Geocomputation with Python

Author:   Michael Dorman ,  Anita Graser ,  Jakub Nowosad ,  Robin Lovelace (University of Leeds, UK)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032458915


Pages:   344
Publication Date:   14 February 2025
Format:   Hardback
Availability:   In Print   Availability explained
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Geocomputation with Python


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Author:   Michael Dorman ,  Anita Graser ,  Jakub Nowosad ,  Robin Lovelace (University of Leeds, UK)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.793kg
ISBN:  

9781032458915


ISBN 10:   1032458917
Pages:   344
Publication Date:   14 February 2025
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Michael Dorman, Ph.D. is a programmer and lecturer at The Department of Environmental, Geoinformatics and Urban Planning Sciences, Ben-Gurion University of the Negev. He is working with researchers and students to develop computational workflows for spatial analysis, mostly through programming in Python, R, and JavaScript, as well as teaching those subjects. Anita Graser, Ph.D. is a Senior Scientist at the Austrian Institute of Technology (AIT), QGIS PSC member and lead developer of MovingPandas. Anita has published several books about QGIS, including “Learning QGIS” and “QGIS Map Design”, teaches Python for QGIS, and writes a popular spatial data science blog. Jakub Nowosad, Ph.D. is an Associate Professor at Adam Mickiewicz University in Poznań and a visiting scientist at the University of Münster. Specializing in spatial pattern analysis in environmental studies, he combines research with a dedication to education and open science principles. Dr. Nowosad is committed to developing scientific software and fostering accessible knowledge through teaching and open-source contributions. Robin Lovelace, Ph.D. is a Professor of Transport Data Science at the University of Leeds., He is the developer of high impact applications for more data-driven transport planning and policy. He has a decade’s experience researching and teaching data science with geographic data and has developed numerous tools to support more data-driven policies, including the award-winning Propensity to Cycle Tool which has transformed the practice of strategic active travel network planning in the UK.

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