Riccardo Pulselli, The Moving City by Francesca Ameglio

Riccardo Maria Pulselli

ISBN: 978-88-88718-26-2

“The Moving City” provides an absorbing account of a widespread research activity that currently involves theorists, technicians, technologists, designers, administrators, and planners. Today, these and other professional figures are committed to the research for tools and techniques that help us to better understand and manage the complexity of the contemporary city. This book illustrates concepts and theories that outline a new systemic approach to the study of a territory, and raise many issues which are immediately dealt with through a practical application: a survey of the dynamics of mobility in the metropolitan area of Central Tuscany. Our goal is to show how Information and Communication Technologies (ICT) represent an opportunity for gathering information on the functioning of vast territorial systems through the processing of real-time statistical data, and how they can be utilized in order to improve our ability to plan and manage urban systems, with the idea of opening a window to the smart city of the future.

Riccardo Maria Pulselli The Moving City

€ 24,00

The Moving City How to Explore Urban Kinetics

Riccardo Maria Pulselli

The Moving City How to Explore Urban Kinetics

University of Siena

Region of Tuscany/ General Directorate of Territorial and Environmental Policies

Ecodynamics Group/ University of Siena http://www.ecodynamics.unisi.it The MoTo (Mobile Toscana) project has been funded by/ the General Directorate of Territorial and Environmental Policies of the Region of Tuscany. MoTo Scientific Director/ Nadia Marchettini Development and elaboration of the research/ Riccardo M. Pulselli and Pietro Romano MoTo has been developed based on data provided by/

Graphic design/ gabriele and francesca PULSELLI Architetti Associati http://www.pulselli.it English text translator and reviewer/ Bonnie Eldred ÂŠ 2011/ all rights reserved Laris Editrice via Fontibuona 6/A, 53034 Colle di Val dâ&#x20AC;&#x2122;Elsa/ SI_Italy http://www.lariseditrice.it ISBN: 978-88-88718-26-2 Cover/ Patchwork by Gabriella Maria Cordelli (graphic elaboration)

to Enzo

Summary

9 20

Foreword by Michael Batty Introduction by Adriano Poggiali

BASE STATION

1/ KINETICS

2/ CELLS

14 24 34

4/ PIXELS

3/ PHYSICAL SPACE

7/ NARRATIVE ELEMENTS

42 5/ UNITS

96 9/ AFTERWORD by Nadia Marchettini

108

6/ MOTO

76 102 8/ THE SMART CITY

Foreword and Introduction

Foreword by Michael Batty, Director of CASA, University College London Cities are restless, ever changing, never in equilibrium. Their physical elements and the populations that occupy them are always moving in space and time. Births, deaths and migration continually reinforce the annual cycle, while movements within the city to and from home, work, entertainment establish diurnal routines that are peppered with less frequent, often disruptive events. Buildings age, are regenerated, demolished, and arise anew with different activities and land uses occupying their physical structures on different cycles from their physical longevity. In all of this, we are forced to consider cities as being structures that are far-from-equilibrium with their own dynamics that are interwoven within their physical fabric in convoluted and complicated ways. These perceptions only now are becoming significant: the kinetics of cities is in its infancy. Changes in how we think about the dynamics of cities are part of the rise of the complexity sciences which consider systems to be far-from-equilibrium subject to chaotic, discontinuous and often disruptive forces that upset the diurnal and annual rhythms that define how cities function. But even more important to an understanding of the contemporary city is the rise of new technologies that are enabling us to interact in ways that are considerably less visible than in the world of past cities where material flows dominated the way in which the parts of a city were stuck together. Information technologies built around the internet, wireless communication infrastructures, smart phones that can access many of these networks, and devices for sensing change and movement in real time are yielding fundamentally new kinds of data that we now have available to understand the city. Some of this data provides us with much better spatial-temporal series of how cities function and change across different scales while at the same time posing massive challenges as how to detect, access, and store the resulting data in a way that extends our analytical understanding. But much of this data that is now driving change in the city is largely invisible to our methods of collection for it requires the very technologies that create that data in the first place to sense and record it, and these are largely inaccessible to our scrutiny. Nevertheless, we need to grasp the nettle of constructing a kinematics of cities that encapsulates all these notions of interaction and communication that form the glue that stitches the locational structure of activities in cities together. This is what Riccardo Pulselli does in this book. Using the example of emergent urban form

and structure in Tuscany centred on Florence, he provides a rich analysis of the diurnal and annual patterns of mobility and change in activities and land uses in the region. Indeed his core argument, which few can disagree with but most have not yet articulated, is implied in his quote from Franco Bolelli who in talking of the contemporary city, says that if “ ... we want to survive and indeed advance, we cannot help but map the territories that we go to explore day by day”. This is something that we have never even tried to broach – monitoring, recording, storing and analysing how cities change every day, but as the Pulselli argues, it is essential not only if we want to get to grips with the essential dynamic of how cities function in real time but also evolve to very different structures over longer periods. His meticulous charting and visualisation of flows and movements in urban Tuscany points the way to how we might begin to construct a science of cities that treats them as fluid, liquid and changeable in ways that defy the fact that our superficial observations at any point in time, see them as rigid, fixed in time, unvarying, and of course in equilibrium. What Pulselli is suggesting here is that when we examine interactions that take place in space and time, we need to move beyond ways of conceptualising them in static ways. We need to consider them collectively in ways that enable us to know something more than the pairwise dynamics that is characteristic of the way we now model interaction and their intensities. This is a huge challenge and this book is a mere beginning. But it points the way forward in a most accessible manner to methods and visualisations of complex urban phenomena. Another of the commentators who he quotes on this work, Paolo Portoghesi, suggests that methods built around these ideas provide “ … a sort of X-ray that renders visible the hitherto invisible fabric of immaterial relations animating a region”. To discover how, read on.

Introduction by Adriano Poggiali, General Directorate of Territorial and Environmental Policies, Region of Tuscany Knowledge for Innovation: the public transport network in the Florence – Prato – Pistoia Area There is no doubt that the knowledge of phenomena is the basis for any planning and organizational process of a city and its territory. The knowledge of the dynamics of mobility linked to the multitude of movements, which often condition the choices made within highly structured territorial systems, becomes a strategic element for the definition and planning of the network of services and their resulting infrastructures. The Florence – Prato - Pistoia (Fi-Po-Pt) area, within the metropolis of central Tuscany, is a complex territorial system, whose strong growth process since the end of the Second World War has defined it as a residential area with a great number of businesses, services, commercial and executive activities. The daily relations among the municipalities around the capital of Florence and those close to Prato and Pistoia, as well as those with the district of Empoli, determine a strong pressure on the city of Florence, as they are especially dynamic and not always easy to read. Many sample investigations of the daily movements in the Fi-Po-Pt metropolitan area have highlighted the particular complexity of the reading and analysis of this area’s mobility. Recent data have revealed how the reasons that move people and determine the high level of mobility are due to the following main motivations: work 36%, study 6%, free time 25%, personal reasons 33%. If we add up free time, study, and personal reasons, we find that 63% of these habitual movements are not involved with work, and therefore are not systematic. And if we then consider that working activities often involve more than one movement with respect to the “classic” work-home route, we can understand how difficult this phenomenon is to interpret. This is shown by the traffic that is found on the “arches” of the current road network, as a sum of the circulation among the centers and urban systems, which produces congestion along several parts of the network and that creates difficulty when accessing the functions, workplaces, schools, services, and residences found there. This is also why it becomes increasingly complex when attempting to define and plan a system

of public transport, as an alternative to the use of a private automobile, that can adequately respond to different mobility needs. However, when options that are coherent with the needs of the population are researched and created, as in the case of Florence’s first tramline, that connects Florence to Scandicci – which, beyond all expectations, moves a considerable number of users, from 25,000 to 40,000 daily – we get very close to that balance that has been pursued and achieved by many European cities. As a matter of fact, a recent survey carried out by the Region of Tuscany, in collaboration with the municipalities of Florence and Scandicci, reveals that approximately 15% of the users of the tramline used to use their automobile for the same journey, and 7% used a motorbike. Therefore, we have from 1900 to 3000 less automobiles and from 900 to 1400 less motorbikes on the thoroughfare. How to create and complete the tramline system network in the area of Florence has generated much debate and differing stances, within the technical-scientific structures that deal with mobility and transport as well. The difficulties in choosing the layout and intensity to utilize on the city’s thoroughfares, and how these are integrated with the primary networks such as the railways or regional services, also depend on the definition of the demand for mobility in an area as complex as that of Florence and the Fi-Po-Pt metropolitan area, with its urban structure and great amount of high-quality historical and residential architectural elements. These are some of the reasons why the Region of Tuscany has approved and financed this proposal by the University of Siena to study the mobility in the metropolitan area of central Tuscany, with research based on the data of the diffusion of cellular telephones in Italy, that utilizes the calls made and received on mobile phones within the Fi-Po-Pt metropolitan system. The results, therefore, are a photograph of the presence and accessibility (with the possibility of estimating the number of people) in the different zones of the metropolitan territory at different times of an average workday. This data that reveals the concentrations of people emphasizes the need to design and create a network of transport services that serves those parts of the territory where the demand for mobility is most concentrated and that, guaranteeing an adequate level of accessibility, constitutes a real alternative to the use of the private automobile, hopefully limiting its use to the outlying areas of the city where one can easily exchange it with an efficient system of transport services.

In order to build a network within a complex urban system, it is necessary to develop a quality transport system; solutions must be designed that, in addition to guaranteeing adequate levels of accessibility, can offer frequent services, high regularity and comfort, reliable travel times. The tramline network becomes, on one hand, an additional means of transport that conditions and attracts users towards the public service in general, and towards the railway transport in particular, for movements in the regional and metropolitan area, and on the other hand it becomes a system for moving within the city of Florence and its outskirts. The creation of this network and its extension towards the suburban zones could also guarantee the city and its hinterland a progressive process of urban reorganization and rationalization, a necessary element of the process of requalification of the territory and the environment, allowing for improvement of the quality of the â&#x20AC;&#x153;urban spacesâ&#x20AC;? and settlements. It is therefore necessary that the system of knowledge of phenomena, like that advanced by the University of Siena, becomes increasingly analytic and dynamic, in order to photograph mobility in its daily development, so that we may create, along with further data banks on accessibility, an element that is fundamental for the planning decisions for the transport and infrastructure network, and to contribute to the examining and monitoring system for the creation and verification of the same projects and achievements.

At all levels we observe events associated with the emergence of novelties. These narrative historical aspects are part of complexity. Complex systems share the feature of exhibiting a great variety of behaviors. […] The most common evidence of complexity comes from phenomena at the macroscopic level. Here emphasis is placed on the origin of collective behavior in multi-unit systems giving rise to new, emergent properties absent at the level of the units when isolated. Ilya Prigogine

1/ KINETICS

Kinetics is the science that studies movement. Kinetic theory was born to explain the essential characteristics of matter, based on the hypothesis that matter is made up of countless small particles in movement. Traditionally, in Physics, this theory allows us to calculate the macroscopic behaviour of gas based on the microscopic properties (velocity, kinetic energy, etc.) of the molecules it is composed of. Chemical kinetics studies the variations of the concentration of reagents and products in time, and can be established experimentally through the observation, with appropriate tools, of processes and chemical reactions. Ilya Prigogine1, the father of Evolutionary Physics, along with Isabelle Stengers, has observed how, in some particular chemical reactions, the kinetics of reactions can cause the formation of spatial and temporal structures that are ordered and distinct, starting from an initial state of uniformity and chaos. Even examples of kinetic art exist, a trend that was popular in the 1960â&#x20AC;&#x2122;s in the United States and Europe, in which the artists ventured into the attempt to render the illusion of movement through the shifting of the view or the perception of figures emerging from a combination of simple elements. Recently, contemporary artists have created installations - such as spaces of kinetic activation, sound-synchronized computer-controlled LED, and traces drawn by the action of an observer - that point at behavioural dynamics and the possible forms in which they appear. In the various frameworks of interpretation, the subject under observation is an overall organization in which a set of related elements come to build a single system that is ordered in space and marked in time. This systemic vision is the key to understanding the properties of the whole in the cases where the formation of dynamic configurations manifest at the macroscopic level, in systems made up of simple components whose interactions occur at the microscopic level. In line with what Ludwig Von Bertalanffy2, one of the fathers of chaos theory, has asserted, in these cases the organization of the system emerges as added information that is not visible when observing the single parts. Kinetics, especially in the fields of the science of chaos and of complex adaptive systems, offers a possible perspective for the interpretation of many real processes and systems with

self-organization properties. Intended broadly, this may indicate a possible direction that the field of action of the disciplines of territory and urban design may expand towards. Dynamics, above all, have assumed fundamental importance for the understanding of urban and metropolitan systems. The formal, structural, and functional aspects of the city are not sufficient to describe its functioning, if not in static terms. In order to grasp the variety of phenomena that occur in urban space, tools are needed that are capable of observing and measuring the dynamics of the system beyond its physical conformation. Today, we may note how the increased complexity and fluidity of the contemporary city â&#x20AC;&#x201C; multipurpose, multimedial, global â&#x20AC;&#x201C; on one hand, and the increased potential for the use of technologies and tools for the capturing and processing of variable information in space and time, on the other, offer the occasion to search for new opportunities for development and to imagine the intelligent cities of the future.

1/ KINETICS

Space of Kinetic Activation: installation by Marina Apollonio (2007) exhibited at the Schirn Kunsthalle Museum in Frankfurt.

where? when?

for how long? Dance Floor: installation by Piotr Uklanski, Palazzo Grassi (1996) â&#x20AC;&#x201C; A lit grid is made dynamic by a sound-synchronized computer-controlled LED system.

1/ KINETICS

Newspaper: installation by Jochem Hendricks (1994) â&#x20AC;&#x201C; black line meanders across the sheets are traces of human eye movements.

how intensely?

In much the same way as a remote sensing specialist might examine the spectral signature of a distant object and make assumptions about its underlying components and structure, today we can understand the temporal signatures of cell-phone antennas and infer the underlying organization of space itself. Thus we are able to shed light on how data generated as a byproduct of network activity by large populations can drive our understanding of the built environment and its usage. Carlo Ratti

2/ CELLS

The capillary gathering of statistical data at the level of elementary units, and its processing with the perspective of understanding the widest territorial dynamics on a vast scale, respond to the need to improve our ability to understand the functioning of urban systems and reduce the level of uncertainty and approximation of the current investigative tools. The possibility for a systematic and accurate monitoring through bottom-up procedures, in which individual behaviors compete for the functioning of a macro system, represents a perspective that is evermore desirable and concrete, also thanks to the recent development of wireless technologies, one of the sectors with the highest rate of innovation and diffusion in recent years. The innovation of the mobile telecommunications network, in particular, consists of the exchange of information in two directions, from fixed positions where the antennas are installed, to the mobile devices in the hands of the individual users, and vice-versa. The level of activity of the network, which depends on the number and activity of users, is already a significant piece of data that can provide an extraordinary opportunity to understand the dynamics of human activity in physical space. In this context, the antennas and receivers can be considered as actual investigative tools. The information registered through the mobile telecommunications network is an emblematic example. If we assume that, with a close approximation, the intensity of telephone traffic is proportional to the number of users present in a given territorial area, it is possible to deduce that the variations in activity correspond proportionately to the variations in population density. Through the systematic measuring of this data, it is possible to monitor times and intensity of use of the space in a vast urban area. The processing in aggregated, and therefore anonymous, form of punctual data, that is localized in space and variable in time, determines an exemplary procedure for obtaining a real measure of dynamic processes in an urban system and for making information visible that otherwise could not be directly observed. The objective is to detect the distribution in space, observe the variations in density over time, and visualize the concentration and the movements of the population throughout the territory. In other words, to understand where, but most of all when, for how long, and how intensely the spaces and services of the contemporary city are used.

The structure and organization of the date / hour land-based network of mobile telecom-06/02 00:00..01:00 06/02 01:00..02:00 munications was reconstructed based06/02 02:00..03:00 03:00..04:00 on the position (geographical coordi- 06/02 06/02 04:00..05:00 06/02 05:00..06:00 nates) and dimension-orientation of 06/02 06:00..07:00 07:00..08:00 the antennas fixed to based stations. 06/02 06/02 08:00..09:00 BASE STATION

06/02 09:00..10:00 06/02 10:00..11:00 06/02 11:00..12:00 06/02 12:00..13:00 06/02 13:00..14:00 06/02 14:00..15:00 06/02 15:00..16:00 06/02 16:00..17:00 06/02 17:00..18:00 06/02 18:00..19:00 06/02 19:00..20:00 06/02 20:00..21:00 06/02 21:00..22:00 06/02 22:00..23:00 06/02 23:00..24:00 06/02 00:00..01:00 06/02 01:00..02:00 06/02 02:00..03:00 06/02 03:00..04:00 06/02 04:00..05:00 06/02 05:00..06:00 06/02 06:00..07:00 06/02 07:00..08:00 06/02 08:00..09:00 06/02 09:00..10:00 06/02 10:00..11:00 06/02 11:00..12:00 06/02 12:00..13:00 06/02 13:00..14:00 06/02 14:00..15:00 06/02 15:00..16:00 06/02 16:00..17:00 06/02 17:00..18:00 06/02 18:00..19:00 06/02 19:00..20:00 06/02 20:00..21:00 06/02 21:00..22:00 06/02 22:00..23:00 06/02 23:00..24:00 06/02 00:00..01:00 06/02 01:00..02:00 06/02 02:00..03:00 06/02 03:00..04:00 06/02 04:00..05:00 06/02 05:00..06:00 06/02 06:00..07:00 06/02 07:00..08:00 06/02 08:00..09:00 06/02 09:00..10:00 06/02 10:00..11:00 06/02 11:00..12:00 06/02 12:00..13:00 06/02 13:00..14:00 06/02 14:00..15:00 06/02 15:00..16:00 06/02 16:00..17:00 06/02 17:00..18:00 06/02 18:00..19:00 06/02 19:00..20:00 06/02 20:00..21:00 06/02 21:00..22:00 06/02 22:00..23:00 06/02 23:00..24:00 06/02 00:00..01:00

