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Assessing Perceived Landscape Change from Opportunistic Spatiotemporal Occurrence Data

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  • Alexander Dunkel

    (Leibniz Institute of Ecological Urban and Regional Development, Weberpl. 1, 01217 Dresden, Germany)

  • Dirk Burghardt

    (Institute of Cartography, Technische Universität Dresden, 01062 Dresden, Germany)

Abstract

The exponential growth of user-contributed data provides a comprehensive basis for assessing collective perceptions of landscape change. A variety of possible public data sources exist, such as geospatial data from social media or volunteered geographic information (VGI). Key challenges with such “opportunistic” data sampling are variability in platform popularity and bias due to changing user groups and contribution rules. In this study, we use five case studies to demonstrate how intra- and inter-dataset comparisons can help to assess the temporality of landscape scenic resources, such as identifying seasonal characteristics for a given area or testing hypotheses about shifting popularity trends observed in the field. By focusing on the consistency and reproducibility of temporal patterns for selected scenic resources and comparisons across different dimensions of data, we aim to contribute to the development of systematic methods for disentangling the perceived impact of events and trends from other technological and social phenomena included in the data. The proposed techniques may help to draw attention to overlooked or underestimated patterns of landscape change, fill in missing data between periodic surveys, or corroborate and support field observations. Despite limitations, the results provide a comprehensive basis for developing indicators with a high degree of timeliness for monitoring perceived landscape change over time.

Suggested Citation

  • Alexander Dunkel & Dirk Burghardt, 2024. "Assessing Perceived Landscape Change from Opportunistic Spatiotemporal Occurrence Data," Land, MDPI, vol. 13(7), pages 1-21, July.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:7:p:1091-:d:1438721
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    References listed on IDEAS

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    1. Luc Anselin & Sanjeev Sridharan & Susan Gholston, 2007. "Using Exploratory Spatial Data Analysis to Leverage Social Indicator Databases: The Discovery of Interesting Patterns," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 82(2), pages 287-309, June.
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