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Monitoring Land Use: Capturing Change through an Information Fusion Approach

Author

Listed:
  • Mark R. Altaweel

    (Computation Institute, University of Chicago, 5640 S. Ellis Avenue, RI 405, Chicago, IL 60637, USA)

  • Lilian N. Alessa

    (Resilience and Adaptive Management Group, University of Alaska Anchorage, 3101 Science Circle, Anchorage, AK 99508, USA)

  • Andrew D. Kliskey

    (Resilience and Adaptive Management Group, University of Alaska Anchorage, 3101 Science Circle, Anchorage, AK 99508, USA)

  • Christopher E. Bone

    (Resilience and Adaptive Management Group, University of Alaska Anchorage, 3101 Science Circle, Anchorage, AK 99508, USA)

Abstract

Social and environmental factors affecting land use change are among the most significant drivers transforming the planet. Such change has been and continues to be monitored through the use of satellite imagery, aerial photography, and technical reports. While these monitoring tools are useful in observing the empirical results of land use change and issues of sustainability, the data they provide are often not useful in capturing the fundamental policies, social drivers, and unseen factors that shape how landscapes are transformed. In addition, some monitoring approaches can be prohibitively expensive and too slow in providing useful data at a timescale in which data are needed. This paper argues that techniques using information fusion and conducting assessments of continuous data feeds can be beneficial for monitoring primary social and ecological mechanisms affecting how geographic settings are changed over different time scales. We present a computational approach that couples open source tools in order to conduct an analysis of text data, helping to determine relevant events and trends. To demonstrate the approach, we discuss a case study that integrates varied newspapers from two Midwest states in the United States, Iowa and Nebraska, showing how potentially significant issues and events can be captured. Although the approach we present is useful for monitoring current web-based data streams, we argue that such a method should ultimately be integrated closely with less managed systems and modeling techniques to enhance not only land use monitoring but also to better forecast and understand landscape change.

Suggested Citation

  • Mark R. Altaweel & Lilian N. Alessa & Andrew D. Kliskey & Christopher E. Bone, 2010. "Monitoring Land Use: Capturing Change through an Information Fusion Approach," Sustainability, MDPI, vol. 2(5), pages 1-22, April.
  • Handle: RePEc:gam:jsusta:v:2:y:2010:i:5:p:1182-1203:d:8157
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    Citations

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    Cited by:

    1. Maggie G. Munthali & Nerhene Davis & Abiodun M. Adeola & Joel O. Botai & Jonathan M. Kamwi & Harold L. W. Chisale & Oluwagbenga O. I. Orimoogunje, 2019. "Local Perception of Drivers of Land-Use and Land-Cover Change Dynamics across Dedza District, Central Malawi Region," Sustainability, MDPI, vol. 11(3), pages 1-25, February.
    2. Astrid Artner-Nehls & Sandra Uthes & Jana Zscheischler & Peter H. Feindt, 2022. "How the Agricultural Press Addresses the Slurry–Water Nexus: A Text Mining Analysis," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    3. Séverin Biaou & Gerard Nounagnon Gouwakinnou & Honoré Samadori Sorotori Biaou & Marc Sèwanou Tovihessi & Beranger Kohomlan Awessou & Fiacre Codjo Ahononga & Felix Ogoubiyi Houéto, 2022. "Identifying the land use and land cover change drivers: methods and case studies of two forest reserves in Northern Benin," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 9885-9905, August.

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