FY36S1_01 550m NN_4848XXX EE_1681XXX

FY36S1_02 1100m NN_4849XXX EE_1682XXX

FY36S1_03 1650m NN_4849XXX EE_1682XXX

FY36S1_04 2200m NN_4849XXX EE_1683XXX

FY36S1_05 2750m NN_4849XXX EE_1684XXX

FY36S1_06 3300m NN_4849XXX EE_1684XXX

FY36S1_07 3850m NN_4849XXX EE_1685XXX

FY36S1_08 4400m NN_4849XXX EE_1685XXX

FY36S1_09 4950m NN_4850XXX EE_1686XXX

FY36S1_10 5500m NN_4850XXX EE_1686XXX

FY36S1_11 6050m NN_4850XXX EE_1687XXX

FY36S1_12 6600m NN_4850XXX EE_1687XXX

FY36S1_13 7150m NN_4850XXX EE_1688XXX

FY36S1_14 7700m NN_4850XXX EE_1688XXX

0 0 0 0 0 0 0 3 15 5 16 12 100 51 94 10 49 13 43 38 36 9 7 10 6 28 0 0 0 0 0 11 42 9 25 74 29 37 45 176 96 68 37 67 85 21 75 0 255 33 240 16 0 0 67 769 3240 3335 3702 3489 3796 4964 3544 3667 3889 3769 4343 4200 2194 979 1149 1110 1168

6 0 2 0 0 2 0 135 512 641 1276 567 1824 842 816 1006 758 1225 1641 1349 1890 1040 338 113 441 1150 33 18 64 0 188 589 1550 1785 1381 2555 2144 1826 1903 2336 3529 3051 3756 3308 2196 651 1596 312 3583 744 566 66 153 54 853 13209 36376 41194 44813 57559 57388 47920 43988 45476 52893 56086 58941 57735 30205 17613 12603 9973 11572

102 70 7 0 0 1 33 1188 3025 5754 6832 7602 5772 5350 8124 15630 6671 10110 13739 15912 13041 6934 4364 1483 2576 1877 898 672 239 424 1498 5081 13429 15535 14989 16474 16259 14525 16795 18701 22058 19558 19081 26125 15830 7125 2726 2559 1291 452 275 28 234 234 249 3650 14643 27882 25559 22468 25711 22753 22487 22665 25538 21820 25905 21339 13332 10942 11018 3127 335

1316 165 73 0 0 166 478 4562 9114 15321 12660 15638 16223 9874 11501 12185 13229 17027 15980 20151 10397 9500 4028 2471 1885 1016 484 427 91 401 757 6753 10209 13728 14043 13482 17000 15437 10340 14177 23192 27380 19939 24178 12431 8577 5919 4238 106 0 95 22 122 0 166 1653 4638 8958 3149 3813 3787 5248 4194 3973 5529 5576 8217 4464 3927 1901 882 660 42

5459 3823 49 4 0 40 136 1493 5068 8411 8707 7960 9868 4279 7022 7451 5232 5973 6133 7064 3758 2947 952 2434 4116 54 24 0 1 35 349 2783 7732 10321 18778 13426 15282 13143 10978 10788 17009 18943 18402 22030 23414 7817 4248 501 0 0 101 59 0 0 0 84 380 477 155 113 338 301 133 152 1424 527 1572 287 0 61 0 0 0

555 281 48 28 0 42 270 2408 7550 12733 13430 14296 10545 6731 9313 13386 12001 11856 12583 11836 8398 4451 2006 1062 3354 237 15 0 194 97 188 1764 5702 7139 5575 7840 7032 7779 3665 8260 7985 6397 11621 12295 10171 4695 1173 780 0 0 0 0 0 0 0 0 5 6 0 0 0 0 0 11 19 4 30 0 7 10 0 0 0

700 410 63 47 45 64 63 1169 4619 5077 7116 9142 16277 5957 6972 7185 6827 4876 6886 6724 3650 3093 1835 1341 244 32 48 0 0 0 0 311 885 1347 487 527 1272 1125 957 645 2433 891 2231 2198 2957 636 1223 353 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 11 0 0 0 0

2552 1098 0 11 0 61 73 542 2268 4522 4252 3627 4509 4288 3537 4534 4359 3890 7679 6890 1874 3593 3582 4808 13 0 0 0 23 0 0 35 233 696 409 1370 1156 266 438 402 299 784 942 1224 74 90 44 48 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0

25 0 0 25 0 11 83 832 1906 5329 2987 835 2440 3098 3015 3364 9524 4400 10101 5874 5899 2534 2585 1206 350 0 0 0 0 0 0 13 92 8 136 129 58 15 38 291 140 51 128 66 74 0 11 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

18 0 0 11 0 0 26 355 517 649 956 707 1554 545 1199 496 1404 912 1155 965 1902 233 578 53 0 0 0 0 0 0 0 0 0 0 0 0 2 0 24 64 0 18 25 35 22 21 0 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 37 386 299 378 665 1575 543 532 1079 903 512 302 318 327 550 19 9 0 0 0 0 0 0 0 0 2 69 4 0 0 0 0 0 22 28 0 13 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 117 202 69 52 52 303 135 258 840 241 377 957 363 756 229 61 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 19 20 0 0 0 0 74 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 13 23 39 20 47 39 34 16 91 100 113 47 65 50 12 133 0 0 0 0 0 0 0 0 33 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

ID cell

time interval

ID antenna FY36S1

01 02 03 04 05 06 07 08 09 10 11 12 13 14

ANT 3 CELLS

ANT 1_FY36S1

ANT 2

DUOMO

ID site/base station

The activity of the antennas (number of calls) was registered at hourly intervals per cell sectors in subsequent segments of 550 meters along the direction of propagation of the signal.

subsequent segments of 550 meters from the antenna

data (number of calls)

geographic coordinates

2/ CELLS

600000

90% activity

Values of activity of the antennas (number of calls in 24 hours) in subsequent segments of 550 meters. The activity is mainly registered within a distance of 4400 m from the antenna (90%).

500000 400000 300000 200000 100000

11%

14%

17%

Cell_14 7700m

Cell_13 7150m

Cell_12 6600m

Cell_11 6050m

Cell_10 5500m

Cell_09 4950m

Cell_08 4400m

> 10%

Cell_07 3850m

Cell_06 3300m

Cell_05 2750m

Cell_04 2200m 25%

33%

precision-approximation 50%

100%

Cell_03 1650m

Cell_02 1100m

Cell_01 550 m

The degree of spatial approximation is directly proportional to the distance from the antenna. The level of precision-approximation varies from 50% to 10% in the first 4400 m in which 90% of the antennaâ&#x20AC;&#x2122;s activity is positioned.

A city is made up of the complexity of its functions. On the same land, in the same square, there are people that live there, that come to enjoy themselves, to shop, to visit; or that come to work. A mix of all these functions in the same place: thatâ&#x20AC;&#x2122;s what makes a city. This intensity is what gives a human dimension to the city. Renzo Piano

3/ PHYSICAL SPACE

“Accessibility” is a key word of the contemporary world when dealing with the management of a territory. It indicates the procedures of physical access to the functions of the city, the possibility to use the space, to have adequate infrastructures available, to use services, to move freely. The growth of cities in size and complexity is a critical factor that is very important in today’s world, as it conditions the dynamics of the system, entails instability and hardship, and compromises the accessibility and efficiency of functions and services. The report by the United Nations entitled World Urbanization Prospects (2009) relates the statistics on the growth of the world population and that of the cities of the world. Since 2009, the number of residents in urban areas (3.42 billion) has exceeded the number of people living in rural areas (3.41 billion); in other words, the world has become more urban than rural, and it is predicted that, according to current trends, the world urban population will continue to grow to a percentage of 84% in 2050 (6.3 billion). In Europe, the population grew from 547 (1950) to 732 billion (2009) and, contextually, the residents in urban areas passed from 281 (51%) to 531 billion (72%). In Italy, the population grew from 2.53 (1950) to 6.83 billion (2009) and, in the urban areas, the residents passed from 54% to 68%. In calculating 2050, this rate is estimated at approximately 80% of the population. The metropolitan area of Central Tuscany is an emblematic case study in the European context, with a resident population density of 820 inh./km2, with maximum values in the city of Florence (3,175 inh./km2).The physical growth of the entire urban system has occurred rapidly and unsystematically in the last 50 years. The increased burden on the territory, in terms of population presence, tourist confluence, mobility of people and goods, and dislocation of services, has ensued more rapidly than the contextual reorganization of the urbanterritorial structure. This structure mostly traces the layout present at the end of the 1800’s, with few new elements except for the infrastructures on the national and regional scale. The general increase in mobility, laid out on a road system conditioned by the historical road network and on a transport network that is limited and not easily adaptable to the dislocation of functions and centers of attraction in peripheral areas, is at the base of the frequent phenomena of congestion and inefficiency.

In the Tuscan Metropolitan Area, as in many other cases in Europe, the progressive integration of functions and the resulting increase in the complexity of dynamics and social relations have made the understanding of the times and conditions of the use of urban space ever more uncertain and complicated. The city has become articulated and manifold, and our ability to give meaning to these changes and manage this complexity has not evolved as much. Traditional approaches, useful as they are, present clear limits. More often than not, these reduce the city to a sum of its parts, and overlook new forms of investigation, new tools and new visions. As Koolhaas, Boeri and other modern urbarnists3 have also recently ascertained, the manifestation of the strengths that configure the city has passed from the visible to the invisible sphere; that is, the city can no longer be represented only in terms of composition and form, but through the investigation of demographic, social, and economic phenomena.

45km

> < 35km >

Plan-Masse Central Tuscany Metropolitan Area: the Florence-Prato-Pistoia plain and the axis Signa-Empoli-SanMiniato are part of a vast metropolitan system that extends over 1575 kmÂ˛ (45Ă&#x2014;35 km), with over 1,200,000 inhabitants.

3/ PHYSICAL SPACE

SYSTEMS AND STRUCTURES Urban shapes and spatial organization

The road system is characterized by the layout of the A1 highway that skirts the urban area of Florence, the A11 highway that passes through the Florence-Prato-Pistoia plain, and the FI-PI-LI freeway in the Arno plain.

