Distributions of Road Spaces in Tokyo Ward Area While Focusing on Pedestrian Spaces

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Distributions of Road Spaces in Tokyo Ward Area While Focusing on Pedestrian Spaces -Toward a Description of Necessary Levels of Roadway Spaces in a Compact City - Sunyong Eom Candidate for PhD Department of Risk Engineering Graduate School of Systems and Information Engineering University of Tsukuba Tsutomu Suzuki Professor Division of Policy and Planning Sciences Faculty of Engineering, Information and Systems University of Tsukuba

c o n t e n t s 01 Introduction 02 Definitions of road spaces 03 Distribution of road spaces 04 Peak analysis of pedestrian spaces 05 Discussion and conclusion 2

Background 01.Introduction Growing needs for compact city Increasing needs to counteract such as global warming, decreases in human population, aging society and the need to conserve resources The compact city is most discussed concept in contemporary urban policy. - Reducing the environmental loads by transportation, revitalizing downtown, reducing infrastructure maintenance expenses GHG emissions by region, 1990-2050 Source : OECD(2012), Compact City Policies Closing shop in downtown(japan) 3

Effect Compact Town Background 01.Introduction Importance of pedestrian space in the compact city Walking and cycling emerges as viable element for the socio-economically and environmentally sustainable city form. - Walking is the cleanest and most natural transportation mode. - Pedestrian space provides more participation and social communication(jou, 2011). Many local government authorities have emphasized the concept of walkable town planning. Accessible town Bustling town Historical and characteristic Town Downtown (urban stock-traffic facilities, infra) Walkable town planning Downtown Regeneration Improve convenience for resident Sustainable city management Reduce environmental overload City planning of downtown development, Ministry of Land, Infrastructure and Transport Greenwich village, New York 4

Background 01.Introduction Shortage of pedestrian space quantity and effective utilization Current urban structure has a high dependence on automobiles. Current pedestrian spaces are not utilized wisely. Pedestrian spaces have been installed according to road class based on automobile flow and not clear standard. Guideline for walkway width in Japan(Road Structure Ordinance) Class of road Year 1970 1982 1993 2001 Class 1 2 Over 3m Over 3m Over 3.5m Class 3 Over 1.5m Class 4 Over 1m Source: Tsuda (2002), Minus Design High pedestrian traffic volume Over 3.5m Over 1.5m Over 2m Other roads Over 2m 5

Purpose of study 01.Introduction Purpose of study Focused on several wards in Tokyo, where pedestrian spaces quite closely resemble the compact city that are envisaged. Ascertaining the distributional characteristics of roadway spaces Contributing to describing our vision for roadway spaces in a compact city 1 Classifying land uses including off ground level spaces 2 Analyzing distributional characteristics of roadway spaces - Total area of roads, distribution analysis by mesh 3 Deriving relations for the pedestrian space with railway stations and building density - Kernel density estimation 6

Land use classification 02. Definitions of road spaces Necessary spaces were created in the third dimension(pedestrian bridge, viaduct). Land use, including off-ground level (OGL) roadway spaces, was classified and areas of roadway categories were calculated. <Land use classification> Viaducts (regular streets, expressways) Pedestrian bridges, decks Ground surface Open Space area Ground level walkways Target area(14wards in Tokyo) OGL space All walkways(pedestrian) OGL walkways All streets(automobile) Underground spaces Tunnels (regular streets, expressways) Building area Ground level streets OGL streets 7

Constructed road space data 02. Definitions of road spaces All roadway spaces were constructed as polygonal data in ArcGIS. - 30% of the total underground area is accounted as pedestrian spaces. Ratio of OGL roadway among all roadway: street-3.5%, walkway-8.8% - OGL spaces are used much more for pedestrians than for vehicles. Road space : 21.7% Above or below ground level OGL OGL walkways streets 0.3% 0.7% GL (100%) Open space area 45.1% Ground level walkways 2.7% Ground level Building area streets 34.1% 18.1% Example of constructed data (West entrance, Shinjuku Station) Data : Zenrin Zmap-TOWN II(GL roadways, OGL walkways) MAPPLE Digital Map Data 10000(OGL streets) Ratios of land use classifications in 14 wards 8

Distribution of road spaces by mesh 03. Distribution of road spaces Distribution of walkway ratios (GL+OGL) High values are observed in the vicinity of railway stations. The highest roadway ratio, 63.3% (Marunouchi Central Entrance of Tokyo Station) The highest walkway ratio, 23.4% (The west entrance of Shinjuku Station) 250m mesh 9

Distribution of road spaces by mesh 03. Distribution of road spaces Ratios of OGL walkways among all walkways High values are distributed around railway stations. Pedestrian spaces were greatly enhanced by OGL structures. Pedestrian spaces have been pursued off the ground surface due to the automobile-centered space. All walkway 100 OGL-55.3% Shinjuku Sta. 39.9% 10.4% OGL walkway 13.0% Tokyo Sta. 40.8% GL walkway 16.8% 4.7% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 250m mesh GL street OGL street GL walkway OGL walkway 10

Ratio (%) Overall ratio of walkways(%) Surrounding area of stations 03. Distribution of road spaces Surrounding area of stations are analyzed to observe composition and road ratio change. Mean roadway ratio of within a 500 m radius of railway stations, 25.1%(266 stations) OGL walkways are concentrated within 200 m of stations. As the number of rider increases, higher walkway ratio was showed. 35.0 12.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0 2.4 4.8 1.1 23.7 0.8 3.9 1.4 0.4 0.4 0.4 3.5 3.2 3.1 1.7 2.1 2.5 0.3 2.7 0.7 22.0 20.8 19.8 19.5 18.1 0-100 100-200 200-300 300-400 400-500 Overall mean Distance from station (m) GL streets OGL streets GL walkways OGL walkways <Mean ratios of roadways with distance from railway stations> 10.0 8.0 6.0 4.0 2.0 0.0 6.4 10.1 7.4 3.8 8.2 4.9 6.6 4.0 5.5 5.0 3.6 3.7 3.3 3.1 3.0 0-100 100-200 200-300 300-400 400-500 Distance from station (m) Under 50k/day 50k-100k/day Over 100k/day <Ratios of walkways, distance from the railway station, and number of riders/day> 11

Characteristics of roadway distribution 03. Distribution of road spaces Relation between Pedestrian space and stations Walkway ratio is especially high in the vicinity of stations. Degree of relation by location and number of riders Other factor of Walkway concentrations Concentrations of walkway are observed in other meshes. Finding out other factor of walkway concentrations By using Kernel density estimation, 1. Degree of relation between pedestrian space and stations considering the number of riders 2. Relation with high building density area where a lot of people can be gathered 12

Kernel density distribution estimation 04. Peak analysis of pedestrian spaces Kernel density distribution is used to analyze relative concentration of pedestrian space considering surrounding area. Pedestrian space peaks : The points of highest density compared to their surroundings Distributions of pedestrian space peaks is compared with the distribution of railway station and building density peak - The pedestrian spaces were rasterized to cell sizes of 1 m, converted to point data. bandwidth source: left-http://www.csun.edu/~sg4002/courses/forensic/lab_kernal_density_smoothing.pdf right-http://jratcliffe.net/ware/spam1.htm 13

Number of peaks Kernel density distribution estimation 04. Peak analysis of pedestrian spaces Peaks and stations within bandwidth from boundary were excluded from analysis. When bandwidth was set at 400m, 250 pedestrian peaks are extracted. - Bandwidth which the number of stations and peaks are similar to figure out whether stations are primary facility of pedestrian space concentration. <Change number of peaks by bandwidth> <Distribution of pedestrian space peaks (bandwidth 400m)> 500 250 pedestrian space peaks 400 300 200 100 0 250 238 230 227 222 418 250 165 89 73 300 400 500 600 700 Bandwidth (m) Peaks Railway stations Pedestrian space density Pedestrian space peak Railway 14

