Vegetation phenology, the seasonal timing of recurring plant life-cycle events, is a key regulator of ecosystem functioning, carbon and water cycling, and species interactions, while also serving as a sensitive indicator of climate variability and climate change. However, existing phenological observations often face trade-offs between species-level detail, temporal frequency, and spatial coverage. Networks of near-surface digital repeat cameras (phenocams) deliver robust, high-frequency phenological signals, but their spatial coverage remains a limitation. In addition to expanding such phenocam networks, this limitation can be tackled by repurposing the outdoor cameras already deployed for other purposes. Here, we present SwissPhenoCam, a country-scale dataset of tree-level phenological greenness observations derived from a network of outdoor digital cameras distributed across Switzerland. By repurposing cameras originally installed for meteorological monitoring, tourism, and other non-ecological applications, SwissPhenoCam demonstrates the potential of existing imaging infrastructure for large-scale phenological observation.</p> <p>The dataset comprises imagery from 34 sites spanning broad elevational, climatic, and biogeographic gradients, with archives extending up to 15 years. Individual trees were delineated and identified to species level where possible, enabling the extraction of species-specific greenness time series and phenological transition dates. The curated dataset contains 5,855 tree-years of observations representing more than 20 tree species and captures substantial environmental variability across Switzerland.</p> <p>Validation against independent observations from the Swiss Phenology Network demonstrates strong agreement between camera-derived and ground-based phenological transition dates, confirming that non-specialized webcams can provide reliable phenological information. Analyses of the dataset reveal pronounced species-specific responses to environmental gradients. Spring green-up is consistently delayed with increasing elevation across deciduous species, whereas autumn senescence shows comparatively weak elevational trends. As a result, growing-season length decreases primarily because of later spring onset rather than earlier autumn decline.</p> <p>The SwissPhenoCam dataset is openly available through Zenodo (<a href="https://doi.org/10.5281/zenodo.20451225" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.20451225</a>) (Garnot et al., 2026) and is intended as a living resource that will expand as observations accumulate. By providing species-resolved, individual-tree phenological observations across a topographically complex landscape, the dataset offers a valuable benchmark for evaluating remote-sensing products, improving phenological models, and assessing climate-change impacts on forest ecosystems. Future work can use this resource to investigate long-term phenological trends, species-specific climate sensitivities, and ecosystem responses to ongoing environmental change.