The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective Marco De Nadai, Jacopo Staiano, Roberto Larcher, Nicu Sebe, Daniele Quercia, Bruno Lepri 

How do you capture death & life of cities? Some cities are alive, others less so ALIVE DEAD DETROIT NEW YORK 

Let’s test an urban theory 3 1 Take the theory “Operationalize” the theory Does it work? Is it still valid? Why does it matter? 2 3 4 

Take the theory STEP 1 

The theory: Jane Jacobs One of the most influential books in city planning • planning models that dominated mid-century planning • American housing policy (HOPE VI) • Melbourne, Toronto etc. 5 1 2 3 4 THEORY TEST Klemek, C. (2011) ‘Dead or Alive at Fifty? Reading Jane Jacobs on her Golden Anniversary’ Dissent, Vol. 58, No. 2, 75–79. 

The theory: not tested! • Not empirically tested until 2015 • Tested in Seoul, from costly surveys collected in years • Theory from 1961! 6 1 2 3 4 THEORY TEST Sung, Hyungun, Sugie Lee, and SangHyun Cheon. "Operationalizing Jane Jacobs’s Urban Design Theory Empirical Verification from the Great City of Seoul, Korea." Journal of Planning Education and Research (2015. 

The theory: Jane Jacobs One of the most influential books in city planning • Death: caused by the elimination of pedestrian activity • Life: created by a vital urban fabric at all times of the day 7 1 2 3 4 THEORY TEST 

Jacobs’ diversity conditions Diversity => Urban vitality There are 4 diversity conditions To be ensured in each city’s district (10,000+ inhabitants) 8 1 2 3 4 THEORY TEST SMALL BLOCKS LAND USE AGED BUILDINGS DENSITY 

Land Use Mix 2+ primary uses (contemporarily) JACOBS’ VIEW: People come for different purposes, continuously EFFECT: “sidewalk ballet” and “eyes on the street” 9 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY 1 2 3 4 THEORY TEST 

Small blocks City blocks should be small/short LAND USE SMALL BLOCKS BLOCKS 10 1 2 3 4 THEORY TEST AGED BUILDINGS DENSITY JACOBS’ VIEW: improves walkability EFFECT: Increase face-to-face interactions 

Aged buildings Buildings mixed (age and types) 11 AGED BUILDINGS 1 2 3 4 THEORY TEST LAND USE DENSITY SMALL BLOCKS JACOBS’ VIEW: To ensure economic diversity EFFECT: high-/low-income residents new/small enterprises 

Density Concentration of people and enterprises JACOBS’ VIEW: People have a reason to live in a district EFFECT: Attract people 12 SMALL BLOCKS DENSITY 1 2 3 4 THEORY TEST LAND USE AGED BUILDINGS 

Necessary, diversity conditions All four factors are necessary 13 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY 1 2 3 4 THEORY TEST 

Border Vacuums • Patches of land dedicated to one single use • They could be either bad and good: • Parks are good for pedestrian activity • But they are exposed to criminality and deprivation if not well managed (e.g. night) 14 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 1 2 3 4 THEORY TEST 

“Operationalize” the theory STEP 2 

“Operationalize” Land Use Mix For district : % = − ( %,+ log (%,+ ) log || +∈5 %,+: % square footage of land use : {residential, commercial, recreation} 16 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 1 3 4 THEORY TEST 2 Ref: R. Cervero. Land-use mixing and suburban mobility. University of California Transportation Center, 1989 EFFECT: The higher, the better. 1 0 

“Operationalize” Small blocks Street intersections are a proxy for: • small blocks • peoples’ interactions For district : |% | % EFFECT: The higher, the better 17 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 1 3 4 THEORY TEST 2 

Aged buildings Aged buildings are supposed to be a proxy for new, small enterprises. For district : 1 |% | ( +∈FG % : set of companies EFFECT: The higher, the worse 18 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 1 3 4 THEORY TEST 2 

“Operationalize” Density For district : Employment density: |HIJKLMNO JNLJKNG| PQNPG Population density: |RLJSKPT%LUG| PQNPG EFFECT: The higher, the better 19 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 1 3 4 THEORY TEST 2 

“Operationalize” Vacuums Distance to highways for district : 1 % ( ( , , ) +∈YG % : the set of the blocks : the set of highways EFFECT: The higher, the better 20 LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 1 3 4 THEORY TEST 2 

