Landscape preference assessment from digital sources: Comparing historical texts and annotated images in the English Lake District

The potential of applications of new data sources such as Volunteered Geographic Information (VGI) to explore questions related to landscape are in their infancy. However, approaches linking, for example, perceived attractiveness of landscapes to the number and location of volunteered images (Tenerelli et al. 2016) or to the number of individuals taking pictures per area unit (Casalegno et al. 2013; Gliozzo et al. 2016) have been already reported. We propose to use other available information related to the crowdsourced photographs (e.g. Flickr, Geograph), commonly described as an exemplar for VGI, namely the rich textual descriptions and associated tags. In this presentation, we will compare these contemporary forms of descriptions to historical descriptions contained in a digitised corpus of 18th-19th century articles describing the Lake District, where references to locations are in the form of toponyms contained in text.
We present preliminary work on three questions. Firstly, we explore the potential of historical texts and modern sources to provide information about landscape preferences in the Lake District with a specific focus on perception. In Tudor (2014) perceptual and aesthetic components of landscape include parameters related to the sight, sounds, smells, preferences, memories, associations, etc. The presence of terms related to aesthetics, for example majestic and sublime landscapes, has already been explored in our historical corpus (Donaldson et al. 2017). However, we argue that other components (e.g. related to visual and aural perception) can be extracted from both historical and contemporary data.
Secondly, we compare changes in landscapes and landscape perception over time and explore, where differences exist, what form these take. We hypothesise that on one hand well known historical authors influenced current perceptions of the Lake District, but on the other hand, we expect to see differences related to the changes in human activity (e.g. mining until 19th century and the abandoned mines today, increased number of visitors, etc.).
Finally, we demonstrate the possibilities of utilising the information gained in a landscape preference model. The model will use language (in the form of words and phrases extracted from written descriptions) as explanatory variables and will be compared to a model based on parameters derived from standard GIS data (e.g. MacFarlane et al. 2004).