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GIS and Machine Learning for Small Area Classifications in Developing Countries

Contributor(s): Ojo, Adegbola (Author)

ISBN: 9780367652326

Publisher: CRC Press

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Description: Using two developing countries as case studies for small area segmentation techniques, the book connects new trans-disciplinary ways of thinking about social and spatial inequalities from a scientific perspective with GIS. This offers stakeholders a framework for engaging in practical dialogue on development policy within urban and rural settings.

Review Quotes:

A very comprehensive, powerful and insightful contribution to the field of Geoinformatics in the Social Sciences. Highly novel both in terms of the study regions it focuses on and in the state-of-the-art methods it engages with and applies.

Dimitris Ballas, Professor of Economic Geography, University of Groningen. The Netherlands

This book represents a clearly written and highly inventive attempt to enrich public policy analysis in developing countries by applying GIS and machine learning for small area classification. It offers both a technical introduction to the topic and a wide range of contemporary illustrative applications from both Nigeria and the Philippines. The book should be of interest to development scholars, methodologists and to human geographers interested in the application of new spatial technologies to Global South contexts.

Roger Burrows, Professor of Cities, School of Architecture, Planning, and Landscape, Newcastle University, UK

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