Diversity Vitality 

“Operationalize” Vitality • Mobile phone Internet activity as a proxy for urban vitality • We calculate the activity density in each district 1 || ( | % | [∈\ : set of hours (180 days x 24h) • Six Italian cities with 100,000+ inhabitants (e.g. Rome, Milan…) • 6 months time span (in 2014) 22 0.2 0.0 0.2 0.4 0.6 0.8 1.0 Land Use Mix 0.8 1.2 1.8 2.7 4.1 6.1 9.3 14.0 21.1 31.9 Activity density ⇥ 103 ROME MILAN 0.8 1.2 1.8 2.7 4.1 6.1 9.3 14.0 21.1 31.9 Activity density 103 1 2 3 4 THEORY TEST MILAN 

Is the theory still valid? STEP 3 

−3 −2 −1 0 1 2 3 −9 −8 −7 −6 −5 −4 −3 −2 . Is the theory still valid? 24 Intersections density (log + Z-score) Activity density (log) 1 2 3 4 THEORY TEST 

−3 −2 −1 0 1 2 3 −9 −8 −7 −6 −5 −4 −3 −2 Is the theory still valid? 25 Intersections density (log + Z-score) Activity density (log) 1 2 3 4 THEORY TEST 

−3 −2 −1 0 1 2 3 −9 −8 −7 −6 −5 −4 −3 −2 R2 : 0.63 Is the theory still valid? 26 Intersections density (log + Z-score) Activity density (log) 1 2 3 4 THEORY TEST 

The log Linear Regression 27 = ^ ^ + a a + ⋯ + ac ac + 1 2 3 4 THEORY TEST 

The log Linear Regression 28 Activity density 1 2 3 4 THEORY TEST = ^ ^ + a a + ⋯ + ac ac + 

The log Linear Regression 29 Activity density Land Use Mix Employment density 1 2 3 4 THEORY TEST = ^ ^ + a a + ⋯ + ac ac + 

Urban diversity to urban vitality 30 1 2 3 4 THEORY TEST URBAN METRICS 

Urban diversity to urban vitality 31 1 2 3 4 THEORY TEST URBAN METRICS CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS 

Urban diversity to urban vitality 32 1 2 3 4 THEORY TEST CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS URBAN METRICS 

Urban diversity to urban vitality 33 CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS URBAN VITALITY 1 2 3 4 THEORY TEST URBAN METRICS 

Jacobs’ theory holds and is still valid 34 CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS URBAN VITALITY 1 2 3 4 THEORY TEST URBAN METRICS Fit a:0.77 

Jacobs’ theory holds and is still valid 35 URBAN VITALITY 1 2 3 4 THEORY TEST URBAN METRICS Fit a:0.77 CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS 

Jacobs’ theory holds and is still valid 36 1 2 3 4 THEORY TEST Urban metric Beta coefficient Employment density 0.434*** Intersections density 0.191*** Housing types 0.1854*** Closeness highways -0.102*** 3rd places x closeness highways 0.07** Closeness parks x closeness highways -0.07*** − 0.77 *** p-value < 0.001; ** p-value < 0.01; 4-fold Cross-validation: 75% training – 25% testing, 1000 interactions 

Jacobs’ theory holds and is still valid 37 CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS URBAN VITALITY 1 2 3 4 THEORY TEST URBAN METRICS Predict a:0.77 

…But something is different 38 CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACES X CLOSENESS TO HIGHWAYS 1 2 3 4 THEORY TEST LAND USE SMALL BLOCKS AGED BUILDINGS DENSITY VACUUMS 

Why does it matter? STEP 4 

Web data and mobile phone records offer insights on how most urban dwellers experience entire cities 1 2 3 4 THEORY TEST 

Why does it matter? • Evaluate the districts vitality • Know in advance the best places for retails • Quantifying regulatory interventions • We created the recipe for city that works 41 1 2 3 4 THEORY TEST 

In the (next) future • Comparative work across cities/regions/countries • How visual perception influences urban vitality? 42 1 2 3 4 THEORY TEST 

Let’s test an urban theory 43 1 The Jacobs’ theory We created the metrics We tested the theory Framework for urban vitality 2 3 4 

Test the un-tested And now? 

Thanks