Gis and Machine Learning for Small Area Classifications in - Developing Countrie

Summary

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.

Product details

• Authors: Adegbola Ojo
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 31.05.2023
• EAN: 9780367652326
• ISBN: 978-0-367-65232-6
• No. of pages: 246
• Subjects: Social sciences, law, business > Sociology > Sociological theories; SOCIAL SCIENCE / Human Geography, POLITICAL SCIENCE / Public Policy / Regional Planning, BUSINESS & ECONOMICS / Development / General, TECHNOLOGY & ENGINEERING / Civil / General, SOCIAL SCIENCE / Sociology / Urban, SOCIAL SCIENCE / Developing & Emerging Countries, The environment, Urban & municipal planning, Regional & area planning, Civil engineering, surveying & building, Human Geography, Urban communities, Development Studies, Urban and municipal planning and policy, Settlement, urban and rural geography, Regional and area planning, Civil engineering, surveying and building, Development and environmental geography