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~ Yoav Lerman's Blog

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Tag Archives: space syntax

Assessing Rail Stations Development Potential

26 Sunday Nov 2017

Posted by Lerman in Israel, Transportation

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Bertolini, Hillier, Rail, space syntax, Station, Train

Transportation means are drivers of urban development. Highways and interchanges induce low density sprawl, while rail stations can induce intense urban and economic development in their vicinity. But like everything else related to planning – urban space is not homogeneous – some places are more central with higher development potential and some less so. Potential assessment can therefore help and guide major planning decisions.

This post is an explanation of a study we did on rail stations and which was presented at the last Space Syntax Symposium in Lisbon last summer. The full paper itself can be found here. At the time, we had to deal with the issue of Binyamina’s train station moving westward in the coming 10-15 years (one of Israel’s mid-size train stations) and this led us to ponder how can the development potential around rail stations be assessed.

To tackle this issue, we synthesized Luca Bertolini’s qualitative studies with Bill Hillier’s quantitative studies. Bertolini has wrote extensively about the significance of train stations and the ways they should be planned to achieve goals such as efficient use of infrastructure and land development. Basically, he points out the fact that a train station is a place where large scale movement (train trips of ten and hundreds of kilometers) meet with small scale movements of pedestrians (movements of few hundred meters) at differing intensity levels. In addition, due to the physical characteristics of the trains themselves, the train stations are usually a barrier to pedestrian movement and cause interruptions in urban space. Therefore, planning a successful train station is a work of art with regards to entrances, exits and fitting in the surrounding space. There are stations where the centrality of the rail network combines with other factors which lead to extensive burden on the land in and out of the station (HaShalom station is a station like that in Israel, but Amsterdam central station and Koln central station show that such stations can be both very intensive and successful), while most stations have much lower intensities. Hillier focuses of analysis of spatial networks based on space syntax (a method in which we at PlaNet specializes at). Combining both approaches allows for some kind of standardization and quantification of Bertolini’s concepts in order to integrate these concepts in urban and transport planning.

For the analysis of Israel train stations we have mapped the entire road network of Israel and its 54 train stations. In order to correlate the model we received from Israel Railways the number of average daily passengers for each station. We have found a satisfactory correlation at the 100 km scale, and we still have work to do with regards to edge stations (that get more passengers that what our model predicts). In the following map the model for assessing trains stations centrality (in the rail network) is shown with three categories – strong, medium and weak stations. Most of the train stations (70%) are weak, while a few (10%) are strong. Tel Aviv’s four stations are obviously strong, while Holon Junction is fifth, which points to a missed opportunity as most of the land around it is not developed at all. The most interesting stations are the medium stations (20%), since they have development potential that can materialize with good planning. The current Binyamina station is among those station and has  neighboring employment center that got built against all odds.

Train stations and their evaluated strength

In order to combing rail movement with pedestrian movement we have employed two more computational steps. We have spread the rail strength index among all segments up to 700 m (pedestrian network distance) based on literature. Furthermore, we have employed a centrality index at 1,250 m radius to give a proxy for pedestrian movement intensity (based on correlated models for pedestrian movement in Israel). All these indices where multiplied together to create a single map which reflects train stations areas development potential.

When analyzing Tel Aviv central area, it is found that the HaHagana station has the largest gap between its centrality potential and the built environment intensity around it. This is also the only station in Tel Aviv where there if free parking, which hints at the inefficient land exploitation. Another station with hidden potential is Yoseftal station which lies between Bat-Yam and Holon. Fortunately, Bat Yam municipality is making plans for intensification and we assume that Holon has something similar in its sleeve.

Close up of the results at the network’s center

The model presented here is a first step in creating quantitative methods for spatial potential assessment of train stations. In the next steps motorized movement and light rail can also be incorporated in order to keep improving the model. The use of such models would allow for identifying places with hidden potential – places where planning efforts would the deliver the most benefits. Such models can also be used when planning new train stations and when relocating existing stations to evaluate the optimal location.

In conclusion, the study presented here is a first of its kind in the scope and analysis for train stations and I hope it will inspire further studies and would also have a real impact in planning. For those interested in delving deeper – the entire paper with all the explanations and reservations can be found here.