A11

FI_PI_LI

The orographical system is characterized by the large Florence-Prato-Pistoia plain and by the Arno basin and its main tributaries: Mugnone, Greve, Bisenzio, Ombrone, Pesa, Elsa. 50% of the territory is hilly, while the Florence-Prato-Pistoia plain occupies 28% of the metropolitan territory. The remaining 22% refers to the Empoli plain.

3/ PHYSICAL SPACE

The built area results as being equal to a surface of 35 km2 for a cubage of 308 million m3 of buildings for civil use, and 16 km2 for a cubage of 104 million m3 of productive buildings (source: regional CTR). The overall urbanized area is equal to 273 km2 (source: ISTAT).

Network Structure: land-based network of mobile telecommunications. In the area of study, data was surveyed for over 10,000 cells.

Manufacturing industrial districts and the nurseries for plants in the area near Pistoia. Urbanization process of the Florence-PratoPistoia plain in 1951 and in 1984. fonte: Edoardo Detti et al. (a cura di). Processo di urbanizzazione nellâ&#x20AC;&#x2122;area Firenze-Prato-Pistoia. La Casa Usher, Firenze 1984

Via della Cupola is an example of the overlapping A1-Inceneritore A11 - aree produttive e artigianali of historical presences with the structures and lungo l’autostrada infrastructures of the contemporary city.

A1-Chiesa sull’Autostrada

Peretola, via Pratese La cupolina

Peretola - viadotto ferroviario

Scandicci, piazza Piave - Biblioteca

Extensive commercial spaces have recently Peretola Airport Osmannoro - Ikea created new polarities and conditioned the mobility system in the vast area.

Scandicci - Teatro Studio

Campi Bisenzio, via F. Cervi area Gigli

The constellation of manufacturing areas spread the territory have hadFranchi a rapid andviale A. Guidoni Firenze, Stazionethroughout Ferroviaria Campo di Marte - Stadio Artemio Firenze, Santa Maria Novella Palazzo di Giustizia

Firenze, viale Giannotti Centro Commerciale Coop

Firenze, via Novoli Palazzo della Regione

Empoli, FI-PI-LI aree produttive e artigianali

Empoli, Stadio Castellani

Prato, Piazza del Duomo

Prato Piazza S.Maria delle Carceri

Pistoia, Piazza del Duomo

Pistoia, Chiesa San Giovanni Fuorcivitas

Pistoia, via Adua Centro direzionale e commerciale

often chaotic development, not adequately integrated with the historical environmental context.

Empoli, via Livornese Centro Commerciale Coop

Prato, via G. Valentini - area mista Prato, Piazzale dell’Arco della Pace

3/ PHYSICAL SPACE

Florence is the city of history, a main tourist attraction butviaalso a -main service Sesto F.no, piazza della Chiesa Scandicci, via Pantano Scandicci, Pisana area residenziale aree residenziali

Sesto F.no, via Pasolini - Iper Coop

Calenzano, via di Prato - Carrefour

Careggi, Ospedale

Firenze, piazza della Signoria

Firenze, Duomo

Firenze, via dei Calzaioli

Firenze, piazza Puccini Teatro Puccini

Novoli Nuova sede universitaria

Brozzi, Quartiere le Piagge “Le Navi”

Parco delle Cascine

Prato, Piazza Mercatale

Prato, via F. Ferrucci Centro Commerciale cated to nurseries

Pistoia - Ansaldo Breda

Pistoia, via S. Pertini - Pistoia Fiere

center for the entire metropolitan area.

Prato, cityIsolotto, of innovation, known as a manufacViadotto dell’Indiano Empoli, Piazza Farinata degli Uberti Collegiata di Sant’Andrea turing center, in particular in the textile sector, hosts the Pecci Museum of Contemporary Art.

A vast part of the Pistoia area is dediPrato, viale L. da Vinci - aree residenziali for plants, a unique garden in the plane’s landscape.

Pistoia, vivaismo

Prato, via Palermo - Centro Commerciale Prato, Museo Pecci d’Arte Contemporanea

Pistoia - via Bure Vecchia centro commerciale

Pistoia - area residenziale

POPULATION

Population growth trend from 1951 to 2005 (source: ISTAT 2001)

Area Metropolitana

900

600 Hinterland Firenze

300 Prato

The curves show that, starting in 1961, while Florence experienced a drop in resident population after a phase of rapid growth, the urban area began to expand continuously throughout the plain, contributing to the development of the vast metropolitan area.

View from Poggetto, Poggio a Caiano

2005

2001

1991

1981

1971

1961

1951

1931

1921

0 1911

Thousands

1.200

Seano (Carmignano) production and handcrafts area

3/ PHYSICAL SPACE

The diagram shows the polarities and the various occupations of the territory. In the Florence-Prato-Pistoia plain, 72% of the population and 81% of the personnel, out of the total for the metropolitan territory, are concentrated.

WORKERS

60%

50%

Textiles Steel Manufacturing Commerce Tourism Services

Concentration of personnel per activity sector in the metropolitan area (source: ISTAT 2001).

40%

30%

20%

10%

Montale

Montemurlo

Firenze

Prato

Poggetto (Poggio a Caiano) production and handcrafts area v.le XVI Aprile: bridge over the Ombrone River

Scandicci

Sesto Fiorentino

Calenzano

Campi Bisenzio

Prato

Quarrata

Montemurlo

Montale

Agliana

Pistoia

Cities […] emerge from the bottom up, and the spatial order we see in patterns at a more aggregate scale can only be interpreted in this way. The way we simulate this emergence is by representing the basic elements (atoms) of the city as being composed of two distinct but correlated entities: cells, which represent the physical and spatial patterns of the city, and agents, which represent the human and social units that make the city work. Michael Batty

4/ PIXELS

The configuration of the contemporary city, or better yet, the use that citizens make of it, is a result that emerges from the bottom up. The way in which we represent the city, and what we call the geo-demographic system, consists of the combination of the geographic spatial dimension with the human social dimension; in the language of models, these can be called cells and agents. In the case of mobile telephone surveying, the variable set of values indicates intensity of activity, that is, the variation in population density over time surveyed within specific spatial areas. The choice of the pixel as the reference spatial unit is an expedient that, even if it does not conform to the real morphology of the territory, allows for a homogeneous treatment of data throughout the surface. The dimension of the pixel corresponds to the best level of spatial definition that can be obtained with a good approximation. The plan for data processing is predisposed to take in information starting from a survey that is accurate but discontinuous (due to the placement of the antennas in the telecommunications network), and to return a normalized data with respect to the minimum spatial reference unit. The transition from discrete, or punctual information (that of the cells), to a set configuration that is diffused and continuous in space (that of the pixels), through geostatic or geoprocessing procedures, is consistent with the interpretation of the city as a single cohesive system equipped with an overall organization. This criteria is shared with other simple models of cities, in which the spaces that host activities are designed within a grid, and the relations among the parts simulate actions that occur within one pixel and that influence the behavior of the adjacent pixels. Among others, the case of the so-called cellular automata is emblematic, as it possesses elements whose local action generates spatial order on a global scale. This same systematic vision is at the basis of another discipline that studies the spatial relations among species in the natural or anthropic landscape. Zev Naveh4, one of the founding fathers of landscape ecology, has described the landscape as an entire concrete human system, ordered and defined in space and time. In his vision, the network of relations cannot be simply understood through an analytical approach, but only through a synthetic vision, within a context, of a set organization.

[a]

FROM CELLS TO PIXELS The new frontier of the study of urban systems does not move away from this approach. This research studies the interactions among the populations and the territories in which they are settled, or rather, the effects of the structures of the urban landscape on processes. Spatial configurations with variable intensities tell of the dynamics of the population in a metropolitan area in relation to a context, a physical space, a set of infrastructures and services. These patterns indicate the relations among used structures and their users, and aid our comprehension of how physical structures condition the number and spatial distribution of â&#x20AC;&#x153;organismsâ&#x20AC;? in time. Data is registered by each individual antenna that transmits its signal over a series of defined areas, called cells [a]. Coordinates and directions of the antennas allow for the detection of the structure of the mobile phone network throughout the territory, and of the dimension-position of the single cells [b]. Activity data from the antennas, referred to the relative cells, is processed and connected to single spatial units identified by a reference grid [c]. The representation of data in the grid allows us to visualize the intensity of activity registered in each pixel in the form of an overall spatial configuration [d].

[b]

[c]

[d]

4/ PIXELS

< 500m >

The pixel is the minimum spatial unit of reference for the processing of the information: the activity data relative to each cell is reported on a cartographic basis through a 500Ă&#x2014;500 m grid.

< 500m >

Matrix: each pixel is identified within the matrix A=(ai,j); i=1â&#x20AC;Ś70, j=1â&#x20AC;Ś90. This allows us to process the punctual data, associated with the centroid of the single cells, with respect to their position within the grid. In this way, it is possible to associate the activity values to the space of one pixel ai,j.

ai,1 ... ...

... ...

a1,1

a70,1

... ... ... ... ... ... ...

... ... ai-1,j-1 ai,j-1 ai+1,j-1 ... ...

a1,j ... ai-1,j ai,j ai+1,j ... ...

... ... ai-1,j+1 ai,j+1 ai+1,j+1 ... ...

