A changing climate might be the tipping point of life-cycle events for predominant species in arid areas that are undergoing degradation. Long-term phenological observations offer solid evidence and prove of this events actually according. Documenting plant’s phenology response to global change, employing "near-remote sensing" like eddy covariance, tramline instruments, and imaging sensors improves phenological events’ understanding. Automated photo-time-series made at high frequency using digital web-cams, records variation over season’s phenology of arid and semi-arid ecosystems. Linking canopy development with flux monitoring networks provides a better understanding of key phenophases and its role on ecosystem function. We are using 4 digital web-cams placed over a 10 m eddy covariance tower at Jornada Basin Experimental Range, which hosts the Jornada Basin Long Term Ecological Research (LTER), in New Mexico. The ones take daily images that are divided into separated red, green, and blue color channels. We calculate relative brightness of each channel for a region of interest within each image, and relate it to eddy covariance and tram-line measurements of surface-atmosphere CO₂ exchange, and field observations of plant phenological events.

Results/Conclusions

We review 4 different cameras from 3 different manufactures. The test was using the Image acquisition tool box of MatLab. I used the green roof of the Biology Building at UTEP, as scenery the cameras were pointed to the same area of interest, under the same lighting conditions. We found that the Microsoft Vx7000 is the best candidate for this project, because the results were very similar to the results of the canon camera, which has higher resolution (8MP). In addition the Microsoft Vx7000 is a low cost webcam. Preliminary results indicate minimal differences in percentages between images exist, which makes it ideal when comparing images from multiple cameras through time. The use of low-cost digital web-cams along with field observations of plant phenological events provides adequate means of monitoring seasonal landscape development.