1Sensor-based monitoring of vegetation phenology is being widely used to quantify 2 phenological responses to climate variability and change. Digital repeat photography, in 3 particular, can characterize the seasonality of canopy greenness. However, these data cannot be 4 directly compared to satellite vegetation indices (e.g., NDVI, the normalized difference 5 vegetation index) that require information about vegetation properties at near-infrared (NIR) 6wavelengths. Here, we develop a new method, using an inexpensive, NIR-enabled camera 7 originally designed for security monitoring, to calculate a "camera NDVI" from sequential 8 visible and visible+NIR photographs. We use a lab experiment for proof-of-concept, and then 9 test the method using a year of data from an ongoing field campaign in a mixed temperate forest. 10Our analysis shows that the seasonal cycle of camera NDVI is almost identical to that of NDVI 11 measured using narrow-band radiometric instruments, or as observed from space by the MODIS 12 platform. This camera NDVI thus provides different information about the state of the canopy 13 than can be obtained using only visible-wavelength imagery. In addition to phenological 14 monitoring, our method should be useful for a variety of applications, including continuous 15 monitoring of plant stress and quantifying vegetation responses to manipulative treatments in 16 large field experiments.