... ... ... ... ... ... ...

a1,90 ... ... ... ... ... a70,90

4/ PIXELS

i=1...70, j=1...90 »

∑ ∑ j+1

t1 i,j

a = ai,j + 0,3

ah,k

k=j-1 j+1

t2 i,j

t1 i,j

a = a + 0,2

ath,k

k=j-1

h i-1,i,i+1

Algorithm: in order to reduce the level of approximation in georeferencing data, starting with the values referred to the single pixels, a procedure is applied that is inspired by the spatial processing techniques of the cellular automata. The initial data localized in each pixel is summed, in a limited percentage, with the data in the pixels adjacent to the inside of a matrix grid 70×90. The calculation, performed in two times, t1 and t2, processes the initial data ai,j (number of calls / hour) within the matrix A=(ai,j); i=1…70, j=1…90. The algorithm, applied to each pixel, allows us to obtain, starting with discrete data, a configuration that is continuous and diffused in space.

(h,k)=(i,j)

4/ PIXELS

The 45x35 km area is transformed into a grid of 90x70 pixels. 6300 pixels make up the reference grid for processing information.

pixel/ minimum spatial unit

We are more likely to choose the best measurements if we can see them, appraise them with outstretched hands, not merely imagine them. Le Corbusier

5/ UNITS

The idea behind the Modulor consists of identifying “proportions and consonance” between us and our environment. This has been concretely translated into the adaptation of forms of architecture to the proportions of the human body, in order to obtain maximum levels of comfort in the use of spaces, furniture, and other common use objects. This is how LeCorbusier’s lesson, based on real measurements and on the rigor of a scientific approach, has conditioned the modern history of design. Could we say the same for urban design? On the vast scale of urban systems, the search for “proportions and consonance” presents clear difficulty. The expansion of settlements, the growth of the demand for mobility and the diffusion of urban functions and services have acquired unforeseeable dimensions and have not been supported by structural adaptation that is equally as fast. Congestion, pollution, and management costs that we incur in the contemporary city are proof of this dissonance between the architecture of the city and the rhythm of society. We believe that the planning of sustainable cities, with the objective, among others, of guaranteeing mobility and accessibility, must be resumed from a deeper knowledge of the dynamics and from the systemic vision of the phenomena that take place in the urban environment. Exploring urban kinetics has a twofold objective: that of obtaining a more exact measure of the activities of the population in space and time, and that of directing attention towards a set organization in which the functioning of the system is determined by the collective behavior of individuals. Today, proportions and consonance must be searched for at the level of the entire system, a cohesive and vital entity, with dynamics at a vast scale. The relations among the parts are an essential aspect and, at the same time, offer a key for interpretation. In a metropolitan area like that of Tuscany, specific areas are separately defined but conceived as part of a whole, each being measured with respect to the entire system. The quantities of activities are distributed in the various areas, or spatial units, as in a series of communicating vessels, each one connected to the others, and the levels of intensity rise and fall based on reciprocal exchanges. The whole is not simply the sum of its parts.

OVERLAP

from census zones to aggregated spatial units The spatial units correspond to urban zones with specific characteristics of physical conformation, structures, and land use. The definition of the units in the Tuscan metropolitan area is based on their correspondence with the ISTAT census zones, for which statistical data is available â&#x20AC;&#x201C; resident population, number of workers â&#x20AC;&#x201C; and on patterns of activity generated by the intensity surveyed for each single pixel. What has changed here is the ex-post identification of structural parts of cities that is consistent with the specific ways in which they are used, based on a capillary survey of statistical data from the bottom-up and with no reference to predefined (ex-ante) areas such as administrative or census boundaries (top-down). Morphing spatial units and census zones: the aggregate spatial units â&#x20AC;&#x201C; census zones comparison is useful for analyzing the dynamics of the activity surveyed in relation to the demographic-functional characteristics (resident population / number of workers) of the single units and to the whole mobility system (origin / destination).

5/ UNITS

RESIDENTS/ WORKERS Classes of aggregate units based on the predominant function, residential or productive. This analysis is based on the relation between the number of the resident population and the number of personnel (Source: ISTAT â&#x20AC;&#x201C; 2001 census and subsequent updates). Five classes are fixed on the map: the intermediate class, in yellow, identifies the mixed areas; the classes in orange indicate a predominantly residential function; vice-versa, those in green indicate zones that are mainly productive and industrial (the data relative to the number of residents does not count those who live in the area but are not legally registered residents, who are numerous in the area in and around Florence). The amounts relative to the population and personnel are reported on the map in black and red, respectively, and expressed in thousandths with respect to the total of the entire area of study.

residents/workers 0,04/0,3

0,3/0,5

0,5/1,6

1,6/3,5

3,5/5,5

5/ UNITS

10 21

Pistoia 19 11 13 4 8 13 11 10

12 9 14 9 6 03 17 21 9 32 18

48 39 19 20

11 9

22 18

9 9

Prato 33 37 2030

5 2

3 17

15 15

40 22

7 4

13 11

6 4

1 5

8 7 3 63 1619 15 3 7 Empoli 6

52 29 0 22 20 21

2 11 3 5 116

213

5 23

44 18

01 0 2

Firenze

16 17 44 38

62 73

2 7 93 81

50 133

51 24

31 18

12 7

4 2 7 6

9 4

9 4 6 3

5 2

6 4

4 3

ORIGIN/ DESTINATION Classes of aggregate units with respect to mobility and the presence of attractors. This analysis is based on the relation between the number of units/people arriving and those departing (Source: ISTAT) at the level of single aggregate spatial units. The data utilized derives from the ISTAT origin-destination matrix, which describes, based on a statistical sample, the number of systematic movements of one census unit towards others, and vice-versa.

origin/destination 0,04/0,3

Five classes are fixed on the map: the intermediate class, in pink, corresponds to the areas where the balance between arriving and departing units is even; those tending towards red indicate the centers of attraction; those tending towards purple indicate the main places of origin that correspond to primarily residential areas. The values express, in thousandths, the number of people entering per single spatial unit with respect to the total movements registered.

