Ground‐truthing of satellite imagery to assess seabird colony size: A test using Adélie penguins

Abstract Adélie penguin ( Pygoscelis adeliae ) colonies can be detected from space using very high‐resolution (VHR; 0.3–0.6 m resolution) satellite imagery, as the contrast between their guano and the surrounding terrain enables colony identification even when physical access is not possible. While VHR imagery has been used to estimate colony size, its potential to detect annual changes remains underexplored, yet is critical for linking population dynamics to oceanographic change. We investigated the utility of VHR imagery for indirect population assessments of this species, expanding on previous work with a decade of imagery and independent population counts. We studied VHR images from four well‐surveyed Ross Sea colonies, that together represent ~10% of the global population: capes Crozier, Bird and Royds, and Inexpressible Island, over the austral summers of 2009–2021. We used supervised object‐based support vector machine classifications to extract guano area from 30 VHR images. We related guano area (m 2 ) to colony size (aerial census counts), assessing for both spatial and temporal autocorrelation. In the process, we investigated various spatial parameters (the average slope steepness, aspect, and perimeter‐to‐area ratio of the guano). Guano area was highly correlated with concurrent counts of breeding pairs, indicating the ability to detect several orders of magnitude difference in colony size. However, large within‐colony variation meant that when using guano area alone the number of breeding pairs had to change by 44% to confidently detect a true change in colony size. Therefore, although VHR imagery can be used to detect significant differences in colony size, minimal sensitivity to interannual fluctuations was indicated, likely due to the difficulty in distinguishing the fresh, current‐year guano from guano of previous years, affected by the rate of weathering. This highlights an important limitation to advances in VHR imagery for some wildlife monitoring and enforces the criticality of ground validation.