PhenoCam Network: Half-Hourly Vegetation Imagery from 300 Sites

The PhenoCam network, operated by researchers from Harvard University and Boston University, collects half-hourly images of vegetated landscapes from approximately 300 automated cameras across North America. The data is used to study plant phenology—the seasonal timing of leafing, flowering, and fruiting—and its relationship to local weather and climate change. Citizen science contributions through the Season Spotter project help classify tens of thousands of these images.

Use Cases

• Modeling plant phenology-climate relationships based on half-hourly image time series.
• Calibrating satellite-derived phenology data using ground-based camera imagery.
• Training computer vision algorithms to detect seasonal transitions like spring green-up and fall senescence.
• Validating climate change model predictions against observed phenological shifts.

Strengths

• Approximately 300 camera sites provide a distributed observational network.
• Half-hourly image capture frequency enables detailed daily and seasonal time-series analysis.
• Integration with satellite data and citizen science classification expands data utility.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Harvard University and Boston University research group.

Collection Method

Automated cameras on weather towers and elevated platforms, supplemented by satellite imagery and citizen science classification.

Geography

North America.