RadialPheno: A tool for near‐surface phenology analysis through radial layouts. (5th June 2019)

• Record Type: Journal Article
• Authors: Mariano, Greice C.; Alberton, Bruna; Morellato, Leonor Patrícia C.; Torres, Ricardo da S.
• Is Part Of: Applications in plant sciences. Volume 7:Number 6(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-05
• Subjects: cyclical temporal data -- information visualization -- leafing -- phenocameras -- radial layouts; Plants -- Periodicals; Plant physiology -- Periodicals; Plant Physiological Phenomena; Plant physiology; Plants; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 580
• DOI: 10.1002/aps3.1253
• Languages: English
• ISSNs: 2168-0450

Abstract

Abstract : Premise: Increasingly, researchers studying plant phenology are exploring novel technologies to remotely observe plant changes over time. The increasing use of phenocams to monitor leaf phenology, based on the analysis of indices extracted from sequences of daily digital vegetation images, has demanded the development of appropriate tools for data visualization and analysis. Here, we describe RadialPheno, a tool that uses radial layouts to represent time series from digital repeat photographs, and applies them to the analysis of leafing patterns and leaf exchange strategies of different vegetations. Methods and Results: We developed a web tool, RadialPheno, provided with the R and Shiny environments, which uses radial visual structures to represent cyclical multidimensional temporal data associated with digital image time series. We demonstrate the application of our methods and tool for a savanna vegetation phenology in the Brazilian Cerrado. We visually represented the greenness index extracted from sequential imagery using the RadialPheno tool. Conclusions: RadialPheno was successfully applied for the visualization and interpretation of individual, species, and community long‐term leafing phenology data associated with near‐surface phenological observations of Cerrado vegetation. RadialPheno was also effective for intercomparisons of ground‐based direct visual observations and camera‐derived phenology observations.