Research sponsored by the USGS Land Change Science (LCS) Program supported development and deployment of an innovative sensor system aimed at enabling improved, near-surface multispectral imaging and monitoring of vegetation seasonality and landscape condition. The research, conducted by the USGS Western Geographic Science Center (WGSC), raises the bar in the quest by scientists to extract reliable, quantitative data and information about seasonal and interannual growth patterns of land vegetation (i.e., landscape phenology), from observations acquired over time by small, relatively low-cost digital cameras, commonly known as “phenocams.”
In recent years, growing recognition of the unique potential of phenocams to improve information and scientific understanding of vegetation and climate change has led to rapid growth in their deployment, sustained operation, and geographic distribution at sites representing diverse vegetation, climate, and land use conditions in the United States and globally. Underlying this growth are simplicity and affordability. These factors, in stark contrast to airborne and satellite remote sensing technologies, render the phenocam a practical remote sensing instrument that can be acquired and operated by individual researchers virtually anywhere in the world.
Although phenocams are now widely used for landscape monitoring, phenocam technology and methods remain in a relatively early stage of development. This WGSC project leads pathfinding research on applications of high dynamic range imaging (HDRI) and other innovative techniques and tools to help realize the full potential of phenocams for land change science through improved, science-quality observations of landscape condition and phenology.
A 4-band camera system developed by the USGS Western Geographic Science Center was installed in 2015 to study vegetation growth dynamics at The Nature Conservancy's Hart Prairie Preserve near Flagstaff, Arizona (above), and several tropical and high-latitude forest sites. The "phenocam" uses innovative imaging techniques for improved detection, monitoring, and analysis of how ecosystems are responding to a variable and changing climate.