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The accurate quantification of thermal environments is crucial for predicting the impacts of climate change across ecosystems. Two major obstacles exist in mapping biologically relevant thermal landscapes: (1) overcoming the mismatch between the scale at which environmental data are typically collected and the scale at which a particular organism experiences thermal variation and (2) quantifying thermal landscapes without substantial measurement gaps in time or space. We present a new method that integrates aerial thermography from uncrewed aerial vehicles with field‐deployed operative temperature models to generate fine‐scale, spatiotemporally complete maps of operative temperature. To ensure the accessibility of our method, we developed an R package, ‘ throne ’, which streamlines the necessary corrections to raw drone data and produces operative thermal landscapes for any day or time during which data loggers were deployed. Our method allows researchers to generate detailed and biologically relevant thermal landscapes for species of interest, which should enhance our understanding of animal thermal ecology and improve our ability to understand the responses of organisms to environmental change.
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Alujević et al. (2025) studied this question.
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