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ARS Home » Pacific West Area » Corvallis, Oregon » Horticultural Crops Disease and Pest Management Research Unit » Research » Publications at this Location » Publication #344046
Research Project: Integrated Disease Management of Exotic and Emerging Plant Diseases of Horticultural Crops

Location: Horticultural Crops Disease and Pest Management Research Unit

Title: Geospatial analytics for plant disease management

Author
item MAGAREY, ROGER - North Carolina State University
item MEENTEMEYER, ROSS - North Carolina State University
item Grunwald, Niklaus - Nik

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 9/30/2019
Publication Date: 7/1/2020
Citation: Magarey, R., Meentemeyer, R., Grunwald, N.J. 2020. Geospatial analytics for plant disease management. Book Chapter. -.

Interpretive Summary: We are at an exciting point in time when we have more data and better models than ever before for predicting the spread of plant diseases and guiding management. Location-based data about plant diseases are being rapidly generated from satellite and airborne remote sensing, in-situ sensors on farm equipment and computer models of land-use and environmental change. But, in practice a burning question often arises: what we are going to do with these advancements to make a difference? Actionable solutions are going to require big data and sophisticated mathematical models that exceed the limits of typical database and analysis software environments. In this chapter, we describe why plant disease management needs geospatial analytics - an emerging branch of data science focused on the discovery and communication of meaningful patterns in location-based data through new algorithms and interactive tools for visualization and decision making.

Technical Abstract: We are at an exciting point in time when we have more data and better models than ever before for predicting the spread of plant diseases and guiding management. Location-based data about plant diseases are being rapidly generated from satellite and airborne remote sensing, in-situ sensors on farm equipment and computer models of land-use and environmental change. But, in practice a burning question often arises: what we are going to do with these advancements to make a difference? Actionable solutions are going to require big data and sophisticated mathematical models that exceed the limits of typical database and analysis software environments. In this chapter, we describe why plant disease management needs geospatial analytics - an emerging branch of data science focused on the discovery and communication of meaningful patterns in location-based data through new algorithms and interactive tools for visualization and decision making.