A methodological framework for analysis of participatory mapping data in research, planning, and management

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openAccess
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Volume Title

A2 Katsausartikkeli tieteellisessä aikakauslehdessä

Date

2021

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Language

en

Pages

28

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International Journal of Geographical Information Science, Volume 35, issue 9, pp. 1848-1875

Abstract

Today, various methods are applied to analyze the data collected through participatory mapping, including public participation GIS (PPGIS), participatory GIS (PGIS), and collecting volunteered geographic information (VGI). However, these methods lack an organized framework to describe and guide their systematic applications. Majority of the published articles on participatory mapping apply a specific subset of analyses that fails to situate the methods within a broader, more holistic context of research and practice. Based on the expert workshops and a literature review, we synthesized the existing analysis methods applied to the data collected through participatory mapping approaches. In this article, we present a framework of methods categorized into three phases: Explore, Explain, and Predict/Model. Identified analysis methods have been highlighted with empirical examples. The article particularly focuses on the increasing applications of online PPGIS and web-based mapping surveys for data collection. We aim to guide both novice and experienced practitioners in the field of participatory mapping. In addition to providing a holistic framework for understanding data analysis possibilities, we also discuss potential directions for future developments in analysis of participatory mapping data.

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| openaire: EC/H2020/856602/EU//FINEST TWINS

Keywords

Online participatory mapping, participatory GIS (PGIS), Public participation GIS (PPGIS)

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Citation

Fagerholm, N, Raymond, C M, Olafsson, A S, Brown, G, Rinne, T, Hasanzadeh, K, Broberg, A & Kyttä, M 2021, ' A methodological framework for analysis of participatory mapping data in research, planning, and management ', International Journal of Geographical Information Science, vol. 35, no. 9, pp. 1848-1875 . https://doi.org/10.1080/13658816.2020.1869747