Distribution of pedestrian space peaks 04. Peak analysis of pedestrian spaces Relationship with railway stations 107 (42.8%) of the 250 pedestrian Bandwidth=400m space peaks were found to be within 200 m of railway stations. Most of pedestrian peaks in the center of target area have relation to station Pedestrian space peak 250(100%) Nearby station 107(42.8%) Railway Others 143(56.2%) Railway Station 15

10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100 Number of railway stations Distribution of pedestrian space peaks 04. Peak analysis of pedestrian spaces Degree of Relationship by number of rider 110(46.2%)of the 238 stations had a pedestrian space peaks within 200m. This relationship strengthens with higher rider numbers at stations. Some stations in outer area can not have pedestrian space peaks. Bandwidth=400m Raito of station nearby pedestrian peaks 60 100% 80% 40 60% 20 0 40% 20% 0% Railway stations 238(100.0%) Nearby peak 110(46.2%) No peak 128(53.8%) Number of riders(thousands/day) Number of riders(thousands/day) Pedestrian space peak Railway 16

Distribution of pedestrian space peaks 04. Peak analysis of pedestrian spaces Relationship with building density peak 219 building density peaks are extracted 85 (34.0%) of the pedestrian space peaks had building density peaks within 200 m Pedestrian peaks within 200m from building density peaks tend to distribute outer side of target area. Bandwidth=400m Pedestrian space peak 250(100%) Nearby building peak and station 41(16.4%) Nearby building peak 44(17.6%) Others 165(66.0%) Building density peak Railway 17

Classification of pedestrian space peak 04. Peak analysis of pedestrian spaces Pedestrian space peaks 60.4% of pedestrian peaks are Bandwidth=400m related with stations or building density peaks Railway station is primary facility of pedestrian space concentration Other, 99, 39.6% Railway station, 66, 26.4% Building peak, 44, 17.6% Both station and building peak, 41, 16.4% Pedestrian space peak Nearby station and building peaks Nearby station Nearby building peak Others Railway Roadway (at least 10m width) 18

歩行者空間の集積要因と関係分析 関係分析の手順 変数の設定 回帰分析の実行 (500mメッシュ単位) - 全体データを用い 相関 回帰分析を行い 異常値を除外 ( 標準化された残差基準 ) - 異常値を除外してから 回帰分析を実行 - 回帰分析による個別予測区間 ( 90% 信頼区間 ) を計算 実際値と信頼区間の上限 下限を比較し 十分な地域 足りない地域区分 十分な地域 足りない地域 19

歩行者空間の集積要因と関係分析 歩行者空間の集積要因 駅の立地 乗降者数 建物の集積などが歩行者空間の集積に影響があると分析された それに加え 歩行者空間の形成に影響があると考えられる変数を追加した 目的変数 : 歩道率 (%) 説明変数 容積率 (%) 区分 駅から距離帯別の面積の比率 (%) 200m ZmapTown データ 乗降者数 ( 面積により配分 )( 万人 ) 200m 基準 国土数値情報交通流動 量駅別乗降数データ ( 端末交通手ー徒歩のみ ) 建物棟数 平均建築面積 ( m2 ) ZmapTown ZmapTown 20

歩行者空間の集積要因と関係分析 回帰分析の結果 残差の分布 地域の区分 残差 -3.74 - -2.29-2.28 - -1.43-1.42 - -0.89-0.88 - -0.40-0.39-0.07 0.08-0.61 0.62-1.30 1.31-2.21 2.22-3.69 3.70-6.57 鉄道 鉄道駅 km 0 1 2 4 km 0 1 2 4 歩行者空間の水準十分な地域少ない地域鉄道駅鉄道

