mass transit system for service in urban areas can generally be divided into two types according to the nature of service: ▪ Trunk and Feeder is a model that is suitable for large service areas. There are various directions of travel such as major cities because they will have lower development costs and operating costs. But travelers will have to change the system often. It will be a model that consists of two types of mass transit routes, namely the Trunk Route and the Feeder Route.The Trunk routes will serve to pick up and transport passengers from different areas to the city center. The Feeder route serves to receive and distribute passengers from different areas to the Trunk routes. ▪ Direct Service or Point to Point, it is a form that provides services in the form of picking up - sending passengers from the point of origin to the destination directly. The passengers do not need to change the system during the journey. It is a public transport system that is suitable for small towns or tourist towns. in order to make the service accessible to the general public under a reasonable budget. For the network according to the master plan, M-MAP has adopted the main route - Trunk and Feeder format because it is a suitable system and is consistent with the previous master plan. By allowing the suburban mass rapid transit system (CT) and the mass rapid transit system (MRT) to act as the main mass transit systems in routes with high travel and provide routes for secondary mass transit systems and auxiliary systems on the secondary routes. The main mass transit routes should use a system that is capab le of transporting a large number of passengers. System capacity should be above 30,000 people/hour/direction. Which often choose to use a heavy rail transit system, which has a route through the business center connecting to dense residential areas. While the secondary and auxiliary transit routes serve to transport passengers from areas, there are not enough passengers for the main system. Connect to the main system the system will have lower system capacity than the main system but will also have a lower investment cost. Secondary and auxiliary mass transit systems come in many forms, such as Light Rail Transit (LRT), Bus Rapid Transit (BRT), etc. 3) Network Pattern The rail mass transit network pattern suggested in the M-MAP master plan is consistent with the main concept of the original rail mass transit master plan, namely the radial and circumferential pattern, which is appropriate for the development approach. of Bangkok, a large city that currently has a single center (Monocentric) and plans to develop a commercial center suburban community centers formed around. The radial route serves to transport passengers from the residential areas in the suburbs to the business and commercial areas in the center of the city. while the ring route within the inner city will make it easier to travel