Resilient Urbanisms
From Landscape Urbanism to Green Infrastructure to Infrastructural Urbanism, each framework regards ecology as a primary tenet.

An ecological system's resilience is build up over time, yet can be undone in a brief moment.

This blog intends to share diverse perspectives on these evolving frameworks and to explore solutions to sustaining resilient urbanisms.

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FOLLOWING eca-scape
GIS Indices

Analyses of landscape structure by means of

calculations of landscape ecology indexes.

The def ned method of calculations of landscape

ecology indexes within landscape structure analysis

was performed for LU/LC classes in identifi ed

categories, spatial and compositional relations of

landscape elements – patches, corridors, matrixes.

The analyses were done in ArcGIS environment

using standard tools and tools that were specifi cally

developed for the analysis of landscape structure.

These are Vector Based Landscape Analysis

Extension for ArcGIS (V-LATE) and Patch Analyst.

Calculated coeffi cients (indexes) can be classifi ed

according to the type of evaluated characteristic

into categories of indexes: of shape, size, diversity,

proximity, edges and statistical indicators.

Nearest neighbour analysis (index) – belongs among

distance analyses that are used to determine the

proximity of objects of a given category. In this

case it is the proximity of objects of the same LU/

LC category determined by the nearest neighbour

method. Map representation of the calculated values

of nearest neighbour analysis provides an overview

of the distribution of particular LU/LC categories

and of the mode (type) of their distribution in the


Area analysis (index) belongs among the basic

spatial analyses. Using the patch area analysis it is

possible to describe landscape graininess on a scale

from very fi ne (patch area less than 0.05 ha), fi ne

(patch area 0.05–0.9 ha), medium (patch area 0.9–35

ha) to coarse graininess > 35 ha). Besides, patch area

is a very important variable infl uencing diversity

and land cover.

Shape analysis (index) belongs among further metric

analyses of landscape space describing landscape

changes over time in the best way. These indicators

are calculated for the particular categories: patch

number, average patch shape, patch perimeter to

area ratio, average fractal dimension. Shape indexes

are signifi cant from the aspect of dissection or, on

the contrary, of geometrization of spatial structures.

The higher the values of shape index, the more

complicated the patch shape while their borders

get longer. On the other hand, the lower the value

of this index, the simpler the shape that can be

described by basic geometric shapes, expressing

the simplifi cation of particular shapes of patches.

Intervals of the patch shape index: 1.00–1.12 –

almost circular shape, 1.12–1.16 – almost square

shape, 1.16–1.90 – almost rectangular shape, > 1.90

distinctly elongated and irregular shape. The shape

characteristics are also important from the aspect of

edge eff ect, i.e. mutual interaction of two adjacent

areas with diff erent mode of use (e.g. arable land and

PGL, arable land and forest, etc.).

Diversity analysis (index) is aimed at the evaluation of

diversity and heterogeneity of analysed patches. In

the particular categories the computation generates

the total number of patches in each category, their

total area and the index Proportion – ratio of areas

of a given category to total area (or the percentage

proportion of a given category in relation to the

whole studied territory). Determination of these

indexes is important for the evaluation of landscape

heterogeneity and contrasts.

In its variability, landscape structure is related to the dynamics of natural and anthropogenic processes conditioning it, and at the same time, they are presented in landscape through its mediation.

The understanding of spatial configuration and its

development in the context of anthropic activities

provides better conditions and prerequisites for

interpretation and prediction of the functional

potential of landscape with all consequences

infl uencing these activities retroactively. Based

on the evaluation of trends, a “middle-course”

version of the proposal of the new arrangement and

functional use of landscape in the given territory

can be chosen and by approximation of landscape

structure characteristics it is possible to defi ne an

optimum landscape structure with regard to nonproduction functions of landscape.

The analysis of function

The key terms to be applied in analysis have their

roots in the broad discipline of ecology and natural

sciences. To develop an understanding of any landscape

or its individual components, we must

address the questions of the function of those components.