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Modernist Planning Results in Fewer and Less Predictable Pedestrians

20 Thursday Aug 2015

Posted by Lerman in Academia, Israel, Land-Use, Planning, Transportation

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Modernism, space syntax, Spatial Analysis

I am glad to share with you a paper that I have co-authored and which was published recently in the International Journal of Geographic Information Science. The paper was written by Prof. Itzhak Omer of Tel Aviv University, Dr. Yodan Rofè of Ben-Gurion University and myself. The full title of the paper is:

“The impact of planning on pedestrian movement: contrasting pedestrian movement models in pre-modern and modern neighborhoods in Israel”

As evident from the name of the paper, this publication deals with the impact of planning on pedestrian movement. We analysed pedestrian movement in 14 neighborhoods in four different cities in Israel – Kfar Saba, Bat Yam, Ashdod and Beer Sheva. These neighborhood where divided to two categories – modern and pre-modern. Essentially, modern neighborhood are those that were planned along modernistic urban planning approach, which adheres to separation of uses and hierarchical road structure. In contrast, pre-modern planning which tends to be denser with a lot more mix of uses and less hierarchical road structure. Basically, all the neighborhoods planned after the establishment of the state of Israel (1948) are modern, while most of the neighborhoods that were established prior to the Israeli state independence are pre-modern. Moreover, the cities of Bat Yam and Kfar Saba have many more pre-modern parts than the cities of Beer Sheva and Ashdod (this city was established in 1956 and consist only of modern planning).

Following are the maps of all the research neighborhoods in their respective cities. Dashed lines mark pre-modern neighborhoods while continuous lines mark modern neighborhoods.

All 14 research neighborhoods
NeighPicAll

We did pedestrian movement surveys in all the research neighborhoods and examined the statistical correlations of  the movement volume with relevant quantifiable variables that describe the built environment. For the analysis of the road structure we have relied heavily on space syntax. Other variables were derived from land use distribution – especially retail and demographic variables such as population densities.

Significant disparities in pedestrian movement volume were found among the cities and among the different neighborhoods. The pre-modern neighborhoods had about twice the pedestrian movement volume of the modern neighborhoods on average. Also, retail fronts were found to be much more prevalent in pre-modern neighborhoods than in modern neighborhoods. The chart below shows the average pedestrian movement volume (per hour) observed in the surveyed road section in all research neighborhoods. In red are the pre-modern neighborhoods, blue signifies the modern neighborhoods and green represents the average for each city. The city of Bat Yam, which is one of the denseset municipalities in Israel has remarkably higher movement volume than the other three cities.

Average pedestrian movement volume per hour in the surveyed road section in all research neighborhoods. Red is for pre-modern neighborhoods, blue for modern neighborhoods and green for entire city average.

Furthermore, our extensive statistical correlations showed that movement in pre-modern neighborhoods is far more predictable than in modern neighborhoods. At the last phase of this study we tried to produce a generic movement model for each type of neighborhood. To validate this model we analysed pedestrian movement in four more neighborhoods in Kfar Saba and in another city called Hod Hasharon (one neighborhood of each type in each city). The model had far more success in the pre-modern neighborhood than in the modern ones.

Besides addressing the issue of pedestrian movement in modern and pre-modern neighborhoods, the paper adds significant findings related to space syntax and the usability of its various attributes. For example, metrically derived attributes (based on metric distance and not on topological and angular distance) were found to be extremely inconsistent. The main conclusion I take from this work is quoted below:

Our study shows that traditional pre-modern urban neighborhoods, with a well-connected street structure, are likely to have not only more walking within them but also a more predictable spatial distribution of pedestrian volume than modern neighborhoods, that are characterized by hierarchical tree-like street layout associated with the idea of the neighborhood unit. We have identified that the correlation of pedestrian volume with the street network’s configuration attributes are significantly higher in pre-modern urban neighborhoods than in the modern neighborhoods. Furthermore, our study revealed that the distribution of pedestrian volume in these neighborhood types interacts differentially with the street network. In modern street layouts, the different types of configuration attributes (topological, angular, and metric) tend to be much more varied in their correlation with pedestrian volume across scale.

 

The full paper provides all the results and findings, expands on the use of space syntax in this research and describe in detail the statistical methods employed. You can find the full paper here, and if you cannot access the full paper and would like to read it you can contact me here and I’ll send you a copy.

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An Innovative Pedestrian Transportation Plan and Its Academic Publication

21 Sunday Dec 2014

Posted by Lerman in Academia, Israel, Planning, Transportation

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Bat Yam, space syntax

This post describes a planning project I’ve been involved with, in which we created an innovative pedestrian transportation plan for the city of Bat Yam in Israel. Bat Yam is an inner suburb in the Tel Aviv Metropolitan area where about 130,000 people live just south of the municipality of Tel Aviv. Besides the novel transportation plan, we have managed to publish an academic paper, adding to the global discussion on city and transporation planning. The paper was published in Geographic Analysis (together with Dr. Yodan Rofè and Prof. Itzhak Omer) in a special issue dedicated to Street Networks and Spatial Analysis, following a workshop in Dresden last year. A non-final version of the paper can be found here (or you can contact me for the final version). And now to the actual story itself.

