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Selected Data About Geographic Locations01:25

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Related Experiment Video

Updated: May 24, 2026

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

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Published on: February 25, 2021

Sensing landscape history with an interactive location based service.

Ron van Lammeren1, Martin Goossen, Paul Roncken

  • 1Wageningen University/Geo Information Science and Remote Sensing, P.O. Box 47, 6700AA Wageningen, The Netherlands.

Sensors (Basel, Switzerland)
|March 9, 2012
PubMed
Summary

The STEAD approach interprets landscape cultural history data from informal interactive location-based services (iLBS). It analyzes user-generated content based on who, what, and where, revealing dominant user groups and content types.

Keywords:
STEAD approachhuman sensorinformal interactive Location Based Servicesphoto classificationsensing cultural-historic objectsspatial density

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Published on: February 25, 2021

Area of Science:

  • Human-computer interaction
  • Cultural geography
  • Digital humanities

Background:

  • Informal interactive location-based services (iLBS) generate user-generated content about cultural-historic landscapes.
  • Interpreting this in-situ, outdoor data requires a structured approach to understand the 'human sensor's' contribution.

Purpose of the Study:

  • To introduce and illustrate the STEAD approach for interpreting landscape cultural history data from human sensors.
  • To analyze user-generated content based on the 'who', 'what', and 'where' facets.

Main Methods:

  • The STEAD approach was applied to data from a 2008 Dutch survey involving 150 participants using a customized iLBS.
  • Analysis focused on user mentality groups ('who'), picture subject types and framing ('what'), and spatial distribution ('where').

Main Results:

  • Three dominant user mentality groups were identified: cosmopolitans, modern materialists, and post-modern hedonists.
  • Place-type pictures were dominant, with foreground framing being slightly preferred.
  • Spatial analysis revealed patterns in the density, distribution, and distance of user-generated pictures.

Conclusions:

  • The STEAD approach provides a framework for understanding human sensor data in cultural-historic landscape interpretation.
  • Further development is needed for the 'when' facet and inter-facet relationships.
  • The approach can support data archives for iLBS applications.