Phenology is the study of biological events that have reoccurring cycles.
These cycles are influenced by both abiotic and biotic factors, and the interactions between these factors.
The PhenoCam network consists of more than 200 web-enabled cameras (PhenoCams) located at various landscapes across the U.S., and other parts of the world. The PhenoCams take an image every 30 minutes and upload the images to the PhenoCam Network’s Website. All PhenoCams collect images that are sensitive to reflective visible radiation, and some have near-infrared sensing capabilities.
You can also access the PhenoCam Network data via the ORNL DAAC
UND's PhenoCam Site
The North Dakota View PhenoCam site is located on the University of North Dakota’s Oakville Prairie Biological Field Station.
- The Oakville Prairie comprises 960 acres of native prairie grassland with a high water table and alkaline soil. Along with the PhenoCam, the site has been equipped with a vegetation height measuring pole, a calibration panel, and a weather station.
- Every 15 minutes, the weather station collects solar radiation, air temperature, relative humidity, dew point, air pressure, wind speed and direction, rainfall, soil moisture, soil temperature at five depths, and leaf wetness.
- The Oakville PhenoCam relies on two solar panels and a wind turbine to charge a 12-volt marine battery, and a cellular modem for Internet connectivity.
About the PhenoCam Project
This project was supported by Cooperative Agreement No. G11AC20461 to Colorado State University, and sub-award G-28580-1 to AmericaView from the U.S. Geological Survey. The Oakville PhenoCam project is a joint effort between the UND departments of Geography & GIS and Biology.
Oakville PhenoCam 2020
Oakville PhenoCam 2019
GCC (Green Chromatic Coordinate) Timeseries Plot
Weather Data at Oakville
Graduate and undergraduate students of Geography who have worked on the assembly, deployment, and operation of the North Dakota View PhenoCam are:
- Bradley Barger
- Mitchell Braget
- Morgen Burke
- Lawrence Burkett
- Earl Klug
- Eohjin Lee
Burke, Morgen WV, and Bradley C. Rundquist. "Scaling Phenocam GCC, NDVI, and EVI2 with Harmonized Landsat-Sentinel using Gaussian Processes." Agricultural and Forest Meteorology 300 (2021): 108316. DOI
Caparó Bellido, Anaí, and Bradley C. Rundquist. "Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland." Remote Sensing 13, no. 11 (2021): 2045. DOI
Yuke, Zhou. "Greenness index from phenocams performs well in linking climatic factors and monitoring grass phenology in a temperate prairie ecosystem." Journal of Resources and Ecology 10, no. 5 (2019): 481-493. DOI
Zhou, Qiang, Jennifer Rover, Jesslyn Brown, Bruce Worstell, Danny Howard, Zhuoting
Wu, Alisa L. Gallant, Bradley Rundquist, and Morgen Burke. "Monitoring landscape dynamics
in central us grasslands with harmonized Landsat-8 and Sentinel-2 time series data."
Remote Sensing 11, no. 3 (2019): 328. DOI
For more information about the PhenoCam project, please contact: