Data amounts of data has also led planners

Data
Augmented Planning and Rational Planning

——A Case Study in
Beijing Urban Greenway System Planning

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

 

1Introduction

We
are living in a new data era where our social life and urban physical
environment can be described in detail. With the development of big data
technology, many city planners and decision-makers argue that we should make
use of data analysis to have a better understanding of what happens to our
cities and combine it with conventional urban planning and design process.

A new term of planning approach named
Data Augmented Planning is put forward by scholar Ying Long. Empowered by
quantitative urban analysis, utilizing approaches such as data analyzing,
modeling and forecasting, data augment planning provides supporting tools
covering the whole planning and design process from investigation, analysis,
project design, evaluation, to feedbacks.

During
the planning process of Beijing Urban Greenway System Planning, GPS data of
hiking in Beijing’s urban area were collected. Based on analysis of these data,
urban planners generalized hikes’ demand and route selection. The overlay of
large amounts of data has also led planners discovered long-distance main walk
line which was then incorporated into the city’s greenway system. In this case,
the big data are used to support the design process, alternatives choosing and
implementation evaluation.

Based
on the case study in Beijing Urban Greenway System Planning, this research compares
the data augment planning to the traditional rational planning approach before
the 1960s from the aspect of their definitions, methods, procedures, features and conceptual
distinctions, frequently used approaches and tools, as well as its expected
applicable situations. The research intends to prove that when
introduced empirical big data analysis, planners will have a more solid
foundation and abundant resource in defining the problems and formulating
goals; and there will be more reference parameters for the plan evaluation.

2Literature
review

The
current challenge faced by the city as well as the city planning and design is
the precondition of development the DAD. Influenced by the ICTs such as Uber
and Sharing Bikes apps, the lifestyle, production,
entertainment, and transportation patterns of cities have changed dramatically.
These changes have put forward new propositions to traditional planning and
design. For example, how does material space design affect the formation of
urban virtual space? How to use the planning policy to play a synergistic role
between the two to improve the vitality of the city in the information age? How
to establish a corresponding planning and design mechanism in an increasingly
transparent urban management system (Ying, 2015)?

Traditional
rational planning and design rely mainly on the planner’s personal knowledge
and experience to develop “rational” plan, and finally “design” the
city or neighborhood (Wang, 2001). Rational urban planning and design focus on
the skill of design, inference training and development of
“hardware”, but the research on “software”, such as
interdisciplinary design methods, processes, and implementation, is weak(Couclelis,
2005).

Thus
the problems of traditional rational planning and design at the present day are
mainly reflected in the following aspects: The inconsistent scale, the
ambiguity of the design scale and the fuzzy scale of the effect scale; the
ambiguous spatial effect; The contradiction between the subjective
understanding of the phenomenon in sites and the outcome of scientific
analysis; Oversimplification of the Geometric space; Unequal distribution of
benefits and the lack of communication with the public; The public interest
cannot be guaranteed; The absence of the context suitability and so on. From
the process point of view: The traditional planning relies too much on the
individual designer’s knowledge structure; The research process mainly adopts a
relatively simple method; The planning result is presented using a simple geometric
space; The implementation effect of the final planning result cannot be traced
and understood because of various reasons (Brail, 2008).

2.1
The concept of DAD

Data
Augmented Design is a planning and design method put forward in the new data environment.
It is based on the combination of different heterogeneous data source, data
analysis, and forecast. It provides data support for every aspect of the city
planning and design and ultimately improves the rationality, innovation, and
flexibility of the planning program.

From
the theoretical perspective, the traditional rational planning and design
follow the classical principles while the data-enhanced design has far-reaching
significance in the new data environment. Its significance may not only be the
application of new design tools or lively data visualization but an improvement
in the deeper level of planning and design methods. DAD will enhance the
transformation of people’s understanding of urban entities. Specifically, the
data will reinforce another understanding of urban entities: the relationship
between entities is understood as the generator of real human activities, and
the knowledge of urban entities will be translated into a new data language for
understanding and present. Form and function are no longer interpreted as
generalized philosophical motif and the particular context should be understood
through building an accurate relationship with data. We will see more
“more complex but interpretable spatial entities.” Thus DAD enhances
our perspective of observing and understanding of the city.

