QScout: A QGIS plugin tool suite for georeferencing and analysis of field‐scouted and remote sensing data

• Published in: Plant phenome journal 2022, Vol.5 (1), p.n/a
• Main Authors: Evans, Joshua R., Romero Galvan, Fernando E., Kanaley, Kathleen, Cadle‐Davidson, Lance, Gold, Kaitlin M.
• Format: Article
• Language: English
• Subjects: Algorithms; Remote sensing; Research methodology; Satellites
• ISSN: 2578-2703; 2578-2703
• DOI: 10.1002/ppj2.20031

Field scouting is an important part of many research methodologies in plant pathology and plant phenomics. However, linking scouting data to field imagery is often hampered by the time‐consuming task of georeferencing with a GIS. Here, we present the QScout tool suite for integrating remote sensing imagery and raster data with field‐scouting data in QGIS, an open‐source GIS program. The central features of QScout are the Drop Pins and Locate Pins plugins, allowing the user to easily link scouted data to remote sensing imagery. QScout also includes the Value Grabber and Grid Aggregator plugins, which transfer raster data into pins and aggregate the data from the pins into a grid, respectively. The final tools, Drop, Grab, and Aggregate and Locate, Grab, and Aggregate, are plugins that combine subsets of the four core plugins. The interface allows GIS users to effectively make use of field‐scouted observations with remote imagery and can improve data organization, analysis, and identification of locations of interest for further scouting or targeted management. QScout is publicly available as a GitHub repository: (https://github.com/GoldLabGrapeSPEC/QScout). Core Ideas Linking remote sensing imagery to ground validation data is an essential first step in nearly all use‐cases. Validation data are frequently not geo‐referenced, which makes connecting it to remote sensing data difficult and time consuming. We have developed an open source tool that can help users easily link non‐georeferenced field data to raster and remote sensing imagery. Our tool can improve data organization, analysis, and identification of locations of interest for investigation.