Integrated Spatial Assessment (ISA): A Multi-Methodological
Approach for Planning Choices
In decision-making processes for
urban planning and design, evaluation can be considered a relevant tool to build choices, to recognize
values, interests and needs, and to explore the different aspects that can
influence decisions. Evaluation can be considered a process to integrate approaches, methods and models, able to
support the different needs of the decision-making process itself. According to
Trochim and Donnelly (2006), it is possible to define a planning-evaluation cycle with various phases requested by both
planners and evaluators. The first phase of such a cycle, the so-called planning phase, is designed in order to
elaborate a set of potential actions, programs, or technologies, and select the
best ones for implementation. The main stages are related to (1) the
formulation of the problem, issue, or concern; (2) the broad conceptualization
of the main alternatives to be considered; (3) the detailing of these
alternatives and their potential implications; (4) the evaluation of the
alternatives and the selection of the preferable one; and (5) the
implementation of the selected
alternative. These stages are considered inherent to planning, but they need a
relevant evaluation work, useful in conceptualization and detailing, and in
assessing alternatives and making a choice of the preferable one. The
evaluation phase also involves a sequence of stages that includes: (1) the
formulation of the major goals and
objectives; (2) the conceptualization and operationalization of the major
components of the evaluation (program, participants, setting, criteria,
measures, etc.); (3) the design of
the evaluation, detailing how these
components will be coordinated; the analysis
of the information, both qualitative and quantitative; and (4) the
utilization of the evaluation results. Indeed, evaluation is intrinsic to all
types of decisionmaking and can take different meanings and roles within
decision-making processes, especially if it is related to spatial planning
(Alexander, 2006). ”Evaluation in planning” or ”evaluation within planning”
seems to better interpret the concept of planning-evaluation
proposed by Lichfield (1996) where the binomial name makes explicit the close
interaction and reciprocal framing of evaluation and planning: evaluation is
conceived as deeply embedded in planning, affecting planning, and evolving with
it (Cerreta, 2010). Indeed, the evolution of evaluation methods reflects their
evolving relationship with the planning process and the way in which they
interact with the diversity and multiplicity of domains and values. To identify
an analytic and evaluative structure able to integrate different purposes and
multidimensional values within the decision-making processes means to develop
evaluation frameworks not focusing only on the environmental, social and
economic effects of different options, but also considering the nature of the
stakes, selecting priorities and values in a multidimensional perspective. It
is crucial to structure complex
decision-making processes oriented to an integrated planning, that can
support the selection, the monitoring and the management of different
resources, and the interaction among decision-makers, decision-takers,
stakeholders and local community.
In the above perspective, it is
essential to adopt normative and instrumental approaches, but also
”explorative” ones, open to plurality and dialogue among the different
expertises involved (Fusco Girard et al., 2007). Facing the complexity of
interacting perspectives, interests, and preferences (Wiek & Walter, 2009)
means to identify a dynamic decisionmaking process, where integration represents the crucial point. An integrated approach to
planning-evaluation involves many institutional and non-institutional
stakeholders with divergent and conflicting values and mandates, with a high
complexity of issues and interdependencies. According to Waddell (2011), the
main challenges for and integrated approach are related to conflicting
institutions, conflicting values, conflicting epistemologies, and conflicting
policies. Different institutions have responsibility for different aspects of
the domain, having narrow and often competing mandates; values differ among
both institutional and non-institutional stakeholders, including the citizens,
and they can be related to tangible and intangible dimensions; divergent
epistemologies surely also are part of the assessment of the problems of
integrating planning, using both quantitative and qualitative methods and
models in order to overcome the gap between implicit
knowledge and explicit knowledge
(Te Brömmelstroet & Bertolini, 2010); conflicting policies at different
levels and scales have to face legislation requirements and restrictions and
need to find ways to open up the planning process on the project evaluation
level to be consistent with broader normative guidance on integrating planning
efforts.
In order to face the different
levels of conflicts related to a spatial planning process, three main types of
integration (Lee, 2006) can be considered:
-
vertical
integration of assessment, which means to link together
separate impacts, that are undertaken at different stages in the policy,
planning and project cycles;
-
horizontal
integration of assessments, which means to bring together
different types of impacts (economic, environmental, social, etc.) into a
single, overall assessment at one or more stages in the planning cycle. It
means also an horizontal co-ordination between contemporaneous assessments for
separate, and also interrelated, planning and project cycles;
-
integration
of assessments into decision-making, that
means to integrate assessment findings into different decision-making stages in
the planning and project cycles.
The
above types of integration can be helpful in facing the complexity of the
planning environment, overcoming the limits of sectoral approaches and taking
into account the multi-sectoral character and broadly defined content of many
of the projects/plans to be assessed, the relative importance of complex
impacts (indirect, induced and cumulative), the spatial and temporal complexity
of their distribution, their multiple links, horizontal and vertical, and
impacts from other projects or plans (Cerreta & De Toro, 2010; Lee, 2006)
(fig. 1).
Fig.
1. Planning-evaluation: integrated approaches and integrated models
At the same time, some key
challenges still facing integrated modelling and their application in practice
include the following main characteristics (Waddell, 2011):
-
Transparency:
models will not be credible as tools for decision support in complex,
conflict-laden domains such as land use, transportation and environmental
planning, unless they can be explained with a sufficient degree of
transparency;
-
Behavioural
validity: for a model to be credible in a contested
domain, it must have sufficient behavioural validity to be believable as an
independent artefact, within some clearly defined scope of applicability.
Behavioural validity includes more common sense or intuitive understandings of
how the world works;
-
Empirical
validity: models must be tested against observed data in
order to assess their empirical validity. A model has to respond to input
assumptions and make predictions that will reasonably correspond to observed
reality. A model can be used to predict outcomes into the future, and it should
be able to capture the essential trends in outcomes over some period of time;
-
Ease
of use: if a model is too complex to explain and
implement, it also will ultimately not succeed in practice. A model system must
strive to achieve a threshold of usability that makes it possible for staff
within planning agencies to be able to use it, taking into account that
complexity can lead to more mistakes;
-
Computational
performance: a model has to be characterised by a good
computational performance able to define a valid simulation of reality modifications;
-
Flexibility:
a model has to be able to satisfy users in all cases and for all applications.
Indeed, models and software platforms that are too rigid become a serious
constraint, and limit applicability; models need to be adaptable to different
users and different data and needs;
-
Data
availability and quality: in implementing a model a
crucial point is developing the input data for it. In general, the science and
tools to develop data usable in modelling are far from addressing the needs of users.
Then data can be incomplete and error prone. Further, it is difficult to
integrate them into a coherent database that is internally consistent. The
difficulty of developing the data for a model system can be a very important
obstacle to consider;
-
Uncertainty:
only recently uncertainty has come into the lexicon of integrated modelling, but is becoming increasingly
important in decision-making process related to spatial planning, especially in
choosing among different alternatives.
The construction of suitable
models is oriented to face complex problems that arise in sociotechnical,
socio-economic and socio-ecological contexts in order to transform an existing
problem situation into a form that is more acceptable, understandable and
manageable (Amin & Roberts, 2008). Often decision-makers and planners
failure to fully understand such problems results in failures to formulate
effective intervention strategies. In this research, Soft Operations Research
(Soft OR) combined with System Dynamics (SD) modelling, Multi-Criteria Analysis
(MCA), Multi-Group Analysis (MGA) and Geographical Information System (GIS) can
help to improve stakeholders’ understanding of a complex problem situation and
to facilitate learning about it in a perspective of defining shared strategic
actions.
Multi-methodological framework in
decision support systems
According to Te Brömmelstroet
& Bertolini (2010), the concept of knowledge
generation is essential for building integrated strategies, where socialization (tacit with tacit: sharing
experiences to create new tacit knowledge, observing other participants,
brainstorming without criticism), externalization
(tacit with explicit: articulating tacit knowledge explicitly, writing it down,
creating metaphors, indicators and models), combination
(explicit with explicit: manipulating explicit knowledge by sorting, adding,
combining, looking to best practices) and internalization
(explicit with tacit: learning by doing, developing shared mental models, goal
based training) (Nonaka & Takeuchi, 1995; Nonaka et al., 2006) represent
the main phases and the four key modes of knowledge conversion.
Through a process of knowledge
generation iteratively acting in all four modes of knowledge conversion,
interplaying between tacit knowledge end explicit knowledge, and by
experiencing the four knowledge conversion modes, planners can develop a shared
explicit language and use it to develop integrated strategies (Healey, 2007; Te
Brömmelstroet & Bertolini, 2010). This approach to knowledge management to
support strategy-making is also consistent with the epistemological structure
of “post-normal science” developed by Funtowicz and Ravetz (1993), considering
two crucial aspects: uncertainty and value conflict.
According to post-normal science,
to recognize the importance of difference implies a different way to address
complex systems and to face complexity means to take into account the
self-organization chances, non-linear dynamics, non-continuous behaviours of
complex systems and participated decision-making processes. This means to
broaden the field of decision-makers and to involve new social actors in order
to create an ”extended community”, able to elaborate new solutions (Funtowicz
& Ravetz, 1994).
The approach of post-normal
science forces decision-makers and planners to find solutions not only coming
from the ”expert knowledge”, but also legitimated by ”common knowledge”,
including uncertainty as part of the decision problem, and considering
solutions based not only on exact scientific data (hard data), but also on public decisions, shared by the community (soft data). Indeed, facing and/or
solving complex problems depends on the capability to consider them under
different points of view, and to manage uncertainty, filling the gap between
experts and community.
According to the above
perspective, it stands out that “integrated evaluations” can be a key tool to
support the decision-making process, especially when uncertainty, complexity
and values of different social groups are many, different and conflicting (van
der Sluijs, 2002). Integrated evaluations not only consider the inputs of data
expressing the impacts of different solutions, but are also ”open” to a wide
public participation, so that they can offer more information for the evaluation
itself and, in addition, can make the decisionmaking processes and the results
more acceptable (Golub, 1997; Munda, 2008). Participation becomes essential not
only to examine and evaluate choices on social, ethic, political, economic,
environmental levels, but also to legitimate choices and make them acceptable
for the community itself. Integrated evaluations constitute an ongoing process
both, iterative and interactive, multi-disciplinary (respecting the issues
addressed) and participative (respecting communities), able to recognize the
relevance of technical indeterminacy
and value multiplicity.
In this view, it is important to
combine different approaches in the same framework, integrating different
evaluation tools, such as environmental, social and ethical balance sheets, and
also Economic Valuation, Input-Output Analysis, Life Cycle Assessment, Risk
Assessment, Ecological Impacts, Ecological Footprint, Mass/Energy Valuation,
MultiCriteria Decision-Aid Methods, Future Studies (Finnveden et al., 2003).
Other relevant tools that could
be useful to consider are those covering the possibility of combining
Multi-Criteria Analysis and Multi-Groups Analysis with Geographical Information
Systems (GIS), Internet Technology, Spatial Decision Support Systems, Cellular
Automata Models. Integration of differing evaluation models with GIS
(Malczewski, 1999) becomes decidedly important in the construction of a Spatial
Decision Support System: a variety of territorial information (social, economic
and environmental) may be easily combined and related to the characteristics of
the different options of territorial use, facilitating the construction of
appropriate indicators and improving impacts forecasting, leading up to a
preference priority list of the various options. Integration among
Multi-Criteria Analysis, Multi-Group Analysis and GIS may be exceptionally
useful when there are strong conflicts, in which the role of local actors,
their relations and objectives may be considered as a structuring element in
the process of information construction in a spatial and dynamic evaluative
model (Al-Shalabi et al., 2006; Joerin & Musy, 2000, Nekhay et al., 2009;
Şener et al., 2010; Thirumalaivasan et al., 2003; Vizzari, 2011). In the
recent years, theoretical research and new technologies have improved the
identification and implementation of integrated approaches for building
planning strategies and actions.
A selection of
multi-methodological decision support systems
Some interesting examples of
integration among different and complementary methods and techniques in spatial
planning field have been proposed, where the application of GIS is combined
with evaluation tools and Planning Support Systems (PSS). A multimethodological
decision support system can be considered as the integration of a dynamic system (able to consider the
time evolution), a deliberative system
(able to include all the stakeholders), a comprehensive
system (able to take account of quantitative and qualitative aspects
related to different components) and a spatial
system (able to identify the territorial effects also through their
visualization) (fig. 2). According to this approach, a multimethodological
decision support system should be characterized by the interaction of Knowledge
Base (KB), Relational Database Management System (RDBMS), Graphical User
Interface (GUI), Geographic Information System (GIS), Multi-Criteria Analysis
(MCA), and Multi-Group Analysis (MGA).
Indeed, PSS include:
visualization tools that make it possible to get a 3-D, visual sense of what
one alternative future might look like; sketch-planning tools that allow users
to enter rules and then to visualize the outcome of those assumptions;
simulation systems trying to model the behaviour of urban agents and the
potential effects of alternative policy actions. Some selected models were
developed in the transport sector, considering the relevance of infrastructures
and mobility in land use transformations.
Fig. 2. Main characteristics of
multi-methodological decision support systems
UrbanSim
UrbanSim,
designed by Paul Waddell in the mid-1990s, falls in the third category of PSS,
but also provide accessible visualization and stakeholder interaction (Waddell,
2002, 2011; Waddell et al., 2003) (fig. 3).
UrbanSim was developed as Land
Use and Transport Interaction (LUTI) model in order to respond to a variety of
needs to assessing the possible consequences of alternative transportation,
land use, and environmental policies, trying to better inform deliberation on
public choices with long-term, significant effects. The main reason was that
the urban environment is so complex that it is not possible to anticipate the
effects of alternative actions without some kind of analysis reflecting the
cause and effect interactions that could have both intended and possibly
unintended consequences. It is a software-based simulation system for
supporting planning and analysis of urban development, incorporating the
interactions between land use, transportation, the economy, and the environment.
Since its initial release, UrbanSim has been increasingly adopted for
operational planning use in the USA, Europe, Asia, and Africa, in planning
agencies and in university research. The user community and research
collaborators directly and indirectly support the application and refinement of
UrbanSim. It is defined by an interactive web site that provides a virtual
meeting ground for users and developers of the system, approximately half of
them from the USA, and half from a rapidly growing list of countries. It can be
used by cities, counties, non-governmental organizations, researchers and
students interested in exploring the effects of infrastructure and policy
choices on community outcomes.
Fig.
3. Example of UrbanSim application (source: http://www.uanalytics.com/urbansim)
Metropolitan
Activity Relocation Simulator (MARS)
Metropolitan
Activity Relocation Simulator (MARS) is
another interesting model designed to improve decision-making process with
specific attention to transport system (Emberger et al., 2006) (fig. 4). It is
a dynamic Land Use and Transport Interaction (LUTI) model designed to support
the decision-makers all through decision-making process (objective definitions,
policy instrument identification, assessment of short and long-term impacts and
appraisal), helping understanding of the concepts underlying the model and
providing a transparent process. MARS is based on the principles of systems
dynamics (Sterman, 2000) and synergetics (Haken, 1983), and is considered an ideal
tool to model dynamic processes.
The MARS model environment allows
to calculate a wide range of relevant indicators, and users can choose the set
of indicators that fit the needs of their specific decision-making context.
Then, MARS calculates the policy-dependent values for the key-indicators and
allows the assessment and appraisal of the strategy, including also
Cost-Benefit Analyses (CBA) and Multi-Criteria Analyses (MCA).
UrbanSim and MARS are only an
example of the most advanced European LUTI models, that also include IRPUD
(Wegener, 1998, 2004), DELTA (Simmonds, 1999, 2001), MEPLAN (Echenique et al.,
1990), MUSSA (Martínez, 1996; Martínez and Donoso, 2001).
Land
Allocation Decision Support System (LADSS)
Land
Allocation Decision Support System (LADSS) (Matthews et al., 1999) is a tool developed at The Macaulay
Land Use Research Institute (UK) for agricultural land use planning. More
recently the term LADSS refers to the research of the team behind the original
planning tool (fig. 5). Indeed, the focus of the research of the LADSS team has
evolved over time from land use decision support towards policy support,
climate change and the concepts of resilience and adaptive capacity. LADSS is
the collective term for a farm-scale integrated modelling framework (IMF) that
is being developed in order to simulate whole-farm systems. The acronym
describes the projects original purpose as a land use planning tool back in the
early 1990s. More recently, the project has expanded beyond its original remit
to focus much more on deliberative processes involving decision-makers and
other stakeholders. The LADSS framework core is biophysical simulation models
overlaid by financial, social and environmental accounting modules. This
framework provides a basis for the case-study assessment of how policy and
environmental changes can impact upon land-use systems. Recently, these studies
have centred around three main themes: Climate Change, CAP Reform and
Agricultural Sustainability.
The
focus of LADSS has changed in recent years from a tool designed to assist in
the decision-making processes of land managers to a much wider framework that
involves stakeholder groups as part of an integrated assessment approach, using
a Decision Support System (DSS) as component of the process to explore options
provides the decision-maker with a better understanding of the consequences of
changes in land use and management. An integrated assessment approach is
preferred, able to combine the DSS with deliberative processes involving
stakeholders. The LADSS software runs on a Sun/Solaris platform and is made up
of a Knowledge Base (KB), Graphical User Interface (GUI), Geographic
Information System (GIS) and Relational Database Management System (RDBMS).
Fig. 4. Example of MARS application
(source: http://www.ivv.tuwien.ac.at)
Fig.
5. Example of LADSS application (source: http://www.macaulay.ac.uk/LADSS)
LUCIS
model
Another interesting approach is
illustrated by the LUCIS Model (Carr
& Zwick, 2007) that provides the information to understand and implement
the Land-Use Conflict Identification Strategy (LUCIS) (fig. 6). LUCIS was
developed over a period of ten years in a graduate design studio at the
University of Florida for students from the Departments of Landscape Architecture
and Urban and Regional Planning. Its conceptual basis was derived from Odum’s
Compartment Model (1969) that proposes four general land-use types for land
classification. It evolved to use traditional land-use suitability analysis as
a basis for projecting future land-use alternatives. Indeed, the LUCIS model
uses the ArcGIS geoprocessing framework to analyze suitability and preference
for major land-use categories, determine potential future conflicts among the
categories, and build future land-use
Fig.
6. Example of LUCIS Model application (source: GeoPlan Center, University of
Florida) scenarios. The basic concept is developing alternative future land use
scenarios considered as a proactive approach to land management, resource
management, and political and economic responsibility. With the help of
technical tools such as Geographic Information Systems (GIS), regions across
the United States are using scenario modelling to paint a picture of future
development patterns. The selected methodology illustrates the impact of
population increase and paves the way for developing more sustainable patterns
of land use, producing a spatial representation of probable patterns of future
land use for the following categories: existing conservation lands, existing
urban lands, existing agricultural lands, areas for future conservation land
use, areas for future urban land use, areas of probable future conflict between
agricultural and conservation land uses, areas of probable future conflict
between agricultural and urban land uses, areas of probably future conflict
between conservation and urban land uses, areas of probable future conflict
among agricultural, conservation and urban land.
What if?
In order to explore possible
futures for a community What if? is
an easy-to-use GIS-based Planning Support System (PSS) (Klosterman, 2001), that
can be implemented to prepare long-term land use, population, housing and
employment projections, political jurisdictions, and user-defined areas such as
school districts, and traffic analysis zones (fig. 7). The
Fig.
7. Example of What if? application (source: Brail, 2008)
package is easy to use,
customized to the user’s GIS data and policy issues, and provides outputs in
easy-to-understand maps and tables. Indeed, What if? can be used to prepare
long-term land use, population, and employment projections for census tracts
and userdefined areas such as political jurisdictions and traffic analysis
zones. It allows users to determine quickly and easily the impacts of
alternative policies to control urban growth, preserving agricultural land, or
expanding public infrastructure in easy-to-understand maps and tables. What if?
has been designed to be used in public settings by professionals, elected
officials and private citizens. Local governments, regional planning
organizations, and non-profit organizations across the United States and around
the world have used it. As its name suggests, What if? allows planners, public
officials, stakeholders, and private citizens to determine what would happen if
public policy choices are made and assumptions about the future would prove to
be true. Policy choices that can be considered in the model include the
expansion of public infrastructure, the implementation of farmland or open
space protection policies, and the adoption of land use plans, zoning
ordinances, and other growth controls. What if? allows users to generate easily
and quickly suitability maps and tables reporting the relative suitability of
different locations for accommodating future land use demands.
Ecosystem Management Decision Support and
Multi-scale Integrated Models of
Ecosystem Services
(MIMES)
An application framework for
decision support of ecological assessments at any geographic scale is Ecosystem Management Decision Support (EMDS) (Reynolds et al., 1996) that
integrates GIS, logic, and decision modelling to provide decision support for a
substantial portion of the adaptive management process of ecosystem
management (fig. 8). The NetWeaver logic
engine evaluates data as respect to a knowledge base that provides a formal
specification for the interpretation of data. The decision engine sets
strategic priorities of landscape units, based on landscape condition derived
from the logic model as well as any other management considerations pertinent
to decision-makers. EMDS integrates state-of-the-art (GIS) as well as logic
programming and decision modelling technologies in the Windows environment to
provide decision support for a substantial portion of the adaptive management
process of ecosystem management. EMDS uses Criterium
DecisionPlus (CDP) from
InfoHarvest, Inc. and NetWeaver from
Rules of Thumb, Inc. as core components. The NetWeaver component performs
logic-based evaluation of environmental data, and logically synthesizes
evaluations to infer the state of landscape features. The Criterium
DecisionPlus component prioritizes landscape features as respect to
user-defined management objectives, using summarized outputs from NetWeaver as
well as additional logistical information considered important to the
decision-makers (InfoHarvest, 2001). In particular, Criterium DecisionPlus
(CDP) decision management system helps structuring and communicating complex
decisions among alternatives. It is a graphical Windows Desktop application
that includes multi-criteria decision analysis (AHP and SMART) and uncertainty
management. CDP manages both qualitative and numerical inputs, and helps
eliciting preferences from decision-makers, and then provides contributions,
sensitivity and tradeoffs analysis in order to validate those preferences.
According
to the necessity to implement an integrated approach in planning, the Multiscale Integrated Models of Ecosystem
Services (MIMES) (Gund Institute for Ecological Economics, 2007) is a suite
of models for land use change and marine spatial planning decision-making (fig.
9). The models quantify the effects of land and sea use change on ecosystem
services and can be run at global, regional, and local levels. The MIMES use input
data from GIS sources, time series, etc., to simulate ecosystem components for
different scenarios defined by stakeholder input. These simulations can help
stakeholders evaluating how development, management and land/sea use decisions
will affect natural, human and built capital. Building interactive databases
for regional, integrated decision-making is an important aspect of implementing
MIMES.
Fig.
8. Example of EMDS application (source: Reynolds et al., 1996)
Fig.
9. Example of MIMES application
INDEX
planning support software, the Land Change Modeler (LCM) for ecological
sustainability, and MAPTALK
The implementation of an
interactive GIS planning support tool is represented by an integrated suite
named INDEX Planning Support Software
useful for assessing community conditions, designing future scenarios in real
time, measuring scenarios with performance indicators, ranking scenarios by
goal achievement, monitoring implementation of adopted plans (Allen, 2001)
(fig. 10). Introduced in 1994, it is now supporting a wide variety of planning
processes across the United States, with over 150 organizations in 35 states
equipped with the software. INDEX is designed to support the entire process of
community planning and development, and applications often begin with benchmark
measurements of existing conditions to identify problems and opportunities
reserving attention in plans. INDEX is used to design and visualize alternative
planning scenarios, analyze and score their performance, and compare and rank
alternatives. Once plans are adopted, INDEX supports implementation by
evaluating the consistency of development proposals against plan goals. Over
time, achievements can be periodically measured with progress reports.
The Land Change Modeller (LCM)
for Ecological Sustainability is an integrated software to
analyze land use change, projecting its trend into the future, and assessing
its implications for habitat and biodiversity change (Clark Labs, 2007) (fig.
11). Commissioned by the Andes Conservation Biology Center of Conservation
International, LCM is a vertical application developed by Clark Labs and
integrated within the IDRISI GIS and Image Processing software package. The
Land Change Modeler for Ecological Sustainability is oriented to the pressing
problem of accelerated land conversion and the very specific analytical needs
of biodiversity conservation. LCM is organized into five main areas: analyzing
past land use change, modelling the process of change, predicting the changes
into the future, assessing implications for biodiversity, and their evaluating
planning interventions for maintaining ecological sustainability.
Fig. 10. Example of INDEX
Planning Support Software application (source: www.crit.com)
Fig. 11. Example of LCM application
(source: Clark Labs, Clark University, www.clarklabs.org)
Another
approach related to dynamic and spatial decision-making is developed by MAPTALK (W!SL, 2003), that offers a
mutual GIS able to make an efficient use of this geographic information in
spatial decision-making processes were stakeholders feel no qualms using it
(fig. 12). Stakeholder participation and group decision-making is effectively
supported by digital support of spatial brainstorms, discussions and
(geographic) information sharing.
MAPTALK thereby facilitates
dialogue, decision-making and constructive engagement, and can be considered as
an accelerator for spatial planning processes. The use of MAPTALK results in a
directly available cohered plan, with a well-documented process. Together with
the Landscape center of Alterra and Wageningen Interactive Network Group (WING)
a service is provided to facilitate interactive spatial planning processes.
Fig. 12. Example of MAPTALK
application (source: http://www.maptalk.nl)
Integrated
planning for resilient communities: A technical guide to integrating hazard,
ecosystem and land use planning
A toolkit is designed to support
integrated planning that addresses hazard mitigation and ecosystem-based
planning within a land use planning context: Integrated Planning for Resilient Communities: A Technical Guide to
Integrating Hazard, Ecosystem and Land Use Planning (Hittle, 2011) (fig.
13).
The toolkit crosses disciplines
and jurisdictional boundaries and can highlight the benefits of ecosystem
conservation. It is characterized by the integration of three decision-support
tools and methods, and the implementation of an integrated analysis of hazards,
ecosystem conservation goals, and land use measures. A skilled expert team for
community resiliency toolkit implementation is necessary, even if the required
expertise will vary according to project size, complexity, and timeline.
Indeed, successful integration
and implementation of ecosystem-based management, hazard analysis, and land use
planning requires public and stakeholder involvement. It is relevant that each
tool has a particular role in the toolkit, even if some roles are shared or
overlap, giving the user flexibility in how the tools are applied:
-
CommunityViz
is the primary tool used to depict land use scenarios and summarize indicators
across all tools. It is used to model future growth, to change suitability to
create different future use patterns, and to associate hazard and ecosystem
data with specific polygons or parcels. It also produces outcomes in terms of
many socioeconomic indicators.
-
NatureServe
Vista takes the land use scenarios from CommunityViz
and depicts additional scenario details important for ecological analyses, such
as hazards or land management activities. Vista then assesses different land
use scenarios to determine
how well they meet conservation
goals for a set of conservation elements. The results are a set of performance
measures as respect to goals, and maps of areas where the scenarios are
compatible with or conflict with conservation goals. Vista also supports
generation of alternative scenarios for assessment in CommunityViz.
-
The Roadmap calculates the exposure of various populations and
facilities to hazards. The outputs of the calculations are percentages of
various populations or facilities impacted by various hazards. It is also
possible to create a spatial representation of where hazard risk and
vulnerability overlap. These spatial representations can guide the creation of
alternative future scenarios, which can then be assessed as respect to
vulnerability, if some assumptions are made about where future populations or
facilities are likely to be.
-
Iterative
Assessment and Planning: the tools are linked using a
series of scenarios, such as (1) current land use and other conditions; (2)
expected ”business-as-usual” land use at a future time, and (3) preferred or
alternative future land use(s). The alternatives identified are entered into
CommunityViz, either by specifically changing land use characteristics for
polygons, or by changing the rules for build-out, suitability scores for
parcels, or the way growth is allocated. Several iterations may be required to
develop a preferred scenario that meets as many objectives as possible. This
process is also educational for stakeholders as the tools can demonstrate
tradeoffs among objectives, or actions that satisfy multiple objectives at
once.
Fig.
13. Example of Integrated Planning for Resilient Communities: application
(source: http://resilient-communities.org)
The result of these steps will be
the “proposed scenario” that can be presented to decisionmakers and
stakeholders for review. Undoubtedly, further requests for changes will be made
and the toolkit can be used to assess the ramifications of any of these
proposed changes. The result of that process will be the “accepted scenario” or
plan that will become the basis of a revised “future land use scenario” in the
toolkit.
The relevance of the selected
models is related to their potential to implement in a synergic way different
planning and evaluation tools, in order to support decision-making process
oriented to the elaboration of strategic planning choice and situated actions.
The Integrated Spatial Assessment
(ISA) approach
Taking into account of the above
potentials and critical aspects of multi-methodological decision support
systems, it is relevant to identify an integrated approach for
planningevaluation where the process and its phases are able to understand the
local needs and guide situated decision-making process.
The proposal of a
multi-methodological evaluative framework, that includes the cognitive skills
and habits of the stakeholders and experts involved in mutual, joint and
dynamic learning processes, can help generating more efficient and effective
results than sectoral approaches, where interdisciplinarity and
transdisciplinarity are essential. In the above perspective the Integrated
Spatial Assessment (ISA) approach has been proposed, in which the recognition
of tangible and intangible values is the basis for a collective decision-making
that includes: the development of goals, the sharing of knowledge, negotiation
and compromise, problem-posing and problem-solving, the evaluation of needs,
and the definition of goals, but also the attention to questions of justice and
equity (Sinclair et al., 2009).
The proposed approach may help
communities clarify values, be more adaptive and proactive, respond to change,
set personal and communal goals, and participate in the planning
decision-making process. At the same time, the application of spatial tools, as
Geographical Information Systems, is a useful support to identify territorial
references and link values and planning choices. The integration of
Multi-Criteria Analysis (MCA) and Multi-Group Analysis (MGA) and Geographical
Information Systems (GIS) is remarkably fruitful in land management where the
role of local agents, their relations and objectives may be considered as a
structuring element for the process of information construction in a spatial
and dynamic evaluative model (Joerin et al., 2001). Compared to traditional
forms of GIS utilization, it should be possible to evaluate data covering not
only the current situation but also:
1.
the spatial characteristics of
options proposed;
2.
the temporal modification of data
following the options implementation;
3.
the expressed preferences of
local agents;
4.
the conflict analysis among the
various stakeholders;
5.
the evaluation of various options
in order to obtain a preference priority list.
Taking into account the previous
steps, we defined a methodological process that combines the contribution of
different methods and tools. In particular, the first methodological step that
we propose is the application of Problem Structuring Methods (PSMs) combined
with Public Participation Geographic Information Systems (PPGIS) for the
construction of a shared knowledge framework. The PSMs are methods that provide
a useful support to information structuring within Decision Support Systems,
and are able to deal with a variety of non-structured problems and situations,
prevailing over traditional approaches and following communicative conceptions
of planning (Rosenhead & Mingers, 2001). In particular, non-structured
problems are characterised by a multiplicity of agents; a multiplicity of
points of view; incommensurable interests, important intangible values, and
uncertainty. In these situations, through PSMs it is possible to visualize a
problem so that participants can clear up their positions and converge in one
or more potential issues aimed at building consensus. Through PSMs it is
possible to represent graphically the complexity of the issues examined,
explore the space-solutions, compare discrete alternatives, face uncertainty in
terms of ”possibilities” and ”scenarios” rather than in terms of probability
and prediction. PSMs are based on an explicit modelling of cause-effect
relations, and their technical simplicity allows them to be used in
“facilitated groups” and workshops.
At the same time, the PPGIS is
defined by Sieber (2006) as the use of GIS to broaden public involvement in
policy-making as well as the value of GIS to promote the goals of
nongovernmental organizations, grassroots groups and community based
organizations. PPGIS is meant to bring the academic practices of GIS and
mapping to a local level in order to promote knowledge production. The idea
behind PPGIS is empowerment and inclusion of marginalized populations, who have
little space in the public arena, through geographical technology education and
participation. PPGIS uses and produces digital maps, satellite imagery, sketch
maps, and many other spatial and visual tools, to change geographical
involvement and awareness at a local level. The local participatory management
of urban neighbourhoods usually comes from “claiming the territory”, and has to
be made compatible with national or local authority regulations in managing and
planning urban territory (McCall, 2003).
The second methodological step
combines Multi-Criteria and Multi-Group Decision Support Systems with GIS in
order to overcome the limitations of specific techniques through the
application of different methods, coming from different disciplines and define
a more complete and integrated framework of analysis and evaluation. Many
experiences of integration of Multi-Criteria Analysis, Multi-Group Analysis and
GIS have been developed referring to different sectors and using different
evaluation methods. This type of integration creates a “spatial multi-criteria
and multi-group analysis”. Spatial multi-criteria decision-making problems
typically involve a set of geographically defined alternatives from which a
choice of one or more alternatives is made as respect to a given set of
evaluation criteria (Jankowski, 1995; Malczewski, 1999). Spatial multi-criteria
analysis is very different from the conventional multi-criteria techniques due
to the inclusion of an explicit geographic component. It requires information
on criterion values and the geographical locations of alternatives in addition
to the decision-makers’ preferences for a set of evaluation criteria. This
means that analysis results depend not only on the geographical distribution of
attributes, but also on the value judgments involved in the decision-making process.
Therefore, two considerations are fundamental for spatial multicriteria
analysis: the GIS component (i.e., data acquisition, storage, etc.); and the
multicriteria analysis component (i.e., aggregation of spatial data and
decision-makers’ preferences into discrete decision alternatives) (Al-Shalabi
et al., 2006). Spatial analysis combined with multi-criteria methods has been
used in recent years to support evaluation, especially in the field of land-use
planning. For example, GIS technology was used to assess the criteria requested
to determine the suitability of land for housing. Because the required criteria
were heterogeneous and measured on various scales, GIS was integrated with an
outranking multi-criteria method called ELECTRE-TRI (Joerin et al., 2001).
Integration between GIS and multi-criteria analysis using Analytical Hierarchy
Process (AHP) was applied in selecting the location for housing sites in a
complex process, involving not only technical requirements, but also physical,
economical, social, environmental and political requirements (Al-Shalabi et
al., 2006). GIS and Multi-Criteria Analysis provided also a better insight into
the consequences of alternative water regimes on the performance of wetland
functions, supporting stakeholders participation. In particular, Multi-Criteria
Analysis was performed using the software package DEFINITE (Janssen et al.,
2005).
Fig. 14. Integrated Spatial
Assessment approach
In general, in the last decade, a
wide range of applications was experimented for decisionmaking, linking
multi-criteria assessment and GIS, considering both different methods and
different fields: urban and territorial planning, nature conservation, risk
management, etc. (Chen et al., 2001; Geneletti, 2004; Malczewski, 2004).
We propose to extend this
integration in the perspective of ”Integrated Assessments” in order to consider
not only the technical aspect of the decision-making problem but also the
involvement and participation of the local community in planning choices.
Indeed, integration between Multi-Criteria Analyses, Multi-Group Analyses and
Geographical Information Systems can be useful when facing conflicts, keeping
in mind the local agents’ role, the existing relationships and the pre-selected
objectives as a structural part of the information building process within a
spatial and dynamic evaluation model. As respect to the traditional use of GIS
we are able to take into account not only the status-quo data, but also the
spatial characteristics of the proposed options, the changing data over time,
the elicitation of agents’ preferences, the conflict analysis, the impact
assessment of the different options (Fusco Girard et al., 2008).
Therefore, it is possible to
structure a decision support system that includes “social creativity” (Fischer
et al., 2005) as the key component for the decision-making process, and
considers the “reflexive community” as a necessary interlocutor to interact
with. In this way, individual and social creativity can be integrated to face
complex problems through innovative approaches. In this perspective,
”Integrated Spatial Assessment” (fig. 14) – which is a participative approach –
is a useful tool for decision-making, including technical and political
evaluations. Furthermore, it refers to articulated and complex value systems,
inserted in conflicting and changing realities, where it is necessary to
operate consistently with sustainability principles.
