Identifying Cultural Resource Hotspots via Crowdsourcing and Expert Perspectives

Madeline Brown, Changjie Chen, Luwei Wang, Timothy Murtha

Research output: Contribution to journalArticlepeer-review


Prioritizing hotspots for cultural resource conservation remains a critical challenge for conservation design and planning on a large-landscape scale. Here, we propose novel methodologies for integrating expert evaluations of cultural resource distribution, diversity, and priorities with an emerg-ing digital geospatial dataset tracing the movement of people to and from sites of interest (SafeGraph). Methods for data processing and analysis are explained in detail and code is shared to promote iterative research combining big data with small-n data. Here, we demonstrate the scope and potential of these methodologies by evaluating the correspondence and dynamics between expert and crowdsourced da-tasets via hotspot analysis and temporal visitation patterns. These emergent crowdsourced metrics of valuation (e. g. number of visitors and time spent in particular cultural landscapes/sites) can be contex-tualized and evaluated in combination with expert assessments of resource prioritization to better un-derstand landscape values across a city-wide spatial extent.

Original languageEnglish (US)
Pages (from-to)155-163
Number of pages9
JournalJournal of Digital Landscape Architecture
Issue number7
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Architecture
  • Computer Science Applications
  • Nature and Landscape Conservation


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