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From the author of Small Change comes this engaging guide to placemaking, packed with practical skills and tools that architects, planners, urban designers and other built environment specialists need in order to engage effectively with development work in any context. Drawing on four decades of practical and teaching experience, the author offers fresh insight into the complexities faced by practitioners when working to improve the communities, lives and livelihoods of people the world over. The book shows how these complexities are a context for, rather than a barrier to, creative work. The book also critiques the single vision top down approach to design and planning. Using examples of successful professional practice across Europe, the US, Africa, Latin America and post-tsunami Asia, the author demonstrates how good policy can derive from good practices when reasoned backwards, as well as how plans can emerge in practice without a preponderance of planning. Reasoning backwards is shown to be a more effective and inclusive way of planning forwards with significant improvements to the quality of process and place. The book also offers a variety of methods and tools for analyzing the issues, engaging with communities and other stakeholders for design and settlement planning and for improving the skills of all involved in placemaking. Ultimately the book serves as an inspiring guide, and a distillation of decades of practical wisdom and experience. The resulting practical handbook is for all those involved in doing, learning and teaching placemaking and urban development world-wide.

Peter Oberlander proposes a number of specific policy shifts to accommodate the poor effectively within the settlement system and to use land strategically as a scarce resource in the development process.

Migration is the principal demographic process shaping patterns of human settlement, and it serves an essential role in human development. While progress has been made in measuring international migration, internal migration statistics are as yet poorly developed in many countries. This article draws on a repository of data established under the IMAGE (Internal Migration Around the GlobE) project to address this deficit by constructing the first comprehensive league table of internal migration intensities for countries around the world. We review previous work, outline the major impediments to making reliable comparisons, and set out a methodology that combines a novel estimation procedure with a flexible spatial aggregation facility. We present the results in the form of league tables of aggregate crude migration intensities that capture all changes of address over one-year or five-year intervals for 96 countries, representing four-fifths of the global population. Explanation for the observed differences has been sought, inter alia, in historical, structural, cultural, and economic forces. We examine the links between development and migration intensity through simple correlations using a range of demographic, economic, and social variables. Results reveal clear associations between internal migration intensities and selected indicators of national development.

Challenging the more conventional approaches to dislocation and resettlement that are the usual focus of discussion on the topic, this book offers a unique theory of dislocation in the form of primitive accumulation. Interrogating the ‘reformist-managerial’ and ‘radical-movementist’ approaches, it historicizes and politicizes the event of dislocation as a moment to usher in capitalism through the medium of development. Such a framework offers alternative avenues to rethinking dislocation and resettlement, and indeed the very idea of development. Arguing that dislocation should not be seen as a necessary step towards achieving progress - as it is claimed in the development discourse - the authors show that dislocation emerges as a socio-political constituent of constructing capitalism. This book will be of interest to academics working on Development Studies, especially on issues relating to the political economy of development and globalization. 1. Debates on Dislocation, Compensation and Resettlement: What Does Our Approach Contribute? 2. Development and Dislocation: Why one Cannot be Addressed Without the Other? 3. From ‘Compensation’ to ‘Resettlement Need’: The Reformist-Managerial Approach 4. De-Familiarising the Economy and Development 5. A Critique of Received Theories of Dislocation, Compensation and Resettlement 6. Western Marxism and its Theory of Primitive Accumulation: Limits and Limitations 7. Primitive Accumulation – World of the Third Marxian Perspective on Dislocation 8. Two Case Studies of Primitive Accumulation in India: Special Economic Zone and Plachimada 9. From Resistance to Resettlement Right: Confronting the ‘Subjects of Development’ and Policy Paradigms Anjan Chakrabarti is Professor in the Department of Economics at the University of Calcutta, India. His publications most recently include (as co-author) Transition and Development in India (also published by Routledge). Anup Kumar Dhar is Associate Fellow at the Centre for the Study of Culture and Society (CSCS), Bangalore, India. As co-authors, they recently published Global Capitalism and World of the Third .

With the rapid advancement of urbanization, the green space well-being (GSWB) of developing countries faces drastic changes and is increasingly threatened. Green and residential spaces are the core elements of GSWB; however, we know very little about the interaction and combination of the two in terms of their effect on GSWB. This study identified the spatiotemporal features of GSWB and critically examined how patterns of residential–green combinations affect GSWB. Based on land-use data for Jinan from 2006 to 2018, and using the spatial measurement tool GeoDa, we found that both green and residential space have increased significantly in central Jinan. At the macro level, the spatial correlation between the two decreased significantly; meanwhile, at the micro level, there are obvious differences in time and geography. This led to differences in the distribution of GSWB between regions with high value and those with low value. We revealed that the development, preservation, and demolition of residential and green spaces influence changes in GSWB. The positive effects on GSWB come from (1) mountain park development policy in built-up areas, (2) theme park development policy in new urban areas, and (3) urban renewal and demolition policy. The negative effects on GSWB come from (1) issues remaining from prior extensive urban development, (2) the replacement of central areas driven by urban branding, and (3) the lack of supervision of nearby facilities for new housing development. To better understand changes in GSWB, it is necessary to consider its internal residential–green spatial collaboration and propose targeted response strategies. This can help to better safeguard the quality of human settlements in the process of urbanization in developing countries.

It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Significant areas of unlit settlements are also located in some developed countries. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%. Nighttime lights from satellite are combined with a map of human settlements, showing that 19% of these areas, mainly in Africa, the Middle East and Asia, have no detectable artificial light. These data were then used in models to predict well-being.