    From the practical perspective, the core
point of DAD can be understood as: various entities in the city are abstracted
into a spatial data system through quantitative models combined with a large
number of heterogeneous city data and models. By making use of increasingly
powerful computing power, the cognitions and complex effects between city
entities are established and then used to support designing, modifying, and
evaluating of planning and design. DAD emphasizes the data-driven design and
very different from the digitalization of city. In the era of big data, much of
the data is made public and able to be visualized, which will change the
traditional methods or models of research. However, digitization or
visualization is distinguished from DAD because DAD is not put forward for
mapping data. DAD comprised of more concrete design methods from planning
practice, and these methods are inseparable from how to understand urban
entities with data. Within the DAD framework, the data will enhance the precise
perception of urban entities and their implications and help to grasp the
different social effects that can be achieved by shaping different spaces.

Therefore,
what DAD enhances is an accurate understanding of urban entities, an accurate
grasp of the complex relationships between the physical organization and its
effects, and the effective implementation of positive impacts on space. In
other words, the purpose of DAD is to precisely design the “place”
that city entities form.

2.2
Principle and characteristics of DAD

The
city is a complex system that holds highly complex functions, and its
complexity is increasing. Accordingly, urbanization is a complicated process in
which different dynamics affect each other. Cities are the means by which
people communicate and interact with each other, so understanding the key to
the city is a complex science that understands how people are connected, and
current urban planning and design is merely a “natural spatial
effect” of planning. Based on an understanding of urban complexity, the
principles of DAD planning and design are to focus on how to stimulate or
preserve the complex functionality of urban development through data (Batty,
2013).

DAD’s
features are mainly reflected in:(1) applicability: directly
facing the planning and design practice; (2) multidimensional: a model that
combines spatial attributes with socio-economic data; (3) return to social
space from physical space: through social networks, points of interest, activities
and mobile data, and quantitative evaluation methods (4) refinement: emphasize
the accurate understanding of the background (context, environment and people),
give full consideration to the subdivision of the population and the environment,
analyze the existing laws and establish different combination modes to provide
support for the special planning and design; (5) the combination of the virtual
world and the real world: a multi-angle understanding of the core issues of the
venue; (6) quantization of design tasks: effect of reference will be the goals
and tasks; (8) traceable and evaluation: Subsequent effort will continue to
strengthen and correct model or design through quantitative evaluation.

 

3
Applications of Data Augmented Planning

3.1
Context of Beijing to adapt DAD

3.2
Case study in Beijing Greenway System
Planning

4
Inspirations of Successful DAD Cases

6
Conclusions

Reference

Brail, R. K. (Ed.).
(2008). Planning support systems for cities and regions. Cambridge: Lincoln Institute
of Land Policy.

Couclelis, H. (2005).
“Where has the future gone?” Rethinking the role of integrated land-use

models
in spatial planning. Environment and Planning A, 37 (8), 1353–1371.

 

Long Ying, WU Kang.
Shrinking Localities in Booming Urbanization of China (2000—2010) J.
Environment and Planning A (Accepted), 2015.

 

Michael Batty. The New
Science of Cities M.Cambridge: Mit Press, 2013.

 

Riba, Arup. Designing
with Data: Shaping Our Future Cities R.
http://www.architecture.com/Files/RIBAHoldings/PolicyAndInternat ionalRelat
ions/Pol icy/Designingwithdata/Designingwithdatashapingourfuturecities.pdf,
2013.

 

Wang Jianguo. Modern Urban Design:
Theory & Methodology(the 2nd Edition) M. Nanjing:Southeast University
Press, 2001.

Author:

x

Hi!
I'm Eileen!

Would you like to get a custom essay? How about receiving a customized one?

Check it out