The integration of Problem
Structuring Methods, Public Participation GIS, Multi-Criteria and Multi-Group
Decision Support Systems and Geographic Information Systems identifies a
decision-making process that allows the analysis of the complexity of human
decisions for a flexible environment in which collective knowledge and learning
has a significant role in decisional processes, and the possibility to explore
the transformation strategy definition in spatial planning field according to
sustainable and complex values.
Cava de’ Tirreni Masterplan: An
example of Integrated Spatial Assessment (ISA) application
For the Masterplan of Cava de’
Tirreni[1], in the Province of Salerno
(Italy), the Strategic Environmental Assessment (SEA) process was elaborated to
give significant support to planning activity and to help the local government
building the suitable choices for the territory. The SEA was seen as an
interactive and dynamic approach throughout the whole planning process
(Fischer, 2007), allowing to:
-
define the status and the
evolution trends of human and natural systems, including hard (objective, related to real world stuff where things are
measured, are fixed in dimensions and location in space) and soft (subjective, related to the world
of ideas, where the characteristics of a thing can change and specifications
are malleable) data, thus creating a complete frame of their interactions to
support decision-making process;
-
assume the environmental,
territorial and social goals, the landscape restoration and environmental
protection as stated in the current law and territorial plans, and to find
goals and main strategic choices according to a bottom-up approach in planning;
-
evaluate the effects of
protection policies and significant transformations of territory designed in
the plan, and consider the possible alternatives;
-
find the measures to avoid the
possible negative effects and to mitigate, reduce and/or compensate the impacts
of the preferable planning choices;
-
define the pressure factors and
the necessary indicators to evaluate and control the plan effects referring to
the goals and the expected results.
In the Cava de’ Tirreni case SEA
process was carried out to support the development of the Masterplan and was a
practical opportunity to test the Integrated Spatial Assessment (ISA) approach
(Fusco Girard et al., 2008). This approach was developed to integrate
multidimensional aspects within a complex development of strategies and choices
in planning, acknowledging the importance of the environmental, social, and
economic effects of a decision-making process focused on the creation of
alternative transformative options (fig. 15).
Fig. 15. Integrated Spatial
Assessment approach in Cava de’ Tirreni Masterplan
In ISA, the recognition of
complex social values (Fusco Girard & Nijkamp, 1997) is the basis for a
collective decision-making process, that includes the steps of problem-setting,
problem-posing and problem-solving, and the sharing of different forms of
knowledge, and that takes into account issues of justice and equity. Different
analyses are combined to manage conflicts and include various levels of
uncertainty.
For the Cava de’ Tirreni
Masterplan there was a continuous and dynamic interaction between assessment
context and assessment process during the whole decision-making process,
allowing to select each time the most appropriate methods and techniques based
on the goals and considering the results of each step.
Public meetings, in depth
interviews, and data and information collection were implemented, mainly aimed
at defining a permanent interaction ”platform” supporting dialogue and mutual
learning between citizens, experts and administrators, in coherence also with
the national and European guidelines on Strategic Environmental Assessment. The
interaction platform is based on a relational frame supported by a Geographic
Information System (GIS); it evolves together with the planning process and
allows the creation and development of all plan-related decisions. The
participation and consultation steps were fundamental for the application of a
sustainable territorial development principle, since finding and recognizing
values and resources is vital to enhance local potentials and select approaches
and tools for a good governance process. Public meetings created a direct
dialogue with citizens and stakeholders and a constant common ground of
discussion among citizens, professionals and Municipality.
The main goal was to broaden the
knowledge of Cava de’ Tirreni, with a special care for the most relevant issues
in future urban, social, economic and cultural transformations of the
territory, and to single out the collective needs. Thus, there was a continuous
interaction process between ”common knowledge” (citizens, associations, civil
society, etc.) and ”expert knowledge” (technicians and administrations),
considering SEA as a ”joint factor” among the actors. Three main topics were
considered during the meetings about the territorial development of Cava de’
Tirreni: What is the vision of future? Which strategies to use? Which actions
to undertake? In the long run, it is very important to decide how to direct
future development, considering not only the scenarios coming from collective
expectations, but also significant strategies and actions, to find the best
ways of intervention on the territory. For the public consultation a
questionnaire was formulated through which associations and citizens could
express their point of view regarding present and future of the city. Starting
from ten visions designed in earlier meetings, the discussion focused on five
main topics: ”Cava as a beautiful and identity-bearing city”’, ”Cava as a
regenerated and friendly city”, ”Cava as a modern and productive city”, ”Cava
as a territorial hub city”, ”Cava as a ecological city”. The visions reflect
the community perception of complex social values of territory and express the
relevant resources at different levels. They were examined with the Strategic
Options Development and Analysis (SODA) approach (Rosenhead & Mingers,
2001), a decision-support system that allows to face complex problems with
non-structured qualitative data starting from the elaboration of ”cognitive
maps”. Using the software Decision Explorer 3.1.0, cognitive maps were
elaborated starting from verbal protocols, structuring the contents under a
formal and methodological point of view (fig. 16). The elaboration of the
cognitive maps explained the structure of argumentations carried out during the
meetings, keeping the rich amount of data and managing the complexity of
information. Through different links identifying the connections of concepts,
the main issues were related to one another distinguishing among ”visions”,
”potentials”, and ”critical points”. The kind and number of each link express
the importance given to the topics by the different groups. The chain of
argumentations allowed to express the expectations, the preferences and the
critical points singled out during the meetings, through a “strategic cognitive
map”, whose topics were classified according to a chromatic scale:
-
orange: visions of the future;
-
green (three different shades): environmental,
infrastructural and settlement potentials;
-
purple (three different shades):
environmental, infrastructural and settlement critical points.
Starting from the argumentations
and the identification of the links in the strategic cognitive map, the whole
cognitive model was analyzed to find the preferable vision. Through the Domain
Analysis and the Central Analysis it was possible to evaluate recurrent topics
that are relevant to decide the guidelines of future scenarios.
The final rank was obtained
comparing the results of Domain Analysis and of Central Analysis. The favourite
vision is ”Cava as a ecological city”, followed by ”Cava as a modern and
productive city”, ”Cava as a territorial hub city”, ”Cava as a regenerated and
friendly city” and ”Cava as a beautiful and identity-bearing city”. Indeed, the
different visions are related to one another and can be seen as complementary
and synergic in a Plan that cares for the complex objectives of sustainability.
