Population mapping in informal settlements with high-resolution satellite imagery and equitable ground-truth

We propose a generalizable framework for the population estimation of dense, informal settlements in low-income urban areas–so called ’slums’–using high-resolution satellite imagery. Precise population estimates are a crucial factor for efficient resource allocations by government authorities and NGO’s, for instance in medical emergencies. We utilize equitable ground-truth data, which is gathered in collaboration with local communities: Through training and community mapping, the local population contributes their unique domain knowledge, while also maintaining agency over their data. This practice allows us to avoid carrying forward potential biases into the modeling pipeline, which might arise from a less rigorous ground-truthing approach. We contextualize our approach in respect to the ongoing discussion within the machine learning community, aiming to make real-world machine learning applications more inclusive, fair and accountable. Because of the resource intensive ground-truth generation process, our training data is limited. We propose a gridded population estimation model, enabling flexible and customizable spatial resolutions. We test our pipeline on three experimental site in Nigeria, utilizing pre-trained and fine-tune vision networks to overcome data sparsity. Our findings highlight the difficulties of transferring common benchmark models to real-world tasks. We discuss this and propose steps forward

Exploring the spatial diffusion of electric vehicles in Scotland

The widespread diffusion of Electric Vehicles (EVs) represents a cornerstone of the Scottish Government's strategy to transition to a sustainable transport system. This diffusion is often discussedin temporal terms which relateto the time required to attain specified sales targets. A somewhat overlooked aspect of this diffusion concerns its spatial distribution. With EVs having been available to purchase in the mainstream market for the past four years, enough data now exists to begin to examine the spatial characteristics of EV adoption. This paper presents an initial analysis of the spatial diffusion of EVs throughout Scotland at the Unitary Authority (UA) level in order to approach two research objectives. Firstly, the analysis considers the relative performance of different UAs in reference to EV adoption to determine if any uptake hotspots are present. Additionally, the analysisinvestigates if the level of EV adoption across UAs is related to other area characteristics of the UAs inclusive of: the socio-demographic and built environment profiles of the UAs; the fleet characteristics of the UAs; the characteristics of the transport system present in the UAs; the environmental attitudes and social behaviours of the UA populace. Findings of the analysis indicate that the level of EV adoption across UAs is significantly positively related to the proportion of a UAs populace that: hold a university degree; consider climate change tobe an immediate and urgent problem; commute to work by foot; and the presence of rapid charge points in a UA. The research presented in this paper is likely to be of interest to national, regional and local transport planners by expanding the knowledge base concerning how new innovations spread through the transport system

Examining spatial proximity to health care facilities in an informal urban setting

This study explores the following research questions using OpenStreetMap-based mapping approach and healthcare facility survey from one of seven slums being studied in Africa and Asia. What are the differentials of spatial proximity to health care providers in informal settlements like slum? What are some of the lessons learnt from using OpenStreetMap-based mapping approach for slum health research? Preliminary findings suggest that residents can access four categories of healthcare facilities (Clinics/Maternity Centres; Patent Medicine Stores; Traditional/Faith Healers; Eye Health Centre) within a walking distance (under 1km) where Clinics and Maternity Centres are farthest from most residents

Towards a participatory methodology for community data generation to analyse urban health inequalities : a multi-country case study

This paper presents results from the application of a methodological framework developed as part of an ongoing research project focused on understanding inequalities in the healthcare access of slum residents of cities in four countries: Bangladesh, Kenya, Pakistan and Nigeria. We employ a systematic approach to produce, curate and analyse volunteered geographic information (VGI) on urban communities, based on a combination of collaborative satellite-imagery digitization and participatory mapping, which relies upon geospatial open-source technologies and the collaborative mapping platform OpenStreetMap. Our approach builds upon and extends humanitarian mapping practices, in order to address the twofold challenge of achieving equitable community engagement whilst generating spatial data that adheres quality standards to produce rigorous and trusted evidence for policy and decision making. Findings show that our method generated promising results both in terms of community engagement and the production of high-quality data on communities to analyse urban inequalities

Slum health mapping as catalyst for a collaborative agenda for research, practice, local citizens and volunteers

