Field studies are fundamental to ecological research, yet many studies rely on unspecified or convenience‐based methods for site selection, potentially introducing bias that can compromise research results. Remote‐sensing data provides a quantitative way to evaluate potential sites without expensive pilot visits; however, interacting with spatial data can be computationally complex. We present an R ‘Shiny' application, ‘SiteTool' ( https://github.com/BioDivHealth/sitetool ), which integrates geospatial data into the site selection process, helping researchers generate a list of potential field sites in a region of interest and ensuring that sites fall along a gradient of variation relevant to their research questions. By integrating remote‐sensing data into an easy‐to‐use interface, this tool improves researchers' ability to make quantitative site selection decisions, ultimately leading to more robust studies and research results.
Imirzian et al. (Tue,) studied this question.