Window Expeditions: A playful approach to crowdsourcing natural language descriptions of everyday lived landscapes
Abstract
Measuring what citizens perceive and value about landscapes is important for landscape monitoring. Capturing temporal, spatial and cultural variation requires collection of data at scale.
One potential proxy data source are textual descriptions of landscapes written by volunteers. We implemented a gamified application and crowdsourced a multilingual corpus of in-situ descriptions of everyday lived landscapes.
Our implementation focused on the aesthetics of exploration, expression and fellowship in the mechanics, dynamics, aesthetics (MDA) framework. We collected 503 natural language landscape descriptions from 384 participants in English (69.7%), German (25.1%) and French (5.3%) and most contributions were made in urban areas (54.7%).
The most frequent noun lemma in English was “tree” and in German “Fenster” (window). By comparing our English collection to corpora of everyday English and landscape descriptions, we identified frequent lemmas such as “tree”, “window”, “light”, “street”, “garden” and “sky” which occurred significantly more than expected.
These terms hint as to important components of the everyday landscapes of our users. We suggest a number of ways in which our corpus could be used in ongoing research on landscapes, complementing existing PPGIS approaches, providing data for domain specific lexicons for landscape analysis and as an input to landscape character assessment.