Background and purpose. Following the paradigmatic examples of the use of OSM for crisis mapping, there have been sustained efforts to use OSM for mapping preventively vulnerable communities in the global South. This includes, for instance, participatory mapping in the slums of sub-Saharan Africa (Hagen, 2017) and the Missing Maps project. Researchers have also started to study these mapping activities (e.g. Albuquerque et al. 2016; Herfort et al. 2017). However, a collaborative agenda in this area is missing that is able to reflect views and needs of researchers, OSM volunteers, humanitarian organisation practitioners and local communities. Methodology and Findings. After a brief review of existing methods used for mapping disadvantaged communities and slums, we introduce the approach and report on preliminary results from an ongoing large-scale project (NIHR Global Health Unit on Improving Health in Slums), which uses OSM for mapping slums in five cities: Dhaka (Bangladesh), Karachi (Pakistan), Nairobi (Kenya), Ibadan and Lagos (Nigeria). Our methods are based on the combination of satellite imagery digitisation with ground-truthing and participatory mapping. The maps produced will result in enhanced information regarding environmental features of the slums and the location of healthcare facilities, which will also be used as a basis for the health-science surveys of the project. In this manner, our approach is aimed at achieving a threefold goal: (a) participation and inclusion of local stakeholders as a strategy to build resilience; (b) worldwide collaboration, connecting to the global Humanitarian OSM network and student mapping societies; (c) quality evaluation mechanisms for generating high-quality data that can also be used for scientific research. Final discussion/Impact. We would like to discuss the approach and results of our project as a basis to invite OSM researchers, practitioners and volunteers to join us in defining a collaborative agenda towards improving methods and practice for mapping vulnerable communities in OSM. This should include challenges from an interdisciplinary perspective that account for technical, methodological, social and ethical issues. As a result, we would like to contribute to the emergence of an OSM research agenda that goes beyond solely using OSM geographic data for research, but also includes ways of engaging the OSM community and local communities in the research process

Towards a Participatory Methodology for Community Data Generation to Analyse Urban Health Inequalities: A Multi-Country Case Study

This paper presents results from the application of a methodological framework developed as part of an ongoing research project focused on understanding inequalities in the healthcare access of slum residents of cities in four countries: Bangladesh, Kenya, Pakistan and Nigeria. We employ a systematic approach to produce, curate and analyse volunteered geographic information (VGI) on urban communities, based on a combination of collaborative satellite-imagery digitization and participatory mapping, which relies upon geospatial open-source technologies and the collaborative mapping platform OpenStreetMap. Our approach builds upon and extends humanitarian mapping practices, in order to address the twofold challenge of achieving equitable community engagement whilst generating spatial data that adheres quality standards to produce rigorous and trusted evidence for policy and decision making. Findings show that our method generated promising results both in terms of community engagement and the production of high-quality data on communities to analyse urban inequalities

OSM Science - The Academic Study of the OpenStreetMap Project, Data, Contributors, Community, and Applications

This paper is an Editorial for the Special Issue titled “OpenStreetMap as a multidisciplinary nexus: perspectives, practices and procedures”. The Special Issue is largely based on the talks presented in the 2019 and 2020 editions of the Academic Track at the State of the Map conferences. As such, it represents the most pressing and relevant issues and topics considered by the academic community in relation to OpenStreetMap (OSM)—a global project and community aimed to create and maintain a free and editable database and map of the world. In this Editorial, we survey the papers included in the Special Issue, grouping them into three research perspectives: applications of OSM for studies within other disciplines, OSM data quality, and dynamics in OSM. This survey reveals that these perspectives, while being distinct, are also interrelated. This calls for the formalization of an ‘OSM science’ that will provide the conceptual grounds to advance the scientific study of OSM, not as a set of individualized efforts but as a unified approac

Bridges and Barriers: An Exploration of Engagements of the Research Community with the OpenStreetMap Community

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify possible causal structures explaining how these patterns may emerge within the context of a specific research group. Results indicate that academic papers generally show few signs of engagement and adopt data-oriented perspectives on the OSM project and product. The interviews expose that more complex perspectives and deeper engagement exist within the research group to which the interviewees belong, e.g., engaging in OSM mapping and direct interactions based on specific points-of-contact in the OSM community. Several conclusions and recommendations emerge, most notably: that every engagement with OSM includes an interpretive act which must be acknowledged and that the academic community should act to triangulate its interpretation of the data and OSM community by diversifying their engagement. This could be achieved through channels such as more direct interactions and inviting members of the OSM community to participate in the design and evaluation of research projects and programmes

In a network of lines that intersect: The socio-economic development impact of marine resource management and conservation in Southeast Asia

Marine protected areas (MPAs) are rapidly spreading to meet global conservation targets, but new governance arrangements can have unintended impacts on socio-economic development that can undermine and counteract their intended outcomes. We use an exploratory mixed-method research design to understand these development impacts and their underlying mechanisms, guided by an innovative activity space framework that situates marine resource management and conservation in a network of relationships between communities, human services, and nature. Qualitative research – based on 22 interviews in Koh Sdach Archipelago, Cambodia – demonstrates how the local community experienced improving relationships with the state and a slowing deterioration of marine resources, but also social division, heightened livelihood anxiety, and potentially a false sense of economic security. We hypothesise on this basis that marine conservation could impede socio-economic development, for which we find support in our quantitative analysis across Cambodia, the Philippines, and Timor-Leste: MPAs materialised in better-off communities but were associated with slower and partly regressive socio-economic development, in particular decreasing wealth and increasing child mortality. These findings suggest that the rapid global expansion of MPA coverage in its current, environmental-conservation-focused form is problematic as it disregards local social realities. Livelihood adaptation support should complement the implementation of marine resource governance mechanisms to mitigate unintended negative consequences