Potential and critical points were analyzed in the same way, highlighting the
most significant ones to solve or enhance. The results identify some essential
issues useful to define the transformations to be included in the Masterplan.
Fig. 16. An example of cognitive
map: visions, potentials and criticalities
Consistently with the
hierarchical structure of the decision-making process, the visions were
articulated into general goals, strategic lines, and strategic actions. In
details, strategic actions were linked to three guide-projects that are the
main reference to direct planning in the operative phase. The guide-projects
are the synthesis of issues coming from the participative and consultative
process and they identify the most relevant transformation and conservation
interventions within an infrastructural, spatial, functional and symbolic
relations system.
To decide the possible placement
of different planning choices, the multicriteria method called Analytic
Hierarchy Process (AHP) (Saaty, 1980, 1992) was used in combination with Geographic
Information System (GIS) elaborations (Marinoni, 2004). The application of AHP
into GIS allowed to go beyond the simple overlay of different themes, making a
pairwise comparison of the criterion of each hierarchical level. For each of
the five visions a ”susceptibility map to localization” was generated,
expressing the attitude of the territory to accept a given strategic action,
considering potential impacts. The lower are the territorial and environmental
impacts caused by an action, the higher the susceptibility of the territory to
receive that action.
To find alternative locations of
strategic actions and of related guide-projects, a three level hierarchical
structure was made for each vision (”environmental themes”, “criteria” and
“values/characteristics”) expressing the last level through a five points scale
associated to a chromatic one. The criteria were given the same weight for all
the visions, while the environmental issues were compared in pair creating five
matrixes, one for each vision. The AHP method allows to combine the weights of
the criteria coming from the comparisons with the scores associated to
different classes of susceptibility to localization obtaining, within GIS, the
susceptibility maps of each planning action (fig. 17).
Fig. 17. The elaboration of maps
of susceptibility to localization
For each Vision we have obtained
the susceptibility map to localization related to biosphere (territorial biopotential index, biodiversity degree,
infrastructural fragmentation index); geosphere
(slopes stability, seismic zoning); landscape
(landscape units); soil (land use,
cultivations productivity); and overall susceptibility map to localization. The
indicators selected for each environmental theme were elaborated starting from
the studies and analysis made by the different experts of the working group and
the database structured by the technical staff of Cava de’ Tirreni
Municipality.
Therefore, for each vision, it
was possible to have the relative map of susceptibility to localization and it
was possible to pass from the Visions to three technical “Guide-projects”
oriented to the city transformation (fig. 18). It is clear that the evaluation
supported the planning phases enhancing the characteristics of each area and,
most of all, placing activities where it is pre-emptively possible to minimize
territorial and environmental impacts, creating the whole strategic planning
frame. Through the interaction among visions identification and maps of
susceptibility to localization it has been possible to develop shared and
complementary guide-projects, where the use of a combination of techniques
penetrates and includes informal, ‘soft spaces’ of decision, able to complement
the more formal process, combining flexible and functional approaches with
formal development plan strategies (Allmendinger & Haughton, 2009; Cerreta,
2010). In the Cava de’ Tirreni masterplan, the opportunities that emerged from
the interactions focused mainly on the preservation of the identity of a
context wishing to regenerate itself. The integrated use of SODA, MCDA and GIS
shaped the different phases, acting as a powerful combination for providing
decision support in strategic decisions. SODA helps decision-makers in devising
visions and exploring possible effects, while MCDA and GIS support an in-depth
performance assessment of each strategic vision and related actions, as well as
the design of more robust options.
Fig.
18. The maps of susceptibility to localization and the three guide-projects
The implementation of ISA
approach helps to overcome the limits of each single method, to accommodate a
multi-dimensional and plural perspective and improve the quality of the
decision-making process. Indeed, by using the ISA approach, we aimed to
integrate social, territorial and environmental aspects in the development of
strategies and planning choices, while recognizing the important role of
stakeholder perceptions and environmental effects within the collective
decision-making process for the creation of alternative opportunities. ISA
approach may enable the interpretation of material and immaterial relations
characterizing a context, the acknowledgement of existing tangible and
intangible values, and the creation of strategies aimed at the production of
new values and at the sustainable development of many local resources in a
multi-dimensional perspective.
Conclusion
The selection of models
illustrated highlights that many computer based tools and instruments have been
developed to try and provide a common language for integrated visioning or
strategy development in planning, even if these instruments face serious
implementation problems in overcoming the gap between instrument development
(by consultants and/or universities) and daily planning practice.
In most cases, the present
technology focus produces instruments based above all on scientific rigor
rather than also on practical relevance; not adapted to the complex and dynamic
planning context; not transparent; not user friendly and not flexible (Te
Brömmelstroet & Bertolini, 2010). Therefore, such instruments cannot
link-up with the context specifics and do not contribute to implement the
Planning Support Systems (PSS) (Geertman, 2006; Uran & Janssen 2003; Vonk
et al., 2005) and to improve communicative planning practice (Timms, 2008;
Willson, 2001).
In order to understand how to
structure and improve integrated planning-evaluation processes, it is relevant
to analyze how it is possible to implement the interaction among the assessment
context, the assessment process and the assessment methods, how to select
different approaches and techniques, and how to choose them considering the
decision context specificity and the type of plan or project.
The ISA approach (Cerreta &
De Toro, 2010) proposed let us explore the tools of the integrated evaluations
helping to recognize their technical effectiveness and, at the same time,
improving the transparency of evaluation process, to build the decision able to
reflect the different needs and expectations. Through such planning-evaluation,
it is possible to help communities become more aware not only of their own
opinions and preferences, but also of those of other subjects, helping to find
participated and shared solutions.
In
this perspective, ISA can be a useful tool for decision-making, including
technical and political evaluations and referring to articulated and complex
value systems, in a conflicting and changing reality. The integration of
Problem Structuring Methods, Public Participation GIS, Multi-Criteria and Multi-Group
Decision Support Systems and Geographic Information Systems identifies a
decision-making process that allows the analysis of the complexity of human
decisions for a flexible environment in which collective knowledge and learning
assume a significant role in decisional processes, and the possibility to
explore the transformation strategy definition in spatial planning field
according to sustainable and complex values.