Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data

Informal settlements are home to the most socially and economically vulnerable people on the planet. In order to deliver effective economic and social aid, non-government organizations (NGOs), such as the United Nations Children's Fund (UNICEF), require detailed maps of the locations of informal settlements. However, data regarding informal and formal settlements is primarily unavailable and if available is often incomplete. This is due, in part, to the cost and complexity of gathering data on a large scale. To address these challenges, we, in this work, provide three contributions. 1) A brand new machine learning data-set, purposely developed for informal settlement detection. 2) We show that it is possible to detect informal settlements using freely available low-resolution (LR) data, in contrast to previous studies that use very-high resolution (VHR) satellite and aerial imagery, something that is cost-prohibitive for NGOs. 3) We demonstrate two effective classification schemes on our curated data set, one that is cost-efficient for NGOs and another that is cost-prohibitive for NGOs, but has additional utility. We integrate these schemes into a semi-automated pipeline that converts either a LR or VHR satellite image into a binary map that encodes the locations of informal settlements.Comment: Published at the AAAI/ACM Conference on AI, ethics and society. Extended results from our previous workshop: arXiv:1812.0081

Assessing texture pattern in slum across scales: an unsupervised approach

According to the Global Report on Human Settlements (United Nations, 2003), almost 1 billion people (32% of the world ’s population) live in squatter settlements or slums. Recently, the perception of these settlements has changed, from harmful tumours which would spread around sickly and unhealthy cities, to a new perspective that interpret them as social expressions of more complex urban dynamics. However, considering a report from UNCHS - United Nations Center for Human Settlements, in relation to illegal and disordered urbanisation issue, some of the main challenges faced by cities are related to mapping and registering geographic information and social data spatial analysis. In this context, we present, in this paper, preliminary results from a study that aims to interpret city from the perspective of urban texture, using for this purpose, high resolution remote sensing images. We have developed analytic experiments of "urban tissue" samples, trying to identify texture patterns which could (or could not) represent distinct levels of urban poverty associated to spatial patterns. Such analysis are based on some complex theory concepts and tools, such as fractal dimension and lacunarity. Preliminary results seems to suggest that the urban tissue is fractal by nature, and from the distinct texture patterns it is possible to relate social pattern to spatial configuration, making possible the development of methodologies and computational tools which could generate, via satellite, alternative and complementary mapping and classifications for urban poverty

The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries

Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups

The civic survey of Greater London: social mapping, planners and urban space in the early twentieth century

This paper examines work conducted between 1915 and 1919 by a group of architects and planners based at the Royal Institute of British Architects. The project, called the Civic Survey of Greater London, and the substantial collection of maps and diagrams that resulted from it are currently unknown in histories of mapping and planning, thus this paper offers a preliminary account and analysis of the work. The paper begins by assessing the development of surveying and mapping techniques in the nineteenth century with the aim of situating the Survey within broader historical trajectories. The following section of the paper examines the immediate context for the Survey, in particular the place of Patrick Geddes and his ideas. The third part of the paper focuses on the work of the Survey itself. The fourth part draws out key analytical threads in dialogue with a number of the maps of the Survey. The emphasis placed here is on exploring lines of continuity between the Civic Survey of Greater London and earlier techniques of representation and governmentality. The concluding section reflects briefly on the reasons for the Survey's subsequent relative obscurity and the importance of the project for later traditions of surveying