The Effect of Population Density on Remote Humanitarian Mapping Activities: A Triple-Difference Analysis
Yaxuan Yin, Jacob Thebault-Spieker
Abstract
The proliferation of OpenStreetMap (OSM) as a collaborative geographic dataset has been instrumental in addressing data gaps globally. However, disparities in map coverage persist, particularly in economically disadvantaged and disaster-prone regions. The emergence of the Humanitarian OpenStreetMap Team (HOT) in 2010 aimed to bridge these gaps by leveraging the collective efforts of volunteers through platforms like the HOT Tasking Manager. While previous research has highlighted the success of these initiatives in recruiting contributors and expanding map coverage, their implications for existing structural biases remain unclear, potentially hindering the regions benefiting from humanitarian activities. Thus, our study employs the difference-in-difference-in-difference (DDD) approach to empirically examine the pattern between contribution dynamics and population density in project regions involved in humanitarian mapping activities. By further investigating the participation of various levels of contributors in projects with different population densities, we aim to inform better design strategies to align contributor expectations and experiences, fostering more equitable and effective humanitarian mapping efforts.
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