0,3/0,5

0,5/1,6

1,6/3,5

3,5/5,5

5/ UNITS

Pistoia

11 4

6 22

10 7

Prato

23 33

27 21

29 4

19 7

7 7

4 7

4 34

19 6

13 9

Empoli

Firenze

9 7

19 2

5 5

AGGREGATED SPATIAL UNITS SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

Agliana 108

680

192

200

1019

433

279

510

216

21 pixel = 5,25 Km2 Agliana Agliana AP 6 pixel = 1,50 Km2

Grassina 170 18 pixel = 4,50 Km2

Bagno a Ripoli Bagno a Ripoli 12 pixel = 3 Km2

Antella 9 pixel = 2,25 Km2

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS

TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

117

Carrefour AP

168

504

465

243

303

869

247

Capraia e Limite

502

118

Montelupo Fiorentino

190

129

12 pixel = 3 Km2 Calenzano Calenzano

28 pixel = 7 Km2

Gigli AP

154

26 pixel = 6,5 Km2 Campi Bisenzio

Campi Bisenzio

40 pixel = 10 Km2 156

Montelupo

16 pixel = 4 Km2

Montelupo AP

12 pixel = 3 Km

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

437

Carmignano Carmignano

363

155

1354

866

392

197

12 pixel = 3 Km2

128 Empoli AP

15 pixel = 3,75 Km

Empoli Centro

174

10 pixel = 2,50 Km2 Empoli 176

Empoli Nord

18 pixel = 4,50 Km

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

153

Empoli Ovest

842

208

406

188

185

280

223

6 pixel = 1,50 Km2

132 Empoli Sud

15 pixel = 3,75 Km2

Empoli

160 Empoli Est AP 6 pixel = 1,50 Km2

158

Fiesole Fiesole 15 pixel = 3,75 Km

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

135

Areoporto

838

463

1994

923

490

282

857

188

1570

390

9 pixel = 2,25 Km

177

Brozzi - Peretola

21 pixel = 5,25 Km2

Campo di Marte

40 pixel = 10 Km2

134

Firenze 144

Careggi

28 pixel = 7 Km2

165

Galluzzo

9 pixel = 2,25 Km

136 Isolotto

28 pixel = 7 Km2

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

149

Novoli

1569

973

1506

691

800

298

1707

2587

561

178

1253

398

34 pixel = 8,50 Km2 Rifredi

129

25 pixel = 6,25 Km2 157 Settignano

6 pixel = 1,50 Km

Firenze Uffizi - Pitti

131 171

25 pixel = 6,25 Km2 159 V.le dei Colli

18 pixel = 4,50 Km

145

V.le Europa

21 pixel = 5,25 Km

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

Polo di Sesto Firenze 8 pixel = 2 Km2

148

656

1349

398

305

529

147

Osmannoro AP

15 pixel = 3,75 Km

Sesto Fiorentino

140

Sesto F.no

33 pixel = 8,25 Km2

Impruneta

120

15 pixel = 3,75 Km2 Impruneta Tavernuzze

9 pixel = 2,25 Km

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

119 Fucecchio Fucecchio

566

239

663

199

389

174

1014

391

20 pixel = 5 Km

175

Lastra a Signa Lastrasigna 14 pixel = 3,50 Km2

91 Monsummano Terme Monsummano Terme 24 pixel = 6 Km2

104

Montale Montale 10 pixel = 2,50 Km2

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

425

Montemurlo AP

219

400

817

274

1364

1622

474

403

1226

219

760

231

24 pixel = 6 Km

Montemurlo Montemurlo

15 pixel = 3,75 Km2

Pistoia Centro

6 pixel = 1,50 Km2

88 Pistoia Est

15 pixel = 3,75 Km2 Pistoia

101

Pistoia Nord

9 pixel = 2,25 Km2

Pistoia Ovest

21 pixel = 5,25 Km2

107

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

110

Pistoia Sud Pistoia

439

207

712

180

387

312

927

503

1123

678

1659

710

21 pixel = 5,25 Km

429

Poggio a Caiano Poggio a Caiano 9 pixel = 2,25 Km

438 Prato AP

44 pixel = 11 Km2

Prato Centro

434

18 pixel = 4,50 Km

Prato Prato Est

424

25 pixel = 6,25 Km2 Prato Nord

25 pixel = 6,25 Km2

423

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

435

Prato Ovest

742

221

1056

448

330

175

276

37 pixel = 9,25 Km2 Prato 436

Prato Sud

18 pixel = 4,50 Km

103

Quarrata Quarrata 24 pixel = 6 Km2

236 San Miniato Sanminiato 20 pixel = 5 Km2

MAIN USE

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

SPATIAL UNIT 1pixel = 0,25 Km2

MUNICIPALITY

ISTAT ZONE

POP/px

WORK/px

MAIN USE

141 Scandicci AP 167

378

1561

333

226

214

533

133

28 pixel = 7 Km2 Scandicci Scandicci Centro

24 pixel = 6 Km2

Indicatore 172 6 pixel = 5,25 Km

Signa Signa

18 pixel = 4,50 Km2 AP= Production Area Production and Handcrafts Area

New Tramway

Urban Center

Commercial Center

Entertainment and Cultural Center

Administration

Hospital

Airport

University

Stadium

Sport Center

Hotel

Historical Center

Rail Station

IN/OUT FLOW

MOBILE ACTIVITY 24 h

5/ UNITS TREND 12 MONTHS

TREND 24 HOURS

12 MONTHS ACTIVITY

Total number of calls in workdays in 12 months The curve shows a profile of the usage of metropolitan functions and spaces by the population (variation in spring and summer).

9,0

8,80

8,0

9,09

8,76

8,56

8,75

8,16

7,85

8,68

8,47

8,45

8,76

7,0 6,0

5,66

5,0

JAN

FEB

MAR

Viadotto dellâ&#x20AC;&#x2122;Indiano

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

DEC

View from Soffiano

5/ UNITS

24 HOURS ACTIVITY

Number of calls in the 24 hours of a workday

The curve reveals information on some aspects of peopleâ&#x20AC;&#x2122;s daily life in the metropolitan area (morning, evening, lunch break).

9,0

8,00

8,0

6,03

7,0

6,91 7,02

3,69

5,0

7,70

6,21 7,13

6,0

8,40

7,10

6,55

6,31

4,59 5,51

4,0 3,0 2,0 1,0

3,02 0,13 0,25

h06

h07

2,00 1,11 h08

0,58 1,12

0,31 0,20 0,14

h09

h10

h11

h12

h13

h14

h15

h16

h17

h18

h19

h20

h21

h22

h23

Convento di S.Lucia alla Castellina Palazzo di Giustizia Parco delle Cascine

ITCS Galileo Galilei School

Piazza Isolotto

h24

h01

h02

h03

h04

h05

Villa Petraia

Doesnâ&#x20AC;&#x2122;t it seem foolish to keep interpreting this world, so immeasurably different from the world of just a few years ago, with old maps, where there is no trace of all these metamorphoses, where the Earth still seems flat? Like the pioneers, if we want to survive and indeed advance, we cannot help but map the territories that we go to explore day by day. Franco Bolelli

6/ MOTO

MoTo is an acronym for Mobile Tuscany, the name for a project funded by the General Direction for Territorial and Environmental Policies of the Region of Tuscany that supports research and innovation in the territorial and environmental field. Moto studies movement as the effect of the combined motion of thousands of particles, individuals in a community. That the dynamics of the population are the subject of the representation is not a trivial factor. It should not be taken for granted that innovation in the territorial and environmental field is aimed towards overcoming the limits imposed by the three dimensions of the cartographic representation of the world. According to Franco Farinelli5, a contemporary geographer, the definition of the city, from the 1700’s until today, as a set of things – houses, streets, public squares and other buildings – is the exact mould of the cartographic definition of the city, from which the mechanism of scale excludes every human being. Despite the vitality and complexity of the contemporary city, we are probably still used to thinking in terms of morphology, matter and function, aspects which are essential for operating within a territory, but that are static and insufficient for managing the dynamics of the contemporary city. In this new dimension, the identification of new investigative tools and new forms of representation is essential. As Farinelli hopes, the subject of geography today must begin to move again, and with it the mind of the geographer, so that it is no longer blocked by adherence to the cartographic model of the world, in which all elements that compose it appear lifeless, and therefore immobile. MoTo is animated by this spirit. Pascal’s systemic vision prevails over Descartes’s analytic vision. The vitality of the population over the physicality of structures. Dynamic over static. Invisible over visible. Time over space. We see it as no accident that the most recent innovations in biological evolution and life science – in the thoughts of Ilya Prigogine, Gregory Bateson, Humberto Maturana, Francisco Varela, Enzo Tiezzi, among others – are grounded in the regained role of time and in the importance of events.

12 MONTHS

Daily activity over twelve months

The series of maps shows the sequence of the overall activity in the 24 hours of a typical workday over 12 months. The maps of the sequence utilize the same scale of values over 12 months.

12 months _ typical workday _ 24 hours total

January

February

The activity of telephone traffic, that indirectly detects the population presence, has been processed starting with the values per pixel and expressed in classes of intensity through the chromatic scale, from yellow to red. In the dynamic sequence accessible through the QR code, the values express, in thousandths, the intensity of activity per spatial unit with respect to the overall activity in the entire area of study. Patterns and numbers allow the simultaneous reading of the results at both a qualitative and quantitative level.

March

6/ MOTO

Results for activity intensity are constant for the January-May and September-December periods; they are maximum in the month of June, when habitual activity overlaps with a significant confluence of tourists. April

May

June

Results for activity intensity decrease in July and are minimal in August, when the main activities slow down or are suspended for the holiday period, before regaining full rhythm in September. July

August

September

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The results clearly show the most visited sites and the main centers of attraction, and offer an overall description of the geo-demographic dynamics in the vast metropolitan area. October

November

December

12 MONTHS – OUTCOMES Daily activity over twelve months 12 months _ outcomes

March: a qualitative analysis has been overlapped with a quan- March titative evaluation, which estimates how the activity is distributed in the various territorial areas. The values express, in thousandths, the activity detected in some areas with respect to the overall activity detected in the area under study. June: the percentage values refer to the variations in intensity detected in the month of June with respect to the month of March. The increase in activity is ascribable to the seasonal increase of tourist activities, which overlap with those of residents. August: the percentage values refer to the variations in intensity detected in the month of August with respect to the month of June. The reduction in activity depends on the holiday interruption of many traditional work activities in the rest of the territory, except for the center of Florence, where an intense presence of tourist activities is registered for the entire summer period.

The diagrams report the intensity of activity found over 12 months in the aggregated units along the Florence-Prato-Pistoia section.

Pistoia 37‰ Prato 97‰

Firenze 152‰

Pistoia Prato Firenze

Settignano Bagno a Ripoli

Campi di Marte V.le Europa Fiesole

Firenze -2%

Novoli Isolotto Careggi Rifredi Uffizi - Pitti V.le dei Colli

Firenze +15%

Carrefour A.P. Calenzano Peretola - Brozzi Osmannoro A.P. Sesto F.no Polo Areoporto

Prato +8%

Campi Bisenzio Gigli A.P.

Pistoia -40%

Prato Sud Prato Centro Prato A.P. Prato Nord Prato Est

August

Agliana A.P. Agliana Montale Montemurlo Montemurlo A.P. Prato Ovest

Pistoia +6%

Pistoia Ovest

June

Pistoia Nord Pistoia Centro Pistoia Sud Pistoia Est

6/ MOTO 83

Prato NW -46% Prato -18% Firenze W -55%

Firenze E -65%

24 HOURS

Hourly activity in a typical workday 17 June 2009_0/24h

6:00 am

7:00 am

8:00 am

9:00 am

6/ MOTO

This series of maps shows the sequence of activity detected for each hour of a typical workday. The chromatic scale corresponds to the intensity of activity. The maps of the sequence utilize the same value scale over 24 hours. In the dynamic sequence accessible through the QR code, the values reported per aggregate units indicate the relative weight (in thousandths) of each unit with respect to the entire area of study.

10:00 am

11:00 am

12:00 am

1:00 pm

2:00 pm

3:00 pm

4:00 pm

5:00 pm

6/ MOTO

6:00 pm

7:00 pm

8:00 pm

9:00 pm

10:00 pm

11:00 pm

12:00 pm

1:00 am

6/ MOTO

2:00 am

3:00 am

4:00 am

5:00 am

SWITCH ON

Hourly activity in the time slot from 7 to 10 am of a typical workday in winter and summer

March

8:00 am

9:00 am

10:00 am

The acceleration of activity in the first hours of the day is shown. From this comparison we may observe a dynamic that is postponed and a general configuration that is more compact in the summer months, as opposed to a dynamic that is earlier and a more extended configuration, including the workplaces and suburbs, in the winter months. August

8:00 am

9:00 am

10:00 am

6/ MOTO

The slowing down of activity in late evening is shown. From this comparison, we may observe a dynamic that is postponed till late at night and more concentrated in the centers with recreational services in the summer months.

