Aestimum 74 (2019)
Articles

Rural environment and landscape quality: an evaluation model integrating social media analysis and geostatistics techniques

Veronica Alampi Sottini
University of Florence GESAAF Piazzale delle Cascine 18, I 50144, Firenze (Italy)
Elena Barbierato
University of Florence GESAAF Piazzale delle Cascine 18, I 50144, Firenze (Italy)
Iacopo Bernetti
University of Florence GESAAF Piazzale delle Cascine 18, I 50144, Firenze (Italy)
Irene Capecchi
University of Florence GESAAF Piazzale delle Cascine 18, I 50144, Firenze (Italy)
Sara Fabbrizzi
University of Florence GESAAF Piazzale delle Cascine 18, I 50144, Firenze (Italy)
Silvio Menghini
University of Florence GESAAF Piazzale delle Cascine 18, I 50144, Firenze (Italy)

Published 2019-10-29

Keywords

  • Cultural Ecosystem Services,
  • Geographical Weighted Regression,
  • Big Data

Abstract

The use of geo-tagged photographs seems to be a promising alternative for assessing the scenic beauty of the agricultural landscape compared to the traditional investigation based on expert and perceptual approaches. The aim of this study is integrating the cumulative viewshed calculated from geotagged photo metadata publicly shared on Flickr with raster data on geomorphology, historical sites, and the natural environment, using landscape ecology metrics and Geographically Weighted Regression modelling. Crowdsourced data provided empirical assessments of the covariates associated with visitor distribution, highlighting how changes in infrastructure, crops and environmental factors can affect visitor’s use. This information can help researchers, managers, and public planners to develop projects, plans and guidelines to increase the visual quality of the agricultural landscape.

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