GIS and Machine Learning for Small Area Classifications in Developing Countries (ePub)
(Sprache: Englisch)
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...
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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.
Autoren-Porträt von Adegbola Ojo
Dr. Adegbola Ojo is Director of Teaching and Learning, Programme Leader, and Senior Lecturer in Urban Geography and Applications of Big Data at the School of Geography, University of Lincoln, UK. He received his PhD in Quantitative Human Geography from the University of Sheffield, his MSc in Geographic Information Science from the University College London, and his BSc in Geography and Planning Sciences from the University of Ado-Ekiti, Nigeria. His research interests are focused in understanding and representing social and spatial dynamics and intricacies of population behavior within a framework of Interdisciplinary Studies, Population Geography, Quantitative Social Science, and Computer Modeling. His research activities are grouped around the development and application of small area classifications, geographic information systems and geographic information science for informing public policy. Dr. Ojo has published many monographs and research articles with reputable journals. He has designed and delivered lectures, workshops, seminars, tutorials, practical labs, and assessments to a range of undergraduate and graduate students and working professionals.
Bibliographische Angaben
- Autor: Adegbola Ojo
- 2020, 1. Auflage, 268 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000289397
- ISBN-13: 9781000289398
- Erscheinungsdatum: 29.12.2020
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eBook Informationen
- Dateiformat: ePub
- Grösse: 11 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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