SWITCH OFF

Hourly activity in the time slot from 9 pm to 2 am of a typical workday in winter and summer

March

10:00 pm

11:00 pm

12:00 pm

1:00 am

2:00 am

August

10:00 pm

11:00 pm

12:00 pm

1:00 am

2:00 am

DIFFERENTIAL ANALYSIS

9:00 am

10:00 am

Variations in activity intensity per hourly intervals

Hourly variation of activity: the map shows the 09-10 variation of activity in a workday. The series of four maps shows the variation in activity of a typical workday in the time slots of the morning (08-09 and 09-10) and evening (18-19 and 19-20). The areas that, in the morning, are involved in an increase in activity (centers of attraction), such as the center of Florence, show a decrease in the late afternoon, in favor of outlying areas and along the main roadways, such as for the beltway around Florence.

increase in activity

decrease in activity The dimension of the pixel is proportionate to the variation in activity. The color gradation indicates, with red tones, an increase in activity, and with purple tones, a decrease. The absence of color identifies the areas where activity remains stable or the variation is minimal.

6/ MOTO

Pistoia

Prato

Firenze

Empoli

The diagrams report the variation in intensity of activity found in the various time slots in the aggregated units along the FlorencePrato-Pistoia section. Pistoia Ovest

Pistoia Firenze

Settignano Bagno a Ripoli

Campi di Marte V.le Europa Fiesole

Novoli Isolotto Careggi Rifredi Uffizi - Pitti V.le dei Colli

9:00 am

Carrefour A.P. Calenzano Peretola - Brozzi Osmannoro A.P. Sesto F.no Polo Areoporto

Prato Campi Bisenzio Gigli A.P.

Prato Sud Prato Centro Prato A.P. Prato Nord Prato Est

9:00 am

Agliana A.P. Agliana Montale Montemurlo Montemurlo A.P. Prato Ovest

8:00 am

Pistoia Nord Pistoia Centro Pistoia Sud Pistoia Est

March 10:00 am

Pistoia Ovest

Pistoia Firenze

Settignano Bagno a Ripoli

Campi di Marte V.le Europa Fiesole

7:00 pm

Carrefour A.P. Calenzano Peretola - Brozzi Osmannoro A.P. Sesto F.no Polo Areoporto Novoli Isolotto Careggi Rifredi Uffizi - Pitti V.le dei Colli

Prato

Campi Bisenzio Gigli A.P.

Prato Sud Prato Centro Prato A.P. Prato Nord Prato Est

7:00 pm

Agliana A.P. Agliana Montale Montemurlo Montemurlo A.P. Prato Ovest

6:00 pm

Pistoia Nord Pistoia Centro Pistoia Sud Pistoia Est

6/ MOTO 95

8:00 pm

The use of base station data to map mobility and relations provides an image of significant aspects of individual and social behaviour, a sort of X-ray that renders visible the hitherto invisible fabric of immaterial relations animating a region. Paolo Portoghesi

7/ NARRATIVE ELEMENTS

The sequence of maps tells a story that takes place in the City. With MoTo, a systematic spatial and temporal pattern that repeats itself daily, almost all year, with some exceptions during the summer season, has been discovered in the Tuscan Metropolitan Area. Salient facts, isolated episodes, those events we can call, in the words of Prigogine, narrative elements, are what tend to temporarily interrupt this pattern. An occasional market, a demonstration, a big event like a rally, a concert, a game at the stadium, are particular phenomena. Broadly speaking, these are comparable to the effects of a perturbation in a system that is in a steady state, in which the exceeding of a level of stability entails an overall reorganization. In the case of the city, we should ask if the variations brought about by this event can be observable and measurable in some way. MoTo has developed a tightly woven analysis of the central area of Florence (over a surface area of 70 km2, equal to approximately 5% of the entire area of study) because, from the observations at a vast scale, it has resulted as being the main center of attraction of the entire metropolitan area. The monitoring technique has visualized, in sequence, the activity surveyed for each hour of a weekday. That day, 29th September 2009, the Champions League: Fiorentina vs Liverpool match was being played. The series clearly shows how, starting at 7 pm, the conformation of the geo-demographic system, with a main centre in the area Uffizi-Pitti, changes noticeably and moves its center of mass into the area of the sports facility. The stadium, with a capacity of 47282 spectators, becomes an extraordinarily important center of attraction in the cityâ&#x20AC;&#x2122;s organization on the occasion of big events, and the maps show their significant effect. From 7 pm to approximately 11 pm (the game began at 8.45 pm), 10 % of the activity of Florence took place in that area. On September 29th, the Fiorentina soccer team, headed by Cesare Prandelli, won the game against Liverpool 2-0 with two goals by Stevan Jovetic. Great game!

7/ NARRATIVE ELEMENTS

ZOOM

Hourly activity for the City of Florence 29 September 2009_7/24h

7:00 am

8:00 am

The sequence of dynamic maps shows, in time, through the color gradation with tones from green to purple, respectively, the areas with minor and major concentration of activity. In the dynamic sequence accessible through the QR code, the values associated with each pixel express, in thousandths, the weight of each unit as compared to the total activity detected in the area under examination.

9:00 am

10:00 am

11:00 am

3:00 pm

2:00 pm

Palazzo della Signoria Ponte Vecchio

Galleria degli Uffizi

7/ NARRATIVE ELEMENTS

4:00 pm

101

6:00 pm

5:00 pm

Santa Croce

Santa Maria del Fiore

View from Piazzale Michelangelo

7:00 pm

8:00 pm

Sinagoga di Firenze

9:00 pm

7/ NARRATIVE ELEMENTS

10:00 pm

Artemio Franchi Stadium

11:00 pm

103

12:00 pm

The stadium results as being an important center of attraction, that significantly conditions the overall organization of the city for the occasion of sports events. View from Piazzale Michelangelo

A more complex symbol, which gave me greater possibilities to express the tension between geometric rationality and the entanglement of human existence, is that of the city. [In Invisible Cities] I have built a multi-faceted structure in which each short text is close to the others in a series that does not imply a logical sequence or a hierarchy, but a network in which one can chart manifold courses and draw multiple and ramified conclusions. Italo Calvino

8/ THE SMART CITY

105

This book presents the results of a project as an account of a diffused research activity that, in recent times, has involved theorists, technicians, technologists, designers, administrators, planners. Today, these and other professional figures (subject) are involved in the research for tools and techniques (means) that help us to better understand and manage the complexity of the contemporary city (object), which we may define as currently out of control. SUBJECT. To this day, the plurality of the problems that emerge from scientific research have brought us to identify a series of concepts that we have aimed to present, even if in the form of simple references, analogies, and suggestions. We have drawn on physics and life sciences â&#x20AC;&#x201C; through references to kinetics, chaos theory, and complexity â&#x20AC;&#x201C; and on research disciplines and techniques such as landscape ecology, geography, geostatistics, remote sensing, and hydrodynamics. This all points towards a goal: to identify a new point of view, a vision that will allow us to observe the systems that are the object of our investigations from a perspective that is wider and more coherent with the needs of contemporary living. To learn concepts and definitions, expertise and know-how in order to build an interdisciplinary knowledge, and to lay the foundations for a new territorial science upon this. MEANS. It is to be hoped that science and technology share a common path. The choice of the mode or tool for observation is an equally important subject of research. The innovation of the approach that we propose consists in the combined analysis of characteristics and parameters that describe urban areas as total dynamic systems. MoTo has developed a monitoring technique of urban dynamics that combines spatial analysis and temporal sequences, mobile telecommunications technologies and Geographic Information Systems (GIS), qualitative and quantitative analyses, overall views (patterns) and the classification of specific areas (units), surveys of repetitive behaviors and the observation of extraordinary and unexpected events and isolated episodes. This wealth of information has required an effort of synthesis that extends to the phase of the communication of the results. This book gathers texts, images, graphic diagrams, charts, tables, and maps. Furthermore, the QR-codes that refer to the dynamic sequences of maps have allowed us to surpass the limits of paper in describing the kinetics of these phenomena. All these aspects, from the processing of data to its analysis and the communication of results, are an important part of the research, and call for consideration on how to improve, through science and technology, our ability to know a territory and to operate within it.

OBJECT. The capillary gathering of data and its processing in order to generate an overall configuration, in the case that we have represented, has followed a path from the bottom up. Bottom-up procedures of data gathering and processing represent the frontier to be expanded with the next information territorial systems. These are potentially applicable, with the aid of digital technology, to a multitude of urban phenomena â&#x20AC;&#x201C; the use of electricity, water, and gas, waste collection, information exchange, the transportation of people and goods, the mobility of people and vehicles â&#x20AC;&#x201C; whose processes are essential to the functioning of the system. The object of our observation is the contemporary city, its complexity and dynamics. One of the many prospects that this work is oriented towards is that of contributing to the construction of the intelligent cities of the future, that is to say the utilization of the technologies that we have and the development of the potential to understand how our communities use the environment. Monitoring urban dynamics and designing the smart city means learning to know the functioning of the city and, on the basis of the information acquired, coordinating our actions in order to improve the accessibility of spaces and services, rationalize the use of resources, optimize modes and times of mobility, increase the integration of functions, and live in more efficient systems.

INTENSITY OF DAILY ACTIVITY 24 hours/ typical workday The map describes how the activity of the population that lives in the metropolitan area is actually distributed in space. The three-dimensional effect and the chromatic scale visually demonstrate the weight of each unit, measured in thousands, compared to the overall activity registered in the entire metropolitan area.

