Filling in the Spaces: Compactifying Cities towards Accessibility and Active Transport
Abstract
:1. Introduction
2. Materials and Methods
2.1. Indicator Motivation
2.1.1. Accessibility
2.1.2. Active Modal Share
2.1.3. Transport Energy Consumption
2.1.4. The 15-Minute City
2.2. GIS Implementation
- An urban area was selected for study. Three datasets are collected and curated into a GIS environment: origins (O), destinations (D), and road network. Origins represent demand (for trips) and are the centroids of buildings (endowed with inhabitant number information). Destinations represent supply and are urban facilities and centroids of job zones (see Section 2.4.1. for details on job zones). The road network connects origins to destinations. Origins and destinations are point feature classes, and the road network is a polyline feature class;
- In a copy of the datasets, new buildings and facilities are positioned in vacant urban spaces, job zones are remade, and connecting roads are drawn. The buildings house population from the outskirts and are endowed with inhabitant information;
- For every origin of each layout, network distances are evaluated in GIS to (a) the nearest urban facilities of each type and (b) the centroid of each job zone;
- Four transport modes are considered: walking, cycling, private motorised transportation, and public transport. For each OD pair, trip probabilities for all those modes are obtained;
- Indicator values for each origin are then calculated for both the real and the compact layouts based on OD distances and trip probabilities;
- From the indicator values, statistical measures and maps are derived for the two layouts.
- The methodology considers only accessibility-related trips, which constitute most trips in an urban environment and can be modelled in GIS as one-way or round trips to predefined destinations, subject to supply attractiveness and demand intensity, two attributes which need be considered in accessibility [109,110];
- If the methodology is applied to a very large city, computational complexity can be reduced by defining origins as centroids of a square mesh over the study area, with associated inhabitant number given by the intersection of building centroids with mesh polygons;
- Urban facility types and respective destination attractiveness are here represented by weights as given in Table 1 below. An empirical 1–2–3 Likert scale for weights was used in the research, based on trip frequency, with three the most frequent. Higher weights mean trips to the corresponding destinations are likely to be more frequent. These weights are consistent with trip frequencies per facility type found by ref. [111];
- If the return trip to a facility is made soon after reaching the destination, the person may experience a feeling of walking or cycling a longer distance. Therefore, in evaluating active transport probabilities (which are a function of distance), a one-way distance is considered for facilities that imply a long stay at the destination (e.g., schools, restaurants), whereas for the other facilities, a two-way distance is considered instead. One- and two-way facilities are indicated in Table 1 by the I or II;
- The four transport modes are comprehensive categories; e.g., for cycling, they include all types of cycles and not just bicycles. Likewise, public transport includes buses, subway, etc.
2.3. Compactification Procedure
- Locate the point with best accessibility in the real city, point P;
- Define a 100 m radius circle centred on P and draw all the possible new buildings within that circle. Assign the population farthest from P to those buildings and remove the buildings originally containing the moved population from the origins dataset;
- Define a ring-like area 100–200 m away from P and repeat the assignment of #2;
- Add 100 m to the ring-like area edges of #3 and repeat #3 until resulting new buildings can no longer be fully populated.
2.4. Accessibility
- : number of origins;
- : number of facility types;
- : number of closest facilities (when it applies), and in this article, K = 3;
- : accessibility score of origin i;
- : network distance from origin i to the k-th closest facility of type j (or job zone);
- : weight of facility type j;
- : freedom of choice factor for the k-th closest facility of type j; .
2.4.1. Accessibility to Jobs
- number of job zones;
- : fraction of total jobs in zone ;
- : distance from origin to the -th job zone centroid.
2.5. Active Modal Share
- The active mode share is estimated from transforming accessibility-related trip distances onto active trip probabilities using log-logistic distributions. Separate walk and walk/cycle probabilities are obtained, the latter by combining walk and cycle probabilities, yielding two types of analysis;
- After discounting the active trip probability, the remaining probability corresponds to motorised trips, which are split onto bus/car trips according to the empirical percentages.
- : active modal share of origin ;
- : active trip probability from origin to the -th closest destination of type , with for j: jobs (: active trip probability from to job centroid ).