Slums are a structural feature of urbanization, and shifting urbanization trends underline their significance for the cities of tomorrow. Despite their importance, data and knowledge on slums are very limited. In consideration of the current data landscape, it is not possible to answer one of the most essential questions: Where are slums located? The goal of this study is to provide a more nuanced understanding of the geography of slums and their growth trajectories. The methods rely on the combination of different datasets (city-level slum maps, world cities, global human settlements layer, Atlas of Informality). Slum data from city-level maps form the backbone of this research and are made compatible by differentiating between the municipal area, the urbanized area, and the area beyond. This study quantifies the location of slums in 30 cities, and our findings show that only half of all slums are located within the administrative borders of cities. Spatial growth has also shifted outwards. However, this phenomenon is very different in different regions of the world; the municipality captures less than half of all slums in Africa and the Middle East but almost two-thirds of all slums in cities of South Asia. These insights are used to estimate land requirements within the Sustainable Development Goals time frame. In 2015, almost one billion slum residents occupied a land area as large as twice the size of the country of Portugal. The estimated 380 million residents to be added up to 2030 will need land equivalent to the size of the country of Egypt. This land will be added to cities mainly outside their administrative borders. Insights are provided on how this land demand differs within cities and between world regions. Such novel insights are highly relevant to the policy actions needed to achieve Target 11.1 of the Sustainable Development Goals (“by 2030, ensure access for all to adequate, safe and affordable housing and basic services, and upgrade slums”) as interventions targeted at slums or informal settlements are strongly linked to political and administrative boundaries. More research is needed to draw attention to the urban expansion of cities and the role of slums and informal settlements.

The coastal zones of Small Island States are hotspots of human habitation and economic endeavour. In the Pacific region, as elsewhere, there are large gaps in understandings of the exposure and vulnerability of people in coastal zones. The 22 Pacific Countries and Territories (PICTs) are poorly represented in global analyses of vulnerability to seaward risks. We combine several data sources to estimate populations to zones 1, 5 and 10 km from the coastline in each of the PICTs. Regional patterns in the proximity of Pacific people to the coast are dominated by Papua New Guinea. Overall, ca. half the population of the Pacific resides within 10 km of the coast but this jumps to 97% when Papua New Guinea is excluded. A quarter of Pacific people live within 1 km of the coast, but without PNG this increases to slightly more than half. Excluding PNG, 90% of Pacific Islanders live within 5 km of the coast. All of the population in the coral atoll nations of Tokelau and Tuvalu live within a km of the ocean. Results using two global datasets, the SEDAC-CIESIN Gridded Population of the World v4 (GPWv4) and the Oak Ridge National Laboratory Landscan differed: Landscan under-dispersed population, overestimating numbers in urban centres and underestimating population in rural areas and GPWv4 over-dispersed the population. In addition to errors introduced by the allocation models of the two methods, errors were introduced as artefacts of allocating households to 1 km x 1 km grid cell data (30 arc-seconds) to polygons. The limited utility of LandScan and GPWv4 in advancing this analysis may be overcome with more spatially resolved census data and the inclusion of elevation above sea level as an important dimension of vulnerability.

Global warming of 1.5 °C above preindustrial levels and a commensurate increase in global greenhouse gas emissions pose an unprecedented danger to human settlements, livelihoods and the sustainable development of Small Island Developing States (SIDS), yet these challenges present tremendous opportunities to rethink development pathways. The paper has two objectives. One is to critically review present vulnerabilities and adaptation strategies employed by the state, private sector, non-governmental organisations, community-based organisations and households. The other is to discuss vulnerabilities and identify adaptation and resiliency strategies which are considered most applicable beyond the 1.5 °C limit. The Caribbean Region is the focus of the paper. A key finding of the paper is that temperature change above the 1.5 °C limit set by the Paris Conference of the Parties will make the natural and human systems of SIDS even more highly vulnerable than they are already. Another finding is that Caribbean states have implemented various innovative climate change adaptation strategies, but their relevance should the 1.5 °C target be exceeded, requires further exploration. The paper is useful to policymakers, decision-makers and finance agencies in search of practical solutions to avert the implications for Caribbean settlements, economies and ecosystems should the temperature warming exceed 1.5 °C.

Spatially explicit and reliable data on poverty is critical for both policy makers and researchers. However, such data remain scarce particularly in developing countries. Current research is limited in using environmental data from different sources in isolation to estimate poverty despite the fact that poverty is a complex phenomenon which cannot be quantified either theoretically or practically by one single data type. This study proposes a random forest regression (RFR) model to estimate poverty at 10 km × 10 km spatial resolution by combining features extracted from multiple data sources, including the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) nighttime light (NTL) data, Google satellite imagery, land cover map, road map and division headquarter location data. The household wealth index (WI) drawn from the Demographic and Health Surveys (DHS) program was used to reflect poverty level. We trained the RFR model using data in Bangladesh and applied the model to both Bangladesh and Nepal to evaluate the model’s accuracy. The results show that the R2 between the actual and estimated WI in Bangladesh is 0.70, indicating a good predictive power of our model in WI estimation. The R2 between actual and estimated WI of 0.61 in Nepal also indicates a good generalization ability of the model. Furthermore, a negative correlation is observed between the district average WI and the poverty head count ratio (HCR) in Bangladesh with the Pearson Correlation Coefficient of -0.6. Using Gini importance, we identify that proximity to urban areas is the most important variable to explain poverty which contribute to 37.9% of the explanatory power. Compared to the study that used NTL and Google satellite imagery in isolation to estimate poverty, our method increases the accuracy of estimation. Given that the data we use are globally and publicly available, the methodology reported in this study would also be applicable in other countries or regions to estimate the extent of poverty.