Assessing the role of citizen science in the validation of remote sensing habitat classifications

1. Habitat degradation requires increased environmental monitoring to enable conservation activities. Citizen Science (CS) and Remote Sensing (RS) are scalable approaches to broaden biodiversity monitoring. However, few studies explore the pairing of these approaches due to data quality concerns in CS and the technical requirements of RS. 2. We address this gap by implementing RS approaches in a novel survey of species-rich grasslands (SRG) across Scotland—Ecosystem Explorers—the ground-truthing of which was achieved by both professional surveys and CS volunteers. Participants assessed the presence of this target habitat, which was then cross-referenced with predicted SRG locations. This agreement was analysed across professionals and citizen scientists, and by participant experience, confidence and age. 3. The level of agreement between the model-predicted and ground-truthed SRG locations was not significantly different between Ecosystem Explorers and professionally collected data, or across participant experience, confidence or age. Furthermore, participant experience, confidence and age did not significantly affect the number of species participants could identify. 4. Practical Implication. We demonstrate that, with adequate training and resources, citizen scientists can identify habitats and species comparably to professionals utilising RS approaches. These findings help alleviate concerns in the union of CS and RS, encouraging this interdisciplinary approach for upscaling environmental monitoring. Our results support the combination of citizen science and remote sensing data, working towards novel solutions for increasing environmental monitoring; the practical implications of which further enhance biodiversity conservation by including remote sensing observations in citizen science projects or vice versa.