Joana Barros

Cities: Continuity, Transformation, and Emergence

This book applies ideas and methods from the complexity perspective to key concerns in the social sciences, exploring co-evolutionary processes that have not yet been addressed in the technical or popular literature on complexity. Authorities in a variety of fields – including evolutionary economics, innovation and regeneration studies, urban modelling and history – re-evaluate their disciplines within this framework. The book explores the complex dynamic processes that give rise to socio-economic change over space and time, with reference to empirical cases including the emergence of knowledge-intensive industries and decline of mature regions, the operation of innovative networks and the evolution of localities and cities. Sustainability is a persistent theme and the practicability of intervention is examined in the light of these perspectives.

The development of a morphological unplanned settlement index using very-high-resolution (VHR) imagery

Spatial metrics combined with spectral information extracted from very-high-resolution (VHR) imagery allow quantification of the general spatial characteristics of urban areas, as well as specific morphological features (i.e., density, size, and pattern) of unplanned settlements. Such morphological features are visible in VHR imagery, but they are challenging to quantify. Still, quantification of the morphological differences between planned and unplanned areas is an important step towards automatic extraction of unplanned areas from VHR imagery. In this work, we discuss how image segmentation assists in the extraction of homogenous urban patches (HUPs), and use spatial metrics to quantify the morphological differences between planned and unplanned HUPs. A set of spatial metrics meaningful to describe morphological features of unplanned areas is selected and combined into an unplanned settlement index (USI) using a multi-criteria evaluation approach. Two case study areas are used to test the USI, i.e., Dar es Salaam, Tanzania, and New Delhi, India. The ability of the developed USI to extract unplanned areas is confirmed via visual comparison with existing land use data, and a quantitative accuracy assessment shows that areas of high USI coincide well with unplanned areas in the reference data. The quantitative accuracy assessment presents an accuracy of greater than 70% for five selected test areas in both cities.

Fuzzy image segmentation for urban land-cover classification

A main problem of hard image segmentation is that, in complex landscapes, such as urban areas, it is very hard to produce meaningful crisp image-objects. This paper proposes a fuzzy approach for image segmentation aimed to produce fuzzy image-regions expressing degrees of membership of pixels to different target classes. This approach, called Fuzzy Image-Regions Method (FIRME), is a natural way to deal with the inherent ambiguity of remotely sensed images. The FIRME approach comprises three main stages: (a) image segmentation which creates fuzzy image-regions, (b) feature analysis which measures properties of fuzzy image regions, and (c) classification which produces the intended land-cover classes. The FIRME method was evaluated in a land-cover classification experiment using high spectral resolution imagery in an urban zone in Bogota, Colombia. Results suggest that in complex environments, fuzzy image segmentation may be a suitable alternative for GEOBIA as it produces higher thematic accuracy than the hard image segmentation and other traditional classifiers.

City of Slums: self-organisation across scales

The city is certainly a fine example of a complex system, where the parts can only be understood through the whole, and the whole is more than the simple sum of the parts. In the present paper we explore the idea that some of these parts are themselves complex systems and the interrelation between complex subsystems with the overall system is a necessary issue to the understanding of the urban complex system.

Exploring Urban Dynamics in Latin American Cities Using an Agent-Based Simulation Approach

The high rates of urban growth in Latin America during the 1960s and 1970s produced rapid urbanization and housing problems. In developing countries, planning policies as well as the research community have approached urban growth as a static problem rather than as a spatial form that emerges from the urban development process and that is part of a constant dynamic process. This paper focuses on a specific kind of urban growth that happens in Latin American cities, called ‘peripherisation’. This is characterized by the formation of low-income residential areas in the peripheral ring of the city and a perpetuation of a dynamic core-periphery spatial pattern. The dynamics of growth and change in Latin American cities are explored using agent-based simulation. The objective is to increase the understanding of urban spatial phenomena in Latin American cities, which is essential to providing a basis for future planning actions and policies. The first part of the chapter presents a brief overview of urban growth and dynamics in Latin American cities. The Peripherisation Model is introduced, and its implementation and evaluation described. Simulation exercises were used to revisit assumptions about urbanization issues in Latin American cities and investigate important aspects of growth and change in these cities. These exercises allowed the problem of urban growth in Latin American cities to be unfolded through their dynamics, relating these dynamics to urban morphology, and thus presenting a new and important perspective on the phenomenon.

Applying neighbourhood classification systems to natural hazards: a case study of Mt Vesuvius

Mt Vesuvius is regarded as one of the most deadly volcanoes on earth. With over 1 million people living on its flanks and in its periphery, there is little doubt that an eruption of sub-Plinian magnitude would be catastrophic to the livelihood and well being of contemporary Neopolitans. Such a large scale eruption would have wide ranging and differential effects on the surrounding population. Whereas previous studies of social vulnerability have focused on individual demographic factors (such as age, income or ethnicity), this research proposes the application of a general neighbourhood classification system to assess natural hazard vulnerability. In this study, Experian’s Mosaic Italy is used to classify and delineate the most vulnerable neighbourhood types around the province of Naples. Among the neighbourhoods considered most at risk, those areas with high proportions of elderly and low income families are deemed particularly vulnerable. With current evacuation plans deemed outdated and poorly communicated to the locals Rolandi (2010), Barberi et al. (2008), this methodology could prove to be a useful input to both town planners and civil protection agencies. A range of statistical measures and geophysical risk boundaries are employed here to assess the different areas of human resilience.

Configuring the neighbourhood effect in irregular cellular automata based models

ABSTRACT Cellular automata (CA) models have been widely employed to simulate urban growth and land use change. In order to represent urban space more realistically, new approaches to CA models have explored the use of vector data instead of traditional regular grids. However, the use of irregular CA-based models brings new challenges as well as opportunities. The most strongly affected factor when using an irregular space is neighbourhood. Although neighbourhood definition in an irregular environment has been reported in the literature, the question of how to model the neighbourhood effect remains largely unexplored. In order to shed light on this question, this paper proposed the use of spatial metrics to characterise and measure the neighbourhood effect in irregular CA-based models. These metrics, originally developed for raster environments, namely the enrichment factor and the neighbourhood index, were adapted and applied in the irregular space employed by the model. Using the results of these metrics, distance-decay functions were calculated to reproduce the push-and-pull effect between the simulated land uses. The outcomes of a total of 55 simulations (5 sets of different distance functions and 11 different neighbourhood definition distances) were compared with observed changes in the study area during the calibration period. Our results demonstrate that the proposed methodology improves the outcomes of the urban growth simulation model tested and could be applied to other irregular CA-based models.

Uneven geographies: Exploring the sensitivity of spatial indices of residential segregation

There has been extensive use of segregation indices for measuring residential segregation since 1950s, with continuous progress made in the field. Recent developments include the propositions of spatial global and local versions of traditionally used segregation indices, which have opened avenues for representing and analysing segregation as a multiscale and spatially varying phenomenon. Much less explored has been the issue of how important research design choices, such as the extent of geographical boundaries, grouping systems and scales of analysis, can influence the measurement of segregation. This paper contributes in this direction by investigating the impact of such decisions in the outcomes of the indices of generalized dissimilarity (D) and information theory (H) using a set of sensitivity analysis. Using a comparative study between London and São Paulo as basis, results obtained with different geographical boundaries, grouping systems and scales for the two indices are analysed visually and quantitatively. Results suggest that although D and H depict the same spatial dimension of segregation (unevenness/clustering), they present different sensitivity to geographical boundaries and grouping systems. The study also revealed how the two indices unfold different aspects of the segregation, which impact on their interpretation and applicability. The study concludes with a discussion of the considerations on research design choices concerning the interpretation of the results, which indicate the two indices should not be used interchangeably.

Introducing GIS across Levels: Designing for Diversity.

Abstract The paper proposes a strategy for designing introductory GIS modules at Birkbeck, University of London. Seven design aspects or elements (content, practical exercises, assessment, pace, mode, level of support, and level of difficulty) for tailoring modules at appropriate levels and for diversity are introduced and their application in Birkbeck’s context discussed. Student’s perceptions on those elements, obtained from surveying a subset of students who had taken multiple introductory GIS modules, is then presented. The paper concludes with a discussion on the relevance of the proposed design elements, reflecting on the differences between tutor’s design intentions and students’ perceptions.