An understanding of the flows and interactions

within and between landscape components

is central to the mission of landscape analysis

(Keene and Strong 1968; Toth 1968, 1972; Forman

and Godron 1986). It is essential to know how a

component works, and the interaction of its parts

in the overall system of the landscape. It is from this

analysis that we develop an understanding of cause

and effect relationships within the landscape. How

a component or a landscape changes over time

(process) is the most significant product we can

derive from landscape analysis (Toth 1979; Forman

and Godron 1986). For it is only from a clear understanding

of landscape processes that the synthesis

of our work can hold the prospect of making a contribution

to a landscape continuum. Process is the

degree to which we grasp intellectually the manner

in which things change. It is our ability to discern

the patterns of shifting relationships among the

identified elements of a given landscape.  

And, even though there are shifting relationships and changes

occurring within all things, they are, at the moment

that we are examining them in time, finite and

actual-they exist. Therefore, ‘if process be fundamental

to actuality, then each ultimate, individual

fact must be describable as process’ (Whitehead

1968, p. 88).

The ‘operationally significant’ elements derived

from the analysis should include: (1) any factor

which limits the growth or reproduction of an individual

or community, e.g., a limiting factor, as

well as the identification of, (2) any changed or new

factor that would set off a chain of events in an environment

or ecosystem, e.g., a trigger factor (Billings

1970), and (3) documentation with respect to a

landscape component’s stability/resiZiency (Holling

and Goldberg 1971; Forman and Godron 1986). In

conjunction with these key terms, the landscape

analysis should be directed by the ‘emerging general

principles’ in landscape ecology in order to make as

clear as possible the flows and interactions within

ecosystems (Forman and Godron 1986).


Analysis is the intellectual wedge used to pry

open the landscape in order to understand and define

its nature, proportion, function, and the relationship

of its parts. Upton and Samson (1961)

maintain that there are three broad analytical approaches

with which we are all familiar: classification,

structure analysis, and operation analysis.

Classification deals with the kinds of things: classes,

subclasses, specimens, qualities, and vertical/

horizontal sorting. Structure analysis deals with the

parts of things but at the same time acknowledges

the spatial relationships between the part and the

whole. Operation analysis deals with the stages of

change in things, wherein we examine a structure

changing in time and space for a purpose. The various

disciplines associated with landscape ecology

vary in their approach and use of these three classifications.

It is important to understand their

differences, for they form part of that ‘tacit infrastructure’

of each discipline. These approaches condition

the way we think about our individual disciplines

with respect to their educational and research activities.

Can there be other analysis….

Unity in Likeness

1979). Finally, the analysis should support

the central theoretical purpose of landscape

ecology: A search for a correlation between form

and its meaning in the landscape, or to borrow from

Bronowski (1975, p. 13). ‘A search for unity in hidden

likenesses’. It is in this broadest sense that our

intelligence is used in dynamic and creative acts of

perception through the mind. It is the ability ‘to

read between the lines’. Intelligence is the mind’s

ability to perceive what lies hidden and to uncover,

reassemble, and create new unity (Bronowski 1975;

Podro 1972; Dubos 1974; Kennedy 1974; Judson

1980; Bohm and Peat 1987).

Defining Landscapes

A landscape has no absolute size; size may differ among organisms depending on the question or problem.

Functional landscapes occur at multiple spatial scales that may not correspond to human perceptions of the environment.

Therefore, the manager or investigator must define the landscape appropriately.

CORRIDOR: narrow, linear elements of a type that differs from that on either side.

The Matrix

Matrix=the most common or connected landscape element type that generally plays the dominant role in landscape function.•The matrix is defined based on the object of interest •The matrix is dynamic and a function of time andspace•The definition of a matrix will influence the interpretation of landscapes as well as landscape metrics -because of its large extent, the matrix may dominate certain metrics.

ALL - Must be defined relative to context of study …

Shannon’s Entropy GIS

6. Computation of Shannon’s Entropy: To determine whether the growth of urban areas was compact or divergent the Shannon’s entropy (Yeh and Liu, 2001Li and Yeh, 2004Lata et al., 2001Sudhira et al., 2004Pathan et al., 2004) was computed for each zones. Shannon’s  entropy  (Hn) given in equation 1, provides the degree of spatial concentration or dispersion of geographical variables among ‘n’ concentric circles across Zones.                                    


Where Pi is the proportion of the built-up in the ith concentric circle. As per Shannon’s Entropy, if the distribution is maximally concentrated in one circle the lowest value zero will be obtained. Conversely, if it is an even distribution among the concentric circles will be given maximum of log n.