Transportation planning is changing. What used to be a concern with motorized vehicles only is evolving into a discipline dealing with multi-modal systems where priority is given to transit and non-motorized means of transport, chief among them being walking. Walking is important for several reasons: reducing reliance on motorized travel, which is rather costly, polluting and accident-prone; walking as part of a daily routine, promotes healthier life-style; and walkability can improve the economy of urban centers. Across the globe, effort are made to improve conditions for pedestrians. Known examples include New York City, Copenhagen and many more. Following this trend, The Israeli government has also published guidelines for streets design (here – in Hebrew). However, pedestrians in Israel are still at the bottom of the transportation and urban planning considerations.

The city of Bat Yam in Israel has chosen to pioneer planning for pedestrians as an integral component of its transportation master plan. The transporation master plan for the city of Bat Yam includes all transportation means (i.e. private vehicles, parking, bicycles and so forth) and was led by PGL Transportation and Engineering Ltd. We were in charge of pedestrian transportation in the overall scheme and we hope that more cities and other public bodies will consider walking as an integral part of urban transportation.

This project touches on one of the growing issues in urban planinng which is evidence-based design. This approach originated in the health and medical fields, and is now entering the realm of city planning. We managed to combine research and praxis and made a contibution towards a change in the area of urban planning. A few different subjects were joined together in this project – Space Syntax, pedestrian movement, general urban transportation and city developement.

Besides analysing pedestrians movement, we had to address expected changes to the urban strcuture of Bat Yam in target year of the plan (2030). The major changes are expected to happen in the southern industrial zone of the city in addition to a new residential neighborhood on open land at the south-western edge of the city. These changes include modifications to the street network as well as land-use changes and plenty of new construction. The southern industrial zone is supposed to grow from current under-utilization to intensely built zone including lots of retail, office and residential high-rise buildings.

We have constructed pedestrian movement models both for the current state of the city of Bat Yam, and for its future state in 2030. The future model included the changes expected to the street network and land-use. The model was constructed based on space syntax methodology and correlated based on pedestrian traffic counts in 69 street segments all over the city. The map of the traffic survey is shown below. I will not go into the entire method (which is explained in detail in the paper) – the large red points represent average movement volume of over 900 pedestrians per hour, the medium points represent average movement volume of over 430 pedestrians per hour, and the small points represent lower volumes.

Three areas in the map have groupings of high movement points. These three areas have some kind of combination of high centrality with high presence of retail. The northern points are in the old center of the city (Memorial Square), the points further south are at the junction of the main commercial street (Balfour Street) and a major east-west street, and the points at the eastern edge are next to the (new) main entrance to the city and its largest shopping mall. Contrary to the municipality’s expectations, pedestrian movement along the beach front (on the western edge of the city) is relatively sparse. Most of the everyday pedestrian movement on a weekday probably is related to functional activity and not to leisure. This movement takes place mainly on the streets that define the epicenter of the city.

Pedestrian movement survey for the city of Bat Yam

PedSurveyHeadTailForPaper

In the movement model itself we managed to achieve a correlation rate of 62% using three variables (not bad compared to similar studies), where the major variable is based on street centrality and the second variable is associated with retail front presence. Thus, we have reached two main conclusions that enable this method to be used in other cities:

1. Pedestrian movement distribution can be explained mainly by spatial structure of the street network. Changes to this network structure are relatively rare, and therefore pedestrian movement distribution will be similar in the year 2030, and the main streets for pedestrian movement will not change in a fundamental way.

2. Because the model is not accurate it should be used with caution. Therefore, we have taken 20% of the streets where pedestrian movement volume is highest and they were declared as the pedestrian core network. This layer was then overlayed on other transportation layers – public transit, private vehicles and bicycles.  This is the place where our model can have impact on the real world and on the future work of the municipality – by directing the focus to streets and places where conflicts among the various road users (pedestrians, bicycles, transit vehicles, and private cars) are expected. This conflict analysis can be used to develop a policy that favors pedestrians as well as to highlight areas where safety improvements are needed. The model also can enable an urban development policy that seeks to improve public space where the highest pedestrian movement rates are expected.

A map of the Superimposed future pedestrian core network, public transit (including planned light rail), bicycle routes (planned), and major vehicular roads.  supermap bat-yam-NEW

As the map shows, there are few important streets, but these few streets carry a large share of the different kinds of transporation means and they are the places where conflicts among road users are expected. These streets deserve most of the planning efforts and investing in them has a large impact on the city and its residents.

The entire paper can be downloaded from here.

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