歩行者空間の集積要因と関係分析 回帰分析の結果 740 個のメッシュの中で 異常値を除外した 698 個を用いた結果である b モデル要約 モデル R R2 乗調整済み R2 乗 推定値の標準誤差 Durbin-Watso n 1.819 a.671.668 1.205 1.554 a. 予測値 : ( 定数 ) 駅 200 割合, 建物棟数, 容積率, 平均建築面積, 乗降者配分 b. 従属変数歩道率 モデル 1 ( 定数 ) 容積率 a 係数 標準化されていない係数 標準化係数 共線性の統計量 B 標準誤差 ベータ t 値 有意確率 許容度 VIF.602.170 3.536.000.015.001.588 23.346.000.751 1.332 建物棟数 -.001.000 -.179-6.456.000.617 1.622 平均建築面積.001.000.082 2.980.003.631 1.586 容積率が100%p 増加すると歩道率は 1.5%p 増加しする 地域内の建物の棟数が1000 棟増えることにより歩道率は1%p 減少する一方で 一棟当りの平均建築面積が1000 m2増加することによる歩道率が1%p 減少すると分析された 大規模の面的開発の方がもっと多い歩行者空間を確保することを表す結果だと考えられる 乗降者配分.049.007.214 7.216.000.539 1.854 駅 200 割合 a. 従属変数歩道率.011.003.096 3.527.000.645 1.551 22

Discussion and conclusion Required quantity of pedestrian space Roadway space distributions for both vehicles and pedestrians (including OGL roadway spaces) in 14 of the wards of Tokyo were analyzed. The result clarified that walkway ratio is especially high in the vicinity of stations. - Over 40% of pedestrian space peaks are linked with railway stations, and this relationship strengthens with higher rider numbers at stations. - Some Stations located in outer side or used by a few people can not have peaks Results of this study cannot explain required quantity of pedestrian spaces. It can be deal with considering the demand of pedestrian space based on traffic volume or building density. 23

Discussion and conclusion Quality of pedestrian space This study focused on quantity of road spaces and figured out that OGL spaces are used at a high ratio in pedestrian spaces. - Ratio of OGL roadway among all roadway: street-3.5%, walkway-8.8% - Pedestrian spaces were greatly enhanced by OGL structures. Even though there are satisfactory amount of pedestrian space, it cannot be said as friendly space for pedestrian - Pedestrian spaces have been pursued off the ground surface due to the automobile-centered space. - OGL pedestrian spaces can be inconvenience because people have to move up and down and can separate people from ground level shops Convenience of movement, network, accessibility to other facilities should be considered together. 24

Discussion and conclusion For further study... > Considering various vehicles Bicycles and the vehicles that are anticipated to be common in the future, such as electric motorbikes and vehicles for elderly people It is needed to consider a difference of necessary space for each vehicles. > Changing demands of roadway space by mixed land use Most parts of present-day Tokyo, land use is functionally separated, in accordance with regulations. Mixed land use moderates the traffic load in compact city. 25

Reference Chicago Department of Transportation, (2012) Chicago Pedestrian Plan, http://chicagopedestrianplan.org/. Desyllas, J., Duxbury, E., Ward, J. and Smith, A., (2003) Pedestrian Demand Modelling of Large Cities: An Applied Example from London, Centre for Advanced Spatial Analysis Working Paper Series, 62. Era, R.T., (2012) Improving Pedestrian Accessibility to Public Space through Space Syntax Analysis, Proceedings of the Eighth International Space Syntax Symposium, Santiago, PUC. Galderisi, A. and Ceudech, A., (2010) Soft Mobility and Pedestrian Networks in Urban Areas, TeMaLab Journal of Mobility, Land Use and Environment, 3, 21-28. Jou, K.K., (2011) Pedestrian Areas and Sustainable Development, World Academy of Science, Engineering and Technology, 53, 483-490. Park, J., (2007) A Design Study of Pedestrian Space as an Interactive Space, The International Association of Societies of Design Research 2007, Hong Kong. 26

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