A methodological framework for analyzing PPGIS data collected in 3D

Public participation geographic information system (PPGIS) is a facilitated Volunteered Geographic Information approach and data collection method that aims to capture the spatial experiences of individuals. Although we experience the space around us three-dimensionally, altitude, as the third dimension, has been often absent from PPGIS research and practice. This is largely because of the complexity of implementing surveys in 3D but can also be attributed to a lack of analytical preparedness for using such data. This study complements 3D PPGIS data collected from a pilot study of the Aninkainen block in Turku, Finland with synthetic, i.e. artificially manufactured, data to propose an analytical framework for the study of 3D PPGIS data. The analytical framework divides methods based on the geographical scale into two groups: micro- and macro-scale analysis. In this framework, we propose the use of geospatial metrics to analyze 3D PPGIS data. We argue that while this multidisciplinary area of research is in its infancy, use of intuitive 3D adapted geometric and landscape metrics can help overcome some of complexities associated with use of this emerging participatory data. We conclude by outlining the limitations and envisioning areas for future research.

Automated summary

Public participation geographic information system (PPGIS) is a method that aims to capture individuals' spatial experiences. However, the third dimension of altitude is often overlooked in PPGIS research and practice due to the complexity of implementing 3D surveys and a lack of analytical preparedness. This study proposes an analytical framework for 3D PPGIS data and suggests the use of geospatial metrics for analysis. The authors argue that 3D adapted geometric and landscape metrics can help overcome the complexities associated with this emerging participatory data.