2.6. Transport Energy Consumption
- : average fuel consumption of accessibility-related trips originating in ;
- : fraction of motorised trips made using the private car;
- : fraction of motorised trips made using public transportation;
- : private car average fuel economy (MJ/passenger.km);
- : public transportation average fuel economy (MJ/passenger.km);
- : one-way distances from origin , respectively, towards/away the -th closest destination of type .
2.7. 15-Minute City
- : attainable fraction of 15-minute city for origin ;
- : 1 if the trip from origin to the -th closest destination of type is possible within 15 min using active modes ; otherwise, 0. For jobs, (: 15-min binary score from to job centroid ).
3. Case Study Results
3.1. Compactification of Coimbra
3.2. Accessibility and the 15-Minute City
3.3. Modal Share
3.4. Transport Energy Consumption
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Weight 1 Facilities | Weight 2 Facilities | Weight 3 Facilities |
---|---|---|
Post offices *II | High schools I | Kindergartens *II |
Sports facilities I | Shopping centres II | Primary schools *II |
Cultural organizations I | Entertainment sites I | Middle schools *I |
Universities and institutes I | Primary healthcare services *I | Grocery stores II |
Elderly care centres I | Pharmacies *II | Supermarkets II |
Churches I | Restaurants I | Bakeries and pastries II |
Parks and green areas *I |
Apartment Typology | Fraction | Minimum Private Area * (m2) | Average Inhabitants |
---|---|---|---|
T0 (studio) | 2% | 35 | 1 |
T1 (one bedroom) | 9% | 52 | 2 |
T2 (two bedrooms) | 32% | 72 | 3 |
T3 (three bedrooms) | 36% | 91 | 4 |
T4 (four bedrooms) | 13% | 105 | 5 |
T5+ (five+ bedrooms) | 9% | 122 | 6 |
Year | Population | Population Increase | Area (ha) | Area Increase | Population Density (inhab./km2) |
---|---|---|---|---|---|
17th Century | Circa 12,000 | N/A | 43 | N/A | 27,907 |
1930 | 36,021 | 200% | 170 | 295% | 21,189 |
2021 | 104,464 | 190% | 8700 | 5018% | 1201 |
Indicator | Compact Coimbra | Notes |
---|---|---|
City area | 16,732 m2 | Coimbra: 141,720 m2 |
New buildings | 636 | New land plots: 196 |
New building area | 296,910 m2 | Gross floor area: circa 1,300,000 m2 |
Moved population | 54,469 inhab. | 52% of total population |
Average residents per building | 86 | |
Average building floors | 4.5 floors | |
Living space per inhabitant | 24 m2 | Coimbra: 47 m2 |
Accessibility (m) | Urban Facilities | Urban Facilities Plus Jobs | ||
---|---|---|---|---|
Coimbra | Compact Cbr. | Coimbra | Compact Cbr. | |
Min | 268 | 252 | 1063 | 948 |
Max | 8099 | 1746 | 9329 | 3092 |
Average | 1936 | 594 | 3088 | 1491 |
Average per inhabit. | 1440 | 638 | 2533 | 1570 |
Standard deviation | 1352 | 188 | 1483 | 280 |
Coeff. of variation | 70% | 32% | 48% | 19% |
15-Min City (%) (Facilities Plus Jobs) | Walking | Walking and Cycling | ||
Coimbra | Compact Cbr. | Coimbra | Compact Cbr. | |
Min | 0.0 | 6.7 | 0.0 | 69.1 |
Max | 71.3 | 76.3 | 91.8 | 100 |
Average | 22.5 | 61.6 | 66.3 | 88.5 |
Average per inhabit. | 30.2 | 58.0 | 71.1 | 85.0 |
Standard deviation | 20.1 | 8.9 | 19.7 | 5.7 |
Coeff. of variation | 95% | 15% | 30% | 7% |
Active Modal Share (%) (Facilities Plus Jobs) | Walking | Walking Plus Cycling | ||
---|---|---|---|---|
Coimbra | Compact Cbr. | Coimbra | Compact Cbr. | |
Min | 0.5 | 5.6 | 3.5 | 28.9 |
Max | 48.0 | 48.7 | 73.7 | 76.3 |
Average | 12.7 | 28.1 | 35.6 | 61.6 |
Average per inhabit. | 16.8 | 25.6 | 42.6 | 58.0 |
Standard deviation | 10.6 | 7.4 | 18.7 | 7.2 |
Coeff. of variation | 83% | 26% | 53% | 12% |
Transp. Energy (MJ/p.t.) (Facilities Plus Jobs) | Active: Walking | Active: Walking Plus Cycling | ||
---|---|---|---|---|
Coimbra | Compact Cbr. | Coimbra | Compact Cbr. | |
Min | 0.690 | 0.605 | 0.190 | 0.132 |
Max | 36.340 | 7.365 | 35.370 | 5.491 |
Average | 8.180 | 2.056 | 6.700 | 0.954 |
Average per inhabit. | 5.901 | 2.254 | 4.533 | 1.103 |
Standard deviation | 6.210 | 0.830 | 6.170 | 0.578 |
Coeff. of variation | 76% | 40% | 92% | 61% |
Indicator | Statistics | |||||||
---|---|---|---|---|---|---|---|---|
Facilities | Facilities + jobs | |||||||
Accessibility (m) | Coimbra | Compact Coimbra | Reduction (m) | Reduction (%) | Coimbra | Compact Coimbra | Reduction (m) | Reduction (%) |
Avg. | 1936 | 594 | 1342 | 69% | 3088 | 1491 | 1597 | 52% |
Avg. per inhab. | 1440 | 638 | 802 | 56% | 2533 | 1570 | 963 | 38% |
Walking | Walking + Cycling | |||||||
15-min city (%) (Facilities + jobs) | Coimbra | Coimbra compact | Increase | Increase (%) | Coimbra | Coimbra compact | Increase | Increase (%) |
Avg. | 22.5 | 61.6 | 39.1 | 174% | 66.3 | 88.5 | 22.2 | 33% |
Avg. per inhab. | 30.2 | 58 | 27.8 | 92% | 71.1 | 85 | 13.9 | 20% |
Walking | Walking + Cycling | |||||||
Active modal share (%) (Fac. + jobs) | Coimbra | Coimbra compact | Increase | Increase (%) | Coimbra | Coimbra compact | Increase | Increase (%) |
Avg. | 12.7 | 28.1 | 15.4 | 121% | 35.6 | 61.6 | 26 | 73% |
Avg. per inhab. | 16.8 | 25.6 | 8.8 | 52% | 42.6 | 58 | 15.4 | 36% |
Walking | Walking + Cycling | |||||||
Transport energy (MJ/p.t.) (Fac. + jobs) | Coimbra | Coimbra compact | Reduction (MJ/p.t.) | Reduction (%) | Coimbra | Coimbra compact | Reduction (MJ/p.t.) | Reduction (%) |
Avg. | 8.18 | 2.056 | 6.124 | 75% | 6.7 | 0.954 | 5.746 | 86% |
Avg. per inhab. | 5.901 | 2.254 | 3.647 | 62% | 4.533 | 1.103 | 3.43 | 76% |
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Monteiro, J.; Para, M.; Sousa, N.; Natividade-Jesus, E.; Ostorero, C.; Coutinho-Rodrigues, J. Filling in the Spaces: Compactifying Cities towards Accessibility and Active Transport. ISPRS Int. J. Geo-Inf. 2023, 12, 120. https://doi.org/10.3390/ijgi12030120
Monteiro J, Para M, Sousa N, Natividade-Jesus E, Ostorero C, Coutinho-Rodrigues J. Filling in the Spaces: Compactifying Cities towards Accessibility and Active Transport. ISPRS International Journal of Geo-Information. 2023; 12(3):120. https://doi.org/10.3390/ijgi12030120
Chicago/Turabian StyleMonteiro, João, Marvin Para, Nuno Sousa, Eduardo Natividade-Jesus, Carlo Ostorero, and João Coutinho-Rodrigues. 2023. "Filling in the Spaces: Compactifying Cities towards Accessibility and Active Transport" ISPRS International Journal of Geo-Information 12, no. 3: 120. https://doi.org/10.3390/ijgi12030120