Density Impacts

There are adverse mental (and other) health consequences resulting from an absence of green space. After allowing for demographic and socio-economic characteristics, a study of three hundred and fifty thousand people in Holland found that the prevalence of depression and anxiety was significantly greater for those living in areas with only 10% green space in their surroundings compared to those with 90% green space.

High-density advocates seem most oblivious to the needs of children. Living in high-density restricts children’s physical activity, independent mobility and active play. Many studies find that child development, mental health and physical health are affected. They also find a likely association of high-rise living with behavioural problems.

The Value of Density

What is density?

Density is the concentration of population and activity in an urban area. The most vibrant, diverse and exciting part of a city is often its centre. Density is at its highest at the centre, where there is the greatest range of people, buildings, public spaces, facilities, services and choices. Here, people can most easily exchange ideas and goods and services, both for business and for pleasure.

Key findings

Urban design that promotes a higher density of buildings and public spaces (in conjunction with other conditions such as mixed use, good building design and adequate open space) can:

  • provide cost savings in land, infrastructure and energy
  • reduce the economic costs of time spent travelling
  • help concentrate knowledge and innovative activity in the core of the city
  • be associated with lower crime and greater safety
  • help preserve green spaces in conjunction with certain kinds of urban development
  • reduce runoff from vehicles to water, and emissions to the air and atmosphere (though air emissions may be more locally concentrated)
  • help encourage greater physical activity, with consequent health benefits
  • promote social connectedness and vitality.

Overview of the research

Density - Often it is the densest parts of cities, such as downtown Auckland, which have the greatest vitality and sense of excitement.High urban density has potential costs in the form of congestion, noise and localised pollution. But low density development - urban sprawl - can also be costly, reflecting the higher economic and environmental costs of mobility. Much of the international research investigates this tension, examining the kinds of value (both private and public) created by dense versus less dense cities.

There is clear evidence about some of the savings offered by high urban density. Market demand leads to high land prices in dense city centres, and provides an impetus to economise on land resources. There are also infrastructure savings (eg, on roads, sewerage, schools), although these costs can rise again in cities with very high densities. High density also leads to energy savings, with significant reductions in petrol use and car dependence - especially in cities with multiple compact centres.

More general economic benefits of high urban density include enhanced ability to attract and concentrate businesses that are not space-intensive, such as knowledge-based industries, and to offer people better access to job opportunities.

Overall pollution from vehicle emissions can be less in dense cities (although there may be localised areas of higher pollution), providing development is carefully located and directed. Infill development is also shown to create less runoff and water pollution.

Density - Higher densities found in town or city centres like central Wellington provide exceptional access to office and retail employment.Urban density and green space are sometimes suggested to be incompatible. It is certainly clear that green space in the city contributes to public health, quality of life and biodiversity. This value is reflected in property prices around iconic green spaces. But it is less clear how much green space is needed to generate these benefits. Incorporating large tracts of green space into the city can create problems elsewhere. It may push development to the periphery where it changes the nature of adjoining rural areas, and generates more traffic and raises the costs of doing business in the wider urban area.

Cities in which compact centres are interspersed with green areas may offer the best solution to these problems.

Density - Northwood residential area in Christchurch offers a choice of housing types, including medium density terraced housing.There must always be some degree of trade-off between density and city greenery. Both the Urban Task Force in the United Kingdom and the United States Environmental Protection Agency, suggest a way through this challenge: the polycentric urban form (or cluster zoning) with high-density areas interspersed with green wedges or areas. Auckland’s node-focused growth strategy has adopted this concept.

Opinions vary about the benefits of higher density: a place that attracts some people with its vitality and ‘buzz’ may deter others. High density city centres can provide a greater range of housing and lifestyle choices. There is also evidence that denser urban areas have a strong sense of community, connectedness and vitality - largely because people are in closer contact with each other. But there may be a point at which this ceases to happen. In very high density areas, people may in fact withdraw from others and seek privacy.

High urban density can be beneficial for public health because it encourages more walking and cycling. High density can also make public transport - which involves more walking than private vehicle use - more viable.

Although there is strong evidence about some of the benefits inherent in high urban density, it is clear that density alone does not deliver benefits unless other important design issues are addressed too. Successful intensification and higher density in cities requires good design that also meets other needs - for instance, adequate open space and pedestrian friendly streets.