SLUMAP is motivated by the need to overcome limitations in existing slum mapping approaches that are impaired by the high acquisition costs of very-high resolution satellite imagery and the study of relatively small areas. Such approaches limit and constrain the evaluation of transferability and generalization. The project will evaluate the hypothesis that automated, free ans open-source solutions (FOSS) along with low-cost imagery, could be used to achieve state-of-the-art (SoA) results in slum mapping and characterization.
The main objective of the study is to contribute to SDG 11 : “Make cities and human settlements inclusive, safe, resilient and sustainable”, by
(i) improving our understanding of the potential of slum detection and characterization using remote sensing and
(ii) developing a general, scalable and open-source methodological framework for sub-Saharan Africa (SSA) to support this task and to meet the requirements of the stakeholders in the big data era.
To achieve these goals, the SLUMAP project will incorporate feedback from regular and structured interaction with stakeholders throughout the project in a bidirectional manner. The project will employ case-studies from three cities in sub-Saharan Africa that contain slums. Satellite data from different sensor types (commercial VHR, low/moderate-cost HR and free HR) will be used to study the influence of spectral and spatial resolution on slum delineation and intra-slum characterization, considering the financial cost of image acquisitions. State-of-the-art classification methodologies will be designed and implemented, embedded in a FOSS semi-automated processing chain. The use of three different case studies will enable a thorough assessment, and the development of transferable and generalizable models. Moreover, a stakeholder needs and requirements assessment at the community, local, national and international level will be done to facilitate science-based policy-making.
SLUMAP is an interdisciplinary project that involves the use of a wide suite of remotely sensed indicators at different spatial and spectral resolutions, and the implementation of different modelling approaches. The project aims to create a holistic and open-access tool for slum mapping at different scales, in sub-Saharan Africa. The successful implementation of SLUMAP will allow for systematic mapping and characterization of slums and will provide key information for local and international pro-poor policy development. The project will contribute to alleviating the knowledge gap regarding transferability and generalization considering the constraining cost of acquisition of satellite imagery.
Our results will complement field household surveys performed by local, regional or international institutions to support the production of useful indicators to locate, delineate and characterize slums. Such spatial information will be useful for decision-making and planning activities for the improvement of slums in terms of sanitation levels, standards of housing, infrastructure and provision of basic services.