8/ THE SMART CITY

Pistoia

9 6

1 3

7 1

Prato

12 21

8 22

14 4

9 1

3 4

1 3 3

7 9

1 28

8 15

5 5

Empoli

Firenze

20 5

2 1

107

Recently, the study of real-time systems, in other words systems in which temporal evolution plays a primary role, has made interesting advances. […] It would be interesting to develop logics that express real “eternal” constraints, such as the three dimensions, on one hand, and that tackle the real meaning of evolution, hence the importance of events and their successions, on the other. Enzo Tiezzi

9/ AFTERWORD

109

Afterword by Nadia Marchettini “Scientists don’t read Shakespeare and humanists have no sense for the beauty of mathematics.” This is how Ilya Prigogine introduced the theme of the dichotomy between these two cultures, scientific and humanistic. The will to overcome this difficulty and to rejoin these two cultures has marked the entire human and academic career of Enzo Tiezzi, and is found in his dialectics, in his scientific essays, in his photographs, poems, novels, in the work of his many pupils. The Ecodynamics Group of the University of Siena, that Enzo founded and directed for many years, is made up of scholars from different disciplines, and from its beginning was conceived in order to concretely carry out an interdisciplinary course of research and to overcome the problem of the fragmentation of knowledge imposed by disproportionate academic boundaries. As Herman Daly6, father of Ecological Economics, has declared, with Joshua Farley: “Real problems do not observe academic boundaries. We certainly believe that thinking should be ‘disciplined’, in the sense of observing logic and facts, but not ‘disciplinary’, in the sense of limiting itself to traditional methodologies and tools that have become enshrined in the academic departments.” The idea of merging cultures, amalgamating disciplines, combining skills, has certainly inspired the initial proposal of the MoTo project, which Enzo headed as scientific director. The variety of topics dealt with in this book, even if they have just been touched on, aim to be further testimony to Enzo’s intuition: he had no hesitation that a physical chemist and an architect – collaborating with the other professional figures present within the group – could together deal with the themes linked to mobility, city planning, and territorial sustainability. I have taken on the role of scientific director of MoTo with the idea of completing a process that was undertaken by Enzo many years ago, long before this project, and with the certainty that the conclusion of this experience indicates a direction, a future prospect, a road with many possible destinations that are still to be explored. A small part of Enzo’s vast scientific heritage.

References and credits Sources for quotes: Prigogine I. From a Space to a Time Culture. Foreword in: Tiezzi E. The Essence of Time. WITpress, Southampton 2003 – Ratti C. Mobile Landscapes. Foreword in: Pulselli R M & Romano P. Urban Systems Dynamics. Alinea, Florence 2009 – Piano R. La Responsabilità dell’Architetto. Conversazione con Renzo Cassigoli. Passigli, Firenze 2000 – Batty M. City and Complexity. MITpress, Cambridge 2005 – Le Corbusier (Jeanneret C E). Le Modulor. Boulogne, L’Architecture d’Aujourd’hui 1950 – Bolelli F. Si fa così. Rubrica di D-la Repubblica 712, 2010 – Portoghesi P. Foreword in: Pulselli R M and Tiezzi E. City Out of Chaos. WITpress, Southampton 2009 – Calvino I. Six Memos for the Next Millennium. Harvard UP, Cambridge 1988 – Tiezzi E. Beauty and Science. WITpress, Southampton 2005. Sources for quotes in the text: 1 – Prigogine I & Stengers I. La Nouvelle Alliance. Métamorphose de la Science. Gallimard, Paris 1979. 2 – Von Bertalanffy L. General System Theory. Penguin Books, Harmondsworth 1972. 3 – Koolhaas R, Boeri S, Kwinter S, Tazi N and Obrist H U. Mutations. Actar, Art en Reve Centre d’Architecture, Bordeaux 2000. 4 – Naveh Z. Landscape ecology as an emerging branch of human ecosystem science. Adv. In Ecology Research 12 189-237 1982. 5 – Farinelli F. Geografia. Einaudi, Vicenza 2005. 6 – Daly H E & Farley J. Ecological Economics. Principles and Applications. Island Press, Washington 2004. Chronicle of the MoTo Project: Ratti C, Pulselli R M, Williams S, Frenchman D. Mobile Landscapes: using location data from cell-phones for urban analysis. Environment & Planning B: Planning and Design 33(5) 2006 727-748 – Pulselli R M, Romano P, Ratti C, Tiezzi E. Computing urban mobile landscapes through monitoring population density based on cell-phone chatting. International Journal of Design & Nature and Ecodynamics 3(2) 2008 121134 – Pulselli R M, Pulselli F M, Ratti C, Tiezzi E. Dynamics and evolution of urban patterns: the evidence of the mobile landscape project #1. (Eds.) Tiezzi E, Brebbia C, Jorgensen S E, Almorza-Gomar D. ECOSUD - Ecosystems and Sustainable Development V. WITpress. Southampton, UK 2005 597-603 – Pulselli R M, Ratti C. Mobile Landscapes. Equilibri 1, 2005 147-155 – Pulselli R M, Pulselli F M, Ratti C, Tiezzi E. Dissipative structures for understanding cities: resource flows and mobility patterns. (Eds.) Boussabaine A H, Lewis J, Kirkham R J, Jared G E M. BECON - Complexity and the Built Environment. Liverpool, UK 2005 271-279 – Pulselli R M, Romano P, Ratti C, Tiezzi E. The ecology of the urban landscape and the chemistry of the city. Abitare la Terra 16 2006 30-35 – Bastianoni S, Pulselli R M, Romano P, Pulselli F M. Dynamics and evolution of urban patterns: the evidence of the Mobile Landscapes project #2. (Ed.) Brebbia C A. Design & Nature IV- Comparing Design in Nature with Science and Engineering. WITpress. Southampton, UK 2008 253-260 – Pulselli R M e Tiezzi E. City Out of Chaos. WITpress, Southampton 2009 – Pulselli R M, Morandi F, Tiezzi E. Integrating thermodynamics and kinetics of urban systems for regional studies. (Eds.) Brebbia C A., Hernandez S, Tiezzi E. The Sustainable City VI, Urban Regeneration and Sustainability. WITpress. Southampton, UK 2010 103-111 – Marchettini N, Pulselli R M, Tiezzi E.B.P. An innovative survey of urban systems dynamics: the evidence of the MoTo project. (Eds.) Brebbia C A, Hernandez S, Tiezzi E. The Sustainable City VI, Urban Regeneration and Sustainability. WITpress. Southampton, UK 2010 97-102 – Pulselli R M & Romano P. Dinamiche dei Sistemi Urbani. Indagine di un’Area Metropolitana - Urban Systems Dynamics. Investigating a Metropolitan Area. Alinea, Firenze 2009 – Pulselli R M, Romano P, Niccolucci V, Marchettini N. Monitoring urban dynamics: the case of the Metropolitan Area of Central Tuscany. (Eds.) Villacampa Y, Brebbia C.A. Ecosystems and Sustainable Development VIII. WITpress. Southampton, UK 2011 157–164. Source for images: p.14, Ilya Prigogine © greyherbert on Flickr – p.17, Marina Apollonio, Space of Kinetic Activation © Frank Rumpenhorst/CORBIS – p.18, Piotr Uklanski, Dance Floor at Palazzo Grassi © TomPeyton on Flickr – p.19, Jochem Hendricks, Eye (Rorary print, 56 pages, 35 x 29 cm, Edition 6.000, Published by San Francisco Museum of Modern Art, 2000) photo by Rolf Abraham – p.20 , Carlo Ratti, © Kris Krüg /PopTech.org – p.24, Renzo Piano, © RPBW/Stefano Glodberg PUBLIFOTO – p.30-31, images from Street View, Google Maps – p.32-33, 74-75, 80-81, 86-87 photos by Pietro Romano – p.34, Mike Batty, Complexity theories of cities have come of age, Delft / NL, 2009 © William Veerbeek – p.37, 40, Aerial photo by AeroFototeca Regionale/Archivio Cartografico-Sistema Informativo Territoriale Ambientale of the Region of Tuscany – p.42, Le Corbusier et le modulor, © René Burri – p.76, Franco Bolelli, frame from the video “Franco Bolelli su Realtà e Illusione” di Alessandro De Leo – p.96, Paolo Portoghesi, © Giovanna Massobrio – p.104, Italo Calvino, © Sophie Bassouls/ CORBIS – p.108, Enzo Tiezzi, p. 100-101, photos by Riccardo Maria Pulselli. The Editor, having obtained the rights to reproduce the images, is available for comment or claims.

The author is pleased to acknowledge: the workgroup of the MoTo project and, in particular, the Scientific Director, Nadia Marchettini, with Pietro Romano, as well as Francesca Ameglio and Bonnie Eldred; along with all the members of the General Directorate of Territorial and Environmental Policies of Region of Tuscany and, in particular, the Director Adriano Poggiali with Walter Pratesi, Sabina Parenti, Elena Calistri, Vincenza Giancristiano and Alessandro Zanieri; Daniele Nutini, Marco Ugolini and Marco Cappelli of Telecom Italia (Florence) for their fundamental contribution to data retrieval and transmission, as well as Davide Micheli and Piero Lovisolo for the rewarding exchange of opinions; the staff of the Territorial-Environmental Information System of the Region of Tuscany; Prof. Simone Bastianoni with Federico M. Pulselli and the whole research team of the Ecodynamics Group at the University of Siena.

Riccardo Maria Pulselli

ISBN: 978-88-88718-26-2

Riccardo Maria Pulselli The Moving City

€ 24,00

The Moving City How to Explore Urban Kinetics